Grafana is an open-source visualisation and dashboarding platform for time-series and observability data. It connects to many data sources (Prometheus, Loki, Tempo, Elasticsearch, MySQL, BigQuery, CloudWatch, Datadog) and renders queries as panels: graphs, tables, heatmaps, single-stat tiles, and more.

Core capabilities

• Dashboards. Compositions of panels with shared time ranges and variable…

OpenTelemetry (OTel) is the CNCF standard for instrumenting applications to produce telemetry: traces, metrics, and logs. It defines an open specification, language SDKs, a vendor-neutral collector, and wire protocols so applications can be instrumented once and the data can be sent to any compatible backend.

What it covers

• API and SDK. Per-language libraries for creating spans, recording…

Distributed tracing captures the path of a single request as it travels through multiple services, recording the timing, parent-child relationships, and metadata of each step. A trace gives operators a flame-graph view of where latency comes from and how services depend on each other.

Core concepts

• Trace. The full record of one request across all services it touches, identified by a…

Metrics are numerical measurements aggregated over time, used for dashboards, alerting, and capacity planning. Where logs answer "what happened to this particular request", metrics answer "how is the system behaving in aggregate".

Metric types

• Counter. Monotonically increasing value: requests served, errors, bytes sent.
• Gauge. A value that can go up or down: queue depth, memory in use,…

The default slog API is loose enough that a careless line ships broken JSON to production. Pin it down with Attr constructors, LogAttrs, a context-borne logger, and sloglint.

The default slog API is loose enough that a careless line ships broken JSON to production. Pin it down with Attr constructors, LogAttrs, a context-borne logger, and sloglint.

Automatically tag Python logs with request context using middleware and contextvars for distributed tracing in ASGI web applications.

Avoid configuring Python's root logger in libraries; use named loggers with NullHandler to let application code control logging behavior.

Learn how to build custom error types in Go to create stack traces without runtime overhead, inspired by Rob Pike's Upspin error handling.

Master Go 1.21's log/slog package for structured logging with levels, JSON output, and attribute grouping. No third-party libraries needed.

Configure Python logging for AWS Lambda's pre-configured handlers while maintaining compatibility with local development environments.