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Author SHA1 Message Date
Jérôme Petazzoni
5f0b5d4ba8 🍂 Highfive Sep/Oct 2024 2024-10-15 19:53:54 +02:00
71 changed files with 2244 additions and 3875 deletions

View File

@@ -57,7 +57,7 @@ need_tag() {
if [ ! -d "tags/$TAG" ]; then
die "Tag $TAG not found (directory tags/$TAG does not exist)."
fi
for FILE in mode provider settings.env status; do
for FILE in settings.env ips.txt; do
if [ ! -f "tags/$TAG/$FILE" ]; then
warning "File tags/$TAG/$FILE not found."
fi

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@@ -19,22 +19,20 @@ _cmd_cards() {
TAG=$1
need_tag
OPTIONS_FILE=$2
[ -f "$OPTIONS_FILE" ] || die "Please specify a YAML options file as 2nd argument."
OPTIONS_FILE_PATH="$(readlink -f "$OPTIONS_FILE")"
die FIXME
# This will process logins.jsonl to generate two files: cards.pdf and cards.html
# This will process ips.txt to generate two files: ips.pdf and ips.html
(
cd tags/$TAG
../../../lib/make-login-cards.py "$OPTIONS_FILE_PATH"
../../../lib/ips-txt-to-html.py settings.yaml
)
ln -sf ../tags/$TAG/cards.html www/$TAG.html
ln -sf ../tags/$TAG/cards.pdf www/$TAG.pdf
ln -sf ../tags/$TAG/ips.html www/$TAG.html
ln -sf ../tags/$TAG/ips.pdf www/$TAG.pdf
info "Cards created. You can view them with:"
info "xdg-open tags/$TAG/cards.html tags/$TAG/cards.pdf (on Linux)"
info "open tags/$TAG/cards.html (on macOS)"
info "xdg-open tags/$TAG/ips.html tags/$TAG/ips.pdf (on Linux)"
info "open tags/$TAG/ips.html (on macOS)"
info "Or you can start a web server with:"
info "$0 www"
}
@@ -259,9 +257,7 @@ _cmd_create() {
terraform init
echo tag = \"$TAG\" >> terraform.tfvars
echo how_many_clusters = $STUDENTS >> terraform.tfvars
if [ "$CLUSTERSIZE" ]; then
echo nodes_per_cluster = $CLUSTERSIZE >> terraform.tfvars
fi
echo nodes_per_cluster = $CLUSTERSIZE >> terraform.tfvars
for RETRY in 1 2 3; do
if terraform apply -auto-approve; then
touch terraform.ok
@@ -328,8 +324,8 @@ _cmd_clusterize() {
grep KUBECOLOR_ /etc/ssh/sshd_config || echo 'AcceptEnv KUBECOLOR_*' | sudo tee -a /etc/ssh/sshd_config
sudo systemctl restart ssh.service"
pssh -I < tags/$TAG/clusters.tsv "
grep -w \$PSSH_HOST | tr '\t' '\n' > /tmp/cluster"
pssh -I < tags/$TAG/clusters.txt "
grep -w \$PSSH_HOST | tr ' ' '\n' > /tmp/cluster"
pssh "
echo \$PSSH_HOST > /tmp/ipv4
head -n 1 /tmp/cluster | sudo tee /etc/ipv4_of_first_node
@@ -350,10 +346,6 @@ _cmd_clusterize() {
done < /tmp/cluster
"
while read line; do
printf '{"login": "%s", "password": "%s", "ipaddrs": "%s"}\n' "$USER_LOGIN" "$USER_PASSWORD" "$line"
done < tags/$TAG/clusters.tsv > tags/$TAG/logins.jsonl
echo cluster_ok > tags/$TAG/status
}
@@ -942,15 +934,6 @@ _cmd_inventory() {
FIXME
}
_cmd logins "Show login information for a group of instances"
_cmd_logins() {
TAG=$1
need_tag $TAG
cat tags/$TAG/logins.jsonl \
| jq -r '"\(.password)\tssh -l \(.login)\(if .port then " -p \(.port)" else "" end)\t\(.ipaddrs)"'
}
_cmd maketag "Generate a quasi-unique tag for a group of instances"
_cmd_maketag() {
if [ -z $USER ]; then
@@ -1001,9 +984,6 @@ _cmd_stage2() {
cd tags/$TAG/stage2
terraform init -upgrade
terraform apply -auto-approve
terraform output -raw logins_jsonl > ../logins.jsonl
terraform output -raw ips_txt > ../ips.txt
echo "stage2_ok" > status
}
_cmd standardize "Deal with non-standard Ubuntu cloud images"
@@ -1183,8 +1163,8 @@ _cmd_tags() {
cd tags
echo "[#] [Status] [Tag] [Mode] [Provider]"
for tag in *; do
if [ -f $tag/logins.jsonl ]; then
count="$(wc -l < $tag/logins.jsonl)"
if [ -f $tag/ips.txt ]; then
count="$(wc -l < $tag/ips.txt)"
else
count="?"
fi
@@ -1347,7 +1327,7 @@ EOF"
_cmd www "Run a web server to access card HTML and PDF"
_cmd_www() {
cd www
IPADDR=$(curl -fsSL canihazip.com/s || echo localhost)
IPADDR=$(curl -sL canihazip.com/s)
info "The following files are available:"
for F in *; do
echo "http://$IPADDR:8000/$F"

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@@ -1,22 +1,32 @@
#!/usr/bin/env python3
import json
import os
import sys
import yaml
import jinja2
# Read settings from user-provided settings file
context = yaml.safe_load(open(sys.argv[1]))
context["logins"] = []
for line in open("logins.jsonl"):
if line.strip():
context["logins"].append(json.loads(line))
ips = list(open("ips.txt"))
clustersize = context["clustersize"]
print("---------------------------------------------")
print(" Number of cards: {}".format(len(context["logins"])))
print(" Number of IPs: {}".format(len(ips)))
print(" VMs per cluster: {}".format(clustersize))
print("---------------------------------------------")
assert len(ips)%clustersize == 0
clusters = []
while ips:
cluster = ips[:clustersize]
ips = ips[clustersize:]
clusters.append(cluster)
context["clusters"] = clusters
template_file_name = context["cards_template"]
template_file_path = os.path.join(
os.path.dirname(__file__),
@@ -25,23 +35,23 @@ template_file_path = os.path.join(
template_file_name
)
template = jinja2.Template(open(template_file_path).read())
with open("cards.html", "w") as f:
f.write(template.render(**context))
print("Generated cards.html")
with open("ips.html", "w") as f:
f.write(template.render(**context))
print("Generated ips.html")
try:
import pdfkit
paper_size = context["paper_size"]
margin = {"A4": "0.5cm", "Letter": "0.2in"}[paper_size]
with open("cards.html") as f:
pdfkit.from_file(f, "cards.pdf", options={
with open("ips.html") as f:
pdfkit.from_file(f, "ips.pdf", options={
"page-size": paper_size,
"margin-top": margin,
"margin-bottom": margin,
"margin-left": margin,
"margin-right": margin,
})
print("Generated cards.pdf")
print("Generated ips.pdf")
except ImportError:
print("WARNING: could not import pdfkit; did not generate cards.pdf")
print("WARNING: could not import pdfkit; did not generate ips.pdf")

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@@ -1,3 +1,5 @@
CLUSTERSIZE=2
USER_LOGIN=k8s
USER_PASSWORD=

View File

@@ -7,7 +7,7 @@
{%- set url = url
| default("http://FIXME.container.training/") -%}
{%- set pagesize = pagesize
| default(10) -%}
| default(9) -%}
{%- set lang = lang
| default("en") -%}
{%- set event = event
@@ -15,36 +15,79 @@
{%- set backside = backside
| default(False) -%}
{%- set image = image
| default(False) -%}
| default("kube") -%}
{%- set clusternumber = clusternumber
| default(None) -%}
{%- set thing = thing
| default("lab environment") -%}
{%- if lang == "en" -%}
{%- set intro -%}
Here is the connection information to your very own
{{ thing }} for this {{ event }}.
You can connect to it with any SSH client.
{%- endset -%}
{%- if qrcode == True -%}
{%- set qrcode = "https://container.training/q" -%}
{%- elif qrcode -%}
{%- set qrcode = qrcode -%}
{%- endif -%}
{%- if lang == "fr" -%}
{%- set intro -%}
Voici les informations permettant de se connecter à votre
{{ thing }} pour cette formation.
Vous pouvez vous y connecter
avec n'importe quel client SSH.
{%- endset -%}
{# You can also set img_bottom_src instead. #}
{%- set img_logo_src = {
"docker": "https://s3-us-west-2.amazonaws.com/www.breadware.com/integrations/docker.png",
"swarm": "https://cdn.wp.nginx.com/wp-content/uploads/2016/07/docker-swarm-hero2.png",
"kube": "https://avatars1.githubusercontent.com/u/13629408",
"enix": "https://enix.io/static/img/logos/logo-domain-cropped.png",
}[image] -%}
{%- if lang == "en" and clustersize == 1 -%}
{%- set intro -%}
Here is the connection information to your very own
machine for this {{ event }}.
You can connect to this VM with any SSH client.
{%- endset -%}
{%- set listhead -%}
Your machine is:
{%- endset -%}
{%- endif -%}
{%- if lang == "en" and clustersize != 1 -%}
{%- set intro -%}
Here is the connection information to your very own
cluster for this {{ event }}.
You can connect to each VM with any SSH client.
{%- endset -%}
{%- set listhead -%}
Your machines are:
{%- endset -%}
{%- endif -%}
{%- if lang == "fr" and clustersize == 1 -%}
{%- set intro -%}
Voici les informations permettant de se connecter à votre
machine pour cette formation.
Vous pouvez vous connecter à cette machine virtuelle
avec n'importe quel client SSH.
{%- endset -%}
{%- set listhead -%}
Adresse IP:
{%- endset -%}
{%- endif -%}
{%- if lang == "en" and clusterprefix != "node" -%}
{%- set intro -%}
Here is the connection information for the
<strong>{{ clusterprefix }}</strong> environment.
{%- endset -%}
{%- endif -%}
{%- if lang == "fr" and clustersize != 1 -%}
{%- set intro -%}
Voici les informations permettant de se connecter à votre
cluster pour cette formation.
Vous pouvez vous connecter à chaque machine virtuelle
avec n'importe quel client SSH.
{%- endset -%}
{%- set listhead -%}
Adresses IP:
{%- endset -%}
{%- endif -%}
{%- if lang == "en" -%}
{%- set slides_are_at -%}
You can find the slides at:
{%- endset -%}
{%- set slides_are_at -%}
You can find the slides at:
{%- endset -%}
{%- endif -%}
{%- if lang == "fr" -%}
{%- set slides_are_at -%}
Le support de formation est à l'adresse suivante :
{%- endset -%}
{%- set slides_are_at -%}
Le support de formation est à l'adresse suivante :
{%- endset -%}
{%- endif -%}
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
@@ -59,21 +102,25 @@
}
body {
/* this is A4 minus 0.5cm margins */
width: 20cm;
height: 28.7cm;
width: 20cm;
height: 28.7cm;
}
{% elif paper_size == "Letter" %}
@page {
size: Letter; /* 8.5in x 11in */
size: Letter;
margin: 0.2in;
}
body {
width: 6.75in; /* two cards wide */
margin-left: 0.875in; /* (8.5in - 6.75in)/2 */
margin-top: 0.1875in; /* (11in - 5 cards)/2 */
/* this is Letter minus 0.2in margins */
width: 8.6in;
heigth: 10.6in;
}
{% endif %}
body, table {
margin: 0;
padding: 0;
line-height: 1em;
font-size: 15px;
font-family: 'Slabo 27px';
@@ -87,45 +134,47 @@ table {
padding-left: 0.4em;
}
td:first-child {
width: 10.5em;
}
div.card {
div {
float: left;
border: 0.01in dotted black;
border: 1px dotted black;
{% if backside %}
height: 33%;
{% endif %}
/* columns * (width+left+right) < 100% */
/*
columns * (width+left+right) < 100%
height: 33%;
width: 24.8%;
width: 33%;
width: 24.8%;
*/
width: 3.355in; /* 3.375in minus two 0.01in borders */
height: 2.105in; /* 2.125in minus two 0.01in borders */
/**/
width: 33%;
/**/
}
p {
margin: 0.8em;
}
div.front {
{% if image %}
background-image: url("{{ image }}");
background-repeat: no-repeat;
background-size: 1in;
background-position-x: 2.8in;
background-position-y: center;
{% endif %}
div.back {
border: 1px dotted grey;
}
span.scale {
white-space: nowrap;
white-space: nowrap;
}
img.logo {
height: 4.5em;
float: right;
}
img.bottom {
height: 2.5em;
display: block;
margin: 0.5em auto;
}
.qrcode img {
height: 5.8em;
padding: 1em 1em 0.5em 1em;
float: left;
width: 40%;
margin: 1em;
}
.logpass {
@@ -140,97 +189,101 @@ span.scale {
height: 0;
}
</style>
<script type="text/javascript" src="qrcode.min.js"></script>
<script type="text/javascript" src="https://cdn.rawgit.com/davidshimjs/qrcodejs/gh-pages/qrcode.min.js"></script>
<script type="text/javascript">
function qrcodes() {
[].forEach.call(
document.getElementsByClassName("qrcode"),
(e, index) => {
new QRCode(e, {
text: "{{ qrcode }}",
correctLevel: QRCode.CorrectLevel.L
});
}
);
[].forEach.call(
document.getElementsByClassName("qrcode"),
(e, index) => {
new QRCode(e, {
text: "{{ qrcode }}",
correctLevel: QRCode.CorrectLevel.L
});
}
);
}
function scale() {
[].forEach.call(
document.getElementsByClassName("scale"),
(e, index) => {
var text_width = e.getBoundingClientRect().width;
var box_width = e.parentElement.getBoundingClientRect().width;
var percent = 100 * box_width / text_width + "%";
e.style.fontSize = percent;
}
);
[].forEach.call(
document.getElementsByClassName("scale"),
(e, index) => {
var text_width = e.getBoundingClientRect().width;
var box_width = e.parentElement.getBoundingClientRect().width;
var percent = 100 * box_width / text_width + "%";
e.style.fontSize = percent;
}
);
}
</script>
</head>
<body onload="qrcodes(); scale();">
{% for login in logins %}
<div class="card front">
{% for cluster in clusters %}
<div>
<p>{{ intro }}</p>
<p>
{% if img_logo_src %}
<img class="logo" src="{{ img_logo_src }}" />
{% endif %}
<table>
<tr>
<td>login:</td>
<td>password:</td>
</tr>
<tr>
<td class="logpass">{{ login.login }}</td>
<td class="logpass">{{ login.password }}</td>
</tr>
<tr>
<td>IP address:</td>
{% if login.port %}
<td>port:</td>
{% endif %}
</tr>
<tr>
<td class="logpass">{{ login.ipaddrs.split("\t")[0] }}</td>
{% if login.port %}
<td class="logpass">{{ login.port }}</td>
{% endif %}
</tr>
{% if clusternumber != None %}
<tr><td>cluster:</td></tr>
<tr><td class="logpass">{{ clusternumber + loop.index }}</td></tr>
{% endif %}
<tr><td>login:</td></tr>
<tr><td class="logpass">{{ user_login }}</td></tr>
<tr><td>password:</td></tr>
<tr><td class="logpass">{{ user_password }}</td></tr>
</table>
</p>
<p>
{{ listhead }}
<table>
{% for node in cluster %}
<tr>
<td>{{ clusterprefix }}{{ loop.index }}:</td>
<td>{{ node }}</td>
</tr>
{% endfor %}
</table>
</p>
<p>
{% if url %}
{{ slides_are_at }}
{{ slides_are_at }}
<p>
<span class="scale">{{ url }}</span>
</p>
{% endif %}
{% if img_bottom_src %}
<img class="bottom" src="{{ img_bottom_src }}" />
{% endif %}
</p>
</div>
{% if loop.index%pagesize==0 or loop.last %}
<span class="pagebreak"></span>
{% if backside %}
{% for x in range(pagesize) %}
<div class="card back">
{{ backside }}
{#
<p>Thanks for attending
"Getting Started With Kubernetes and Container Orchestration"
during CONFERENCE in Month YYYY!</p>
<p>If you liked that workshop,
I can train your team, in person or
online, with custom courses of
any length and any level.
</p>
{% if qrcode %}
<p>If you're interested, please scan that QR code to contact me:</p>
<span class="qrcode"></span>
{% for x in range(pagesize) %}
<div class="back">
<p>Thanks for attending
"Getting Started With Kubernetes and Container Orchestration"
during CONFERENCE in Month YYYY!</p>
<p>If you liked that workshop,
I can train your team, in person or
online, with custom courses of
any length and any level.
</p>
{% if qrcode %}
<p>If you're interested, please scan that QR code to contact me:</p>
<span class="qrcode"></span>
{% else %}
<p>If you're interested, you can contact me at:</p>
{% endif %}
<p>jerome.petazzoni@gmail.com</p>
#}
</div>
{% endfor %}
<span class="pagebreak"></span>
{% endif %}
<p>If you're interested, you can contact me at:</p>
{% endif %}
<p>jerome.petazzoni@gmail.com</p>
</div>
{% endfor %}
<span class="pagebreak"></span>
{% endif %}
{% endif %}
{% endfor %}
</body>

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@@ -1,19 +0,0 @@
cards_template: cards.html
paper_size: Letter
url: https://2024-11-qconsf.container.training
event: workshop
backside: |
<div class="qrcode"></div>
<p>
Thanks for attending the Asynchronous Architecture Patterns workshop at QCON!
</p>
<p>
<b>This QR code will give you my contact info</b> as well as a link to a feedback form.
</p>
<p>
If you liked this workshop, I can train your team, in person or online, with custom
courses of any length and any level, on Docker, Kubernetes, and MLops.
</p>
qrcode: https://2024-11-qconsf.container.training/#contact
thing: Kubernetes cluster
image: logo-kubernetes.png

View File

@@ -8,8 +8,8 @@ resource "random_string" "_" {
resource "time_static" "_" {}
locals {
min_nodes_per_pool = var.min_nodes_per_cluster
max_nodes_per_pool = var.max_nodes_per_cluster
min_nodes_per_pool = var.nodes_per_cluster
max_nodes_per_pool = var.nodes_per_cluster * 2
timestamp = formatdate("YYYY-MM-DD-hh-mm", time_static._.rfc3339)
tag = random_string._.result
# Common tags to be assigned to all resources

