Kubernetes
by Cloud Native Computing Foundation
The Kubernetes API server knows what each cluster is doing: which pods run in which namespaces, how many replicas each deployment wants and has, what nodes can allocate and which warning events fired. Snapshots of that state in the Lake give platform teams a queryable history for capacity planning, cost allocation by namespace and post-incident review.
- Category
- Cloud & Data Platforms
- Type
- Containers & orchestration
- Interface
- REST API
- Built with
- Connect Any API
- Credentials
- Access token, Service account key
02Data
What you can sync.
- Pods
- Deployments
- Nodes
- Events
- Namespaces
Put Kubernetes pods next to revenue and usage, so every cost has an owner and a reason.
Need more? Name any other Kubernetes data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- An access token
- A service account key
Kubernetes uses an access token or a service account key. You add the credentials once, when the AI asks for them, and it tells you where to create them in Cloud Native Computing Foundation if you need help.
04Questions
Questions you can answer.
Once Kubernetes data is in your Lake, ask an AI Mind in plain words or build the answer in DataPrism BI.
- Which namespaces had the most container restarts and OOMKilled terminations this week?
- Which deployments ran with fewer ready replicas than desired, and for how long?
- How do CPU and memory requests per namespace compare with allocatable capacity on the nodes?
- Which warning events preceded the last three failed rollouts?
05How it works
How it works in DataMind.
-
Pick Kubernetes.
Open Lake, pick Kubernetes in the source picker and name the connection. Connect Any API opens with a ready prompt that points the AI at the Kubernetes API docs.
-
Answer a few questions.
The AI reads the Kubernetes documentation, then asks which credentials you will use, which data to sync (for example pods and deployments), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
It builds the connector, tests it and shows you sample rows. Then Kubernetes data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
06Pairs
Works well with Kubernetes.
Sources teams join with Kubernetes in the Warehouse, each one connected the same way.
