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Continuous Deployment
with Kubernetes, Docker
and GitLab CI
@alexander_kiel

Clojure Berlin 2016
Continuous Deployment with Kubernetes, Docker and GitLab CI
Outline
• Continuous Deployment why?
• Docker
• Kubernetes
• Sample Clojure Service
• Deploy with GitLabCI
Continuous Deployment
• What do we want?
• Increase responsiveness
• Decrease time to market
• Gain confidence by deploying often in small amounts
• How to achieve that?
• Automate everything
• Always deploy the master into production
• Use feature toggles when needed
Simple Git Workflow
• Works for in-house apps
• not for libs or shipping apps
• No versions, no tags, just SHA’s
• Latest commit on master is always
deployed to production
• Feature/fix branches are merged
when ready
master
feature/fix
branches
1ebb95d
be61dda
6e4010d
Docker
• Like VM’s but much more light-weight and shippable
• Runs on Linux, executes processes in an isolated environment
(resource limitation, filesystem, network)
• Container principle: Can contain everything, but looks the
same from the outside
• A container platform can run every container
• Developers have max. freedom what to do
• In contrast: PaaS like Heroku - has to support the language
Kubernetes
• Container runtime platform
• Originally designed by Google - now Open Source
• One of the most active projects on GitHub - 20,000
stars, 40,000 commits, 15,000 issues, 200 releases
• Alternatives: Apache Mesos, Docker Swarm (lacks
features)
Kubernetes Architecture
k8s-master-1
k8s-master-2
k8s-master-3
load-balancer-1
load-balancer-2
DNS RR
k8s-worker-1
proxy
app-1
k8s-worker-2
proxy
app-2
k8s-worker-n
proxy
app-k
etcd cluster

quorum
HAProxy
• Runs on VMware ESX
• CoreOS Linux
• Single YAML file as configuration
• Everything in containers
Kubernetes - Pods
• A Pod is a deployable unit in
Kubernetes
• Pods can contain multiple
containers
• Containers inside a Pod share
on port space, can use
localhost and can
communicate via IPC and
shared memory
• Idea: one process per
container - many cooperating
processes in one Pod
apiVersion: v1

kind: Pod

metadata:

name: <pod-name>

labels:

<key>: <value>

spec:

containers:

- name: <container-name>

image: <container-image>

ports:

- containerPort: 80

env:

- name: <key>

value: <value>
Kubernetes - Deployments
• A Deployment ensures that
certain number of Pods are
always running
• It consists of a Pod template
and the number of replicas
• It supports hot-redeployments
by changing parts of the Pod
template
• Horizontal scaling is possible
apiVersion: extensions/v1beta1

kind: Deployment

metadata:

name: <deployment-name>

spec:

replicas: 2

template:

metadata:
labels:
<key>: <value>
spec:
containers:
- name: <container-name>
image: <container-image>
ports:
- containerPort: 80
env:
- name: <key>
value: <value>
Kubernetes - Services
• Kubernetes uses an overlay
network to provide different address
spaces (we use flannel)
• Every Pod has an IP address - but it
changes every time one is created
• Services provide a stable IP
address for groups of Pods
• Service names are resolvable by an
internal DNS
• Service selectors are used to match
Pods according to there labels
apiVersion: v1
kind: Service
metadata:
name: clojure-berlin-2016
labels:
app: lens
spec:
type: NodePort
ports:
- port: 80
targetPort: 80
protocol: TCP
selector:
service: clojure-
berlin-2016
Kubernetes - External Access
• Kubernetes networks are internal
only
• External access through load
balancers necessary
• Certain Platforms like Google
Compute Engine provide load
balancer integration with Kubernetes
• We have our own solution as a
combination of HAProxy and
Kubernetes NodePort
• Kubernetes Services with type
NodePort are exposed on every
worker under a certain port
frontend http
bind 0.0.0.0:80
mode http
option httplog
acl host_clj hdr(host)
clj.<domain>
use_backend clj if host_clj
backend clj
mode http
balance roundrobin
option httplog
server worker-1 <ip>:32599 check
server worker-2 <ip>:32599 check
Deployment Lifecycle
GitLab CI
Source Code
build
test
Kubernetes
Test
Cluster
Kubernetes
Prod
Cluster
automatic deployment
manual
deployment
git
push
Sample Clojure Service
• .gitlab-ci.yml
• Like .travis.yml contains instructions for GitLabCI
how to test, build and deploy
• Dockerfile
• Instructions for Docker how to build the image of
the app
• Artifact of the build is a docker image - not
uberjar
• kube-deployment.yml
• Kubernetes deployment instructions
• kube-svc.yml
• Kubernetes service description
https://github.com/alexanderkiel/clojure-berlin-2016
The Core Namespace
(ns clojure-berlin-2016.core
(:require [aleph.http :as http]
[clojure.core.async :refer [<!! chan]]))
(defn -main [& args]
(-> (fn [_]
{:status 200
:body "Clojure Berlin 2016"})
(http/start-server {:port 8080}))
(<!! (chan)))
• A simple web server returning "Clojure Berlin 2016"
The Leiningen Project File
(defproject clojure-berlin-2016 "<VERSION>"
:dependencies [[aleph "0.4.1"]
[org.clojure/clojure "1.8.0"]
[org.clojure/core.async "0.2.395"]]
:main clojure-berlin-2016.core)
• <VERSION> is replaced at build time by the Git SHA
• :main is for lein run to work
.gitlab-ci.yml - test/build
image: clojure:lein-2.7.1
stages:
- test
- build
- deploy
test:
stage: test
tags:
- docker
script:
- lein test
build:
stage: build
tags:
- docker
script:
- sed -i "s/<VERSION>/$CI_BUILD_REF/" project.clj
- docker build -t clojure-berlin-2016:$CI_BUILD_REF .
- docker push clojure-berlin-2016:$CI_BUILD_REF
.gitlab-ci.yml - deploy branch
deploy-branch:
stage: deploy
environment: test
image: dreg.life.uni-leipzig.local/kubectl:0.4
tags:
- docker
script:
- sed -i "s/<VERSION>/$CI_BUILD_REF/" kube-deployment.yml
- kubectl config use-context gitlab-ci-test
- kubectl apply -f kube-deployment.yml
except:
- master
when: manual
• Used to test a feature/fix branch in a full environment
.gitlab-ci.yml - deploy test
deploy-master:
stage: deploy
environment: test
image: dreg.life.uni-leipzig.local/kubectl:0.4
tags:
- docker
script:
- sed -i "s/<VERSION>/$CI_BUILD_REF/" kube-deployment.yml
- kubectl config use-context gitlab-ci-test
- kubectl apply -f kube-deployment.yml
only:
- master
.gitlab-ci.yml - deploy prod
deploy-prod:
stage: deploy
environment: prod
image: dreg.life.uni-leipzig.local/kubectl:0.4
tags:
- docker
script:
- sed -i "s/<VERSION>/$CI_BUILD_REF/" kube-deployment.yml
- kubectl config use-context gitlab-ci-prod-a
- kubectl apply -f kube-deployment.yml
only:
- master
when: manual
Docker file
FROM clojure:lein-2.7.1
COPY src /app/src
COPY project.clj /app/
WORKDIR /app
RUN lein with-profile production deps
EXPOSE 80
CMD ["lein", "with-profile", "production", "run"]
• Just copy the sources into the container
• Use Leiningen itself to run in production
kube-deployment.yml
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: clojure-berlin-2016
spec:
replicas: 2
template:
metadata:
labels:
app: lens
service: clojure-berlin-2016
spec:
containers:
- name: clojure-berlin-2016
image: dreg.life.uni-leipzig.local/clojure-berlin-2016:<VERSION>
ports:
- containerPort: 8080
resources:
requests:
cpu: "125m"
memory: "1Gi"
limits:
cpu: 1
memory: "2Gi"
kube-svc.yml
apiVersion: v1
kind: Service
metadata:
name: clojure-berlin-2016
labels:
app: lens
spec:
type: NodePort
ports:
- port: 80
targetPort: 8080
protocol: TCP
selector:
service: clojure-berlin-2016
Steps to Follow
• Create the Kubernetes Service
• kubectl create -f kube-svc.yml
• Edit HAProxy Config
• add rules and backend for the service
• Push to GitLab
• git push
Pipeline in GitLab CI
Deployment in GitLabCI
Environments in GitLabCI
• Very good visibility of wich commit is deployed in
which environment right now
• Manual deployment to prod possible
Environment History
• Easy to see when what commit was deployed
• Rollback possible
Numbers
• Our team has 4 developers
• We run 2 Kubernetes clusters (test and prod) with
about 96 GB RAM and and 24 vCPU’s each
• We run about 60 pods in production
• We have other services like central log aggregation
running using Fluentd and Elasticsearch/Kibana
Thank You
• Sample Project on Github

https://github.com/alexanderkiel/clojure-berlin-2016
• Twitter

@alexander_kiel
• Mail

alexanderkiel@gmx.net

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Continuous Deployment with Kubernetes, Docker and GitLab CI

