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Add container engines chapter; orchestration overview chapter
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Jerome Petazzoni
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c0,1.4,1.2,2.6,2.6,2.6c1,0,1.8-0.5,2.3-1.3c0.3,0.7,0.5,1.6,0.5,2.4c0,3.5-2.8,6.3-6.3,6.3c-3.5,0-6.3-2.8-6.3-6.3
|
||||
C169.6,306.3,172.4,303.5,175.9,303.5"/>
|
||||
<path fill-rule="evenodd" clip-rule="evenodd" fill="#3A4D54" d="M19.6,282.7h193.6h23.9h190.5c0.4,0,1.6,0.1,1.2,0
|
||||
c-9.2-2.2-24.9-6.2-23.5-15.8c0.1-0.7-0.2-0.8-0.6-0.3c-16.6,17.5-54.1,12.2-64.3,3.2c-0.2-0.1-0.4-0.1-0.5,0.1
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||||
c-11.5,15.4-73.3,9.7-79.3-2.3c-0.1-0.2-0.4-0.3-0.6-0.1c-14.1,15.7-55.7,15.7-69.8,0c-0.2-0.2-0.5-0.1-0.6,0.1
|
||||
c-6,12-67.8,17.7-79.3,2.3c-0.1-0.2-0.3-0.2-0.5-0.1c-10.1,8.9-44.5,14.3-61.2-3c-0.3-0.3-0.8-0.1-0.8,0.4
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||||
C48.9,277.6,28.1,280.5,19.6,282.7"/>
|
||||
<path fill="#C0DBE0" d="M199.4,364.7c-21.9-10.4-33.9-24.5-40.6-39.9c-8.1,2.3-17.9,3.8-29.3,4.4c-4.3,0.2-8.8,0.4-13.5,0.4
|
||||
c-5.4,0-11.2-0.2-17.2-0.5c20.1,20.1,44.8,35.5,90.5,35.8C192.7,364.9,196.1,364.8,199.4,364.7z"/>
|
||||
<path fill="#D4EDF1" d="M167,339c-3-4.1-6-9.3-8.1-14.2c-8.1,2.3-17.9,3.8-29.3,4.4C137.4,333.4,148.5,337.4,167,339z"/>
|
||||
</g>
|
||||
<circle fill="#3A4D54" cx="34.8" cy="311" r="5.9"/>
|
||||
<path fill="#3A4D54" d="M346.8,297.2l-1-2.8c0,0,5.3-11.7-7.4-11.7c-12.7,0,3.5-4.7,3.5-4.7l21.8,2.8l9.6,6.8l-16.1,4.1
|
||||
L346.8,297.2z"/>
|
||||
<path fill="#3A4D54" d="M78.7,297.2l1-2.8c0,0-5.3-11.7,7.4-11.7s-3.5-4.7-3.5-4.7l-21.8,2.8l-9.6,6.8l16.1,4.1L78.7,297.2z"/>
|
||||
<path fill="#3A4D54" d="M361.7,279.5v4.4l15.6,6.7l45.5-4.1l7.3-3.7c0,0-3.8-0.6-7.3-1.7c-3.6-1.1-15.2-1.6-15.2-1.6h-28.3
|
||||
l-13.6,1.8L361.7,279.5z"/>
|
||||
</g>
|
||||
</svg>
|
||||
|
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|
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@@ -16,7 +16,7 @@ chapters:
|
||||
- common/about-slides.md
|
||||
- common/toc.md
|
||||
- - intro/Docker_Overview.md
|
||||
#- intro/Docker_History.md
|
||||
- intro/Docker_History.md
|
||||
- intro/Training_Environment.md
|
||||
- intro/Installing_Docker.md
|
||||
- intro/First_Containers.md
|
||||
@@ -40,6 +40,12 @@ chapters:
|
||||
- - intro/Local_Development_Workflow.md
|
||||
- intro/Working_With_Volumes.md
|
||||
- intro/Compose_For_Dev_Stacks.md
|
||||
- intro/Docker_Machine.md
|
||||
- intro/Advanced_Dockerfiles.md
|
||||
- - intro/Namespaces_Cgroups.md
|
||||
- intro/Copy_On_Write.md
|
||||
- intro/Containers_From_Scratch.md
|
||||
- intro/Container_Engines.md
|
||||
- intro/Orchestration_Overview.md
|
||||
- common/thankyou.md
|
||||
- intro/links.md
|
||||
|
||||
177
slides/intro/Container_Engines.md
Normal file
177
slides/intro/Container_Engines.md
Normal file
@@ -0,0 +1,177 @@
|
||||
# Docker Engine and other container engines
|
||||
|
||||
* We are going to cover the architecture of the Docker Engine.
