GitOps: Git based application deployment patterns on Kubernetes

A take on analyzing what GitOps is, in the current context. Presented at ContainerDays 2018 at Hamburg.

Transcript

1. GitOps - when Git ❤ K8s
   Git based application deployment patterns on
   Kubernetes
   

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2. Hello!
   I’m Shahidh
   @shahidh_k GraphQL on Postgres
   

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3. Git
   

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4. Declarative tools
   

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5. Declarative
   tools
   ❤
   Git as source
   of truth
   

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6. Git: source of truth
   ● Application Source Code
   ● Application Configuration as Code
   ○ Kubernetes
   ○ Docker
   ● System Configuration as Code
   ○ Ansible
   ○ Chef
   ○ Puppet
   ● Infrastructure as Code
   ○ Terraform
   ○ CloudFormation
   

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7. Git push
   

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8. ● Write code
   ● git push heroku master
   Changed the world for developers
   Suddenly they’re all ninjas
   Developers are doing DevOps!
   Git push workflow
   

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9. The simplest DevOps task:
   Build & Deploy on Kubernetes
   

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10. Build & Deploy
    $ docker build -t registry.com/my-image:my-tag .
    $ docker push registry.com/my-image:my-tag
    $ kubectl set image deployment/my-deployment
    container=registry.com/my-image:my-tag
    

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11. $ git push dev master
    

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12. Demo 1 : Git push to update webpage
    

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13. Gitkube architecture
    git-remote
    k8s :: deployment,svc
    Exposed externally
    SSH-key based auth
    deployment
    $ git push dev master
    CRD configuration
    k8s :: CRD
    Deployments to update
    authorised-keys
    Dockerfile path
    controller
    k8s :: operator
    Apply changes
    $ kubectl ... remote.yaml
    > your computer
    Kubernetes cluster
    

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14. Extend to more DevOps tasks?
    git push to:
    ● Build and run unit-tests
    ● Deploy code
    ● Deploy configuration
    ● Apply stateful migrations
    ● Run integration tests
    

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15. Demo 2: Sending a slack notification on deploy
    

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16. git push
    to
    apply Kubernetes objects
    (git hooks are amazing)
    

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17. K8s controller
    >
    yaml
    Control
    -loops
    containers, iptables,
    resource allocation,
    volumes
    You do this
    This just
    happens
    

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18. CRD + Operator
    >
    yaml
    Operator
    (does stateful
    things)
    Jobs, pods, volumes
    You do this
    This just
    happens
    

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19. Eventual consistency - no pipelines
    >
    yaml
    containers, iptables,
    resource allocation,
    volumes
    K8s
    controllers
    You do this
    This just happens.
    Eventually.
    Custom
    operators
    >
    yaml
    >
    yaml
    >
    yaml
    >
    yaml
    Run jobs, reconfigure
    deployments
    

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20. Typical DevOps pipeline
    Build + run unit-tests Dockerfile
    Production build (artifacts) Multi-stage dockerfile
    Deploy configuration Update Kubernetes manifests
    Run stateful tasks (database migrations) Update CRs
    Run integration tests
    Run jobs with init-containers
    to check if microservices are
    ready
    

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21. GitOps
    

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22. GitOps
    ● Code, config, monitoring, policy etc. declarative & version controlled
    ● What can be described and observed can be automated and controlled
    and accelerated
    ● Git as a source of truth for the desired state of whole system
    ● Compare desired state to actual state and act
    ● Make ops changes by pull requests to this repo
    ● All changes need to go through git review process, no kubectl
    ● Use a k8s operator on the cluster to drive the observed cluster state to
    desired state
    ● Pipelines, observability, control
    Source: Weaveworks
    

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23. GitOps 1. Way of doing DevOps -- not a
    replacement
    2. Commit desired state in a git repo --
    not the steps to achieve the state
    3. Declarative vs Imperative DevOps
    4. Pipelines by default are imperative
    devops
    5. GitOps by definition is declarative
    devops
    6. Yaml file with a set of steps does not
    make it declarative
    

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24. GitOps Advantages
    ● Declarative: desired
    state is clear
    ● Git: recreate/rollback,
    audit trail
    ● Observability: diff with
    actual state
    ● Git as a dev-operator
    boundary
    Disadvantages
    ● Cannot have
    everything in git
    (secrets, dynamic
    variables etc.)
    ● New tools (k8s
    operators) required
    to achieve state
    instead of simple
    scripts
    

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25. Git as the
    developer -
    operator
    boundary
    

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26. Git: stable developer - ops boundary
    ● Consistent tooling for devs
    ● Freedom for operators to
    change the plumbing
    underneath
    ● Git hooks on client/server
    side, webhook integrations
    offered by GitHub, GitLab,
    BitBucket etc.
    ● CRD + Operator on K8s
    

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27. Constraints
    ● git-hooks and webhooks can only
    make use of information inside the
    git repository
    ● or the environment that the
    git-hook/webhook runs in
    ● K8s Operators need manifests
    ● Key constraint: Everything must
    become declarative
    

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28. Everything as
    Code
    

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29. What did we achieve?
    Reduced toolset
    Developers only need to use git for all
    DevOps tasks
    Complete extensibility
    Git-hooks, k8s operators allow for infinite
    customisation and tooling to be
    implemented by operators without
    affecting the developer workflow in the
    slightest
    

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30. On pipelines
    ● Pipelines executing a sequence
    of tasks - imperative
    ● CI/CD tools - GitLab Auto
    DevOps, Jenkins X
    ● As more parts of it becomes
    declarative, we can start
    applying these configuration
    ● The CRD+Operator pattern works
    well
    ● No more pipelines?
    

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31. Git based tools on K8s
    

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32. Some more demos?
    

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33. Thank you for listening!
    Questions?
    @shahidh_k
    

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34. References
    ● GitOps - Operations by Pull Request
    ● Can GitOps solve the developer / ops boundary once and for all?
    ● GitOps - Modern best practices for high velocity app dev using cloud
    native tools
    

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