View File

@@ -217,27 +217,16 @@ resource "kubernetes_certificate_signing_request_v1" "cluster_admin_${index}" {
%{ endfor ~}
output "ips_txt" {
output "ip_addresses_of_nodes" {
value = join("\n", [
%{ for index, cluster in clusters ~}
join("\n", concat(
join("\t", concat(
[
random_string.shpod_${index}.result,
"ssh -l k8s -p $${kubernetes_service.shpod_${index}.spec[0].port[0].node_port}"
],
split(" ", file("./externalips.${index}"))
)),
%{ endfor ~}
""
])
}
output "logins_jsonl" {
value = join("\n", [
%{ for index, cluster in clusters ~}
jsonencode({
login = "k8s",
password = random_string.shpod_${index}.result,
port = kubernetes_service.shpod_${index}.spec[0].port[0].node_port,
ipaddrs = replace(file("./externalips.${index}"), " ", "\t"),
}),
%{ endfor ~}
""
])
}

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@@ -7,16 +7,11 @@ variable "how_many_clusters" {
default = 2
}
variable "min_nodes_per_cluster" {
variable "nodes_per_cluster" {
type = number
default = 2
}
variable "max_nodes_per_cluster" {
type = number
default = 4
}
variable "node_size" {
type = string
default = "M"

View File

@@ -71,10 +71,10 @@ resource "local_file" "ip_addresses" {
resource "local_file" "clusters" {
content = join("", formatlist("%s\n", [
for cid in range(1, 1 + var.how_many_clusters) :
join("\t",
join(" ",
[for nid in range(1, 1 + var.nodes_per_cluster) :
local.ip_addresses[format("c%03dn%03d", cid, nid)]
])]))
filename = "clusters.tsv"
filename = "clusters.txt"
file_permission = "0600"
}

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68
slides/1.yml Normal file
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@@ -0,0 +1,68 @@
title: |
Docker Intensif
chat: "[Mattermost](https://training.enix.io/mattermost)"
gitrepo: github.com/jpetazzo/container.training
slides: https://2024-10-enix.container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics.md
- containers/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
- # DAY 1
#- containers/Docker_Overview.md
#- containers/Docker_History.md
- containers/Training_Environment.md
#- containers/Installing_Docker.md
- containers/First_Containers.md
- containers/Background_Containers.md
- containers/Initial_Images.md
- containers/Building_Images_Interactively.md
- containers/Building_Images_With_Dockerfiles.md
- containers/Cmd_And_Entrypoint.md
- containers/Copying_Files_During_Build.md
- containers/Exercise_Dockerfile_Basic.md
- # DAY 2
- containers/Container_Networking_Basics.md
- containers/Local_Development_Workflow.md
- containers/Container_Network_Model.md
- containers/Compose_For_Dev_Stacks.md
- containers/Exercise_Composefile.md
- # DAY 3
- containers/Start_And_Attach.md
- containers/Naming_And_Inspecting.md
- containers/Labels.md
- containers/Getting_Inside.md
- containers/Dockerfile_Tips.md
- containers/Advanced_Dockerfiles.md
- containers/Multi_Stage_Builds.md
- containers/Publishing_To_Docker_Hub.md
- containers/Exercise_Dockerfile_Advanced.md
- # DAY 4
- containers/Buildkit.md
- containers/Network_Drivers.md
- containers/Namespaces_Cgroups.md
#- containers/Copy_On_Write.md
- containers/Orchestration_Overview.md
#- containers/Docker_Machine.md
#- containers/Init_Systems.md
#- containers/Application_Configuration.md
#- containers/Logging.md
#- containers/Containers_From_Scratch.md
#- containers/Container_Engines.md
#- containers/Pods_Anatomy.md
#- containers/Ecosystem.md
- shared/thankyou.md
#- containers/links.md

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@@ -1,11 +1,11 @@
title: |
Kubernetes
Fondamentaux Kubernetes
chat: "[Mattermost](https://training.enix.io/mattermost)"
gitrepo: github.com/jpetazzo/container.training
slides: https://2024-10-boursorama.container.training/
slides: https://2024-10-enix.container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
@@ -24,75 +24,69 @@ content:
- shared/handson.md
#- shared/webssh.md
- shared/connecting.md
- exercises/k8sfundamentals-brief.md
- exercises/yaml-brief.md
- exercises/localcluster-brief.md
- exercises/healthchecks-brief.md
- shared/toc.md
- # 1 Monday morning
- # 1
#- k8s/versions-k8s.md
- shared/sampleapp.md
#- shared/composescale.md
#- shared/hastyconclusions.md
- shared/composedown.md
- k8s/concepts-k8s.md
- k8s/kubectlget.md
- k8s/kubectl-run.md
- k8s/kubectlexpose.md
#- k8s/shippingimages.md
- k8s/service-types.md
- k8s/kubenet.md
- k8s/shippingimages.md
#- k8s/buildshiprun-selfhosted.md
- k8s/buildshiprun-dockerhub.md
- exercises/k8sfundamentals-details.md
- k8s/ourapponkube.md
- # 2 Monday afternoon
- k8s/service-types.md
- k8s/kubenet.md
#- k8s/exercise-wordsmith.md
- # 2
- shared/yaml.md
- k8s/labels-annotations.md
- k8s/kubectl-logs.md
- k8s/logs-cli.md
- # 3 Tuesday morning
- shared/yaml.md
- k8s/yamldeploy.md
- k8s/namespaces.md
- shared/declarative.md
- k8s/declarative.md
- k8s/deploymentslideshow.md
- k8s/ingress.md
- k8s/cert-manager.md
- k8s/setup-overview.md
- k8s/setup-devel.md
#- k8s/setup-managed.md
#- k8s/setup-selfhosted.md
- k8s/localkubeconfig.md
- k8s/accessinternal.md
- k8s/kubectlproxy.md
- exercises/yaml-details.md
- exercises/ingress-details.md
- # 4 Tuesday afternoon
- k8s/volumes.md
#- k8s/exercise-configmap.md
- k8s/configuration.md
- k8s/secrets.md
- # 5 Wednesday morning
- exercises/localcluster-details.md
- # 3
#- k8s/kubectlscale.md
- k8s/scalingdockercoins.md
- shared/hastyconclusions.md
- k8s/daemonset.md
- k8s/rollout.md
- k8s/healthchecks.md
#- k8s/healthchecks-more.md
- k8s/dashboard.md
- k8s/k9s.md
- k8s/tilt.md
- exercises/healthchecks-details.md
- # 6 Wednesday afternoon
- k8s/resource-limits.md
- k8s/metrics-server.md
- k8s/cluster-sizing.md
#- k8s/horizontal-pod-autoscaler.md
- exercises/reqlim-details.md
- # 7 Thursday morning
- k8s/authn-authz.md
- k8s/admission.md
- k8s/cainjector.md
- k8s/kyverno.md
- exercises/rbac-details.md
- exercises/kyverno-ingress-domain-name-details.md
- # 8 Thursday afternoon
- k8s/statefulsets.md
- k8s/consul.md
- k8s/pv-pvc-sc.md
- k8s/volume-claim-templates.md
- k8s/stateful-failover.md
- # 9 Friday morning
- k8s/helm-intro.md
- k8s/helm-chart-format.md
- k8s/helm-create-basic-chart.md
- exercises/helm-generic-chart-details.md
- # 10 Friday afternoon
- k8s/helm-create-better-chart.md
- k8s/helm-dependencies.md
- k8s/helm-values-schema-validation.md
- k8s/helm-secrets.md
- exercises/helm-umbrella-chart-details.md
- # 4
- k8s/ingress.md
#- k8s/ingress-tls.md
#- k8s/ingress-advanced.md
- k8s/volumes.md
#- k8s/exercise-configmap.md
#- k8s/build-with-docker.md
#- k8s/build-with-kaniko.md
- k8s/configuration.md
- k8s/secrets.md
- k8s/batch-jobs.md
- shared/thankyou.md

46
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@@ -0,0 +1,46 @@
title: |
Packaging d'applications
pour Kubernetes
chat: "[Mattermost](https://training.enix.io/mattermost)"
gitrepo: github.com/jpetazzo/container.training
slides: https://2024-10-enix.container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics.md
- k8s/intro.md
- shared/about-slides.md
- k8s/prereqs-advanced.md
- shared/handson.md
- shared/webssh.md
- shared/connecting.md
#- shared/chat-room-im.md
#- shared/chat-room-zoom.md
- shared/toc.md
-
- k8s/demo-apps.md
- k8s/kustomize.md
- k8s/helm-intro.md
- k8s/helm-chart-format.md
- k8s/helm-create-basic-chart.md
- exercises/helm-generic-chart-details.md
-
- k8s/helm-create-better-chart.md
- k8s/helm-dependencies.md
- k8s/helm-values-schema-validation.md
- k8s/helm-secrets.md
- exercises/helm-umbrella-chart-details.md
-
- k8s/ytt.md
- k8s/gitworkflows.md
- k8s/flux.md
- k8s/argocd.md
- shared/thankyou.md

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@@ -0,0 +1,72 @@
title: |
Kubernetes Avancé
chat: "[Mattermost](https://training.enix.io/mattermost)"
gitrepo: github.com/jpetazzo/container.training
slides: https://2024-10-enix.container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics.md
- k8s/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-zoom.md
- k8s/prereqs-advanced.md
- shared/handson.md
- shared/webssh.md
- shared/connecting.md
- shared/toc.md
- exercises/netpol-brief.md
- exercises/sealed-secrets-brief.md
- exercises/kyverno-ingress-domain-name-brief.md
- exercises/reqlim-brief.md
- #1
- k8s/demo-apps.md
- k8s/netpol.md
- k8s/authn-authz.md
- k8s/sealed-secrets.md
- k8s/cert-manager.md
- k8s/cainjector.md
- k8s/ingress-tls.md
- exercises/netpol-details.md
- exercises/sealed-secrets-details.md
- #2
- k8s/extending-api.md
- k8s/crd.md
- k8s/operators.md
- k8s/admission.md
- k8s/cainjector.md
- k8s/kyverno.md
- exercises/kyverno-ingress-domain-name-details.md
- #3
- k8s/resource-limits.md
- k8s/metrics-server.md
- k8s/cluster-sizing.md
- k8s/horizontal-pod-autoscaler.md
- k8s/apiserver-deepdive.md
- k8s/aggregation-layer.md
- k8s/hpa-v2.md
- exercises/reqlim-details.md
- #4
- k8s/statefulsets.md
- k8s/consul.md
- k8s/pv-pvc-sc.md
- k8s/volume-claim-templates.md
#- k8s/eck.md
#- k8s/portworx.md
- k8s/openebs.md
- k8s/stateful-failover.md
- k8s/operators-design.md
- k8s/operators-example.md
- k8s/owners-and-dependents.md
- k8s/events.md
- k8s/finalizers.md
- shared/thankyou.md

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@@ -0,0 +1,59 @@
title: |
Opérer Kubernetes
chat: "[Mattermost](https://training.enix.io/mattermost)"
gitrepo: github.com/jpetazzo/container.training
slides: https://2024-10-enix.container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics-ludovic.md
- k8s/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
# DAY 1
-
- k8s/prereqs-advanced.md
- shared/handson.md
- k8s/architecture.md
- k8s/deploymentslideshow.md
- k8s/dmuc-easy.md
-
- k8s/dmuc-medium.md
- k8s/dmuc-hard.md
- k8s/cni-internals.md
#- k8s/interco.md
- k8s/apilb.md
-
- k8s/internal-apis.md
- k8s/staticpods.md
- k8s/cluster-upgrade.md
- k8s/cluster-backup.md
#- k8s/cloud-controller-manager.md
-
- k8s/control-plane-auth.md
- k8s/user-cert.md
- k8s/csr-api.md
- k8s/openid-connect.md
- k8s/pod-security-intro.md
- k8s/pod-security-policies.md
- k8s/pod-security-admission.md
- shared/thankyou.md
#-
# |
# # (Extra content)
# - k8s/apiserver-deepdive.md
# - k8s/setup-overview.md
# - k8s/setup-devel.md
# - k8s/setup-managed.md
# - k8s/setup-selfhosted.md

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@@ -2,7 +2,6 @@
#/ /kube-halfday.yml.html 200!
#/ /kube-fullday.yml.html 200!
#/ /kube-twodays.yml.html 200!
/ /kube.yml.html 200!
# And this allows to do "git clone https://container.training".
/info/refs service=git-upload-pack https://github.com/jpetazzo/container.training/info/refs?service=git-upload-pack
@@ -24,3 +23,5 @@
# Survey form
/please https://docs.google.com/forms/d/e/1FAIpQLSfIYSgrV7tpfBNm1hOaprjnBHgWKn5n-k5vtNXYJkOX1sRxng/viewform
/ /highfive.html 200!

View File

@@ -40,7 +40,7 @@
- In multi-stage builds, all stages can be built in parallel
(example: https://github.com/jpetazzo/shpod; [before][shpod-before-parallel] and [after][shpod-after-parallel])
(example: https://github.com/jpetazzo/shpod; [before] and [after])
- Stages are built only when they are necessary
@@ -50,8 +50,8 @@
- Files are cached in the builder
[shpod-before-parallel]: https://github.com/jpetazzo/shpod/blob/c6efedad6d6c3dc3120dbc0ae0a6915f85862474/Dockerfile
[shpod-after-parallel]: https://github.com/jpetazzo/shpod/blob/d20887bbd56b5fcae2d5d9b0ce06cae8887caabf/Dockerfile
[before]: https://github.com/jpetazzo/shpod/blob/c6efedad6d6c3dc3120dbc0ae0a6915f85862474/Dockerfile
[after]: https://github.com/jpetazzo/shpod/blob/d20887bbd56b5fcae2d5d9b0ce06cae8887caabf/Dockerfile
---
@@ -121,10 +121,10 @@ docker buildx build … \
- Must not use binary downloads with hard-coded architectures!
(streamlining a Dockerfile for multi-arch: [before][shpod-before-multiarch], [after][shpod-after-multiarch])
(streamlining a Dockerfile for multi-arch: [before], [after])
[shpod-before-multiarch]: https://github.com/jpetazzo/shpod/blob/d20887bbd56b5fcae2d5d9b0ce06cae8887caabf/Dockerfile
[shpod-after-multiarch]: https://github.com/jpetazzo/shpod/blob/c50789e662417b34fea6f5e1d893721d66d265b7/Dockerfile
[before]: https://github.com/jpetazzo/shpod/blob/d20887bbd56b5fcae2d5d9b0ce06cae8887caabf/Dockerfile
[after]: https://github.com/jpetazzo/shpod/blob/c50789e662417b34fea6f5e1d893721d66d265b7/Dockerfile
---

View File

@@ -120,11 +120,11 @@ class: extra-details
(and won't end up in the resulting image)
- See the [documentation][dockerignore] for the little details
- See the [documentation] for the little details
(exceptions can be made with `!`, multiple directory levels with `**`...)
[dockerignore]: https://docs.docker.com/engine/reference/builder/#dockerignore-file
[documentation]: https://docs.docker.com/engine/reference/builder/#dockerignore-file
???

View File

@@ -1,5 +0,0 @@
#!/bin/sh
for LINK in $(cat */*.md | sed -n 's/^\[\(.*\)\]:.*/\1/p' | sort | uniq -d); do
grep '^\['"$LINK"'\]:' */*.md
done

129
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@@ -0,0 +1,129 @@
<?xml version="1.0"?>
<html>
<head>
<style>
td {
background: #ccc;
padding: 1em;
}
</style>
</head>
<body>
<table>
<tr>
<td>Mardi 24 septembre 2024</td>
<td>
<a href="1.yml.html">Docker Intensif</a>
</td>
</tr>
<tr>
<td>Mercredi 25 septembre 2024</td>
<td>
<a href="1.yml.html">Docker Intensif</a>
</td>
</tr>
<tr>
<td>Jeudi 26 septembre 2024</td>
<td>
<a href="1.yml.html">Docker Intensif</a>
</td>
</tr>
<tr>
<td>Vendredi 27 septembre 2024</td>
<td>
<a href="1.yml.html">Docker Intensif</a>
</td>
</tr>
<tr>
<td>Mardi 1er octobre 2024</td>
<td>
<a href="2.yml.html">Fondamentaux Kubernetes</a>
</td>
</tr>
<tr>
<td>Mercredi 2 octobre 2024</td>
<td>
<a href="2.yml.html">Fondamentaux Kubernetes</a>
</td>
</tr>
<tr>
<td>Jeudi 3 octobre 2024</td>
<td>
<a href="2.yml.html">Fondamentaux Kubernetes</a>
</td>
</tr>
<tr>
<td>Vendredi 4 octobre 2024</td>
<td>
<a href="2.yml.html">Fondamentaux Kubernetes</a>
</td>
</tr>
<tr>
<td>Lundi 7 octobre 2024</td>
<td>
<a href="4.yml.html">Kubernetes Avancé</a>
</td>
</tr>
<tr>
<td>Mardi 8 octobre 2024</td>
<td>
<a href="4.yml.html">Kubernetes Avancé</a>
</td>
</tr>
<tr>
<td>Mercredi 9 octobre 2024</td>
<td>
<a href="4.yml.html">Kubernetes Avancé</a>
</td>
</tr>
<tr>
<td>Jeudi 10 octobre 2024</td>
<td>
<a href="4.yml.html">Kubernetes Avancé</a>
</td>
</tr>
<tr>
<td>Vendredi 11 octobre 2024</td>
<td>
<a href="5.yml.html">Opérer Kubernetes</a>
</td>
</tr>
<tr>
<td>Lundi 14 octobre 2024</td>
<td>
<a href="5.yml.html">Opérer Kubernetes</a>
</td>
</tr>
<tr>
<td>Mardi 15 octobre 2024</td>
<td>
<a href="5.yml.html">Opérer Kubernetes</a>
</td>
</tr>
<tr>
<td>Mercredi 16 octobre 2024</td>
<td>
<a href="3.yml.html">Packaging d'applications pour Kubernetes</a>
</td>
</tr>
<tr>
<td>Jeudi 17 octobre 2024</td>
<td>
<a href="3.yml.html">Packaging d'applications pour Kubernetes</a>
</td>
</tr>
<tr>
<td>Vendredi 18 octobre 2024</td>
<td>
<a href="3.yml.html">Packaging d'applications pour Kubernetes</a>
</td>
</tr>
</table>
</body>
</html>

