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Kubernetes manifest

As explained in Machine Learning Platform Engineering

A Kubernetes manifest is a declarative document that specifies the desired state of one or more Kubernetes resources.

A Kubernetes manifest is a declarative document describing the desired state of Kubernetes resources. In an ML deployment workflow, CI/CD generates or updates manifests that reference the newly built service image, and applying them deploys the updated service. section 1.3.3

Manifests provide the operational contract between deployment automation and the Kubernetes cluster:

  • Reference the container image produced by CI/CD and stored in a container registry. section 1.3.3
  • Declare resource settings such as a service type, allowing Kubernetes to expose the application as ClusterIP or LoadBalancer. section 3.4.2
  • Act as the expected state that Argo CD compares with the live manifest and synchronizes from Git. section 3.4.2

Detecting configuration drift

After deployment, changing the fast-api-app service from ClusterIP to LoadBalancer makes Argo CD report the application as out of sync. Its diff identifies the service type as the difference between the live and expected manifests. section 3.4.2

Figure 3.14 Argo CD ensures that the manifests in Git and the ones deployed in K8s match.
A screen shot of a cartoon

AI-generated content may be incorrect.

Use the diagram to inspect how Argo CD keeps Git manifests and deployed Kubernetes resources aligned. section 3.4.2

How Machine Learning Platform Engineering covers it

How deep it goes
Explains image references, service types, live-state diffs, and synchronization, but omits manifest syntax and resource schema details.
Examples
Uses the fast-api-app service, ClusterIP and LoadBalancer types, Argo CD diffs, and kubectl port-forwarding.
What you can do after
Operate/configure ML deployments by applying manifests and synchronizing them through Argo CD.
How it connects
Connects Kubernetes manifests with containerization, container registries, CI/CD, Git, Helm, and Argo CD.

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This explainer was generated by Manning's knowledge graph from the text of Machine Learning Platform Engineering. The section links point to the parts of the book it draws on.