Platform and infrastructure questions for DevOps, SRE, and any backend role expected to own its service in production.
13 published across 8 topics.
DevOps and cloud fundamentals57 short answers on one page, for revising rather than studying.Processes and signals, file descriptors, DNS and TLS, and debugging connectivity from first principles.
Work up the layers and let each command eliminate a class of cause: resolve the name, check the route, see whether anything is listening, then decide from the failure mode whether packets are being refused, silently dropped, or answered by something that never replies.
df asks the filesystem how many blocks are allocated; du walks the directory tree and adds up what it can see. They diverge when space is held by files that are deleted but still open, when inodes rather than blocks have run out, when a mount hides files beneath it, or when the reserve for root is what you are hitting.
Namespaces and cgroups, image layering, multi-stage builds, and container security basics.
A CPU limit is a quota per scheduling period, so exceeding it means the process is throttled until the next period and gets slower. A memory limit has no throttle: the kernel reclaims what it can and then the cgroup OOM killer terminates a process, which surfaces as exit code 137.
An image is an ordered stack of read-only filesystem layers plus a config document, addressed by digest. A container is an ordinary host process with namespaces restricting what it can see and cgroups restricting what it can use, sharing the host kernel instead of booting its own.
Scheduling, controllers and reconciliation, services and ingress, probes, and resource management.
CrashLoopBackOff means the container starts and exits repeatedly, so read the previous container's logs and the exit code first, then work outward through probes, configuration, dependencies, and resource limits.
Removing a pod from its EndpointSlice and sending it SIGTERM happen concurrently, and the data-plane update takes time to propagate, so requests keep arriving at a pod that has already begun shutting down. The fix is a preStop delay plus an application that finishes in-flight work before exiting.
Pipeline design, artefact promotion, deployment strategies, and safe rollback mechanics.
Build one immutable artefact, promote that same artefact through environments behind ordered quality gates, and deploy so traffic can be shifted back instantly. Rollback only stays possible if schema changes are backward-compatible expand-contract steps decoupled from the code deploy.
Replace the stored key with OIDC federation so each job exchanges a short-lived signed token for temporary credentials, then make the trust policy specific to a repository, branch or environment. Also narrow the pipeline's own token, pin third-party steps to commit SHAs, and attest what you built.
Terraform state and drift, module design, and managing environments without duplication.
State is the mapping from a config address to a real resource ID, so it is the only thing that tells Terraform whether to create or update. Drift, imports, refactors and concurrent applies are all consequences of that mapping being separate from both the code and the infrastructure.
Compute, networking, identity, and managed-service selection across Azure, AWS, and GCP.
Decide by what the managed service removes from your on-call load versus which controls it removes from you, and price the option honestly rather than by sticker rate. The bills that surprise teams are internet egress, cross-zone traffic, and capacity that is provisioned but idle.
SLIs, SLOs and error budgets, incident command, on-call design, and blameless postmortems.
An SLI measures user-visible behaviour, an SLO is the internal target for that measurement, and an SLA is the contractual promise with penalties. The error budget is the allowed shortfall: 99.9% over a 30-day month is 43.2 minutes, and its job is to trigger an agreed policy.
Declare it, take the incident commander role explicitly, and mitigate before you diagnose - roll back or shed load first, understand later. Keep one channel as the record, publish updates on a fixed cadence, hand over rather than push through, and let the review produce owned actions instead of narrative.
Situations to work through: a failing rollout, an exhausted node, a leaked credential, a 3am pager.
Stabilise first and diagnose second, which usually means reverting the change before you understand it. Take one artefact of evidence on the way out, time-box the decision aloud, communicate impact on a fixed cadence, and treat the incident as open until the damage the deploy caused is repaired.