  • 1. Continuous Deployment with Kubernetes, Docker and GitLab CI @alexander_kiel
 Clojure Berlin 2016
  • 3. Outline • Continuous Deployment why? • Docker • Kubernetes • Sample Clojure Service • Deploy with GitLabCI
  • 4. Continuous Deployment • What do we want? • Increase responsiveness • Decrease time to market • Gain confidence by deploying often in small amounts • How to achieve that? • Automate everything • Always deploy the master into production • Use feature toggles when needed
  • 5. Simple Git Workflow • Works for in-house apps • not for libs or shipping apps • No versions, no tags, just SHA’s • Latest commit on master is always deployed to production • Feature/fix branches are merged when ready master feature/fix branches 1ebb95d be61dda 6e4010d
  • 6. Docker • Like VM’s but much more light-weight and shippable • Runs on Linux, executes processes in an isolated environment (resource limitation, filesystem, network) • Container principle: Can contain everything, but looks the same from the outside • A container platform can run every container • Developers have max. freedom what to do • In contrast: PaaS like Heroku - has to support the language
  • 7. Kubernetes • Container runtime platform • Originally designed by Google - now Open Source • One of the most active projects on GitHub - 20,000 stars, 40,000 commits, 15,000 issues, 200 releases • Alternatives: Apache Mesos, Docker Swarm (lacks features)
  • 8. Kubernetes Architecture k8s-master-1 k8s-master-2 k8s-master-3 load-balancer-1 load-balancer-2 DNS RR k8s-worker-1 proxy app-1 k8s-worker-2 proxy app-2 k8s-worker-n proxy app-k etcd cluster
 quorum HAProxy • Runs on VMware ESX • CoreOS Linux • Single YAML file as configuration • Everything in containers
  • 9. Kubernetes - Pods • A Pod is a deployable unit in Kubernetes • Pods can contain multiple containers • Containers inside a Pod share on port space, can use localhost and can communicate via IPC and shared memory • Idea: one process per container - many cooperating processes in one Pod apiVersion: v1
 kind: Pod
 metadata:
 name: <pod-name>
 labels:
 <key>: <value>
 spec:
 containers:
 - name: <container-name>
 image: <container-image>
 ports:
 - containerPort: 80
 env:
 - name: <key>
 value: <value>
  • 10. Kubernetes - Deployments • A Deployment ensures that certain number of Pods are always running • It consists of a Pod template and the number of replicas • It supports hot-redeployments by changing parts of the Pod template • Horizontal scaling is possible apiVersion: extensions/v1beta1
 kind: Deployment
 metadata:
 name: <deployment-name>
 spec:
 replicas: 2
 template:
 metadata: labels: <key>: <value> spec: containers: - name: <container-name> image: <container-image> ports: - containerPort: 80 env: - name: <key> value: <value>
  • 11. Kubernetes - Services • Kubernetes uses an overlay network to provide different address spaces (we use flannel) • Every Pod has an IP address - but it changes every time one is created • Services provide a stable IP address for groups of Pods • Service names are resolvable by an internal DNS • Service selectors are used to match Pods according to there labels apiVersion: v1 kind: Service metadata: name: clojure-berlin-2016 labels: app: lens spec: type: NodePort ports: - port: 80 targetPort: 80 protocol: TCP selector: service: clojure- berlin-2016
  • 12. Kubernetes - External Access • Kubernetes networks are internal only • External access through load balancers necessary • Certain Platforms like Google Compute Engine provide load balancer integration with Kubernetes • We have our own solution as a combination of HAProxy and Kubernetes NodePort • Kubernetes Services with type NodePort are exposed on every worker under a certain port frontend http bind 0.0.0.0:80 mode http option httplog acl host_clj hdr(host) clj.<domain> use_backend clj if host_clj backend clj mode http balance roundrobin option httplog server worker-1 <ip>:32599 check server worker-2 <ip>:32599 check
  • 13. Deployment Lifecycle GitLab CI Source Code build test Kubernetes Test Cluster Kubernetes Prod Cluster automatic deployment manual deployment git push
