Intermediate everything in DevOps & Cloud, page 8
Inference performance bottlenecks on Lambda
Cold starts loading the model, memory and CPU limits, no GPU, and package size dominate; mitigate with provisioned concurrency, loading the model once outside the handler, smaller models, and right-sized…
Deploying a real-time inference endpoint
Package the model artifact and inference code in a container, choose instance type and autoscaling, configure the endpoint with health checks, and plan safe rollout like canary plus monitoring.
Idempotency in data ingestion pipelines
Idempotency means re-running a step yields the same result with no duplicates; it matters because retries and at-least-once delivery are inevitable; achieve it with deduplication keys or upserts.
Handling late data in streaming windows
Use event-time windows with watermarks to bound lateness, allow a grace period before finalizing, and route data later than that to a side output.
Diagnosing and fixing data skew in Spark
This is data skew, caused by uneven key distribution concentrating rows on few partitions; mitigate with salting, broadcast joins, repartitioning, or adaptive execution.
Partitioning order events in a data lake
Partition by the columns queries filter on, typically date hierarchy and category, balancing granularity to avoid too many tiny files.
Reducing cross-region data transfer costs
Identify cross-region, cross-AZ, and internet egress; co-locate chatty components; add VPC endpoints, CDN caching, and compression.
Lifecycle storage tiering for compliance logs
Hot tier for 7-day query window, lifecycle rules transitioning to infrequent-access then archive, expiration at one year.
Rightsizing an underutilized VM fleet safely
Gather multi-week percentile metrics across CPU, memory, network and disk; pick smaller or right-family types; roll out gradually with monitoring.
Diagnose 100% CPU on a managed database
Correlate the spike with deploys and traffic, find top queries via the engine's views, inspect plans for missing indexes, then tune before scaling.
Enforce a cloud resource compliance policy
Prevent at creation with org policies or admission checks, detect violations via continuous config scanning, and auto-remediate by stripping the IP or alerting owners.
State drift in Terraform
Drift is when live infrastructure diverges from recorded state, usually via manual console changes; detect with plan or refresh, remediate by re-applying or importing.
Centralized logging across microservices
Ship structured logs from every service into a central searchable store, then propagate a correlation ID through all hops to trace one request.
Distributed tracing for serverless apps
Propagate a trace context through every hop, instrument with OpenTelemetry or X-Ray, capture spans including the database, and correlate traces with structured logs.
Idempotency in event-driven systems
Idempotency means repeated processing yields the same end state; it matters because messages get redelivered; achieve it with idempotency keys and conditional writes.
State machines versus long-running functions
State machines externalize state, pause for human input without running compute, give built-in retries and audit history, and bill per transition.
Running stateful apps with StatefulSets
Stateful apps need stable identity and storage; a StatefulSet gives stable names, ordered rollout, and per-Pod volumes.
Exposing Kubernetes services to the internet
A Service gives stable access and LoadBalancer exposes one service, while Ingress adds L7 host and path routing with TLS for many services.
Multi-stage Docker builds
A build stage compiles with the toolchain, the final stage uses a minimal base and copies only the artifact, cutting size and attack surface.
CI/CD pipeline for a container PaaS
Run tests, build the image, push the tag to a registry, then deploy it to Cloud Run. The registry is the build-to-deploy handoff.
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