72
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@@ -0,0 +1,72 @@
title: |
Introduction
to Containers
chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics.md
- containers/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
-
#- containers/Docker_Overview.md
#- containers/Docker_History.md
- containers/Training_Environment.md
#- containers/Installing_Docker.md
- containers/First_Containers.md
- containers/Background_Containers.md
#- containers/Start_And_Attach.md
- containers/Naming_And_Inspecting.md
#- containers/Labels.md
- containers/Getting_Inside.md
- containers/Initial_Images.md
-
- containers/Building_Images_Interactively.md
- containers/Building_Images_With_Dockerfiles.md
- containers/Cmd_And_Entrypoint.md
- containers/Copying_Files_During_Build.md
- containers/Exercise_Dockerfile_Basic.md
-
- containers/Container_Networking_Basics.md
#- containers/Network_Drivers.md
- containers/Local_Development_Workflow.md
- containers/Container_Network_Model.md
- shared/yaml.md
- containers/Compose_For_Dev_Stacks.md
- containers/Exercise_Composefile.md
-
- containers/Multi_Stage_Builds.md
#- containers/Publishing_To_Docker_Hub.md
- containers/Dockerfile_Tips.md
- containers/Exercise_Dockerfile_Advanced.md
#- containers/Docker_Machine.md
#- containers/Advanced_Dockerfiles.md
#- containers/Buildkit.md
#- containers/Init_Systems.md
#- containers/Application_Configuration.md
#- containers/Logging.md
#- containers/Namespaces_Cgroups.md
#- containers/Copy_On_Write.md
#- containers/Containers_From_Scratch.md
#- containers/Container_Engines.md
#- containers/Pods_Anatomy.md
#- containers/Ecosystem.md
#- containers/Orchestration_Overview.md
- shared/thankyou.md
- containers/links.md

View File

@@ -0,0 +1,73 @@
title: |
Introduction
to Containers
chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- in-person
content:
- shared/title.md
# - shared/logistics.md
- containers/intro.md
- shared/about-slides.md
#- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
- - containers/Docker_Overview.md
- containers/Docker_History.md
- containers/Training_Environment.md
- containers/Installing_Docker.md
- containers/First_Containers.md
- containers/Background_Containers.md
- containers/Start_And_Attach.md
- - containers/Initial_Images.md
- containers/Building_Images_Interactively.md
- containers/Building_Images_With_Dockerfiles.md
- containers/Cmd_And_Entrypoint.md
- containers/Copying_Files_During_Build.md
- containers/Exercise_Dockerfile_Basic.md
- - containers/Multi_Stage_Builds.md
- containers/Publishing_To_Docker_Hub.md
- containers/Dockerfile_Tips.md
- containers/Exercise_Dockerfile_Advanced.md
- - containers/Naming_And_Inspecting.md
- containers/Labels.md
- containers/Getting_Inside.md
- - containers/Container_Networking_Basics.md
- containers/Network_Drivers.md
- containers/Container_Network_Model.md
#- containers/Connecting_Containers_With_Links.md
- containers/Ambassadors.md
- - containers/Local_Development_Workflow.md
- containers/Windows_Containers.md
- containers/Working_With_Volumes.md
- shared/yaml.md
- containers/Compose_For_Dev_Stacks.md
- containers/Exercise_Composefile.md
- containers/Docker_Machine.md
- - containers/Advanced_Dockerfiles.md
- containers/Buildkit.md
- containers/Init_Systems.md
- containers/Application_Configuration.md
- containers/Logging.md
- containers/Resource_Limits.md
- - containers/Namespaces_Cgroups.md
- containers/Copy_On_Write.md
#- containers/Containers_From_Scratch.md
- - containers/Container_Engines.md
- containers/Pods_Anatomy.md
- containers/Ecosystem.md
- containers/Orchestration_Overview.md
- shared/thankyou.md
- containers/links.md

81
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@@ -0,0 +1,81 @@
title: |
Introduction
to Containers
chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics.md
- containers/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
- # DAY 1
- containers/Docker_Overview.md
#- containers/Docker_History.md
- containers/Training_Environment.md
- containers/First_Containers.md
- containers/Background_Containers.md
- containers/Initial_Images.md
-
- containers/Building_Images_Interactively.md
- containers/Building_Images_With_Dockerfiles.md
- containers/Cmd_And_Entrypoint.md
- containers/Copying_Files_During_Build.md
- containers/Exercise_Dockerfile_Basic.md
-
- containers/Dockerfile_Tips.md
- containers/Multi_Stage_Builds.md
- containers/Publishing_To_Docker_Hub.md
- containers/Exercise_Dockerfile_Advanced.md
-
- containers/Naming_And_Inspecting.md
- containers/Labels.md
- containers/Start_And_Attach.md
- containers/Getting_Inside.md
- containers/Resource_Limits.md
- # DAY 2
- containers/Container_Networking_Basics.md
- containers/Network_Drivers.md
- containers/Container_Network_Model.md
-
- containers/Local_Development_Workflow.md
- containers/Working_With_Volumes.md
- shared/yaml.md
- containers/Compose_For_Dev_Stacks.md
- containers/Exercise_Composefile.md
-
- containers/Installing_Docker.md
- containers/Container_Engines.md
- containers/Init_Systems.md
- containers/Advanced_Dockerfiles.md
- containers/Buildkit.md
-
- containers/Application_Configuration.md
- containers/Logging.md
- containers/Orchestration_Overview.md
-
- shared/thankyou.md
- containers/links.md
#-
#- containers/Docker_Machine.md
#- containers/Ambassadors.md
#- containers/Namespaces_Cgroups.md
#- containers/Copy_On_Write.md
#- containers/Containers_From_Scratch.md
#- containers/Pods_Anatomy.md
#- containers/Ecosystem.md

View File

@@ -42,19 +42,22 @@ ArgoCD manages **applications** by **syncing** their **live state** with their *
- It's OK to use local clusters (kind, minikube...)
- We need to install the ArgoCD CLI ([argocd-packages], [argocd-binaries])
- We need to install the ArgoCD CLI ([packages], [binaries])
- **Highly recommended:** set up CLI completion!
- Of course we'll need a Git service, too
[packages]: https://argo-cd.readthedocs.io/en/stable/cli_installation/
[binaries]: https://github.com/argoproj/argo-cd/releases/latest
---
## Setting up ArgoCD
- The easiest way is to use upstream YAML manifests
- There is also a [Helm chart][argocd-helmchart] if we need more customization
- There is also a [Helm chart][argohelmchart] if we need more customization
.lab[
@@ -67,6 +70,8 @@ ArgoCD manages **applications** by **syncing** their **live state** with their *
]
[argohelmchart]: https://artifacthub.io/packages/helm/argo/argocd-apps
---
## Logging in with the ArgoCD CLI
@@ -132,6 +137,8 @@ ArgoCD manages **applications** by **syncing** their **live state** with their *
- Let's have a look at ArgoCD architecture!
[issue14167]: https://github.com/argoproj/argo-cd/issues/14167
---
class: pic
@@ -190,6 +197,8 @@ It is responsible for invoking any user-defined hooks for lifecycle events (*Pre
- If you create a new, empty repository, add some manifests to it
[kubercoins]: https://github.com/jpetazzo/kubercoins
---
## Add an Application
@@ -259,6 +268,8 @@ It is responsible for invoking any user-defined hooks for lifecycle events (*Pre
🤔 We're getting errors!
[pollinginterval]: https://argo-cd.readthedocs.io/en/stable/faq/#how-often-does-argo-cd-check-for-changes-to-my-git-or-helm-repository
---
## Sync failed
@@ -446,6 +457,8 @@ Then click on the "CREATE" button (top left).
- Today we'll just turn on automated sync for the staging namespace
[rollouts]: https://argoproj.github.io/rollouts/
---
## Enabling auto-sync
@@ -502,7 +515,7 @@ git push origin staging
- Let's how to deploy Helm charts with ArgoCD!
- In the [kubercoins] repository, there is a branch called [helm-branch]
- In the [kubercoins] repository, there is a branch called [helm]
- It provides a generic Helm chart, in the [generic-service] directory
@@ -510,6 +523,12 @@ git push origin staging
- Let's create one application for each of the 5 components of our app!
[cmp]: https://argo-cd.readthedocs.io/en/stable/operator-manual/config-management-plugins/
[kubercoins]: https://github.com/jpetazzo/kubercoins
[helm]: https://github.com/jpetazzo/kubercoins/tree/helm
[generic-service]: https://github.com/jpetazzo/kubercoins/tree/helm/generic-service
[values]: https://github.com/jpetazzo/kubercoins/tree/helm/values
---
## Creating a Helm Application
@@ -560,6 +579,10 @@ git push origin staging
(blue/green, canary...)
[sso]: https://argo-cd.readthedocs.io/en/stable/operator-manual/user-management/#sso
[Dex]: https://github.com/dexidp/dex
[rollouts]: https://argoproj.github.io/argo-rollouts/
---
## Acknowledgements
@@ -572,20 +595,6 @@ for contributing an initial version and suggestions to this ArgoCD chapter.
All remaining typos, mistakes, or approximations are mine (Jérôme Petazzoni).
[argocd-binaries]: https://github.com/argoproj/argo-cd/releases/latest
[argocd-helmchart]: https://artifacthub.io/packages/helm/argo/argocd-apps
[argocd-packages]: https://argo-cd.readthedocs.io/en/stable/cli_installation/
[cmp]: https://argo-cd.readthedocs.io/en/stable/operator-manual/config-management-plugins/
[Dex]: https://github.com/dexidp/dex
[generic-service]: https://github.com/jpetazzo/kubercoins/tree/helm/generic-service
[helm-branch]: https://github.com/jpetazzo/kubercoins/tree/helm
[issue14167]: https://github.com/argoproj/argo-cd/issues/14167
[kubercoins]: https://github.com/jpetazzo/kubercoins
[pollinginterval]: https://argo-cd.readthedocs.io/en/stable/faq/#how-often-does-argo-cd-check-for-changes-to-my-git-or-helm-repository
[rollouts]: https://argoproj.github.io/rollouts/
[sso]: https://argo-cd.readthedocs.io/en/stable/operator-manual/user-management/#sso
[values]: https://github.com/jpetazzo/kubercoins/tree/helm/values
???
:EN:- Implementing gitops with ArgoCD

View File

@@ -1,173 +0,0 @@
# Bento & PostgreSQL
- Bento can also use SQL databases for input/output
- We're going to demonstrate that by writing to a PostgreSQL database
- That database will be deployed with the Cloud Native PostGres operator
(https://cloudnative-pg.io/)
---
## CNPG in a nutshell
- Free, open source
- Originally created by [EDB] (EnterpriseDB, well-known PgSQL experts)
- Non-exhaustive list of features:
- provisioning of Postgres servers, replicas, bouncers
- automatic failover
- backups (full backups and WAL shipping)
- provisioning from scratch, from backups, PITR
- manual and automated switchover (e.g. for node maintenance)
- and many more!
[EDB]: https://www.enterprisedb.com/workload/kubernetes
---
## What we're going to do
1. Install CNPG.
2. Provision a Postgres cluster.
3. Configure Bento to write to that cluster.
4. Set up a Grafana dashboard to see the data.
---
## 1⃣ Installing CNPG
Many options available, see the [documentation][cnpg-install]:
- raw YAML manifests
- kubectl CNPG plugin (`kubectl cnpg install generate`)
- Helm chart
- OLM
[cnpg-install]: https://cloudnative-pg.io/documentation/1.24/installation_upgrade/
---
## 2⃣ Provisioning a Postgres cluster
Minimal manifest:
```yaml
apiVersion: postgresql.cnpg.io/v1
kind: Cluster
metadata:
name: db
spec:
storage:
size: 1Gi
```
---
class: extra-details
## For production...
We might also add:
- `spec.monitoring.enablePodMonitor: true`
- `spec.instances: 2`
- `resources.{requests,limits}.{cpu,memory}`
- `walStorage.size`
- `backup`
- `postgresql.parameters`
See [this manifest][cluster-maximal] for a detailed example.
[cluster-maximal]: https://github.com/jpetazzo/pozok/blob/main/cluster-maximal.yaml
---
## 3⃣ Configuring Bento to write to SQL
- We'll use the [`sql_insert`][sql-insert] output
- If our cluster is named `mydb`, there will be a Secret `mydb-app`
- This Secret will contain a `uri` field
- That field can be used as the `dns` in the Bento configuration
- We will also need to create the table that we want to use
(see next slide for instructions)
[sql-insert]: https://warpstreamlabs.github.io/bento/docs/components/outputs/sql_insert
---
## Creating a table
- If we just want to store the city name and its population:
```sql
CREATE TABLE IF NOT EXISTS cities (
city varchar(100) NOT NULL,
population integer
);
```
- This statement can be executed:
- manually, by getting a `psql` shell with `kubectl cnpg psql mydb app`
- automatically, with Bento's `init_statatement`
---
## 4⃣ Viewing the table in Grafana
- In Grafana, in the home menu on the lift, click "connections"
- Add a PostgreSQL data source
- Enter the host:port, database, user, password
- Then add a visualization using that data source
(it should be relatively self-explanatory!)
---
class: extra-details
## Automating it all
- Expose PostgreSQL credentials through environment variables
(in the Bento container)
- Use the `${...}` syntax in Bento to use these environment variables
- Export the Grafana dashboard to a JSON file
- Store the JSON file in a ConfigMap, with label `grafana_dashboard=1`
- Create that ConfigMap in the namespace where Grafana is running
- Similarly, data sources (like the Redis and the PostgreSQL one) can be defined in YAML
- And that YAML can be put in a ConfigMap with label `grafana_datasource=1`

View File

@@ -1,450 +0,0 @@
# Autoscaling with KEDA
- Cluster autoscaling = automatically add nodes *when needed*
- *When needed* = when Pods are `Pending`
- How do these pods get created?
- When the Ollama Deployment is scaled up
- ... manually (e.g. `kubectl scale`)
- ... automatically (that's what we want to investigate now!)
---
## Ways to implement autoscaling
- Custom code
(e.g. crontab checking some value every few minutes and scaling accordingly)
- Kubernetes Horizontal Pod Autoscaler v1
(aka `kubectl autoscale`)
- Kubernetes Horizontal Pod Autoscaler v2 with custom metrics
(e.g. with Prometheus Adapter)
- Kubernetes Horizontal Pod Autoscaler v2 with external metrics
(e.g. with KEDA)
---
## Custom code
- No, we're not going to do that!
- But this would be an interesting exercise in RBAC
(setting minimal amount of permissions for the pod running our custom code)
---
## HPAv1
Pros: very straightforward
Cons: can only scale on CPU utilization
How it works:
- periodically measures average CPU *utilization* across pods
- if utilization is above/below a target (default: 80%), scale up/down
---
## HPAv1 in practice
- Create the autoscaling policy:
```bash
kubectl autoscale deployment ollama --max=1000
```
(The `--max` is required; it's a safety limit.)
- Check it:
```bash
kubectl describe hpa
```
- Send traffic, wait a bit: pods should be created automatically
---
## HPAv2 custom vs external
- Custom metrics = arbitrary metrics attached to Kubernetes objects
- External metrics = arbitrary metrics not related to Kubernetes objects
--
🤔
---
## HPAv2 custom metrics
- Examples:
- on Pods: CPU, RAM, network traffic...
- on Ingress: requests per second, HTTP status codes, request duration...
- on some worker Deployment: number of tasks processed, task duration...
- Requires an *adapter* to:
- expose the metrics through the Kubernetes *aggregation layer*
- map the actual metrics source to Kubernetes objects
Example: the [Prometheus adapter][prometheus-adapter]
[prometheus-adapter]: https://github.com/kubernetes-sigs/prometheus-adapter
---
## HPAv2 custom metrics in practice
- We're not going to cover this here
(too complex / not enough time!)
- If you want more details, check [my other course material][hpav2slides]
[hpav2slides]: https://2024-10-enix.container.training/4.yml.html#toc-scaling-with-custom-metrics
---
## HPAv2 external metrics
- Examples:
- arbitrary Prometheus query
- arbitrary SQL query
- number of messages in a queue
- and [many, many more][keda-scalers]
- Also requires an extra components to expose the metrics
Example: [KEDA (https://keda.sh/)](https://keda.sh)
[keda-scalers]: https://keda.sh/docs/latest/scalers/
---
## HPAv2 external metrics in practice
- We're going to install KEDA
- And set it up to autoscale depending on the number of messages in Redis
---
## Installing KEDA
Multiple options (details in the [documentation][keda-deploy]):
- YAML
- Operator Hub
- Helm chart 💡
```bash
helm upgrade --install --repo https://kedacore.github.io/charts \
--namespace keda-system --create-namespace keda keda
```
[keda-deploy]: https://keda.sh/docs/latest/deploy/
---
## Scaling according to Redis
- We need to create a KEDA Scaler
- This is done with a "ScaledObject" manifest
- [Here is the documentation][keda-redis-lists] for the Redis Lists Scaler
- Let's write that manifest!
[keda-redis-lists]: https://keda.sh/docs/latest/scalers/redis-lists/
---
## `keda-redis-scaler.yaml`
```yaml
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
name: ollama
spec:
scaleTargetRef:
name: ollama
triggers:
- type: redis
metadata:
address: redis.`default`.svc:6379
listName: cities
listLength: "10"
```
---
## Notes
- We need to update the `address` field with our namespace
(unless we are running in the `default` namespace)
- Alternative: use `addressFromEnv` and set an env var in the Ollama pods
- `listLength` gives the target ratio of `messages / replicas`
- In our example, KEDA will scale the Deployment to `messages / 100`
(rounded up!)
---
## Trying it out
- Apply the ScaledObject manifest
- Start a Bento pipeline loading e.g. 100-1000 cities in Redis
(100 on smaller clusters / slower CPUs, 1000 on bigger / faster ones)
- Check pod and nod resource usage
- What do we see?
--
🤩 The Deployment scaled up automatically!
--
🤔 But Pod resource usage remains very low (A few busy pods, many idle)
--
💡 Bento doesn't submit enough requests in parallel!
---
## Improving throughput
We're going to review multiple techniques:
1. Increase parallelism inside the Bento pipeline.
2. Run multiple Bento consumers.
3. Couple consumers and processors more tightly.
---
## 1⃣ Increase pipeline parallelism
- Set `parallel` to `true` in the `http` processor
- Wrap the input around a `batched` input
(otherwise, we don't have enough messages in flight)
- Increase `http` timeout significantly (e.g. to 5 minutes)
---
## Results
🎉 More messages flow through the pipeline
🎉 Many requests happen in parallel
🤔 Average Pod and Node CPU utilization is higher, but not maxed out
🤔 HTTP queue size (measured with HAProxy metrics) is relatively high
🤔 Latency is higher too
Why?
---
## Too many requests in parallel
- Ealier, we didn't have enough...
- ...Now, we have too much!
- However, for a very big request queue, it still wouldn't be enough
💡 We currently have a fixed parallelism. We need to make it dynamic!
---
## 2⃣ Run multiple Bento consumers
- Restore the original Bento configuration
(flip `parallel` back to `false`; remove the `batched` input)
- Run Bento in a Deployment
(e.g. with the [Bento Helm chart][bento-helm-chart])
- Autoscale that Deployment like we autoscaled the Ollama Deployment
[bento-helm-chart]: https://github.com/warpstreamlabs/bento-helm-chart
---
## Results
🤔🤔🤔 Pretty much the same as before!
(High throughput, high utilization but not maxed out, high latency...)
--
🤔🤔🤔 Why?
---
## Unbalanced load balancing
- All our requests go through the `ollama` Service
- We're still using the default Kubernetes service proxy!
- It doesn't spread the requests properly across all the backends
---
## 3⃣ Couple consumers and processors
What if:
--
instead of sending requests to a load balancer,
--
each queue consumer had its own Ollama instance?
---
## Current architecture
<pre class="mermaid">
flowchart LR
subgraph P1["Pod"]
H1["HAProxy"] --> O1["Ollama"]
end
subgraph P2["Pod"]
H2["HAProxy"] --> O2["Ollama"]
end
subgraph P3["Pod"]
H3["HAProxy"] --> O3["Ollama"]
end
Q["Queue<br/>(Redis)"] <--> C["Consumer<br/>(Bento)"] --> LB["Load Balancer<br/>(kube-proxy)"]
LB --> H1 & H2 & H3
</pre>
---
## Proposed architecture
<pre class="mermaid">
flowchart LR
subgraph P1["Consumer Pod"]
C1["Bento"] --> H1["HAProxy"] --> O1["Ollama"]
end
subgraph P2["Consumer Pod"]
C2["Bento"] --> H2["HAProxy"] --> O2["Ollama"]
end
subgraph P3["Consumer Pod"]
C3["Bento"] --> H3["HAProxy"] --> O3["Ollama"]
end
Queue["Queue"] <--> C1 & C2 & C3
</pre>
---
## 🏗️ Let's build something!
- Let's implement that architecture!
- See next slides for hints / getting started
---
## Hints
We need to:
- Update the Bento consumer configuration to talk to localhost
- Store that configuration in a ConfigMap
- Add a Bento container to the Ollama Deployment
- Profit!
---
## Results
🎉 Node and Pod utilization is maximized
🎉 HTTP queue size is bounded
🎉 Deployment autoscales up and down
---
## ⚠️ Scaling down
- Eventually, there are less messages in the queue
- The HPA scales down the Ollama Deployment
- This terminates some Ollama Pods
🤔 What happens if these Pods were processing requests?
--
- The requests might be lost!
---
## Avoiding lost messages
Option 1:
- cleanly shutdown the consumer
- make sure that Ollama can complete in-flight requests
(by extending its grace period)
- find a way to terminate Ollama when no more requests are in flight
Option 2:
- use *message acknowledgement*

