AWS CloudWatch Metrics and Alarms: Practical Observability
Build a meaningful CloudWatch setup with custom metrics, composite alarms, and dashboards that catch real incidents without paging on noise.
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Build a meaningful CloudWatch setup with custom metrics, composite alarms, and dashboards that catch real incidents without paging on noise.
A practical tour of monitoring services with Prometheus for metrics collection and Grafana for dashboards, alerts, and SLO tracking.
A tour of the modern observability stack: metrics, logs, traces, and events. Learn how the pillars fit together and how to choose tooling without drowning in dashboards.
Service Level Indicators, Objectives, and error budgets demystified: how to pick the right metric, set a target, and use the budget as a decision tool.
Profile Go programs with pprof: enable the HTTP endpoint, capture CPU and heap profiles, read flame graphs, and find the hot spot that is actually costing you latency.
Master systemd's journal: query logs with structured filters, tail in real time, persist across reboots, and forward to a central collector.
A practical guide to attributing, monitoring, and controlling LLM spend per user, per feature, and per request without slowing down delivery.
Set up structured, high-performance logging in Node.js with Pino, including child loggers, redaction, and pretty-printing for development.
How to set up Python logging properly: loggers vs handlers, structured logs, contextual fields, log levels that scale, and how to avoid the classic print-debug trap.
Use LangSmith to trace, debug, and evaluate RAG pipelines step by step, from instrumentation to dataset replay and regression detection.