SKU/Artículo: AMZ-B0FYRYWHBN
PRODUCTION DEBUGGING WITH ROOKOUT: LIVE TROUBLESHOOTING WITHOUT DOWNTIME: Debug Kubernetes, serverless, and microservices in real-time with non-breaking breakpoints and dynamic logging
Format:
Kindle
Detalles del producto
Disponibilidad:
Fuera de stock
Fuera de stock
Peso con empaque:
0.76 kg
0.76 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Cut incident time with safe live debugging that works in production.When defects only appear under real load, you need a precise way to see what code is doing without halting threads or shipping risky builds. This book shows how to use non breaking breakpoints and dynamic logging to collect the right facts from running services, with strict guardrails that keep traffic flowing.You will learn a proven operating model, from labels and scoping to TTL and hit caps, plus data paths that satisfy security and compliance. Every step is grounded in real deployments across Kubernetes, serverless, and microservices.Set risk based criteria for when to place a live breakpoint in production, then contain scope with labels, predicates, TTL, and hit capsUnderstand the control plane, language agents, and snapshot flow, including Data On Prem routing with an ETL controller inside your boundaryStand up language stacks that actually work, JVM with JAVA_TOOL_OPTIONS and attach, .NET with portable PDBs, Node and Python with early initShip sources and symbols correctly, verify mapping, and keep packaging faithful across jars, containers, and serverless bundlesRun Kubernetes workflows at scale, target by namespace and version, manage secrets, and operate Cloud Native Debug Sessions safelyWork within serverless latency budgets, apply handler wrappers, do timeout math, and use provisioned concurrency or SnapStart when neededCorrelate across microservices with OpenTelemetry, carry span context into snapshots, and use the Tracing Timeline for end to end clarityTurn on Live Logger with contextual filters, keep verbosity safe during incidents, and tie hits back to traces and queuesBuild security you can defend, tested redaction patterns for PII and secrets, SIEM grade audit export, and change tracking for approvalsMeasure overhead honestly with k6 or wrk, track cold starts and steady state, and set p95 gates and rollback rulesCoexist cleanly with APMs, JVM instrumentation that plays well with Byte Buddy and OneAgent, and practical Dynatrace alignmentWire integrations that teams use, Sentry breadcrumbs and context, Datadog events and log correlation, Elasticsearch indices with ILMRun a regulated rollout, dual control approvals, canary enablement, and clear exit criteria that auditors can reviewThis is a code heavy guide with working examples, from YAML manifests and Systemd units to JSON policies and Shell scripts, so you can move from idea to a running session without guesswork.Grab your copy today and bring live debugging into your production practice with confidence.
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