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GitOps 101
2019-11-05, Michael Hausenblas
Who am I?
• Developer Advocate in the AWS container service team
• Previous roles at Red Hat, Mesosphere, MapR, applied research
• Find me via …
• Slack: AWS dev, Kubernetes, CNCF, Weaveworks
• Twitter: @mhausenblas
• Mail: hausenbl@amazon.com
Books
programming-kubernetes.info kubernetes-security.info
Note: book signing Thu 7 Nov from 10:30 to 11:30
Who are you?
Agenda
v Kubernetes and Git 101
v GitOps motivation & model
v BREAK 10:30am to 11am
v GitOps in action
v Progressive delivery
v Challenges
Learning goals
• Being able to explain what GitOps is
• Know about the benefit of GitOps
• Having some hands-on experience with an example GitOps set up
• Being able to decide if GitOps is the right choice for team/project
Kubernetes 101
Architecture
Overview
Architecture
API Server
kubectl get deploys
Kubernetes resources
• Core and custom resources
• spec: kubectl/HTTP API (via params and/or YAML/JSON)
• status: kubectl/HTTP API (YAML/JSON)
• Namespaces
• Labels and selectors, annotations
• Pods
• Deployments
• Services
Kubernetes resources
Boundaries
Running on Kubernetes?
Operators
operator = custom resource + custom controller
A short deployment history
• Shell scripts, Make files
• Ansible, Chef, Puppet, etc.
• Helm, ksonnet, kustomize, etc.
• GitOps
Git 101
remote
repo
working
directory
index
local
repo
git add git commit
git clone/pull
git push
What is GitOps?
What is GitOps?
GitOps is a standardized workflow for how to deploy, configure, monitor,
update and manage infrastructure-as-code
Core idea is having a Git repository that contains declarative
descriptions of the infrastructure desired in the production environment
and an automated process to make production environment match the
described state in the repository
What is GitOps?
• An operation model
• Derived from operation knowledge
• Technology agnostic
• A set of principles
• A way to speed up your team
GitOps: an operation model
Providing …
• A single source of truth for the
desired system’s state
• Separation of concerns between
development and deployment process
• Transparency and auditability
• Risk reduction (rollbacks)
Why should we care?
• Auditing and attribution
• Separation of concerns
• No crossing security boundary
• Process & constraints enforcement
• Great software ↔ human collaboration point
• Easy to validate for correctness (policies)
• System can self heal
The GitOps Model
Kubernetes
cluster
kubectl
(direct access)
configuration
repository
deployment
agent
image
repository
state
continuously
monitored
control loop
GitOps Principles
1 The entire system is described declaratively
2 The canonical desired system state is versioned (Git)
3 Approved changes to the desired state are
automatically applied to the system
4 Software agents ensure correctness
and alert on divergence
1 The entire system is described declaratively
Beyond code, data ⇒
Implementation independent
Easy to abstract in simple ways
Easy to validate for correctness
Easy to generate & manipulate from code
image
repository
1
The entire system is described declaratively
The canonical desired system state is versioned (Git)
Canonical Source of Truth (DRY)
With declarative definition, trivialises rollbacks
Excellent security guarantees for auditing
Sophisticated approval processes
Great software ↔ human collaboration point
2
image
repository
2
The desired system state is versioned
Approved changes to the desired state are
automatically applied to the system
Significant velocity gains
Privileged operators don’t cross security boundaries
Separates the What and the How
3
image
repository
3
Approved changes to the desired state are
automatically applied to the system
Software agents ensure correctness
and alert on divergence
4
Continuously checking that desired state is met
System can self-heal
Recovers from errors without intervention
(layer 8 issues)
It’s the control loop for your operations
image
repository
4
Software agents ensure correctness
and alert on divergence
Typical CI/CD pipeline
Continuous Integration
cluster API
Continuous Delivery/Deployment
container
registry
CI
code repo
dev RW
CI creds
Git creds
RW
CR creds
RO
RW
API creds
CR creds
Shares credentials cross several logical security boundaries.
Boundary
RO RW
container
registry (CR)
creds
cluster API
GitOps pipeline
container
registry
CI
code repo
dev RO
CR creds
CI creds
Git creds
RO
deploy
CR creds
RO
RW
config repo
creds
CR creds
Credentials are never shared across a logical security boundary.
RW RW
RW
cluster API
creds
canonical desired state store
config repo
cluster API
GitOps pipeline
container
registry
CI
code repo
dev RO
CR creds
CI creds
Git creds
RO
deploy
CR creds
RO
RW
config repo
creds
CR creds
Credentials are never shared across a logical security boundary.
RW RW
RW
cluster API
creds
operator RW config repo
process & constraints enforcement
Example workflow
• One Git branch for development:
• All developers can push changes there for testing purposes
• One Git branch for staging:
• Project lead or devops manager has ability to push/merge here for testing the
complete staged application
• One Git branch for production:
• The system operations manager is the only person to have push/merge
authorization here
Example workflow
GitOps in Action!
Tooling
• CNCF Flux
• ArgoCD
• Gitkube
• Tekton
• JenkinsX
Flux
github.com/fluxcd/flux
301.sh/velocity-gitops-101
Trainings environment:
Trainings repo:
github.com/mhausenblas/gitops101
So what actually happened?
1. We installed the Flux agent in our cluster
2. We added the agent key to our repository, so that it can read and
write the configuration
3. We configured the agent to watch to our repository
4. The agent noticed some manifests in the repository, and
automatically applied them
5. Kubernetes deployed the manifests
Progressive delivery
What is progressive delivery?
Progressive Delivery is Continuous Delivery with fine-grained control
over the blast radius, requiring:
• CI pipeline that produces immutable build artifacts
• CD pipeline designed for desired state reconciliation
• Smart routing for user facing apps and service to service
communication
• Observability (performance stats + business metrics)
• Fail fast mentality
Flagger
Flagger is a Kubernetes operator that automates the promotion of
canary deployments using App Mesh, Istio, Gloo or NGINX routing for
traffic shifting and Prometheus metrics for canary analysis.
Flagger implements a control loop that gradually shifts traffic to the
canary while measuring key performance indicators. Based on the KPIs
analysis a canary is promoted or aborted.
Flagger
Challenges
Technical challenges
• All your artifacts in VCS such as Git?
• Tooling selection
• app-focused vs infra-focused
• pace of ecosystem
Organizational challenges
• Is there a devops mentality in your organization?
• Is your organization ready for “cloud native”?
Recap and Resources
Recap: GitOps CI/CD
• Git is our single source of truth
• Deployments and rollback are all done via Git
• Auditing built-in
• Having separate pipelines for CI and CD enables better security
• Automated the deployment
• It’s easier to deal with if a deployment goes wrong
Resources
• https://www.gitops.tech
• https://github.com/weaveworks/awesome-gitops
• https://thenewstack.io/what-is-gitops-and-why-it-might-be-the-next-
big-thing-for-devops/
• https://www.reddit.com/r/kubernetes/comments/c2wgdz/gitops_in_
production_share_your_experiences/
• https://deploy.live/blog/a-year-with-gitops-in-production/
Rate the session
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