View File

@@ -1,623 +0,0 @@
# Getting started with Bento
How can we move to a message queue architecture...
*...without rewriting a bunch of code?*
🤔
---
## Bento
https://bento.dev/
"Fancy stream processing made operationally mundane"
"Written in Go, deployed as a static binary, declarative configuration. Open source and cloud native as utter heck."
With ✨ amazing ✨ documentation 😍
---
class: extra-details
## Tiny bit of history
- Original project: Benthos
- May 30, 2024: [Redpanda acquires Benthos][redpanda-acquires-benthos]
- Benthos is now Redpanda Connect
- some parts have been relicensed as commercial products
- May 31, 2024: [Warpstream forks Benthos][warpstream-forks-benthos]
- that fork is named "Bento"
- it's fully open source
- We're going to use Bento here, but Redpanda Connect should work fine too!
---
## Bento concepts
- Message stream processor
- Each pipeline is configured by a YAML configuration that defines:
- input (where do we get the messages?)
- pipeline (optional: how do we transform the messages?)
- output (where do we put the messages afterwards?)
- Once Bento is started, it runs the pipelines forever
(except for pipelines that have a logical end, e.g. reading from a file)
- Embedded language (Bloblang) to manipulate/transform messages
---
## Messages
- Typically JSON objects
(but raw strings are also possible)
- Nesting, arrays, etc. are OK
---
## Getting started with Bento
We're going to:
1. Import a bunch of cities from a CSV file into a Redis queue.
2. Read back these cities using a web server.
3. Use an "enrichment workflow" to query our LLM for each city.
---
## 1⃣ Importing cities
Let's break down the work:
- download the data set
- create the Bento configuration
- deploy Redis
- start Bento
---
## Downloading the data set
- Example database:
https://www.kaggle.com/datasets/juanmah/world-cities
- Let's download and uncompress the data set:
```bash
curl -fsSL https://www.kaggle.com/api/v1/datasets/download/juanmah/world-cities |
funzip > cities.csv
```
(Ignore the "length error", it's harmless!)
- Check the structure of the data set:
```bash
head cities.csv
```
---
## Creating the Bento configuration
- We need to find which `input` and `output` to use
- Check the list with `bento list` or the [documentation][bento-inputs]
- Then run `bento create INPUTNAME/PIPELINENAME/OUTPUTNAME`
- Generate a configuration file:
```bash
bento create csv//redis_list > csv2redis.yaml
```
- Edit that configuration file; look for the `(required)` parameters
(Everything else can go away!)
---
## Resulting configuration
If we trim all the default values, here is the result:
```yaml
input:
csv:
paths: ["cities.csv"]
output:
redis_list:
url: redis://redis:6379 # No default (required)
key: cities
```
We'll call that value `csv2redis.yaml`.
---
## Deploying Redis
- Create a Deployment:
```bash
kubectl create deployment redis --image redis
```
- Expose it:
```bash
kubectl expose deployment redis --port 6379
```
---
## Starting Bento
Option 1: run it manually in a pod, to see what's going on.
```bash
bento --config csv2redis.yaml
```
Option 2: run it with e.g. the Bento Helm chart.
*We're not going to do that yet, since this particular pipeline has a logical end.*
*(The Helm chart is best suited to pipelines that run forever.)*
---
## Expected output
.small[
```
INFO Running main config from specified file @service=bento bento_version="" path=csv2redis.yaml
INFO Launching a Bento instance, use CTRL+C to close @service=bento
INFO Listening for HTTP requests at: http://0.0.0.0:4195 @service=bento
INFO Input type csv is now active @service=bento label="" path=root.input
INFO Output type redis_list is now active @service=bento label="" path=root.output
INFO Pipeline has terminated. Shutting down the service @service=bento
```
]
The pipeline should complete in just a few seconds.
---
## Checking what's in Redis
- Connect to our Redis instance:
```bash
redis-cli -h redis
```
- List keys:
```redis
KEYS *
```
- Check that the `cities` list has approx. 47000 elements:
```redis
LLEN cities
```
- Get the first element of the list:
```redis
LINDEX cities 0
```
---
## Fun with Bloblang
- Let's add a filter to keep only cities with a population above 10,000,000
- Add the following block to the Bento configuration:
```yaml
pipeline:
processors:
- switch:
- check: this.population == ""
processors:
- mapping: root = deleted()
- check: this.population.int64() < 10000000
processors:
- mapping: root = deleted()
```
(See the [docs][bento-switch] for details about the `switch` processor.)
---
## Testing our processor
- First, delete the existing `cities` list:
```bash
redis-cli -h redis DEL cities
```
- Then, run the Bento pipeline again:
```bash
bento --config csv2redis.yaml
```
(It should complain about a few cities where the population has a decimal point.)
- Check how many cities were loaded:
```bash
redis-cli -h redis LLEN cities
```
(There should be 47.)
---
## 2⃣ Consume the queue over HTTP
- We want to "get the next city" in the queue with a simple `curl`
- Our input will be `redis_list`
- Our output will be `http_server`
---
## Generate the Bento configuration
Option 1: `bento create redis_list//http_server`
Option 2: [read the docs][output-http-server]
---
## 🙋 Choose your own adventure
Do you want to try to write that configuration?
Or shall we see it right away?
--
⚠️ Spoilers on next slide!
---
## `redis2http.yaml`
```yaml
input:
redis_list:
url: redis://redis:`6379`
key: cities
output:
http_server:
path: /nextcity
```
This will set up an HTTP route to fetch *one* city.
It's also possible to batch, stream...
⚠️ As of November 2024, `bento create` uses port 6397 instead of 6379 for Redis!
---
## Trying it out
- Run Bento with this configuration:
```bash
bento --config redis2http.yaml &
```
- Retrieve one city:
```bash
curl http://localhost:4195/nextcity
```
- Check what happens after we retrive *all* the cities!
---
## 3⃣ Query our LLM for each city
- We want to ask our LLM who's the mayor of each of these cities
- We'll use a prompt that will usually ensure a short answer
(so that it's faster; we don't want to wait 30 seconds per city!)
- We'll test the prompt with the Ollama CLI
- Then we'll craft a proper HTTP API query
- Finally, we'll configure an [enrichment workflow][enrichment] in Bento
---
## Test our prompt
Assuming that our earlier Ollama Deployment is still running:
```bash
kubectl exec deployment/ollama -- \
ollama run qwen2:1.5b "
Who is the mayor of San Francisco?
Just give the name by itself on a single line.
If you don't know, don't say anything.
"
```
---
## Turn the prompt into an HTTP API query
Note: to install `http` in an Alpine container, run `apk add httpie`.
```bash
http http://ollama.default:11434/api/generate \
model=qwen2:1.5b stream:=false prompt="
Who is the mayor of Paris?
Just give the name by itself on a single line.
If you don't know, don't say anything.
"
```
We get a JSON payload, and we want to use the `response` field.
---
## Configure an enrichment workflow
The [Bento documentation][enrichment] is really good!
We need to set up:
- a `branch` processor
- a `request_map` to transform the city into an Ollama request
- an `http` processor to submit the request to Ollama
- a `result_map` to transform the Ollama response
---
## Without the `branch` processor
<pre class="mermaid">
flowchart LR
CITY["
city: Paris
country: France
population: 1106000
iso2: FR
...
"]
REQ["
model: qwen2:1.5b
stream: false
prompt: Who is the mayor of Paris?
"]
REP["
response: Anne Hidalgo
eval_count: ...
prompt_eval_count: ...
(other ollama fields)
"]
CITY@{ shape: card}
REQ@{ shape: card}
REP@{ shape: card}
style CITY text-align: left
style REQ text-align: left
style REP text-align: left
mapping@{ shape: diam }
http["http processor"]@{ shape: diam }
CITY --> mapping --> REQ --> http --> REP
</pre>
- We transform the `city` into an Ollama request
- The `http` processor submits the request to Ollama
- The final output is the Ollama response
---
## With the `branch` processor
<pre class="mermaid">
flowchart LR
CITY["
city: Paris
country: France
population: 1106000
iso2: FR
...
"]
REQ["
model: qwen2:1.5b
stream: false
prompt: Who is the mayor of Paris?
"]
REP["
response: Anne Hidalgo
eval_count: ...
prompt_eval_count: ...
(other ollama fields)
"]
OUT["
city: Paris
country: France
population: 1106000
iso2: FR
...
mayor: Anne Hidalgo
"]
CITY@{ shape: card}
REQ@{ shape: card}
REP@{ shape: card}
OUT@{ shape: card}
style CITY text-align: left
style REQ text-align: left
style REP text-align: left
style OUT text-align: left
branch@{ shape: diam }
request_map@{ shape: diam }
result_map@{ shape: diam }
http["http processor"]@{ shape: diam }
CITY --> branch
branch --> result_map
branch --> request_map
request_map --> REQ
REQ --> http
http --> REP
REP --> result_map
result_map --> OUT
</pre>
- The `branch` processor allows doing the processing "on the side"
- `request_map` and `result_map` transform the message before/after processing
- Then, the result is combined with the original message (the `city`)
---
```yaml
input:
csv:
paths: ["cities.csv"]
pipeline:
processors:
- branch:
request_map: |
root.model = "qwen2:1.5b"
root.stream = false
root.prompt = (
"Who is the mayor of %s? ".format(this.city) +
"Just give the name by itself on a single line. " +
"If you don't know, don't say anything."
)
processors:
- http:
url: http://ollama:11434/api/generate
verb: POST
result_map: |
root.mayor = this.response
```
---
## Trying it out
- Save the YAML on the previous page into a configuration file
- Run Bento with that configuration file
- What happens?
--
🤔 We're seeing errors due to timeouts
```
ERRO HTTP request to 'http://ollama...' failed: http://ollama...:
Post "http://ollama...": context deadline exceeded
(Client.Timeout exceeded while awaiting headers)
```
---
## 🙋 Choose your own adventure
How should we address errors?
- Option 1: increase the timeout in the [http][bento-http] processor
- Option 2: use a [retry][bento-retry] processor in the pipeline
- Option 3: use a [reject_errored][bento-reject] output
---
## 🏗️ Let's build something!
- We want to process 1000 cities with our LLM
(guessing who the mayor is, or something similar)
- Store the output wherever we want
(Redis, CSV file, JSONL files...)
- Deal correctly with errors
(we'll check that there are, indeed, 1000 cities in the output)
- Scale out to process faster
(scale ollama to e.g. 10 replicas, enable parallelism in Bento)
---
class: title
🍱 Lunch time! 🍱
---
## What happened?
- If your Ollama pods have *resource requests*:
→ your cluster may have auto-scaled
- If your Ollama pods don't have *resource requests*:
→ you probably have a bunch of container restarts, due to out-of-memory errors
🤔 What's that about?
[bento-http]: https://warpstreamlabs.github.io/bento/docs/components/processors/http/
[bento-inputs]: https://warpstreamlabs.github.io/bento/docs/components/inputs/about/
[bento-reject]: https://warpstreamlabs.github.io/bento/docs/components/outputs/reject_errored
[bento-retry]: https://warpstreamlabs.github.io/bento/docs/components/processors/retry
[bento-switch]: https://warpstreamlabs.github.io/bento/docs/components/processors/switch/
[enrichment]: https://warpstreamlabs.github.io/bento/cookbooks/enrichments/
[output-http-server]: https://warpstreamlabs.github.io/bento/docs/components/outputs/http_server
[redpanda-acquires-benthos]: https://www.redpanda.com/press/redpanda-acquires-benthos
[warpstream-forks-benthos]: https://www.warpstream.com/blog/announcing-bento-the-open-source-fork-of-the-project-formerly-known-as-benthos

View File

@@ -1,250 +0,0 @@
# Bento & RabbitMQ
- In some of the previous runs, messages were dropped
(we start with 1000 messages in `cities` and have e.g. 955 in `mayors`)
- This is caused by various errors during processing
(e.g. too many timeouts; Bento being shutdown halfway through...)
- ...And by the fact that we are using a Redis queue
(which doesn't offer delivery guarantees or acknowledgements)
- Can we get something better?
---
## The problem
- Some inputs (like `redis_list`) don't support *acknowledgements*
- When a message is pulled from the queue, it is deleted immediately
- If the message is lost for any reason, it is lost permanently
---
## The solution
- Some inputs (like `amqp_0_9`) support acknowledgements
- When a message is pulled from the queue:
- it is not visible anymore to other consumers
- it needs to be explicitly acknowledged
- The acknowledgement is done by Bento when the message reaches the output
- The acknowledgement deletes the message
- No acknowledgement after a while? Consumer crashes/disconnects?
Message gets requeued automatically!
---
## `amqp_0_9`
- Protocol used by RabbitMQ
- Very simplified behavior:
- messages are published to an [*exchange*][amqp-exchanges]
- messages have a *routing key*
- the exchange routes the message to one (or zero or more) queues
</br>(possibly using the routing key or message headers to decide which queue(s))
- [*consumers*][amqp-consumers] subscribe to queues to receive messages
[amqp-exchanges]: https://www.rabbitmq.com/tutorials/amqp-concepts#exchanges
[amqp-consumers]: https://www.rabbitmq.com/tutorials/amqp-concepts#consumers
---
## Using the default exchange
- There is a default exchange (called `""` - empty string)
- The routing key indicates the name of the queue to deliver to
- The queue needs to exist (we need to create it beforehand)
---
class: extra-details
## Defining custom exchanges
- Create an exchange
- exchange types: direct, fanout, topic, headers
- durability: persisted to disk to survive server restart or not?
- Create a binding
- which exchange?
- which routing key? (for direct exchanges)
- which queue?
---
## RabbitMQ on Kubernetes
- RabbitMQ can be deployed on Kubernetes:
- directly (creating e.g. a StatefulSet)
- with the RabbitMQ operator
- We're going to do the latter!
- The operator includes the "topology operator"
(to configure queues, exchanges, and bindings through custom resources)
---
## Installing the RabbitMQ operator
- Let's install it with this Helm chart:
```bash
helm upgrade --install --repo https://charts.bitnami.com/bitnami \
--namespace rabbitmq-system --create-namespace \
rabbitmq-cluster-operator rabbitmq-cluster-operator
```
---
## Deploying a simple RabbitMQ cluster
- Let's use the YAML manifests in that directory:
https://github.com/jpetazzo/beyond-load-balancers/tree/main/rabbitmq
- This creates:
- a `RabbitmqCluster` called `mq`
- a `Secret` called `mq-default-user` containing access credentials
- a durable `Queue` named `q1`
(We can ignore the `Exchange` and the `Binding`, we won't use them.)
---
## 🏗️ Let's build something!
Let's replace the `cities` Redis list with our RabbitMQ queue.
(See next slide for steps and hints!)
---
## Steps
1. Edit the Bento configuration for our "CSV importer".
(replace the `redis_list` output with `amqp_0_9`)
2. Run that pipeline and confirm that messages show up in RabbitMQ.
3. Edit the Bento configuration for the Ollama consumer.
(replace the `redis_list` input with `amqp_0_9`)
4. Trigger a scale up of the Ollama consumer.
5. Update the KEDA Scaler to use RabbitMQ instead of Redis.
---
## 1⃣ Sending messages to RabbitMQ
- Edit our Bento configuration (the one feeding the CSV file to Redis)
- We want the following `output` section:
```yaml
output:
amqp_0_9:
exchange: ""
key: q1
mandatory: true
urls:
- "${AMQP_URL}"
```
- Then export the AMQP_URL environment variable using `connection_string` from Secret `mq-default-user`
💡 Yes, we can directly use environment variables in Bento configuration!
---
## 2⃣ Testing our AMQP output
- Run the Bento pipeline
- To check that our messages made it:
```bash
kubectl exec mq-server-0 -- rabbitmqctl list_queues
```
- We can also use Prometheus metrics, e.g. `rabbitmq_queue_messages`
---
## 3⃣ Receiving messages from RabbitMQ
- Edit our other Bento configuration (the one in the Ollama consumer Pod)
- We want the following `input` section:
```yaml
input:
amqp_0_9:
urls:
- `amqp://...:5672/`
queue: q1
```
---
## 4⃣ Triggering Ollama scale up
- If the autoscaler is configured to scale to zero, disable it
(easiest solution: delete the ScaledObject)
- Then manually scale the Deployment to e.g. 4 Pods
- Check that messages are processed and show up in the output
(it should still be a Redis list at this point)
---
## 5⃣ Autoscaling on RabbitMQ
- We need to update our ScaledObject
- Check the [RabbitMQ Queue Scaler][keda-rabbitmq]
- Multiple ways to pass the AMQP URL:
- hardcode it (easier solution for testing!)
- use `...fromEnv` and set environment variables in target pod
- create and use a TriggerAuthentication
💡 Since we have the AMQP URL in a Secret, TriggerAuthentication works great!
[keda-rabbitmq]: https://keda.sh/docs/latest/scalers/rabbitmq-queue/

