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https://github.com/jpetazzo/container.training.git
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wip
This commit is contained in:
Jerome Petazzoni
@@ -12,6 +12,7 @@ Preparation:
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- Make sure that you have SSH keys loaded (`ssh-add -l`).
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- Source `rc`.
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- Run `pcopykey`.
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- Source `postprep.rc`.
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(This will install a few extra packages, add entries to
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/etc/hosts, generate SSH keys, and deploy them on all hosts.)
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@@ -17,6 +17,9 @@ while ips:
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ips = ips[clustersize:]
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clusters.append(cluster)
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def makenames(addrs):
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return [ "node%d"%(i+1) for i in range(len(addrs)) ]
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html = open("ips.html", "w")
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html.write("<html><head><style>")
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html.write("""
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@@ -47,9 +50,9 @@ for i, cluster in enumerate(clusters):
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html.write("cluster for this orchestration workshop. You can connect ")
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html.write("to each VM with your SSH client.</p>\n")
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html.write("<p>login=docker password=training</p>\n")
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html.write("<p>IP addresses:<ul>\n")
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for ipaddr in cluster:
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html.write("<li>%s</li>\n"%ipaddr)
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html.write("<p>Your machines are:<ul>\n")
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for ipaddr, hostname in zip(cluster, makenames(cluster)):
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html.write("<li>%s - %s</li>\n"%(hostname, ipaddr))
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html.write("</ul></p>")
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html.write("</div>")
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html.close()
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@@ -146,7 +146,7 @@ to be done from the first VM, `node1`.
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# Our sample application
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- Let's look at the general layout of
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- Let's look at the general layout of the
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[source code](https://github.com/jpetazzo/orchestration-workshop)
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- Each directory = 1 microservice
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@@ -219,7 +219,7 @@ rng:
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- Get 10 bytes of random data:
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<br/>`curl localhost:8001/10`
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<br/>(the output might confuse your terminal, since this is binary data)
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- Test the performance on one big request::
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- Test the performance on one big request:
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<br/>`curl -o/dev/null localhost:8001/10000000`
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<br/>(should take ~1s, and show speed of ~10 MB/s)
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@@ -233,9 +233,9 @@ Next: we'll see how it behaves with many small requests.
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.exercise[
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- Test 1000 requests of 1000 bytes each:
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- Test 100 requests of 1000 bytes each:
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<br/>`ab -n 100 localhost:8001/1000`
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- Test 1000 requests, 10 requests in parallel:
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- Test 100 requests, 10 requests in parallel:
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<br/>`ab -n 100 -c 10 localhost:8001/1000`
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<br/>(look how the latency has increased!)
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- Try with 100 requests in parallel:
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@@ -339,7 +339,9 @@ Take note of the performance numbers (requests/s).
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## Benchmarking the hasher on smaller data
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Here we hashed 1 meg. Later we will hash much smaller payloads.
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Here we hashed 1 meg.
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Later we will hash much smaller payloads.
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Let's repeat the tests with smaller data.
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@@ -621,6 +623,60 @@ docker run -d -p 80 jpetazzo/hamba 80 www1 1234 www2 2345
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---
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# Connecting to containers on other hosts
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- We want to scale across multiple nodes
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- We will deploy the same stack multiple times
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- But we want every stack to use the same Redis
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<br/>(in other words: Redis is our only *stateful* service here)
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---
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## The plan
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- Deploy our Redis service separately
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- use the same `redis` image
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- make sure that Redis server port (6379) is publicly accessible,
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using port 6379 on the Docker host
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- Update our Docker Compose YAML file
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- remove the `redis` section
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- in the `links` section, remove `redis`
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- instead, put a `redis` entry in `extra_hosts`
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---
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## Deploy Redis
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.exercise[
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- Start a new redis container, mapping port 6379 to 6379:
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```
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docker run -d -p 6379:6379 redis
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```
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- Note the IP address of this Docker host
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- Try to connect to it (from anywhere):
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```
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telnet ip.ad.dr.ess 6379
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```
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]
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To exit a telnet session: `Ctrl-] c ENTER`
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---
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# Introducing Swarm
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@@ -975,21 +1031,39 @@ Some Redis commands: `"SET key value"` `"GET key"`
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- Start our services:
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<br/>`docker-compose -f deploy.yml up -d`
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<br/>`docker-compose -f deploy.yml scale worker=10`
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<br/>`docker-compose -f deploy.yml scale rng=10`
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<br/>`docker-compose -f deploy.yml scale worker=8`
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<br/>`docker-compose -f deploy.yml scale rng=4`
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- Generate plumbing commands:
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<br/>`../connect-services.py deploy.yml`
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]
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- Execute plumbing commands:
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<br/>`../connect-services.py deploy.yml | sh`
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Review the plumbing commands, then execute them.
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]
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---
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# Scaling on Swarm
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## Notes
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# Cluster metrics
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- If you want to scale up or down, you have to re-do
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the whole plumbing
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- This is not a design issue; just an implementation detail
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of the `connect-services.py` script
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- Possible improvements:
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- get list of containers using a single API call
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- use labels to tag ambassador containers
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- update script to do fine-grained updates of `/etc/hosts`
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- update script to add/remove ambassadors carefully
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<br/>(instead of destroying+recreating them all)
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---
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# Introducing Mesos
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