|
||||
|
||||
* We will also present other container engines.
|
||||
|
||||
---
|
||||
|
||||
class: pic
|
||||
|
||||
## Docker Engine external architecture
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## Docker Engine external architecture
|
||||
|
||||
* The Engine is a daemon (service running in the background).
|
||||
|
||||
* All interaction is done through a REST API exposed over a socket.
|
||||
|
||||
* On Linux, the default socket is a UNIX socket: `/var/run/docker.sock`.
|
||||
|
||||
* We can also use a TCP socket, with optional mutual TLS authentication.
|
||||
|
||||
* The `docker` CLI communicates with the Engine over the socket.
|
||||
|
||||
Note: strictly speaking, the Docker API is not fully REST.
|
||||
|
||||
Some operations (e.g. dealing with interactive containers
|
||||
and log streaming) don't fit the REST model.
|
||||
|
||||
---
|
||||
|
||||
class: pic
|
||||
|
||||
## Docker Engine internal architecture
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## Docker Engine internal architecture
|
||||
|
||||
* Up to Docker 1.10: the Docker Engine is one single monolithic binary.
|
||||
|
||||
* Starting with Docker 1.11, the Engine is split into multiple parts:
|
||||
|
||||
- `dockerd` (REST API, auth, networking, storage)
|
||||
|
||||
- `containerd` (container lifecycle, controlled over a gRPC API)
|
||||
|
||||
- `containerd-shim` (per-container; does almost nothing but allows to restart the Engine without restarting the containers)
|
||||
|
||||
- `runc` (per-container; does the actual heavy lifting to start the container)
|
||||
|
||||
* Some features (like image and snapshot management) are progressively being pushed from `dockerd` to `containerd`.
|
||||
|
||||
For more details, check [this short presentation by Phil Estes](https://www.slideshare.net/PhilEstes/diving-through-the-layers-investigating-runc-containerd-and-the-docker-engine-architecture).
|
||||
|
||||
---
|
||||
|
||||
## Other container engines
|
||||
|
||||
The following list is not exhaustive.
|
||||
|
||||
Furthermore, we limited the scope to Linux containers.
|
||||
|
||||
Containers also exist (sometimes with other names) on Windows, macOS, Solaris, FreeBSD ...
|
||||
|
||||
---
|
||||
|
||||
## LXC
|
||||
|
||||
* The venerable ancestor (first realeased in 2008).
|
||||
|
||||
* Docker initially relied on it to execute containers.
|
||||
|
||||
* No daemon; no central API.
|
||||
|
||||
* Each container is managed by a `lxc-start` process.
|
||||
|
||||
* Each `lxc-start` process exposes a custom API over a local UNIX socket, allowing to interact with the container.
|
||||
|
||||
* No notion of image (container filesystems have to be managed manually).
|
||||
|
||||
* Networking has to be setup manually.
|
||||
|
||||
---
|
||||
|
||||
## LXD
|
||||
|
||||
* Re-uses LXC code (through liblxc).
|
||||
|
||||
* Builds on top of LXC to offer a more modern experience.
|
||||
|
||||
* Daemon exposing a REST API.
|
||||
|
||||
* Can manage images, snapshots, migrations, networking, storage.
|
||||
|
||||
* "offers a user experience similar to virtual machines but using Linux containers instead."
|
||||
|
||||
---
|
||||
|
||||
## rkt
|
||||
|
||||
* Compares to `runc`.
|
||||
|
||||
* No daemon or API.
|
||||
|
||||
* Strong emphasis on security (through privilege separation).
|
||||
|
||||
* Networking has to be setup separately (e.g. through CNI plugins).
|
||||
|
||||
* Partial image management (pull, but no push).
|
||||
|
||||
(Image build is handled by separate tools.)
|
||||
|
||||
---
|
||||
|
||||
## CRI-O
|
||||
|
||||
* Designed to be used with Kubernetes as a simple, basic runtime.
|
||||
|
||||
* Compares to `containerd`.
|
||||
|
||||
* Daemon exposing a gRPC interface.
|
||||
|
||||
* Controlled using the CRI API (Container Runtime Interface defined by Kubernetes).
|
||||
|
||||
* Needs an underlying OCI runtime (e.g. runc).
|
||||
|
||||
* Handles storage, images, networking (through CNI plugins).
