What are your non-negotiable Kubernetes deployment practices for resilience and secu

[William.R]

My team is migrating our monolithic application to a microservices architecture on Kubernetes, and while we have the basic deployments running, I'm concerned our configuration lacks resilience and follows poor security practices. We're manually applying YAML files and haven't established patterns for secrets management, resource limits, or automated rollbacks, which feels like a disaster waiting to happen. For engineers who manage production Kubernetes clusters, what are your non-negotiable Kubernetes deployment best practices for ensuring stability and security? How do you structure your namespaces and network policies, and what tools or processes do you use for configuration management and secret injection that balance security with developer productivity?

[Gary.R]

Non-negotiables for a stable cluster: start with namespaces for each environment or team, plus ResourceQuota and LimitRange so nobody drains resources. Enforce a default-deny network policy and keep pods behind a proper Ingress with TLS. Require readiness and liveness probes, apply RBAC with least privilege, and enable secrets encryption at rest. Don’t forget a PodDisruptionBudget and an attitude of immutable deployments (deploy new images, roll back cleanly).

[Ella18]

Secrets management is where many teams trip: avoid storing secrets in manifests. Use a Secrets Store CSI driver with your cloud KMS or an external secrets manager (Vault, AWS Secrets Manager, etc.) or encrypt with SOPS and pull in at runtime. For config, use ConfigMaps and overlays (Helm values or Kustomize). Consider a GitOps workflow (Argo CD or Flux) to bridge the gap between code and deployments, with secrets injected at runtime rather than baked into images.

[NathanS]

Deployment and rollback strategy is where it matters most. Prefer GitOps tooling (Argo CD/Flux) and canary or blue‑green rollouts (Argo Rollouts) so you can observe before full promotion. Keep a robust rollback path via image versions and rollout history, ensure health checks drive traffic, and size autoscaling with HPA. Document decisions and have a tested upgrade path to minimize blast radius.

[OliverS]

Security governance is foundational. Use admission controls (OPA Gatekeeper or Kyverno) to enforce policies like non-root containers, read-only root filesystem, and restricted privilege. Apply Pod Security Standards where possible and supplement with runtime controls (seccomp, AppArmor). Enable TLS everywhere, rotate credentials, and regularly scan images (vulnerability scanners and SBOMs). Use RBAC with the principle of least privilege and review access logs to detect misuse.

[JackZJ]

Observability and reliability later win small battles. Instrument everything with Prometheus and Grafana, plus alert rules that reflect real SLOs. Collect logs with Loki/EFK and traces with Jaeger or OpenTelemetry. Implement canary tests and progressive rollouts to catch regressions early, and use a PodDisruptionBudget to protect critical deployments. If you’re starting, pick one monitoring stack and grow from there.

[Nicholas37]

Starting plan you can actually execute this month: (1) inventory all deployments; (2) decide your namespace structure; (3) enable a default-deny network policy; (4) set ResourceQuota and LimitRange; (5) switch to a secrets-management path (external secret store or Vault) and enable encryption at rest; (6) add readiness/liveness checks and a simple canary rollout; (7) implement basic observability (Prometheus + Grafana, Loki). If you want, tell me your stack and cloud provider and I’ll tailor concrete commands and a minimal starter manifest set.