Everything in Docker & Kubernetes, page 11
Prometheus Exporters: Translating Metrics for Monitoring
A Prometheus Exporter is a translator, converting metrics from third-party systems like databases or hardware into the format Prometheus can scrape. Use one when you can't modify an app's code directly.
Prometheus Architecture: A Pull-Based Monitoring System
Prometheus is a monitoring system that actively pulls metrics from your services, rather than waiting for them to push data. It's the standard for tracking performance in dynamic environments like Kubernetes.
Kubernetes Cluster-Level Logging
Cluster-level logging treats logs as a stream, not as files on ephemeral pods. It centralizes logs from all nodes before they disappear when a pod dies, which is essential for debugging any production application.
Kubernetes Metrics Server: The Engine for Autoscaling
Metrics Server is the dedicated speedometer for your cluster's pods, feeding CPU and memory usage to Kubernetes's autoscalers. It powers the Horizontal and Vertical Pod Autoscalers and the kubectl top command. The footgun: it's *only* for autoscaling.
Kubernetes Events: The Cluster's Short-Term Memory
Think of Kubernetes Events as a cluster's temporary log, recording state changes like a Pod starting or a container failing. Use them with kubectl describe to debug issues in real-time.
The Three Pillars of Observability
Observability isn't one tool; it's a three-legged stool of metrics, logs, and traces. Metrics give the 'what' (CPU is high), logs the 'why' (an error loop), and traces the 'where' (which service is slow). The footgun is treating them as separate silos.
Falco: Real-Time Threat Detection for Cloud-Native
Falco is a runtime security camera, watching Linux syscalls to detect threats in real time. It's used in Kubernetes to spot abnormal behavior like privilege escalation or writing to /etc. The key is it only *detects* and *alerts*; it doesn't block threats.
Kubernetes Audit Logging: Your Cluster's Black Box Recorder
Kubernetes audit logging is the security camera for your API server, recording every API call to answer "who did what, and when?". It's essential for security forensics and compliance, but a common footgun is using a weak default or logging everything.
Kubernetes API Server Authorization Modules
Kubernetes API server authorization is like a chain of security guards. A request must get a "yes" from at least one configured module (like RBAC) to pass. This is fundamental to securing any cluster. The footgun is that the chain stops at the first "allow."
K8s Authentication: Proving Who You Are to the API Server
The K8s API Server is a vault door; authentication is proving your identity to the guard. It tries a chain of methods—like OIDC for users or tokens for pods—until one succeeds. The footgun: unauthenticated requests become system:anonymous, a major risk.
Kubernetes Admission Controllers: The API's Gatekeepers
Think of admission controllers as bouncers for your Kubernetes API. They intercept requests before objects are saved, enforcing custom policies like security rules or required labels. The footgun: a broken controller can block all changes to your cluster.
Pod Security Admission: Kubernetes' Built-in Guardrails
Think of Pod Security Admission (PSA) as a bouncer for your namespaces, enforcing security rules before pods can run. It applies security standards (Privileged, Baseline, Restricted) via simple labels.
Pod Security Standards: A Security Checklist for Pods
Pod Security Standards are a built-in security checklist for your pods. You apply a level (Restricted, Baseline, Privileged) to a namespace to prevent risky configurations like running as root.
Pod Security Context: Set Security Rules for Pods
A Pod Security Context defines security settings for all containers in a Pod, like setting permissions for a user group before adding users. Use it to enforce non-root execution or manage shared volume permissions.
Kubernetes RBAC: Roles vs. ClusterRoles
Think of Kubernetes RBAC Roles as permissions for a single room (a Namespace), while ClusterRoles grant access to the entire building (the cluster). Use Roles for namespaced apps and ClusterRoles for admin tasks.
Kubernetes Scheduler Framework: A Plugin System for Pod Placement
The Kubernetes Scheduler Framework is a plugin pipeline for pod placement. Use it to add custom logic—like co-scheduling ML jobs or avoiding specific nodes—without forking Kubernetes. The footgun: a slow plugin can bottleneck your entire cluster's scheduling.
Kubernetes CPU Management: Static vs. None Policy
K8s CPU policies control if your pod gets a dedicated CPU core or just a time-slice of a shared one. The default none policy maximizes utilization, while static gives exclusive cores to latency-sensitive apps.
Pod Priority: Deciding Who Gets Evicted in Kubernetes
Pod Priority is a VIP pass for your critical workloads, telling the scheduler which pods can bump others off a node. This ensures system-critical services run even on a full cluster. The footgun: high-priority pods can cause cascading evictions if not planned.
Kubernetes LimitRange: Setting Guardrails for Pod Resources
LimitRange acts like a bouncer for Pod resources, setting min/max CPU and memory rules for each Pod in a namespace. It's used to prevent resource hogging and apply sensible defaults.
Node Affinity: Tell Your Pods Where to Go
Node affinity is like giving pods a 'preferred seating' list for nodes. You guide the scheduler to nodes with specific labels, like those with GPUs or in a certain zone. The footgun is confusing 'required' (a hard rule) with 'preferred' (a suggestion).
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