|
||||
|
||||
We're not aware of anyone using it directly (i.e. outside of Kubernetes).
|
||||
|
||||
---
|
||||
|
||||
## systemd
|
||||
|
||||
* "init" system (PID 1) in most modern Linux distributions.
|
||||
|
||||
* Offers tools like `systemd-nspawn` and `machinectl` to manage containers.
|
||||
|
||||
* `systemd-nspawn` is "In many ways it is similar to chroot(1), but more powerful".
|
||||
|
||||
* `machinectl` can interact with VMs and containers managed by systemd.
|
||||
|
||||
* Exposes a DBUS API.
|
||||
|
||||
* Basic image support (tar archives and raw disk images).
|
||||
|
||||
* Network has to be setup manually.
|
||||
|
||||
---
|
||||
|
||||
## Overall ...
|
||||
|
||||
* The Docker Engine is very developer-centric:
|
||||
|
||||
- easy to install
|
||||
|
||||
- easy to use
|
||||
|
||||
- no manual setup
|
||||
|
||||
- first-class image build and transfer
|
||||
|
||||
* As a result, it is a fantastic tool in development environments.
|
||||
|
||||
* On servers:
|
||||
|
||||
- Docker is a good default choice
|
||||
|
||||
- If you use Kubernetes, the engine doesn't matter
|
||||
|
||||
3
slides/intro/Containers_From_Scratch.md
Normal file
3
slides/intro/Containers_From_Scratch.md
Normal file
@@ -0,0 +1,3 @@
|
||||
# Building containers from scratch
|
||||
|
||||
FIXME
|
||||
3
slides/intro/Copy_On_Write.md
Normal file
3
slides/intro/Copy_On_Write.md
Normal file
@@ -0,0 +1,3 @@
|
||||
# Copy-on-write filesystems
|
||||
|
||||
FIXME
|
||||
3
slides/intro/Docker_Machine.md
Normal file
3
slides/intro/Docker_Machine.md
Normal file
@@ -0,0 +1,3 @@
|
||||
# Managing hosts with Docker Machine
|
||||
|
||||
FIXME
|
||||
3
slides/intro/Namespaces_Cgroups.md
Normal file
3
slides/intro/Namespaces_Cgroups.md
Normal file
@@ -0,0 +1,3 @@
|
||||
# Container internals: namespaces and cgroups
|
||||
|
||||
FIXME
|
||||
427
slides/intro/Orchestration_Overview.md
Normal file
427
slides/intro/Orchestration_Overview.md
Normal file
@@ -0,0 +1,427 @@
|
||||
# Orchestration, an overview
|
||||
|
||||
In this chapter, we will:
|
||||
|
||||
* Explain what is orchestration and why we would need it.
|
||||
|
||||
* Present (from a high-level perspective) some orchestrators.
|
||||
|
||||
* Show one orchestrator (Kubernetes) in action.
|
||||
|
||||
---
|
||||
|
||||
class: pic
|
||||
|
||||
## What's orchestration?
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## What's orchestration?
|
||||
|
||||
According to Wikipedia:
|
||||
|
||||
*Orchestration describes the __automated__ arrangement,
|
||||
coordination, and management of complex computer systems,
|
||||
middleware, and services.*
|
||||
|
||||
--
|
||||
|
||||
*[...] orchestration is often discussed in the context of
|
||||
__service-oriented architecture__, __virtualization__, provisioning,
|
||||
Converged Infrastructure and __dynamic datacenter__ topics.*
|
||||
|
||||
--
|
||||
|
||||
What does that really mean?
|
||||
|
||||
---
|
||||
|
||||
## Example 1: dynamic cloud instances
|
||||
|
||||
--
|
||||
|
||||
- Q: do we always use 100% of our servers?
|
||||
|
||||
--
|
||||
|
||||
- A: obviously not!