View File

@@ -55,7 +55,6 @@
`cert-manager.io/allow-direct-injection: "true"`
- See [cert-manager documentation] for details
[cert-manager documentation]: https://cert-manager.io/docs/concepts/ca-injector/
- See [cert-manager documentation][docs] for details
[docs]: https://cert-manager.io/docs/concepts/ca-injector/

View File

@@ -272,9 +272,9 @@ This can be overridden by setting the annotation:
- Can express `minAvailable` or `maxUnavailable`
- See [documentation][doc-pdb] for details and examples
- See [documentation] for details and examples
[doc-pdb]: https://kubernetes.io/docs/tasks/run-application/configure-pdb/
[documentation]: https://kubernetes.io/docs/tasks/run-application/configure-pdb/
---

View File

@@ -225,4 +225,4 @@ consul agent -data-dir=/consul/data -client=0.0.0.0 -server -ui \
:EN:- Scheduling pods together or separately
:EN:- Example: deploying a Consul cluster
:FR:- Lancer des pods ensemble ou séparément
:FR:- Exemple : lancer un cluster Consul
:FR:- Example : lancer un cluster Consul

View File

@@ -75,7 +75,7 @@ This is (approximately) what we're going to do:
--repository=$GITHUB_REPO \
--branch=main \
--path=./clusters/$FLUX_CLUSTER \
--personal --private=false
--personal --public
```
]

View File

@@ -1,132 +0,0 @@
class: title
*Tell me and I forget.*
<br/>
*Teach me and I remember.*
<br/>
*Involve me and I learn.*
Misattributed to Benjamin Franklin
[(Probably inspired by Chinese Confucian philosopher Xunzi)](https://www.barrypopik.com/index.php/new_york_city/entry/tell_me_and_i_forget_teach_me_and_i_may_remember_involve_me_and_i_will_lear/)
---
## Hands-on sections
- There will be *a lot* of examples and demos
- If you are attending a live workshop:
- follow along with the demos, ask questions at any time
- if you can, try to run some of the examples and demos in your environment
- if things are going too fast, ask the trainer to slow down :)
- If you are watching a recording or only reading the slides:
- it is **strongly** recommended to run **all** the examples and demos
- take advantage of the fact that you can pause at any time
---
class: in-person
## Where are we going to run our containers?
---
class: in-person, pic
![You get a cluster](images/you-get-a-cluster.jpg)
---
## If you're attending a live training or workshop
- Each person gets a private lab environment
- Your lab environments will be available for the duration of the workshop
(check with your instructor to know exactly when they'll be shut down)
- Note that for budget reasons¹, your environment will be fairly modest
- scenario 1: 4 nodes with 2 cores and 4 GB RAM ; no cluster autoscaling
- scenario 2: 1 node with 4 cores and 8 GB RAM ; cluster autoscaling
.footnote[¹That cloud thing is mighty expensive, yo]
---
## Running your own lab environment
- If you are following a self-paced course...
- Or watching a replay of a recorded course...
- ...You will need to set up a local environment for the labs
*or*
- If you want to use a specific cloud provider...
- Or want to see these concepts "at scale"...
- ...You can set up your own clusters with whatever capacity suits you
---
## Deploying your own Kubernetes cluster
- You need cloud provider credentials for this
- Option 1: use the cloud provider CLI, web UI, ...
- Option 2: use [one of these Terraform configurations][one-kubernetes]
(set `cluster_name`, `node_size`, `max_nodes_per_pool`, `location`, and GO!)
[one-kubernetes]: https://github.com/jpetazzo/container.training/tree/main/prepare-labs/terraform/one-kubernetes
---
## Deploying your own Kubernetes cluster.red[**s**]
- If you want to deliver your own training or workshop:
- deployment scripts are available in the [prepare-labs] directory
- you can use them to automatically deploy many lab environments
- they support many different infrastructure providers
- they can deploy dozens (even hundreds) of clusters at a time
[prepare-labs]: https://github.com/jpetazzo/container.training/tree/main/prepare-labs
---
class: in-person
## Why don't we run containers locally?
- Installing this stuff can be hard on some machines
(32 bits CPU or OS... Laptops without administrator access... etc.)
- *"The whole team downloaded all these container images from the WiFi!
<br/>... and it went great!"* (Literally no-one ever)
- All you need is a computer (or even a phone or tablet!), with:
- an Internet connection
- a web browser
- an SSH client
- Some of the demos require multiple nodes to demonstrate scaling

View File

@@ -158,6 +158,8 @@
- Let's see the specific details for each of them!
[grpc]: https://grpc.github.io/grpc/core/md_doc_health-checking.html
---
## `httpGet`
@@ -294,6 +296,8 @@ class: extra-details
- Leverages standard [GRPC Health Checking Protocol][grpc]
[grpc]: https://grpc.github.io/grpc/core/md_doc_health-checking.html
---
## Timing and thresholds
@@ -509,10 +513,7 @@ class: extra-details
- Sometimes it can also make sense to embed a web server in the worker
[grpc]: https://grpc.github.io/grpc/core/md_doc_health-checking.html
???
:EN:- Using healthchecks to improve availability
:FR:- Utiliser des *healthchecks* pour améliorer la disponibilité

View File

@@ -1,165 +0,0 @@
# Managing our stack with `helmfile`
- We've installed a few things with Helm
- And others with raw YAML manifests
- Perhaps you've used Kustomize sometimes
- How can we automate all this? Make it reproducible?
---
## Requirements
- We want something that is *idempotent*
= running it 1, 2, 3 times, should only install the stack once
- We want something that handles udpates
= modifying / reconfiguring without restarting from scratch
- We want something that is configurable
= with e.g. configuration files, environment variables...
- We want something that can handle *partial removals*
= ability to remove one element without affecting the rest
- Inspiration: Terraform, Docker Compose...
---
## Shell scripts?
✅ Idempotent, thanks to `kubectl apply -f`, `helm upgrade --install`
✅ Handles updates (edit script, re-run)
✅ Configurable
❌ Partial removals
If we remove an element from our script, it won't be uninstalled automatically.
---
## Umbrella chart?
Helm chart with dependencies on other charts.
✅ Idempotent
✅ Handles updates
✅ Configurable (with Helm values: YAML files and `--set`)
✅ Partial removals
❌ Complex (requires to learn advanced Helm features)
❌ Requires everything to be a Helm chart (adds (lots of) boilerplate)
---
## Helmfile
https://github.com/helmfile/helmfile
✅ Idempotent
✅ Handles updates
✅ Configurable (with values files, environment variables, and more)
✅ Partial removals
✅ Fairly easy to get started
🐙 Sometimes feels like summoning unspeakable powers / staring down the abyss
---
## What `helmfile` can install
- Helm charts from remote Helm repositories
- Helm charts from remote git repositories
- Helm charts from local directories
- Kustomizations
- Directories with raw YAML manifests
---
## How `helmfile` works
- Everything is defined in a main `helmfile.yaml`
- That file defines:
- `repositories` (remote Helm repositories)
- `releases` (things to install: Charts, YAML...)
- `environments` (optional: to specialize prod vs staging vs ...)
- Helm-style values file can be loaded in `enviroments`
- These values can then be used in the rest of the Helmfile
- Examples: [install essentials on a cluster][helmfile-ex-1], [run a Bento stack][helmfile-ex-2]
[helmfile-ex-1]: https://github.com/jpetazzo/beyond-load-balancers/blob/main/helmfile.yaml
[helmfile-ex-2]: https://github.com/jpetazzo/beyond-load-balancers/blob/main/bento/helmfile.yaml
---
## `helmfile` commands
- `helmfile init` (optional; downloads plugins if needed)
- `helmfile apply` (updates all releases that have changed)
- `helmfile sync` (updates all releases even if they haven't changed)
- `helmfile destroy` (guess!)
---
## Helmfile tips
As seen in [this example](https://github.com/jpetazzo/beyond-load-balancers/blob/main/bento/helmfile.yaml#L21):
- variables can be used to simplify the file
- configuration values and secrets can be loaded from external sources
(Kubernetes Secrets, Vault... See [vals] for details)
- current namespace isn't exposed by default
- there's often more than one way to do it!
(this particular section could be improved by using Bento `${...}`)
[vals]: https://github.com/helmfile/vals
---
## 🏗️ Let's build something!
- Write a helmfile (or two) to set up today's entire stack on a brand new cluster!
- Suggestion:
- one helmfile for singleton, cluster components
<br/>
(All our operators: Prometheus, Grafana, KEDA, CNPG, RabbitMQ Operator)
- one helmfile for the application stack
<br/>
(Bento, PostgreSQL cluster, RabbitMQ)

View File

@@ -96,7 +96,7 @@ class: extra-details
---
## Choose your own adventure!
## Choose your adventure!
- We present 3 methods to obtain a certificate

View File

@@ -195,4 +195,4 @@ class: extra-details
:EN:- Installing metrics-server
:EN:- Le *resource metrics pipeline*
:FR:- Installation de metrics-server
:FR:- Installtion de metrics-server

View File

@@ -1,53 +0,0 @@
## What we will / won't cover
- Kubernetes provides low-level building blocks (pods, deployments, services...)
- There are many high-level frameworks out there for serverless, AI...:
[Knative](https://knative.dev/docs/),
[KubeAI](https://www.kubeai.org/),
[Kueue](https://kueue.sigs.k8s.io/)...
- We're going to sit somewhere in the middle:
reimplement some of the features of these high-level frameworks, in a flexible way
- This workshop will (hopefully!) give you a better eye to evaluate these frameworks, too
- We won't showcase GPUs today for budget reasons
(giving everyone a few GPU nodes would be prohibitive, sorry!)
---
## A word about our demo app
- We'll use Ollama with a relatively small LLM
(qwen2:1.5b)
- We'll use it to generate very short completions
(a few seconds of CPU)
- All the challenges that we will address are also visible on longer requests
(in fact, they are even more visible on longer requests!)
- We're sticking to short requests to save time and cover a lot of ground today
(but feel free to use more expensive prompts if you'd like!)
---
## Tiny bit of backstory...
The original prompt that we used when building the first version of this content was:
```
If you go to {city}, I suggest that you
```
This would typically take 10-30 seconds - and with much bigger Kubernetes nodes.
Today, we suggest that we use a prompt that generates shorter answers!

View File

@@ -1,343 +0,0 @@
# Ollama in a nutshell
https://ollama.dev
"Get up and running with large language models"
"Docker, but for LLMs"
- Server to host (run) LLMs
- Controlled with CLI or API
- Download a model with `ollama pull`
- Run inference with `ollama run`
---
## Quick demo
⚠️ **Important note 1:** the commands in this section aren't meant
to be executed on your Kubernetes clusters. They are meant to
be executed on a local machine, and they assume that Ollama is
installed and running. If you don't have Ollama on your local
machine, it's OK to skip these demos!
⚠️ **Important note 2:** the models used by Ollama are fairly big
(1.5 GB for the one used here; up to 10s or 100s of GB for bigger
models). We do not recommend downloading them on conference WiFi.
Assuming Ollama is installed and running:
```
ollama run qwen2:1.5b "What's the solution to global warming?"
```
We're going to use this model because it's relatively small.
Many others are available (see https://ollama.dev/search).
---
## Other useful commands
- Start an interactive chat session:
```bash
ollama run qwen2:1.5b
```
- Pull an model (or check for updates):
```bash
ollama pull qwen2:1.5b
```
- See information on a model:
```bash
ollama show qwen2:1.5b
```
---
## Models on disk, in memory
- See models available on disk:
```bash
ollama list
```
- See models loaded in memory:
```bash
ollama ps
```
- Unload a model:
```bash
ollama stop qwen2:1.5b
```
Models are automatically unloaded after 5 minutes (by default).
Ollama loads models in RAM, and in VRAM if it detects a supported GPU.
---
# Ollama on Kubernetes
Let's run Ollama on our Kubernetes cluster!
- Option 1: `kubectl run`
- Option 2: create a Deployment and a Service
- Option 3: use a Helm chart
---
## 1⃣ `kubectl run`
Note: the `ollama/ollama` image is quite big (~2 GB transfer, ~4 GB on disk).
```bash
kubectl run ollama --image ollama/ollama
```
Wait for the pod to be up and running:
```bash
kubectl wait pod ollama --for=condition=Ready
```
(If that command times out, try again and/or specify a higher timeout.)
```bash
kubectl exec ollama -- ollama run qwen2:1.5b "What's Bach's best piece?"
```
Shutdown the pod:
```bash
kubectl delete pod ollama
```
---
## 2⃣ Deployment + Service
Create the Deployment:
```bash
kubectl create deployment ollama --image ollama/ollama
```
Create the Service:
```bash
kubectl create service clusterip ollama --tcp 11343
```
Wait for the Service Endpoints to be available:
```bash
kubectl wait endpoints ollama --for=jsonpath={..ip}
```
---
## By the way... Why port 11434?
| 1 | 1 | 4 | 3 | 4 |
|---|---|---|---|---|
| L | L | A | M | A |
---
## Connecting to the Service
Let's use the `/api/generate` endpoint:
```bash
kubectl run httpclient --rm -it --image alpine/httpie -- --ignore-stdin \
http://ollama:11434/api/generate \
model=qwen2:1.5b prompt="Write a limerick about Kubernetes"
```
(See [Ollama API docs](https://github.com/ollama/ollama/blob/main/docs/api.md#generate-a-completion) for details.)
--
🤔 We get an error: the model needs to be downloaded first.
💡 When we used the `ollama run` CLI command earlier, it did it automatically for us.
---
## Pulling the model
Method 1:
```bash
kubectl exec deployment/ollama -- ollama pull qwen2:1.5b
```
Method 2:
```bash
kubectl run httpclient --rm -it --image alpine/httpie -- --ignore-stdin \
http://ollama:11434/api/pull \
name=qwen2:1.5b
```
---
## Houston, we (are going to) have a problem...
- This works when there is only one pod
- What happens if we scale up the Deployment?
- We need to pull the model on every pod
- How should we do that?
---
## Potential solutions
- Bake the model into the image
🙅 Personal opinion: this is a bad idea (image size, maintenance...)
- Directly send a "pull" command to each pod, individually
🙁 Hackish, not great
- Use a Kubernetes lifecycle hook
💡 That works!
- Use a sidecar container to pull the model
🤔 Doable, but more work than the lifecycle hook
---
## 🙋 Choose your own adventure
Should we add that lifecycle hook?
---
## 3⃣ Helm chart
- Let's check the [ArtifactHUB] for an Ollama Helm chart
- The most popular (as of November 2024) is [this one, by OTWLD][ollama-chart]
- ~~It has pockets~~
- It can pre-pull models! 🎉
[ArtifactHub]: https://artifacthub.io
[ollama-chart]: https://artifacthub.io/packages/helm/ollama-helm/ollama
---
## Installing the Helm chart
Traditional method:
```bash
helm repo add ollama https://otwld.github.io/ollama-helm/
helm install ollama ollama/ollama --set ollama.models={qwen2:1.5b}
```
Idempotent¹, single-command method:
```bash
helm upgrade --install --repo https://otwld.github.io/ollama-helm/ \
ollama ollama --set ollama.models={qwen2:1.5b}
```
.footnote[¹Idempotent: which can be executed multiple times without adverse effect.]
---
## Testing the Helm installation
Just like before:
```bash
kubectl run httpclient --rm -it --image alpine/httpie -- --ignore-stdin \
http://ollama:11434/api/generate \
model=qwen2:1.5b prompt="Write a limerick about YAML" stream:=false
```
And while we're here, check resource usage:
```bash
kubectl exec deployment/ollama -ti -- top
```
There should be two processes:
- `ollama` itself, relatively small (~100 MB)
- the LLM subprocess, relatively big (~1.4 GB for qwen2:1.5b)
---
class: extra-details
## HTTPie
https://httpie.io/
- CLI client to send requests to web services
- Similar to curl, but made specifically to talk to API backends
```bash
httpie <URL> [key=value] [key=value] [key:=value]
```
- The `key=value` pairs get turned into a JSON object
- `key:=value` indicates a parameter to be sent "as-is"
(ideal for e.g. boolean or numbers)
---
## Sending some load
We're going to use `hey`:
```bash
kubectl run hey --rm -it --image nixery.dev/hey -- \
hey -c 10 -n 10 -t 60 -m POST \
-d '{"model": "qwen2:1.5b", "prompt": "vi or emacs?"}' \
http://ollama:11434/api/generate
```
Some explanations:
- `nixery.dev` = automatically generates images with [Nixery]
- `-c` = concurrent requests
- `-n` = total number of requests
- `-t` = timeout in seconds
This is probably going to take (literally) a minute.
[Nixery]: https://nixery.dev/
---
## Performance analysis
- Let's start an interactive container with `hey`
(e.g., use the `alpine` image, then `apk add hey`)
- Try 10 requests, with a concurrency of 1/2/4
- Meanwhile, check the logs of the `ollama` pod
- Some results (your results may vary depending on CPU, random seed...):
- 1 = 0.08 reqs/s, average latency: 12s
- 2 = 0.10 reqs/s, average latency: 18s
- 4 = 0.12 reqs/s, average latency: 28s
- Higher concurrency = slightly higher throughput, much higher latency
🤔 We need metrics!

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@@ -1,273 +0,0 @@
# Adding metrics
We want multiple kinds of metrics:
- instantaneous pod and node resource usage
- historical resource usage (=graphs)
- request duration
---
## 1⃣ Instantaneous resource usage
- We're going to use metrics-server
- Check if it's already installed:
```bash
kubectl top nodes
```
- If we see a list of nodes, with CPU and RAM usage:
*great, metrics-server is installed!*
- If we see `error: Metrics API not available`:
*metrics-server isn't installed, so we'll install it!*
---
## Installing metrics-server
- In a lot of places, this is done with a little bit of custom YAML
(derived from the [official installation instructions](https://github.com/kubernetes-sigs/metrics-server#installation))
- We can also use a Helm chart:
```bash
helm upgrade --install metrics-server metrics-server \
--create-namespace --namespace metrics-server \
--repo https://kubernetes-sigs.github.io/metrics-server/ \
--set args={--kubelet-insecure-tls=true}
```
- The `args` flag specified above should be sufficient on most clusters
- After a minute, `kubectl top nodes` should show resource usage
---
## 2⃣ Historical resource usage
- We're going to use Prometheus (specifically: kube-prometheus-stack)
- This is a Helm chart bundling:
- Prometheus
- multiple exporters (node, kube-state-metrics...)
- Grafana
- a handful of Grafana dashboards
- Open Source
- Commercial alternatives: Datadog, New Relic...
---
## Installing kube-prometheus-stack
We're going to expose both Prometheus and Grafana with a NodePort:
```bash
helm upgrade --install --repo https://prometheus-community.github.io/helm-charts \
promstack kube-prometheus-stack \
--namespace prom-system --create-namespace \
--set prometheus.service.type=NodePort \
--set grafana.service.type=NodePort \
--set prometheus.prometheusSpec.podMonitorSelectorNilUsesHelmValues=false \
--set prometheus.prometheusSpec.serviceMonitorSelectorNilUsesHelmValues=false \
#
```
This chart installation can take a while (up to a couple of minutes).
---
class: extra-details
## `...NilUsersHelmValues=false` ???
- kube-prometheus-stack uses the "Prometheus Operator"
- To configure "scrape targets", we create PodMonitor or ServiceMonitor resources
- By default, the Prometheus Operator will only look at \*Monitors with the right labels
- Our extra options mean "use all the Monitors that you find!"
---
## Connecting to Grafana
Check the NodePort allocated to Grafana:
```bash
kubectl get service promstack-grafana --namespace prom-system
```
Get the public address of one of our nodes:
```bash
kubectl get nodes -o wide
