Reliability articles

Keep inference available during Kubernetes node drains

Set a PodDisruptionBudget around usable inference capacity, inspect blocked evictions, and account for replacement GPUs and model warmup.

Keep long-running workloads authenticated through token rotation

Use projected ServiceAccount tokens and refresh-aware clients so long-running training, notebooks, and services can keep authenticating without static credentials.

Restart containers selectively with Kubernetes restart rules

Use exit-code-based container restart rules, observe what stays within the Pod, and distinguish local recovery from retrying a complete ML operation.

Build a reliable foundation for autonomous agents

Build an operational foundation for autonomous agents using Polyaxon workload profiles, durable state, bounded authority, evaluation, and recovery ownership.

Scale agentic AI without breaking the infrastructure

Scale AI agents with admission control, dependency-aware concurrency, durable state, bounded authority, backpressure, and outcome-based capacity planning.

Evaluate AI agent infrastructure reliability

Evaluate AI agent infrastructure reliability through task-level outcomes, recovery behavior, Polyaxon execution evidence, and explicit operational ownership.

Rotate workload TLS with Kubernetes Pod certificates

Use Pod certificate projections and trust bundles for workload TLS, with signer prerequisites and rotation handling for long-running ML services.