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## Example 1: dynamic cloud instances
|
||||
|
||||
- Every night, scale down
|
||||
|
||||
(by shutting down extraneous replicated instances)
|
||||
|
||||
- Every morning, scale up
|
||||
|
||||
(by deploying new copies)
|
||||
|
||||
- "Pay for what you use"
|
||||
|
||||
(i.e. save big $$$ here)
|
||||
|
||||
---
|
||||
|
||||
## Example 1: dynamic cloud instances
|
||||
|
||||
How do we implement this?
|
||||
|
||||
- Crontab
|
||||
|
||||
- Autoscaling (save even bigger $$$)
|
||||
|
||||
That's *relatively* easy.
|
||||
|
||||
Now, how are things for our IAAS provider?
|
||||
|
||||
---
|
||||
|
||||
## Example 2: dynamic datacenter
|
||||
|
||||
- Q: what's the #1 cost in a datacenter?
|
||||
|
||||
--
|
||||
|
||||
- A: electricity!
|
||||
|
||||
--
|
||||
|
||||
- Q: what uses electricity?
|
||||
|
||||
--
|
||||
|
||||
- A: servers, obviously
|
||||
|
||||
- A: ... and associated cooling
|
||||
|
||||
--
|
||||
|
||||
- Q: do we always use 100% of our servers?
|
||||
|
||||
--
|
||||
|
||||
- A: obviously not!
|
||||
|
||||
---
|
||||
|
||||
## Example 2: dynamic datacenter
|
||||
|
||||
- If only we could turn off unused servers during the night...
|
||||
|
||||
- Problem: we can only turn off a server if it's totally empty!
|
||||
|
||||
(i.e. all VMs on it are stopped/moved)
|
||||
|
||||
- Solution: *migrate* VMs and shutdown empty servers
|
||||
|
||||
(e.g. combine two hypervisors with 40% load into 80%+0%,
|
||||
<br/>and shutdown the one at 0%)
|
||||
|
||||
---
|
||||
|
||||
## Example 2: dynamic datacenter
|
||||
|
||||
How do we implement this?
|
||||
|
||||
- Shutdown empty hosts (but keep some spare capacity)
|
||||
|
||||
- Start hosts again when capacity gets low
|
||||
|
||||
- Ability to "live migrate" VMs
|
||||
|
||||
(Xen already did this 10+ years ago)
|
||||
|
||||
- Rebalance VMs on a regular basis
|
||||
|
||||
- what if a VM is stopped while we move it?
|
||||
- should we allow provisioning on hosts involved in a migration?
|
||||
|
||||
*Scheduling* becomes more complex.
|
||||
|
||||
---
|
||||
|
||||
## What is scheduling?
|
||||
|
||||
According to Wikipedia (again):
|
||||
|
||||
*In computing, scheduling is the method by which threads,
|
||||
processes or data flows are given access to system resources.*
|
||||
|
||||
The scheduler is concerned mainly with:
|
||||
|
||||
- throughput (total amount or work done per time unit);
|
||||
- turnaround time (between submission and completion);
|
||||
- response time (between submission and start);
|
||||
- waiting time (between job readiness and execution);
|
||||
- fairness (appropriate times according to priorities).
|
||||
|
||||
In practice, these goals often conflict.
|
||||
|
||||
**"Scheduling" = decide which resources to use.**
|
||||
|
||||
---
|
||||
|
||||
## Exercise 1
|
||||
|
||||
- You have:
|
||||
|
||||
- 5 hypervisors (physical machines)
|
||||
|
||||
- Each server has:
|
||||
|
||||
- 16 GB RAM, 8 cores, 1 TB disk
|
||||
|
||||
- Each week, your team asks:
|
||||
|
||||
- one VM with X RAM, Y CPU, Z disk
|
||||
|
||||
Scheduling = deciding which hypervisor to use for each VM.
|
||||
|
||||
Difficulty: easy!
|
||||
|
||||
---
|
||||
|
||||
<!-- Warning, two almost identical slides (for img effect) -->
|
||||
|
||||
## Exercise 2
|
||||
|
||||
- You have:
|
||||
|
||||
- 1000+ hypervisors (and counting!)
|
||||
|
||||
- Each server has different resources:
|
||||
|
||||
- 8-500 GB of RAM, 4-64 cores, 1-100 TB disk
|
||||
|
||||
- Multiple times a day, a different team asks for:
|
||||
|
||||
- up to 50 VMs with different characteristics
|
||||
|
||||
Scheduling = deciding which hypervisor to use for each VM.
|
||||
|
||||
Difficulty: ???
|
||||
|
||||
---
|
||||
|
||||
<!-- Warning, two almost identical slides (for img effect) -->
|
||||
|
||||
## Exercise 2
|
||||
|
||||
- You have:
|
||||
|
||||
- 1000+ hypervisors (and counting!)
|
||||
|
||||
- Each server has different resources:
|
||||
|
||||
- 8-500 GB of RAM, 4-64 cores, 1-100 TB disk
|
||||
|
||||
- Multiple times a day, a different team asks for:
|
||||
|
||||
- up to 50 VMs with different characteristics
|
||||
|
||||
Scheduling = deciding which hypervisor to use for each VM.
