CKA in 2026 — troubleshooting is now the biggest domain
The Certified Kubernetes Administrator curriculum, its domain weightings, what changed, and why the exam rewards speed at the terminal more than knowledge.
Showing all 14 posts
Configuring MCP servers correctly — the parts that bite
The two-part declaration people get half right, why an API key is not an MCP credential, and where secrets should live so a prompt injection cannot read them.
Using Claude in DevOps without pretending it's magic
Where an LLM helps a delivery pipeline, where it is the wrong tool, and the four architectural choices that decide which of those two you end up with.
The liveness probe that makes your uptime worse
Liveness, readiness and startup probes do different jobs. Conflating them is one of the few Kubernetes misconfigurations that actively causes outages.
Default-deny NetworkPolicy without breaking DNS
Locking a namespace to default-deny and adding traffic back safely, why DNS breaks first, and the selector mistake that silently allows far more than intended.
Claude Code for platform teams: a setup that survives contact
Project context, permission boundaries, hooks and subagents — the configuration that decides whether agentic coding helps a platform team or generates work for it.
CKS — the Kubernetes security exam, and the CKA prerequisite trap
Curriculum weightings for the Certified Kubernetes Security Specialist, the prerequisite rule that is more ambiguous than people assume, and how to prepare.
CKAD — the Kubernetes exam for people who ship on it
Curriculum weightings for the Certified Kubernetes Application Developer, how it differs from CKA in character rather than difficulty, and how to prepare.
CKA, CKAD or CKS — which Kubernetes exam to take first
A side-by-side of the three CNCF Kubernetes certifications by cost, weighting and audience, plus the ordering constraint that decides it for most people.
Requests and limits — CPU and memory are not analogous
What happens when a container exceeds its CPU limit versus its memory limit, why the two answers differ, and what that means for how you set them.
Horizontal Pod Autoscaler: why it scales late, or not at all
The requests dependency nobody mentions, how the HPA replica formula really works, stabilisation windows, and why CPU is the wrong signal for most queue workloads.
PodDisruptionBudgets: the reason your node drain hangs
What a PDB does and does not protect against, the single-replica trap that blocks upgrades forever, and how to set minAvailable so maintenance can still happen.
Evaluating an AI feature without relying on vibes
Building an eval set that catches regressions, where LLM-as-judge is trustworthy and where it is not, and how to run it in CI without constant flakiness.
Cutting LLM cost in a pipeline without cutting quality
Prompt caching, model tiering, batching and effort control: four levers that cut spend on an LLM feature, in the order that returns most for least risk.
No posts match that search.