```
In a browser, connect to the public address of any node, on the node port.
The default login and password are `admin` / `prom-operator`.
Check the dashboard "Kubernetes / Compute Resources / Namespace (Pods)".
Select a namespace and see the CPU and RAM usage for the pods in that namespace.
---
## 3⃣ Request duration
- Unfortunately, as of November 2024, ollama doesn't expose metrics
(there is ongoing discussion about it: [issue 3144][3144], [PR 6537][6537])
- There are some [garbage AI-generated blog posts claiming otherwise][garbage]
(but it's AI-generated, so it bears no connection to truth whatsoever)
- So, what can we do?
[3144]: https://github.com/ollama/ollama/issues/3144#issuecomment-2153184254
[6537]: https://github.com/ollama/ollama/pull/6537
[garbage]: https://www.arsturn.com/blog/setting-up-ollama-prometheus-metrics
---
## HAProxy to the rescue
- HAProxy is a proxy that can handle TCP, HTTP, and more
- It can expose detailed Prometheus metrics about HTTP requests
- The plan: add a sidecar HAProxy to each Ollama container
- For that, we need to give up on the Ollama Helm chart
(and go back to basic manifests)
---
## 🙋 Choose your own adventure
Do we want to...
- write all the corresponding manifests?
- look at pre-written manifests and explain how they work?
- apply the manifests and carry on?
---
## 🏗️ Let's build something!
- If you have created Deployments / Services: clean them up first!
- Deploy Ollama with a sidecar HAProxy (sample configuration on next slide)
- Run a short benchmark campaign
(e.g. scale to 4 pods, try 4/8/16 parallel requests, 2 minutes each)
- Check live resource usage with `kubectl top nodes` / `kubectl top pods`
- Check historical usage with the Grafana dashboards
(for HAProxy metrics, you can use [Grafana dashboard 12693, HAProxy 2 Full][grafana-12693])
- If you don't want to write the manifests, you can use [these][ollama-yaml]
[grafana-12693]: https://grafana.com/grafana/dashboards/12693-haproxy-2-full/
[ollama-yaml]: https://github.com/jpetazzo/beyond-load-balancers/tree/main/ollama
---
```
global
#log stdout format raw local0
#daemon
maxconn 32
defaults
#log global
timeout client 1h
timeout connect 1h
timeout server 1h
mode http
`option abortonclose`
frontend metrics
bind :9000
http-request use-service prometheus-exporter
frontend ollama_frontend
bind :8000
default_backend ollama_backend
`maxconn 16`
backend ollama_backend
server ollama_server localhost:11434 check
```
---
class: extra-details
## ⚠️ Connection queues
- HAProxy will happily queue *many* connections
- If a client sends a request, then disconnects:
- the request stays in the queue
- the request gets processed by the backend
- eventually, when the backend starts sending the reply, the connection is closed
- This can result in a backlog of queries that take a long time to resorb
- To avoid that: `option abortonclose` (see [HAProxy docs for details][abortonclose])
- Note that the issue is less severe when replies are streamed
[abortonclose]: https://www.haproxy.com/documentation/haproxy-configuration-manual/latest/#4-option%20abortonclose
---
class: extra-details
## Ad-hoc HAProxy dashboard
- To consolidate all frontend and backend queues on a single graph:
- query: `haproxy_frontend_current_sessions`
- legend: `{{namespace}}/{{pod}}/{{proxy}}`
- options, "Color scheme", select "Classic palette (by series name)"
---
## What do we see?
- Imperfect load balancing
- Some backends receive more requests than others
- Sometimes, some backends are idle while others are busy
- However, CPU utilization on the node is maxed out
- This is because our node is oversubscribed
- This is because we haven't specified resource requests/limits (yet)
(we'll do that later!)

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@@ -1,155 +0,0 @@
## Setting resource requests and limits
- Thanks to *requests*:
- our pods will have resources *reserved* for them
- we won't pack too many pods on a single node
- cluster autoscaling will trigger when needed (if possible!)
- Thanks to *limits*:
- our pods won't use more than a given amount of resources
- they won't use up all the available resources on the node
- behavior will be more consistent between loaded and unloaded state
---
## Memory
- Personal advice: set request and limit to the same value
- Check current or historical usage and add a bit of padding
(the more data historical data we have, the less padding we need)
- Consider 10% padding for "dataless" pods, more for pods with data
(so that the pod has "reserves" for page cache usage)
⚠️ Pods hitting their memory limit will be **killed!**
---
## CPU
- It's not necessary to set requests and limits to the same value
(this would cause a lot of waste for idle workloads)
- Let's see a few possible strategies!
---
## CPU for mostly idle pods
E.g.: web services, workers handling very few requests...
- Set the limit to at least one whole core
(to avoid throttling, especially on bursty workloads)
- Requests can be very low (e.g. 0.1 core)
⚠️ If requests are too low and the node is very loaded,
the pod will slow down significantly!
(Because CPU cycles are allocated proportionally to CPU requests.)
---
## Inelastic CPU-hungry pods
- Pods with a fixed number of threads:
*set requests and limits to that number of threads*
- Pods where a specific level of performance needs to be guaranteed:
*set requests and limits to the number of cores providing that performance*
⚠️ If you set limits to higher levels, performance will be unpredictible!
(You'll get good performance when the node has extra cycles.)
---
## Elastic CPU-hungry pods
- Pods that could potentially use all the cores
(e.g. machine learning training and inference, depending on the models)
- Decide how many pods per node you want to pack
- Set CPU requests as a fraction of the number of cores of the nodes
(minus some padding)
- Example:
- nodes with 32 cores
- we want 4 pods per node
- CPU request: 7.5 cores
- Set limits to a higher level (up to node size)
---
## In practice
- Check memory usage of our Ollama pods:
```bash
kubectl top pods
```
(Or even better, look at historical usage in Prometheus or Grafana!)
- Check how many cores we have on our nodes:
```bash
kubectl get nodes -o json | jq .items[].status.capacity.cpu
kubectl get nodes -o custom-columns=NAME:metadata.name,CPU:status.capacity.cpu
```
- Let's decide that we want two Ollama pods per node
- What requests/limits should we set?
---
## Setting resources for Ollama
- Assumptions:
- we want two pods per node
- each pod uses ~1500MiB RAM
- nodes have 4 cores
- We'll set memory requests and limits to 2G
- We'll set CPU requests to 1.5 (4 cores / 2 pods, minus padding)
- We'll set CPU limits to twice the requests
```bash
kubectl set resources deployment ollama \
--requests=cpu=1.5,memory=2G \
--limits=cpu=3,memory=2G
```
⚠️ If you have an HAProxy side car, this will set its resources too!
---
## Results
- After setting these resource requests, we should see cluster autoscaling
- If not: scale up the Ollama Deployment to at least 3 replicas
- Check cluster autoscaler status with:
```bash
kubectl describe configmap --namespace kube-system cluster-autoscaler-status
```

View File

@@ -40,7 +40,7 @@ using Kubernetes manifests and tooling.*
- etc.
[ArgoCD]: https://argoproj.github.io/cd/
[ArgoCD]: https://github.com/argoproj/argo-cd
[AWS]: https://aws-controllers-k8s.github.io/community/docs/community/services/
[cert-manager]: https://cert-manager.io/
[External Secrets Operator]: https://external-secrets.io/

View File

@@ -1,4 +1,4 @@
# Pre-requirements
## Pre-requirements
- Kubernetes concepts

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@@ -1,210 +0,0 @@
# Message Queue Architecture
There are (at least) three ways to distribute load:
- load balancers
- batch jobs
- message queues
Let's do a quick review of their pros/cons!
---
## 1⃣ Load balancers
<pre class="mermaid">
flowchart TD
Client["Client"] ---> LB["Load balancer"]
LB ---> B1["Backend"] & B2["Backend"] & B3["Backend"]
</pre>
---
## Load balancers
- Latency: ~milliseconds (network latency)
- Overhead: very low (one extra network hop, one log message?)
- Great for short requests (a few milliseconds to a minute)
- Supported out of the box by the Kubernetes Service Proxy
(by default, this is `kube-proxy`)
- Suboptimal resource utilization due to imperfect balancing
(especially when there are multiple load balancers)
---
## 2⃣ Batch jobs
<pre class="mermaid">
flowchart TD
subgraph K["Kubernetes Control Plane"]
J1["Job"]@{ shape: card}
J2["Job"]@{ shape: card}
J3["..."]@{ shape: text}
J4["Job"]@{ shape: card}
end
C["Client"] ---> K
K <---> N1["Node"] & N2["Node"] & N3["Node"]
</pre>
---
## Batch jobs
- Latency: a few seconds (many Kubernetes controllers involved)
- Overhead: significant due to all the moving pieces involved
(job controller, scheduler, kubelet; many writes to etcd and logs)
- Great for long requests (a few minutes to a few days)
- Supported out of the box by Kubernetes
(`kubectl create job hello --image alpine -- sleep 60`)
- Asynchronous processing requires some refactoring
(we don't get the response immediately)
---
## 3⃣ Message queues
<pre class="mermaid">
flowchart TD
subgraph Q["Message queue"]
M1["Message"]@{ shape: card}
M2["Message"]@{ shape: card}
M3["..."]@{ shape: text}
M4["Message"]@{ shape: card}
end
C["Client"] ---> Q
Q <---> W1["Worker"] & W2["Worker"] & W3["Worker"]
</pre>
---
## Message queues
- Latency: a few milliseconds to a few seconds
- Overhead: intermediate
(very low with e.g. Redis, higher with e.g. Kafka)
- Great for all except very short requests
- Requires additional setup
- Asynchronous processing requires some refactoring
---
## Dealing with errors
- Load balancers
- errors reported immediately (client must retry)
- some load balancers can retry automatically
- Batch jobs
- Kubernetes retries automatically
- after `backoffLimit` retries, Job is marked as failed
- Message queues
- some queues have a concept of "acknowledgement"
- some queues have a concept of "dead letter queue"
- some extra work is required
---
## Some queue brokers
- Redis (with e.g. RPUSH, BLPOP)
*light, fast, easy to setup... no durability guarantee, no acknowledgement, no dead letter queue*
- Kafka
*heavy, complex to setup... strong deliverability guarantee, full featured*
- RabbitMQ
*somewhat in-between Redis and Kafka*
- SQL databases
*often requires polling, which adds extra latency; not as scalable as a "true" broker*
---
## More queue brokers
Many cloud providers offer hosted message queues (e.g.: Amazon SQS).
These are usually great options, with some drawbacks:
- vendor lock-in
- setting up extra environments (testing, staging...) can be more complex
(Setting up a singleton environment is usually very easy, thanks to web UI, CLI, etc.; setting up extra environments and assigning the right permissions with e.g. IAC is usually significantly more complex.)
---
## Implementing a message queue
1. Pick a broker
2. Deploy the broker
3. Set up the queue
4. Refactor our code
---
## Code refactoring (client)
Before:
```python
response = http.POST("http://api", payload=Request(...))
```
After:
```python
client = queue.connect(...)
client.publish(message=Request(...))
```
Note: we don't get the response right way (if at all)!
---
## Code refactoring (server)
Before:
```python
server = http.server(request_handler=handler)
server.listen("80")
server.run()
```
After:
```python
client = queue.connect(...)
while true:
message = client.consume()
response = handler(message)
# Write the response somewhere
```

View File

@@ -194,7 +194,7 @@ class: extra-details
- use [static CPU manager policy](https://kubernetes.io/docs/tasks/administer-cluster/cpu-management-policies/#static-policy)
For more details, check [this blog post](https://erickhun.com/posts/kubernetes-faster-services-no-cpu-limits/) or these: ([part 1](https://engineering.indeedblog.com/blog/2019/12/unthrottled-fixing-cpu-limits-in-the-cloud/), [part 2](https://engineering.indeedblog.com/blog/2019/12/cpu-throttling-regression-fix/)).
For more details, check [this blog post](https://erickhun.com/posts/kubernetes-faster-services-no-cpu-limits/) or these ones ([part 1](https://engineering.indeedblog.com/blog/2019/12/unthrottled-fixing-cpu-limits-in-the-cloud/), [part 2](https://engineering.indeedblog.com/blog/2019/12/cpu-throttling-regression-fix/)).
---

View File

@@ -245,9 +245,9 @@
- command-line flags
- Precedence of the different methods is defined in the [docs][data-values-merge-order]
- Precedence of the different methods is defined in the [docs]
[data-values-merge-order]: https://carvel.dev/ytt/docs/v0.41.0/ytt-data-values/#data-values-merge-order
[docs]: https://carvel.dev/ytt/docs/v0.41.0/ytt-data-values/#data-values-merge-order
---
@@ -462,13 +462,13 @@ spec:
- By default, `#@overlay/match` must find *exactly* one match
(that can be changed by specifying `expects=...`, `missing_ok=True`... see [docs][docs-ytt-overlaymatch])
(that can be changed by specifying `expects=...`, `missing_ok=True`... see [docs])
- By default, the specified fields (here, `spec.replicas`) must exist
(that can also be changed by annotating the optional fields)
[docs-ytt-overlaymatch]: https://carvel.dev/ytt/docs/v0.41.0/lang-ref-ytt-overlay/#overlaymatch
[docs]: https://carvel.dev/ytt/docs/v0.41.0/lang-ref-ytt-overlay/#overlaymatch
---
@@ -573,7 +573,7 @@ metadata:
## Overlays vs data values
- The documentation has a [detailed discussion][data-values-vs-overlays] about this question
- The documentation has a [detailed discussion][docs] about this question
- In short:
@@ -587,7 +587,7 @@ metadata:
(keeping in mind that overlays are harder to write/understand/maintain)
[data-values-vs-overlays]: https://carvel.dev/ytt/docs/v0.41.0/data-values-vs-overlays/
[docs]: https://carvel.dev/ytt/docs/v0.41.0/data-values-vs-overlays/
---

65
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@@ -0,0 +1,65 @@
title: |
Kubernetes
for Admins and Ops
#chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
chat: "In person!"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
- static-pods-exercise
content:
- shared/title.md
- logistics.md
- k8s/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
-
- k8s/prereqs-advanced.md
- shared/handson.md
- k8s/architecture.md
#- k8s/internal-apis.md
- k8s/deploymentslideshow.md
- k8s/dmuc-easy.md
-
- k8s/dmuc-medium.md
- k8s/dmuc-hard.md
#- k8s/multinode.md
#- k8s/cni.md
- k8s/cni-internals.md
#- k8s/interco.md
-
- k8s/apilb.md
#- k8s/setup-overview.md
#- k8s/setup-devel.md
#- k8s/setup-managed.md
#- k8s/setup-selfhosted.md
- k8s/cluster-upgrade.md
- k8s/cluster-backup.md
- k8s/staticpods.md
-
#- k8s/cloud-controller-manager.md
#- k8s/bootstrap.md
- k8s/control-plane-auth.md
- k8s/pod-security-intro.md
- k8s/pod-security-policies.md
- k8s/pod-security-admission.md
- k8s/user-cert.md
- k8s/csr-api.md
- k8s/openid-connect.md
-
#- k8s/lastwords-admin.md
- k8s/links.md
- shared/thankyou.md

96
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View File

@@ -0,0 +1,96 @@
title: |
Kubernetes
for administrators
and operators
#chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
chat: "In person!"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics.md
- k8s/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
# DAY 1
- - k8s/prereqs-advanced.md
- shared/handson.md
- k8s/architecture.md
- k8s/internal-apis.md
- k8s/deploymentslideshow.md
- k8s/dmuc-easy.md
- - k8s/dmuc-medium.md
- k8s/dmuc-hard.md
#- k8s/multinode.md
#- k8s/cni.md
- k8s/cni-internals.md
#- k8s/interco.md
- - k8s/apilb.md
- k8s/setup-overview.md
#- k8s/setup-devel.md
- k8s/setup-managed.md
- k8s/setup-selfhosted.md
- k8s/cluster-upgrade.md
- k8s/staticpods.md
- - k8s/cluster-backup.md
- k8s/cloud-controller-manager.md
- k8s/healthchecks.md
- k8s/healthchecks-more.md
# DAY 2
- - k8s/kubercoins.md
- k8s/logs-cli.md
- k8s/logs-centralized.md
- k8s/authn-authz.md
- k8s/user-cert.md
- k8s/csr-api.md
- - k8s/openid-connect.md
- k8s/control-plane-auth.md
###- k8s/bootstrap.md
- k8s/netpol.md
- k8s/pod-security-intro.md
- k8s/pod-security-policies.md
- k8s/pod-security-admission.md
- - k8s/resource-limits.md
- k8s/metrics-server.md
- k8s/cluster-sizing.md
- k8s/disruptions.md
- k8s/horizontal-pod-autoscaler.md
- - k8s/prometheus.md
#- k8s/prometheus-stack.md
- k8s/extending-api.md
- k8s/crd.md
- k8s/operators.md
- k8s/eck.md
###- k8s/operators-design.md
###- k8s/operators-example.md
# CONCLUSION
- - k8s/lastwords.md
- k8s/links.md
- shared/thankyou.md
- |
# (All content after this slide is bonus material)
# EXTRA
- - k8s/volumes.md
- k8s/configuration.md
- k8s/secrets.md
- k8s/statefulsets.md
- k8s/consul.md
- k8s/pv-pvc-sc.md
- k8s/volume-claim-templates.md
#- k8s/portworx.md
- k8s/openebs.md
- k8s/stateful-failover.md

93
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@@ -0,0 +1,93 @@
title: |
Advanced
Kubernetes
chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics.md
- k8s/intro.md
- shared/about-slides.md
#- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
- #1
- k8s/prereqs-advanced.md
- shared/handson.md
- k8s/architecture.md
- k8s/internal-apis.md
- k8s/deploymentslideshow.md
- k8s/dmuc-easy.md
- #2
- k8s/dmuc-medium.md
- k8s/dmuc-hard.md
#- k8s/multinode.md
#- k8s/cni.md
#- k8s/interco.md
- k8s/cni-internals.md
- #3
- k8s/apilb.md
- k8s/control-plane-auth.md
- |
# (Extra content)
- k8s/staticpods.md
- k8s/cluster-upgrade.md
- #4
- k8s/kustomize.md
- k8s/helm-intro.md
- k8s/helm-chart-format.md
- k8s/helm-create-basic-chart.md
- |
# (Extra content)
- k8s/helm-create-better-chart.md
- k8s/helm-dependencies.md
- k8s/helm-values-schema-validation.md
- k8s/helm-secrets.md
- k8s/ytt.md
- #5
- k8s/extending-api.md
- k8s/operators.md
- k8s/sealed-secrets.md
- k8s/crd.md
- #6
- k8s/ingress-tls.md
- k8s/ingress-advanced.md
#- k8s/ingress-canary.md
- k8s/cert-manager.md
- k8s/cainjector.md
- k8s/eck.md
- #7
- k8s/admission.md
- k8s/kyverno.md
- #8
- k8s/aggregation-layer.md
- k8s/metrics-server.md
- k8s/prometheus.md
- k8s/prometheus-stack.md
- k8s/hpa-v2.md
- #9
- k8s/operators-design.md
- k8s/operators-example.md
- k8s/kubebuilder.md
- k8s/events.md
- k8s/finalizers.md
- |
# (Extra content)
- k8s/owners-and-dependents.md
- k8s/apiserver-deepdive.md
#- k8s/record.md
- shared/thankyou.md

136
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@@ -0,0 +1,136 @@
title: |
Deploying and Scaling Microservices
with Kubernetes
#chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
chat: "In person!"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics.md
- k8s/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
-
- shared/prereqs.md
- shared/handson.md
#- shared/webssh.md
- shared/connecting.md
#- k8s/versions-k8s.md
- shared/sampleapp.md
#- shared/composescale.md
#- shared/hastyconclusions.md
- shared/composedown.md
- k8s/concepts-k8s.md
- k8s/kubectlget.md
-
- k8s/kubectl-run.md
#- k8s/batch-jobs.md
- shared/declarative.md
- k8s/declarative.md
- k8s/deploymentslideshow.md
- k8s/kubectlexpose.md
- k8s/service-types.md
- k8s/kubenet.md
- k8s/shippingimages.md
#- k8s/buildshiprun-selfhosted.md
- k8s/buildshiprun-dockerhub.md
- k8s/ourapponkube.md
#- k8s/exercise-wordsmith.md
-
- k8s/labels-annotations.md
- k8s/kubectl-logs.md
- k8s/logs-cli.md
- k8s/yamldeploy.md
- k8s/namespaces.md
- k8s/setup-overview.md
- k8s/setup-devel.md
#- k8s/setup-managed.md
#- k8s/setup-selfhosted.md
-
- k8s/dashboard.md
- k8s/rollout.md
- k8s/healthchecks.md
- k8s/ingress.md
#- k8s/volumes.md
- k8s/configuration.md
- k8s/secrets.md
- k8s/openebs.md
#- k8s/k9s.md
#- k8s/tilt.md
#- k8s/kubectlscale.md
