Kubernetes Manifest Architect
Generate multi-resource production manifests with hardened securityContext, health probes, resource limits, and best practice audits.
Resource Requests & Limits (Prevent OOMKilled & Throttling)
Ingress Configuration (networking.k8s.io/v1)
Liveness Probe (Restart on Failure)
Readiness Probe (Route Traffic on Success)
Zero-Downtime RollingUpdate Strategy
Production Readiness & Security Audit Checklist
Kubernetes Production Workload Architecture
Deploying containers on Kubernetes requires more than just wrapping a Docker image in a Deployment. A resilient, enterprise-grade workload must properly coordinate resource QoS classes, graceful termination handshakes, Pod Anti-Affinity, and PodDisruptionBudgets.
Architectural Showdowns: Kubernetes Workload Patterns
Configured when requests == limits for both CPU and memory. The kubelet grants the highest eviction priority and assigns dedicated CPU cores if the static CPU manager is enabled.
- Last to be terminated when a node experiences memory pressure
- Eliminates CFS CPU throttling latency spikes
- Ideal for low-latency financial APIs and databases
Configured when requests < limits. Allows pods to burst into unallocated node headroom when load spikes occur, but risks eviction if the node runs out of physical memory.
- Maximizes cluster bin-packing and hardware efficiency
- Subject to CPU throttling under cluster-wide load
- Subject to OOMKill if overall node memory is exhausted
The modern successor to Ingress (GA in 1.28+). Splits configuration between GatewayClass, Gateway, and HTTPRoute resources with expressive native routing.
- Native canary traffic splitting without vendor annotations
- Cross-namespace routing delegation across teams
- First-class support for gRPC, TCP, and TLS route types
Monolithic single-resource abstraction designed in 2015. Requires hundreds of proprietary, vendor-specific annotations for basic operational features.
- Cannot share ports across multiple namespaces easily
- No standardized traffic splitting or header rewriting
- Portability between Nginx, Traefik, and AWS ALB is broken
Five Fatal Production Pitfalls in Kubernetes
When a pod without memory limits experiences a memory leak, it consumes all unallocated RAM on the physical worker node. The Linux kernel OOM killer activates and begins killing other innocent pods on the node. The kubelet enters MemoryPressure state, evicting pods and redistributing the load to adjacent nodes, triggering a cascading crash across the entire cluster.
A liveness probe tells Kubernetes when a container process is deadlocked and needs a hard SIGKILL restart. If your liveness probe checks downstream database connectivity, an unexpected database blip causes Kubernetes to SIGKILL all application pods at once. When hundreds of pods restart simultaneously, their database connection pools fire all at once, creating a catastrophic thundering herd.
Deploying with image: myapp:latest breaks GitOps immutability and makes rollbacks impossible. Different worker nodes pull different layer hashes depending on when they cached the image, leading to a split-brain deployment where some pods run build A and others run build B. Always pin immutable semantic versions or Git commit SHA digests (e.g. myapp:v2.4.1@sha256:...).
By default, Docker and Kubernetes containers execute as root (UID 0). If an application vulnerability allows Remote Code Execution (RCE), an attacker has root privileges inside the container, can write executable binaries to /bin or /tmp, and can attempt container breakout exploits against the host Linux kernel. Setting runAsNonRoot: true and readOnlyRootFilesystem: true completely eliminates this threat.
When cloud providers perform automated Kubernetes control plane or node pool upgrades, the kubectl drain command evicts pods from the target node. If a deployment has 3 replicas and all 3 reside on that node without a PDB, the node drain terminates all 3 pods simultaneously before new ones can initialize, causing customer-facing 502/503 errors. A PDB with minAvailable: 2 guarantees zero downtime.