  • 14. Sample Clojure Service • .gitlab-ci.yml • Like .travis.yml contains instructions for GitLabCI how to test, build and deploy • Dockerfile • Instructions for Docker how to build the image of the app • Artifact of the build is a docker image - not uberjar • kube-deployment.yml • Kubernetes deployment instructions • kube-svc.yml • Kubernetes service description https://github.com/alexanderkiel/clojure-berlin-2016
  • 15. The Core Namespace (ns clojure-berlin-2016.core (:require [aleph.http :as http] [clojure.core.async :refer [<!! chan]])) (defn -main [& args] (-> (fn [_] {:status 200 :body "Clojure Berlin 2016"}) (http/start-server {:port 8080})) (<!! (chan))) • A simple web server returning "Clojure Berlin 2016"
  • 16. The Leiningen Project File (defproject clojure-berlin-2016 "<VERSION>" :dependencies [[aleph "0.4.1"] [org.clojure/clojure "1.8.0"] [org.clojure/core.async "0.2.395"]] :main clojure-berlin-2016.core) • <VERSION> is replaced at build time by the Git SHA • :main is for lein run to work
  • 17. .gitlab-ci.yml - test/build image: clojure:lein-2.7.1 stages: - test - build - deploy test: stage: test tags: - docker script: - lein test build: stage: build tags: - docker script: - sed -i "s/<VERSION>/$CI_BUILD_REF/" project.clj - docker build -t clojure-berlin-2016:$CI_BUILD_REF . - docker push clojure-berlin-2016:$CI_BUILD_REF
  • 18. .gitlab-ci.yml - deploy branch deploy-branch: stage: deploy environment: test image: dreg.life.uni-leipzig.local/kubectl:0.4 tags: - docker script: - sed -i "s/<VERSION>/$CI_BUILD_REF/" kube-deployment.yml - kubectl config use-context gitlab-ci-test - kubectl apply -f kube-deployment.yml except: - master when: manual • Used to test a feature/fix branch in a full environment
  • 19. .gitlab-ci.yml - deploy test deploy-master: stage: deploy environment: test image: dreg.life.uni-leipzig.local/kubectl:0.4 tags: - docker script: - sed -i "s/<VERSION>/$CI_BUILD_REF/" kube-deployment.yml - kubectl config use-context gitlab-ci-test - kubectl apply -f kube-deployment.yml only: - master
  • 20. .gitlab-ci.yml - deploy prod deploy-prod: stage: deploy environment: prod image: dreg.life.uni-leipzig.local/kubectl:0.4 tags: - docker script: - sed -i "s/<VERSION>/$CI_BUILD_REF/" kube-deployment.yml - kubectl config use-context gitlab-ci-prod-a - kubectl apply -f kube-deployment.yml only: - master when: manual
  • 21. Docker file FROM clojure:lein-2.7.1 COPY src /app/src COPY project.clj /app/ WORKDIR /app RUN lein with-profile production deps EXPOSE 80 CMD ["lein", "with-profile", "production", "run"] • Just copy the sources into the container • Use Leiningen itself to run in production
  • 22. kube-deployment.yml apiVersion: extensions/v1beta1 kind: Deployment metadata: name: clojure-berlin-2016 spec: replicas: 2 template: metadata: labels: app: lens service: clojure-berlin-2016 spec: containers: - name: clojure-berlin-2016 image: dreg.life.uni-leipzig.local/clojure-berlin-2016:<VERSION> ports: - containerPort: 8080 resources: requests: cpu: "125m" memory: "1Gi" limits: cpu: 1 memory: "2Gi"
  • 23. kube-svc.yml apiVersion: v1 kind: Service metadata: name: clojure-berlin-2016 labels: app: lens spec: type: NodePort ports: - port: 80 targetPort: 8080 protocol: TCP selector: service: clojure-berlin-2016
  • 24. Steps to Follow • Create the Kubernetes Service • kubectl create -f kube-svc.yml • Edit HAProxy Config • add rules and backend for the service • Push to GitLab • git push
  • 27. Environments in GitLabCI • Very good visibility of wich commit is deployed in which environment right now • Manual deployment to prod possible
  • 28. Environment History • Easy to see when what commit was deployed • Rollback possible
  • 29. Numbers • Our team has 4 developers • We run 2 Kubernetes clusters (test and prod) with about 96 GB RAM and and 24 vCPU’s each • We run about 60 pods in production • We have other services like central log aggregation running using Fluentd and Elasticsearch/Kibana
  • 30. Thank You • Sample Project on Github
 https://github.com/alexanderkiel/clojure-berlin-2016 • Twitter
 @alexander_kiel • Mail
 [email protected]