#- k8s/scalingdockercoins.md
#- shared/hastyconclusions.md
#- k8s/daemonset.md
#- shared/yaml.md
#- k8s/exercise-yaml.md
#- k8s/localkubeconfig.md
#- k8s/access-eks-cluster.md
#- k8s/accessinternal.md
#- k8s/kubectlproxy.md
#- k8s/healthchecks-more.md
#- k8s/record.md
#- k8s/ingress-tls.md
#- k8s/kustomize.md
#- k8s/helm-intro.md
#- k8s/helm-chart-format.md
#- k8s/helm-create-basic-chart.md
#- k8s/helm-create-better-chart.md
#- k8s/helm-dependencies.md
#- k8s/helm-values-schema-validation.md
#- k8s/helm-secrets.md
#- k8s/exercise-helm.md
#- k8s/ytt.md
#- k8s/gitlab.md
#- k8s/create-chart.md
#- k8s/create-more-charts.md
#- k8s/netpol.md
#- k8s/authn-authz.md
#- k8s/user-cert.md
#- k8s/csr-api.md
#- k8s/openid-connect.md
#- k8s/pod-security-intro.md
#- k8s/pod-security-policies.md
#- k8s/pod-security-admission.md
#- k8s/exercise-configmap.md
#- k8s/build-with-docker.md
#- k8s/build-with-kaniko.md
#- k8s/logs-centralized.md
#- k8s/prometheus.md
#- k8s/prometheus-stack.md
#- k8s/statefulsets.md
#- k8s/consul.md
#- k8s/pv-pvc-sc.md
#- k8s/volume-claim-templates.md
#- k8s/portworx.md
#- k8s/openebs.md
#- k8s/stateful-failover.md
#- k8s/extending-api.md
#- k8s/crd.md
#- k8s/admission.md
#- k8s/operators.md
#- k8s/operators-design.md
#- k8s/operators-example.md
#- k8s/staticpods.md
#- k8s/finalizers.md
#- k8s/owners-and-dependents.md
#- k8s/gitworkflows.md
-
#- k8s/whatsnext.md
- k8s/lastwords.md
#- k8s/links.md
- shared/thankyou.md

91
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@@ -0,0 +1,91 @@
title: |
Kubernetes 101
#chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/training-20180413-paris)"
chat: "In person!"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
#- logistics.md
# Bridget-specific; others use logistics.md
- logistics-bridget.md
- k8s/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
- - shared/prereqs.md
- shared/handson.md
#- shared/webssh.md
- shared/connecting.md
- k8s/versions-k8s.md
- shared/sampleapp.md
# Bridget doesn't go into as much depth with compose
#- shared/composescale.md
#- shared/hastyconclusions.md
- shared/composedown.md
- k8s/concepts-k8s.md
- shared/declarative.md
- k8s/declarative.md
#- k8s/kubenet.md
- k8s/kubectlget.md
- k8s/setup-overview.md
#- k8s/setup-devel.md
#- k8s/setup-managed.md
#- k8s/setup-selfhosted.md
- - k8s/kubectl-run.md
#- k8s/batch-jobs.md
#- k8s/labels-annotations.md
- k8s/kubectl-logs.md
- k8s/deploymentslideshow.md
- k8s/kubectlexpose.md
#- k8s/service-types.md
- k8s/shippingimages.md
#- k8s/buildshiprun-selfhosted.md
- k8s/buildshiprun-dockerhub.md
- k8s/ourapponkube.md
#- k8s/localkubeconfig.md
#- k8s/access-eks-cluster.md
#- k8s/accessinternal.md
#- k8s/kubectlproxy.md
- - k8s/dashboard.md
#- k8s/k9s.md
#- k8s/tilt.md
#- k8s/kubectlscale.md
- k8s/scalingdockercoins.md
- shared/hastyconclusions.md
- k8s/daemonset.md
- k8s/rollout.md
#- k8s/record.md
- - k8s/logs-cli.md
# Bridget hasn't added EFK yet
#- k8s/logs-centralized.md
- k8s/namespaces.md
- k8s/helm-intro.md
#- k8s/helm-chart-format.md
- k8s/helm-create-basic-chart.md
#- k8s/helm-create-better-chart.md
#- k8s/helm-dependencies.md
#- k8s/helm-values-schema-validation.md
#- k8s/helm-secrets.md
#- k8s/kustomize.md
#- k8s/ytt.md
#- k8s/netpol.md
- k8s/whatsnext.md
# - k8s/links.md
# Bridget-specific
- k8s/links-bridget.md
- shared/thankyou.md

174
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@@ -0,0 +1,174 @@
title: |
Deploying and Scaling Microservices
with Docker and Kubernetes
chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- in-person
content:
- shared/title.md
#- logistics.md
- k8s/intro.md
- shared/about-slides.md
#- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
-
- shared/prereqs.md
- shared/handson.md
#- shared/webssh.md
- shared/connecting.md
- k8s/versions-k8s.md
- shared/sampleapp.md
#- shared/composescale.md
#- shared/hastyconclusions.md
- shared/composedown.md
- k8s/concepts-k8s.md
-
- k8s/kubectlget.md
- k8s/kubectl-run.md
- k8s/batch-jobs.md
- k8s/labels-annotations.md
- k8s/kubectl-logs.md
- k8s/logs-cli.md
- shared/declarative.md
- k8s/declarative.md
- k8s/deploymentslideshow.md
-
- k8s/kubectlexpose.md
- k8s/service-types.md
- k8s/kubenet.md
- k8s/shippingimages.md
- k8s/buildshiprun-selfhosted.md
- k8s/buildshiprun-dockerhub.md
- k8s/ourapponkube.md
#- k8s/exercise-wordsmith.md
- shared/yaml.md
- k8s/yamldeploy.md
- k8s/namespaces.md
-
- k8s/setup-overview.md
- k8s/setup-devel.md
- k8s/setup-managed.md
- k8s/setup-selfhosted.md
- k8s/dashboard.md
- k8s/k9s.md
- k8s/tilt.md
#- k8s/kubectlscale.md
- k8s/scalingdockercoins.md
- shared/hastyconclusions.md
- k8s/daemonset.md
#- k8s/exercise-yaml.md
-
- k8s/rollout.md
- k8s/healthchecks.md
- k8s/healthchecks-more.md
- k8s/record.md
-
- k8s/localkubeconfig.md
#- k8s/access-eks-cluster.md
- k8s/accessinternal.md
- k8s/kubectlproxy.md
-
- k8s/ingress.md
- k8s/ingress-advanced.md
#- k8s/ingress-canary.md
- k8s/ingress-tls.md
- k8s/cert-manager.md
- k8s/cainjector.md
- k8s/kustomize.md
- k8s/helm-intro.md
- k8s/helm-chart-format.md
- k8s/helm-create-basic-chart.md
- k8s/helm-create-better-chart.md
- k8s/helm-dependencies.md
- k8s/helm-values-schema-validation.md
- k8s/helm-secrets.md
#- k8s/exercise-helm.md
- k8s/gitlab.md
- k8s/ytt.md
-
- k8s/netpol.md
- k8s/authn-authz.md
- k8s/pod-security-intro.md
- k8s/pod-security-policies.md
- k8s/pod-security-admission.md
- k8s/user-cert.md
- k8s/csr-api.md
- k8s/openid-connect.md
- k8s/control-plane-auth.md
-
- k8s/volumes.md
#- k8s/exercise-configmap.md
- k8s/build-with-docker.md
- k8s/build-with-kaniko.md
-
- k8s/configuration.md
- k8s/secrets.md
- k8s/statefulsets.md
- k8s/consul.md
- k8s/pv-pvc-sc.md
- k8s/volume-claim-templates.md
- k8s/portworx.md
- k8s/openebs.md
- k8s/stateful-failover.md
-
- k8s/gitworkflows.md
- k8s/flux.md
- k8s/argocd.md
-
- k8s/logs-centralized.md
- k8s/prometheus.md
- k8s/prometheus-stack.md
- k8s/resource-limits.md
- k8s/metrics-server.md
- k8s/cluster-sizing.md
- k8s/disruptions.md
- k8s/cluster-autoscaler.md
- k8s/horizontal-pod-autoscaler.md
- k8s/hpa-v2.md
-
- k8s/extending-api.md
- k8s/apiserver-deepdive.md
- k8s/crd.md
- k8s/aggregation-layer.md
- k8s/admission.md
- k8s/operators.md
- k8s/operators-design.md
- k8s/operators-example.md
- k8s/kubebuilder.md
- k8s/sealed-secrets.md
- k8s/kyverno.md
- k8s/eck.md
- k8s/finalizers.md
- k8s/owners-and-dependents.md
- k8s/events.md
-
- k8s/dmuc-easy.md
- k8s/dmuc-medium.md
- k8s/dmuc-hard.md
#- k8s/multinode.md
#- k8s/cni.md
- k8s/cni-internals.md
- k8s/apilb.md
- k8s/staticpods.md
-
- k8s/cluster-upgrade.md
- k8s/cluster-backup.md
- k8s/cloud-controller-manager.md
-
- k8s/lastwords.md
- k8s/links.md
- shared/thankyou.md

136
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@@ -0,0 +1,136 @@
title: |
Deploying and Scaling Microservices
with Kubernetes
#chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
chat: "In person!"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics.md
- k8s/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
-
- shared/prereqs.md
- shared/handson.md
#- shared/webssh.md
- shared/connecting.md
#- k8s/versions-k8s.md
- shared/sampleapp.md
#- shared/composescale.md
#- shared/hastyconclusions.md
- shared/composedown.md
- k8s/concepts-k8s.md
- k8s/kubectlget.md
-
- k8s/kubectl-run.md
- k8s/batch-jobs.md
- k8s/labels-annotations.md
- k8s/kubectl-logs.md
- k8s/logs-cli.md
- shared/declarative.md
- k8s/declarative.md
- k8s/deploymentslideshow.md
- k8s/kubectlexpose.md
- k8s/service-types.md
- k8s/kubenet.md
- k8s/shippingimages.md
#- k8s/buildshiprun-selfhosted.md
- k8s/buildshiprun-dockerhub.md
- k8s/ourapponkube.md
#- k8s/exercise-wordsmith.md
-
- k8s/yamldeploy.md
- k8s/setup-overview.md
- k8s/setup-devel.md
#- k8s/setup-managed.md
#- k8s/setup-selfhosted.md
- k8s/dashboard.md
- k8s/k9s.md
#- k8s/tilt.md
#- k8s/kubectlscale.md
- k8s/scalingdockercoins.md
- shared/hastyconclusions.md
- k8s/daemonset.md
- shared/yaml.md
#- k8s/exercise-yaml.md
-
- k8s/localkubeconfig.md
#- k8s/access-eks-cluster.md
- k8s/accessinternal.md
#- k8s/kubectlproxy.md
- k8s/rollout.md
- k8s/healthchecks.md
#- k8s/healthchecks-more.md
- k8s/record.md
-
- k8s/namespaces.md
- k8s/ingress.md
#- k8s/ingress-advanced.md
#- k8s/ingress-canary.md
#- k8s/ingress-tls.md
- k8s/kustomize.md
- k8s/helm-intro.md
- k8s/helm-chart-format.md
- k8s/helm-create-basic-chart.md
- k8s/helm-create-better-chart.md
- k8s/helm-dependencies.md
- k8s/helm-values-schema-validation.md
- k8s/helm-secrets.md
#- k8s/exercise-helm.md
#- k8s/ytt.md
- k8s/gitlab.md
-
- k8s/netpol.md
- k8s/authn-authz.md
#- k8s/csr-api.md
#- k8s/openid-connect.md
#- k8s/pod-security-intro.md
#- k8s/pod-security-policies.md
#- k8s/pod-security-admission.md
-
- k8s/volumes.md
#- k8s/exercise-configmap.md
#- k8s/build-with-docker.md
#- k8s/build-with-kaniko.md
- k8s/configuration.md
- k8s/secrets.md
- k8s/logs-centralized.md
#- k8s/prometheus.md
#- k8s/prometheus-stack.md
-
- k8s/statefulsets.md
- k8s/consul.md
- k8s/pv-pvc-sc.md
- k8s/volume-claim-templates.md
#- k8s/portworx.md
- k8s/openebs.md
- k8s/stateful-failover.md
#- k8s/extending-api.md
#- k8s/admission.md
#- k8s/operators.md
#- k8s/operators-design.md
#- k8s/operators-example.md
#- k8s/staticpods.md
#- k8s/owners-and-dependents.md
#- k8s/gitworkflows.md
-
- k8s/whatsnext.md
- k8s/lastwords.md
- k8s/links.md
- shared/thankyou.md

View File

@@ -0,0 +1,76 @@
## Introductions (en 🇫🇷)
- Bonjour !
- Sur scène : Julien
- En backstage : Alexandre, Antoine, Aurélien (x2), Benji, David, Kostas, Nicolas, Paul, Sébastien, Thibault...
- Horaires : tous les jours de 9h à 13h
- On fera une pause vers (environ) 11h
- N'hésitez pas à poser un maximum de questions!
- Utilisez @@CHAT@@ pour les questions, demander de l'aide, etc.
[@alexbuisine]: https://twitter.com/alexbuisine
[EphemeraSearch]: https://ephemerasearch.com/
[@jpetazzo]: https://twitter.com/jpetazzo
[@jpetazzo@hachyderm.io]: https://hachyderm.io/@jpetazzo
[@s0ulshake]: https://twitter.com/s0ulshake
[Quantgene]: https://www.quantgene.com/
---
## Les 15 minutes du matin
- Chaque jour, on commencera à 9h par une mini-présentation de 15 minutes
(sur un sujet choisi ensemble, pas forcément en relation avec la formation!)
- L'occasion de s'échauffer les neurones avec 🥐/☕️/🍊
(avant d'attaquer les choses sérieuses)
- Puis à 9h15 on rentre dans le vif du sujet
---
## Travaux pratiques
- À la fin de chaque matinée, il y a un exercice pratique concret
(pour mettre en œuvre ce qu'on a vu)
- Les exercices font partie de la formation !
- Ils sont prévus pour prendre entre 15 minutes et 2 heures
(selon les connaissances et l'aisance de chacun·e)
- Chaque matinée commencera avec un passage en revue de l'exercice de la veille
- On est là pour vous aider si vous bloquez sur un exercice !
---
## Allô Docker¹ ?
- Chaque après-midi : une heure de questions/réponses ouvertes !
(sauf le vendredi)
- Mardi: 15h-16h
- Mercredi: 16h-17h
- Jeudi: 14h-15h
- Sur [Jitsi][jitsi] (lien "visioconf" sur le portail de formation)
.footnote[¹Clin d'œil à l'excellent ["Quoi de neuf Docker?"][qdnd] de l'excellent [Nicolas Deloof][ndeloof] 🙂]
[qdnd]: https://www.youtube.com/channel/UCOAhkxpryr_BKybt9wIw-NQ
[ndeloof]: https://github.com/ndeloof
[jitsi]: https://training.enix.io/jitsi-magic/jitsi.container.training/AlloDockerMai2023

View File

@@ -0,0 +1,76 @@
## Introductions (en 🇫🇷)
- Bonjour !
- Sur scène : Ludovic
- En backstage : Alexandre, Antoine, Aurélien (x2), Benjamin (x2), David, Kostas, Nicolas, Paul, Sébastien, Thibault...
- Horaires : tous les jours de 9h à 13h
- On fera une pause vers (environ) 11h
- N'hésitez pas à poser un maximum de questions!
- Utilisez @@CHAT@@ pour les questions, demander de l'aide, etc.
[@alexbuisine]: https://twitter.com/alexbuisine
[EphemeraSearch]: https://ephemerasearch.com/
[@jpetazzo]: https://twitter.com/jpetazzo
[@jpetazzo@hachyderm.io]: https://hachyderm.io/@jpetazzo
[@s0ulshake]: https://twitter.com/s0ulshake
[Quantgene]: https://www.quantgene.com/
---
## Les 15 minutes du matin
- Chaque jour, on commencera à 9h par une mini-présentation de 15 minutes
(sur un sujet choisi ensemble, pas forcément en relation avec la formation!)
- L'occasion de s'échauffer les neurones avec 🥐/☕️/🍊
(avant d'attaquer les choses sérieuses)
- Puis à 9h15 on rentre dans le vif du sujet
---
## Travaux pratiques
- À la fin de chaque matinée, il y a un exercice pratique concret
(pour mettre en œuvre ce qu'on a vu)
- Les exercices font partie de la formation !
- Ils sont prévus pour prendre entre 15 minutes et 2 heures
(selon les connaissances et l'aisance de chacun·e)
- Chaque matinée commencera avec un passage en revue de l'exercice de la veille
- On est là pour vous aider si vous bloquez sur un exercice !
---
## Allô Docker¹ ?
- Chaque après-midi : une heure de questions/réponses ouvertes !
(sauf le vendredi)
- Mardi: 15h-16h
- Mercredi: 16h-17h
- Jeudi: 17h-18h
- Sur [Jitsi][jitsi] (lien "visioconf" sur le portail de formation)
.footnote[¹Clin d'œil à l'excellent ["Quoi de neuf Docker?"][qdnd] de l'excellent [Nicolas Deloof][ndeloof] 🙂]
[qdnd]: https://www.youtube.com/channel/UCOAhkxpryr_BKybt9wIw-NQ
[ndeloof]: https://github.com/ndeloof
[jitsi]: https://training.enix.io/jitsi-magic/jitsi.container.training/AlloDockerMai2024

View File

@@ -1,20 +1,18 @@
## Introductions
## Introductions (en 🇫🇷)
- Hello! I'm Jérôme Petazzoni ([@jpetazzo], [@jpetazzo@hachyderm.io], Enix SAS)
- Bonjour !
- Schedule: FIXME
- Sur scène : Jérôme ([@jpetazzo@hachyderm.io])
- Feel free to interrupt for questions at any time
- En backstage : Alexandre, Antoine, Aurélien (x2), Benjamin, David, Kostas, Nicolas, Paul, Sébastien, Thibault...
- *Especially when you see full screen container pictures!*
- Horaires : tous les jours de 9h à 13h
- Live feedback, questions, help: @@CHAT@@
- On fera une pause vers (environ) 11h
- You ~~should~~ must ask questions! Lots of questions!
- N'hésitez pas à poser un maximum de questions!
(especially when you see full screen container pictures)
- Use @@CHAT@@ to ask questions, get help, etc.
- Utilisez @@CHAT@@ pour les questions, demander de l'aide, etc.
[@alexbuisine]: https://twitter.com/alexbuisine
[EphemeraSearch]: https://ephemerasearch.com/
@@ -25,30 +23,54 @@
---
## Un petit sondage ...
## Les 15 minutes du matin
Sur une échelle de 0 à 5, où vous situez-vous avec Kubernetes ?
- Chaque jour, on commencera à 9h par une mini-présentation de 15 minutes
0⃣ Kuberne-quoi ? 😅
(sur un sujet choisi ensemble, pas forcément en relation avec la formation!)
1⃣ J'ai déjà vu quelques présentations, démos ... Mais jamais utilisé
- L'occasion de s'échauffer les neurones avec 🥐/☕️/🍊
2⃣ J'ai déjà fait quelques tutos mais je ne connais pas bien les concepts
(avant d'attaquer les choses sérieuses)
3⃣ J'utilise occasionnellement ; j'ai (ou peut avoir) accès à un cluster (local, cloud, n'importe) ; je connais les concepts de Pod, Deployment, Service
4⃣ Je déploie régulièrement sur un cluster (que ça soit dev en local ou prod) ; je sais écrire / générer et utiliser des manifests YAML
5⃣ Je connais tout ça et j'ai aussi déjà manipulé au moins un concept avancé comme le RBAC, les Ingress, les requests/limits
- Puis à 9h15 on rentre dans le vif du sujet
---
## Exercises
## Travaux pratiques
- In the middle of each day, there is a series of exercises
- À la fin de chaque matinée, il y a un exercice pratique concret
- To make the most out of the training, please try the exercises!
(pour mettre en œuvre ce qu'on a vu)
(it will help to practice and memorize the content of the day)
- Les exercices font partie de la formation !
- We'll run polls to know how much time to spend on reviewing the exercises
- Ils sont prévus pour prendre entre 15 minutes et 2 heures
(selon les connaissances et l'aisance de chacun·e)
- Chaque matinée commencera avec un passage en revue de l'exercice de la veille
- On est là pour vous aider si vous bloquez sur un exercice !
---
## Allô Docker¹ ?
- Chaque après-midi : une heure de questions/réponses ouvertes !
(sauf le dernier jour)
- Une heure de questions/réponses ouvertes !
- Mercredi: 15h00-16h00
- Jeudi: 16h00-17h00
- Sur [Jitsi][jitsi] (lien "visioconf" sur le portail de formation)
.footnote[¹Clin d'œil à l'excellent ["Quoi de neuf Docker?"][qdnd] de l'excellent [Nicolas Deloof][ndeloof] 🙂]
[qdnd]: https://www.youtube.com/channel/UCOAhkxpryr_BKybt9wIw-NQ
[ndeloof]: https://github.com/ndeloof
[jitsi]: https://training.enix.io/jitsi-magic/jitsi.container.training/HighFiveAutomne2024

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@@ -1,44 +0,0 @@
title: |
Asynchronous Architecture Patterns To Scale ML and Other High Latency Workloads on Kubernetes
#chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
chat: "In person!"
gitrepo: github.com/jpetazzo/container.training
slides: https://FIXME.container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
content:
- shared/title.md
- logistics.md
- shared/about-slides.md
#- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- k8s/prereqs-advanced.md
- k8s/handson-mlops.md
- shared/connecting.md
- k8s/mlops-headsup.md
- shared/toc.md
-
- k8s/ollama-intro.md
- k8s/ollama-metrics.md
- k8s/queue-architecture.md
- k8s/bento-intro.md
-
- k8s/resource-limits.md
- k8s/cluster-autoscaler.md
- k8s/ollama-reqlim.md
- k8s/bento-hpa.md
- k8s/bento-rmq.md
- k8s/bento-cnpg.md
- k8s/helmfile.md
- shared/thankyou.md
- shared/contact.md

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@@ -46,7 +46,7 @@
(let's say we'll keep them online at least 1 year, how about that?)
- You can download the slides using this URL:
- You can download the slides using that URL:
@@ZIP@@

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@@ -1,16 +1,15 @@
class: in-person
## Testing the connection to our lab environment
## Connecting to our lab environment
.lab[
- Connect to your lab environment with your SSH client:
- Log into the first VM (`node1`) with your SSH client:
```bash
ssh `user`@`A.B.C.D`
ssh -p `32323` `user`@`A.B.C.D`
```
(Make sure to replace the highlighted values with the ones provided to you!)
(Replace `user` and `A.B.C.D` with the user and IP address provided to you)
<!--
```bash
@@ -28,7 +27,7 @@ done
You should see a prompt looking like this:
```
[A.B.C.D] (...) user@machine ~
[A.B.C.D] (...) user@node1 ~
$
```
If anything goes wrong — ask for help!
@@ -41,11 +40,9 @@ class: in-person
- The shell history of the instructor is available online in real time
- The instructor will provide you a "magic URL"
- Note the IP address of the instructor's virtual machine (A.B.C.D)
(typically, the instructor's lab address on port 1088 or 30088)
- Open that URL in your browser and you should see the history
- Open http://A.B.C.D:1088 in your browser and you should see the history
- The history is updated in real time
@@ -119,17 +116,21 @@ You will need a Docker ID to use Play-With-Docker.
---
## We don't need to connect to ALL the nodes
## We will (mostly) interact with node1 only
- If your cluster has multiple nodes (e.g. `node1`, `node2`, ...):
*These remarks apply only when using multiple nodes, of course.*
unless instructed, **all commands must be run from the first node**
- Unless instructed, **all commands must be run from the first VM, `node1`**
- We don't need to check out/copy code or manifests on other nodes
- We will only check out/copy the code on `node1`
- During normal operations, we do not need access to the other nodes
(but we could log into these nodes to troubleshoot or examine stuff)
- If we had to troubleshoot issues, we would use a combination of:
- SSH (to access system logs, daemon status...)
- Docker API (to check running containers and container engine status)
---