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## Exercise 3
|
||||
|
||||
- You have machines (physical and/or virtual)
|
||||
|
||||
- You have containers
|
||||
|
||||
- You are trying to put the containers on the machines
|
||||
|
||||
- Sounds familiar?
|
||||
|
||||
---
|
||||
|
||||
## Scheduling with one resource
|
||||
|
||||
|
||||
|
||||
Can we do better?
|
||||
|
||||
---
|
||||
|
||||
## Scheduling with one resource
|
||||
|
||||
|
||||
|
||||
Yup!
|
||||
|
||||
---
|
||||
|
||||
## Scheduling with two resources
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## Scheduling with three resources
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## You need to be good at this
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## But also, you must be quick!
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## And be web scale!
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## And think outside (?) of the box!
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## Good luck!
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## TL,DR
|
||||
|
||||
* Scheduling with multiple resources (dimensions) is hard.
|
||||
|
||||
* Don't expect to solve the problem with a Tiny Shell Script.
|
||||
|
||||
* There are literally tons of research papers written on this.
|
||||
|
||||
---
|
||||
|
||||
## But our orchestrator also needs to manage ...
|
||||
|
||||
* Network connectivity (or filtering) between containers.
|
||||
|
||||
* Load balancing (external and internal).
|
||||
|
||||
* Failure recovery (if a node or a whole datacenter fails).
|
||||
|
||||
* Rolling out new versions of our applications.
|
||||
|
||||
(Canary deployments, blue/green deployments...)
|
||||
|
||||
|
||||
---
|
||||
|
||||
## Some orchestrators
|
||||
|
||||
We are going to present briefly a few orchestrators.
|
||||
|
||||
There is no "absolute best" orchestrator.
|
||||
|
||||
It depends on:
|
||||
|
||||
- your applications,
|
||||
|
||||
- your requirements,
|
||||
|
||||
- your pre-existing skills...
|
||||
|
||||
---
|
||||
|
||||
## Nomad
|
||||
|
||||
- Open Source project by Hashicorp.
|
||||
|
||||
- Arbitrary scheduler (not just for containers).
|
||||
|
||||
- Great if you want to schedule mixed workloads.
|
||||
|
||||
(VMs, containers, processes...)
|
||||
|
||||
- Less integration with the rest of the container ecosystem.
|
||||
|
||||
---
|
||||
|
||||
## Mesos
|
||||
|
||||
- Open Source project in the Apache Foundation.
|
||||
|
||||
- Arbitrary scheduler (not just for containers).
|
||||
|
||||
- Two-level scheduler.
|
||||
|
||||
- Top-level scheduler acts as a resource broker.
|
||||
|
||||
- Second-level schedulers (aka "frameworks") obtain resources from top-level.
|
||||
|
||||
- Frameworks implement various strategies.
|
||||
|
||||
(Marathon = long running processes; Chronos = run at intervals; ...)
|
||||
|
||||
- Commercial offering through DC/OS my Mesosphere.
|
||||
|
||||
---
|
||||
|
||||
## Rancher
|
||||
|
||||
- Rancher 1 offered a simple interface for Docker hosts.
|
||||
|
||||
- Rancher 2 is a complete management platform for Docker and Kubernetes.
|
||||
|
||||
- Technically not an orchestrator, but it's a popular option.
|
||||
|
||||
---
|
||||
|
||||
## Swarm
|
||||
|
||||
- Tightly integrated with the Docker Engine.
|
||||
|
||||
- Extremely simple to deploy and setup, even in multi-manager (HA) mode.
|
||||
|
||||
- Secure by default.
|
||||
|
||||
- Strongly opinionated:
|
||||
|
||||
- smaller set of features,
|
||||
|
||||
- easier to operate.
|
||||
|
||||
---
|
||||
|
||||
## Kubernetes
|
||||
|
||||
- Open Source project initiated by Google.
|
||||
|
||||
- Contributions from many other actors.
|
||||
|
||||
- *De facto* standard for container orchestration.
|
||||
|
||||
- Many deployment options; some of them very complex.
|
||||
|
||||
- Reputation: steep learning curve.
|
||||
|
||||
- Reality:
|
||||
|
||||
- true, if trying to understand *everything*;
|
||||
|
||||
- false, if we focus on what matters.
|
||||
|
||||
---
|
||||
|
||||
## Kubernetes in action
|
||||
|
||||
FIXME (describe the demo?)
|
||||
Reference in New Issue
Block a user