Next-Gen Server Administration & InfraOps
Kubernetes at Scale and Service Mesh
Kubernetes handles scheduling and self-healing, but running it at scale means managing upgrades, multi-tenancy, and traffic between services. A service mesh adds mTLS, traffic shaping, and observability without changing application code.
Points clés
- Standardize on a managed or well-documented Kubernetes distribution and keep versions current.
- Use namespaces, quotas, and network policies to isolate tenants and workloads.
- Adopt a service mesh for mTLS, traffic splitting, and retry policies between services.
- Set resource requests and limits on every pod and enforce them with admission policies.
- Automate cluster upgrades with tested runbooks and rollback plans.
- Centralize logs, metrics, and traces with consistent labeling across clusters.
- Scan images and enforce signed, trusted registries in production.
- Test failure scenarios with chaos experiments before they happen in production.
Questions fréquentes
Do I need a service mesh?
Not always. Start simple and add a mesh when mTLS, traffic control, or deep observability become requirements.
Managed or self-hosted Kubernetes?
Managed reduces toil for most teams. Self-host when compliance or cost demands it.
How do you handle multi-cluster?
Federation or GitOps-driven identical clusters with clear ownership per cluster.
What is the biggest scaling risk?
Untested upgrades and missing resource limits. Both cause outages under load.
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