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@@ -1,45 +0,0 @@
name: contact
## Contact information
.column-half[
Instructor:
📛 Jérôme Petazzoni
<br/>
📩 jerome.petazzoni@gmail.com
<br/>
🔗 https://linkedin.com/in/jpetazzo
<br/>
🦣 https://hachyderm.io/@jpetazzo
I can teach custom courses:
- Docker, Kubernetes, MLOps
- from intro level to "black belt"
- on site or remotely
Reach out if you're interested!
]
.column-half[
Assistant:
📛 AJ Bowen
<br/>
📩 aj@soulshake.net
<br/>
🔗 https://linkedin.com/in/ajbowen
<br/>
📃 https://github.com/soulshake
I can consult on the following topics:
- Kubernetes
- CI/CD
- Terraform & Infra-as-code
- Docker
- AWS
]

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@@ -1,26 +0,0 @@
<!-- QRcode generated with "qrencode -t UTF-8" -->
.center[
<pre style="padding-top: 0em; font-size: 18px; line-height: 20px;">
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</pre>
]

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@@ -1,11 +1,24 @@
class: title, self-paced
class: title
Thank you!
Merci !
![end](images/end.jpg)
---
class: title, in-person
## Derniers mots...
That's all, folks! <br/> Questions?
- Le portail de formation reste en ligne après la formation
- N'hésitez pas à nous contacter via la messagerie instantanée !
- Les VM ENIX restent en ligne au moins une semaine après la formation
(mais pas les clusters cloud ; eux on les éteint très vite)
- N'oubliez pas de remplier les formulaires d'évaluation
(c'est pas pour nous, c'est une obligation légale😅)
- Encore **merci** à vous !
![end](images/end.jpg)

72
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@@ -0,0 +1,72 @@
title: |
Container Orchestration
with Docker and Swarm
chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
- snap
- btp-auto
- benchmarking
- elk-manual
- prom-manual
content:
- shared/title.md
- logistics.md
- swarm/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
- - shared/prereqs.md
- shared/handson.md
- shared/connecting.md
- swarm/versions.md
- shared/sampleapp.md
- shared/composescale.md
- shared/hastyconclusions.md
- shared/composedown.md
- swarm/swarmkit.md
- shared/declarative.md
- swarm/swarmmode.md
- swarm/creatingswarm.md
#- swarm/machine.md
- swarm/morenodes.md
- - swarm/firstservice.md
- swarm/ourapponswarm.md
- swarm/hostingregistry.md
- swarm/testingregistry.md
- swarm/btp-manual.md
- swarm/swarmready.md
- swarm/stacks.md
- swarm/cicd.md
- swarm/updatingservices.md
- swarm/rollingupdates.md
- swarm/healthchecks.md
- - swarm/operatingswarm.md
- swarm/netshoot.md
- swarm/ipsec.md
- swarm/swarmtools.md
- swarm/security.md
- swarm/secrets.md
- swarm/encryptionatrest.md
- swarm/leastprivilege.md
- swarm/apiscope.md
- - swarm/logging.md
- swarm/metrics.md
- swarm/gui.md
- swarm/stateful.md
- swarm/extratips.md
- shared/thankyou.md
- swarm/links.md

71
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@@ -0,0 +1,71 @@
title: |
Container Orchestration
with Docker and Swarm
chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
#chat: "[Gitter](https://gitter.im/jpetazzo/workshop-yyyymmdd-city)"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- self-paced
- snap
- btp-manual
- benchmarking
- elk-manual
- prom-manual
content:
- shared/title.md
- logistics.md
- swarm/intro.md
- shared/about-slides.md
- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
- - shared/prereqs.md
- shared/handson.md
- shared/connecting.md
- swarm/versions.md
- shared/sampleapp.md
- shared/composescale.md
- shared/hastyconclusions.md
- shared/composedown.md
- swarm/swarmkit.md
- shared/declarative.md
- swarm/swarmmode.md
- swarm/creatingswarm.md
#- swarm/machine.md
- swarm/morenodes.md
- - swarm/firstservice.md
- swarm/ourapponswarm.md
#- swarm/hostingregistry.md
#- swarm/testingregistry.md
#- swarm/btp-manual.md
#- swarm/swarmready.md
- swarm/stacks.md
- swarm/cicd.md
- swarm/updatingservices.md
#- swarm/rollingupdates.md
#- swarm/healthchecks.md
- - swarm/operatingswarm.md
#- swarm/netshoot.md
#- swarm/ipsec.md
#- swarm/swarmtools.md
- swarm/security.md
#- swarm/secrets.md
#- swarm/encryptionatrest.md
- swarm/leastprivilege.md
- swarm/apiscope.md
- swarm/logging.md
- swarm/metrics.md
#- swarm/stateful.md
#- swarm/extratips.md
- shared/thankyou.md
- swarm/links.md

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@@ -0,0 +1,80 @@
title: |
Container Orchestration
with Docker and Swarm
chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- in-person
- btp-auto
content:
- shared/title.md
#- shared/logistics.md
- swarm/intro.md
- shared/about-slides.md
#- shared/chat-room-im.md
#- shared/chat-room-slack.md
#- shared/chat-room-zoom-meeting.md
#- shared/chat-room-zoom-webinar.md
- shared/toc.md
- - shared/prereqs.md
- shared/handson.md
- shared/connecting.md
- swarm/versions.md
- |
name: part-1
class: title, self-paced
Part 1
- shared/sampleapp.md
- shared/composescale.md
- shared/hastyconclusions.md
- shared/composedown.md
- swarm/swarmkit.md
- shared/declarative.md
- swarm/swarmmode.md
- swarm/creatingswarm.md
#- swarm/machine.md
- swarm/morenodes.md
- - swarm/firstservice.md
- swarm/ourapponswarm.md
- swarm/hostingregistry.md
- swarm/testingregistry.md
- swarm/btp-manual.md
- swarm/swarmready.md
- swarm/stacks.md
- swarm/cicd.md
- |
name: part-2
class: title, self-paced
Part 2
- - swarm/operatingswarm.md
- swarm/netshoot.md
- swarm/swarmnbt.md
- swarm/ipsec.md
- swarm/updatingservices.md
- swarm/rollingupdates.md
- swarm/healthchecks.md
- swarm/nodeinfo.md
- swarm/swarmtools.md
- - swarm/security.md
- swarm/secrets.md
- swarm/encryptionatrest.md
- swarm/leastprivilege.md
- swarm/apiscope.md
- swarm/logging.md
- swarm/metrics.md
- swarm/stateful.md
- swarm/extratips.md
- shared/thankyou.md
- swarm/links.md

75
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@@ -0,0 +1,75 @@
title: |
Container Orchestration
with Docker and Swarm
chat: "[Slack](https://dockercommunity.slack.com/messages/C7GKACWDV)"
gitrepo: github.com/jpetazzo/container.training
slides: https://container.training/
#slidenumberprefix: "#SomeHashTag &mdash; "
exclude:
- in-person
- btp-auto
content:
- shared/title.md
#- shared/logistics.md
- swarm/intro.md
- shared/about-slides.md
- shared/toc.md
- - shared/prereqs.md
- shared/handson.md
- shared/connecting.md
- swarm/versions.md
- |
name: part-1
class: title, self-paced
Part 1
- shared/sampleapp.md
- shared/composescale.md
- shared/hastyconclusions.md
- shared/composedown.md
- swarm/swarmkit.md
- shared/declarative.md
- swarm/swarmmode.md
- swarm/creatingswarm.md
#- swarm/machine.md
- swarm/morenodes.md
- - swarm/firstservice.md
- swarm/ourapponswarm.md
- swarm/hostingregistry.md
- swarm/testingregistry.md
- swarm/btp-manual.md
- swarm/swarmready.md
- swarm/stacks.md
- |
name: part-2
class: title, self-paced
Part 2
- - swarm/operatingswarm.md
#- swarm/netshoot.md
#- swarm/swarmnbt.md
- swarm/ipsec.md
- swarm/updatingservices.md
- swarm/rollingupdates.md
#- swarm/healthchecks.md
- swarm/nodeinfo.md
- swarm/swarmtools.md
- - swarm/security.md
- swarm/secrets.md
- swarm/encryptionatrest.md
- swarm/leastprivilege.md
- swarm/apiscope.md
#- swarm/logging.md
#- swarm/metrics.md
- swarm/stateful.md
- swarm/extratips.md
- shared/thankyou.md
- swarm/links.md

View File

@@ -221,10 +221,3 @@ td {
padding: 0.1em 0.5em;
background: #eee;
}
/* Use this to layout a slide in two columns */
.column-half {
float: left;
width: 50%;
}

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@@ -32,19 +32,7 @@
excludedClasses: [@@EXCLUDE@@]
});
</script>
<script type="module">
import mermaid from 'https://cdn.jsdelivr.net/npm/mermaid@11/dist/mermaid.esm.min.mjs';
mermaid.initialize({ startOnLoad: false });
slideshow.on('afterShowSlide', function (slide) {
mermaid.run({
nodes: document.querySelectorAll('div.remark-visible .mermaid'),
});
});
// Reminder, if you want to tinker with mermaid,
// you need to export it, for instance like this:
// window.mermaid = mermaid;
</script>
<!--
These two scripts will be available only when loading the
content using the pub/sub server. Otherwise, they'll just