Find the runtime bottleneck behind "Python is slow"
Track process RSS, GC collection counts across generations, active thread count, and CPU time. Spot memory leaks in long-running workers before they force a restart.

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Debug slow views, trace requests across async boundaries, and monitor background workers end to end. Built natively on OpenTelemetry with no proprietary agent or SDK.
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Process memory, GC collections, active threads, and asyncio task counts for Python in production.
Track process RSS, GC collection counts across generations, active thread count, and CPU time. Spot memory leaks in long-running workers before they force a restart.


Distributed traces that follow context through asyncio coroutines, Celery task chains, and multi-process worker pools. You see the full flow from web handler to background job, not just the WSGI request.
Logs, traces, metrics, and alerts in one connected view. Click from one to any other.

Click from a log line to its trace, then jump from a span to the underlying metrics. Works with the standard logging module, Loguru, and structlog. OpenTelemetry's trace-context correlation and Dash0's resource-centric design make it automatic, no manual linking.
Define checks on Python process memory, Celery queue depth, or HTTP latency using PromQL or the query builder. Reuse open-source alert rules from Awesome Prometheus Alerts and get notified via email, Slack, or any webhook.

Install the OpenTelemetry distro, bootstrap your libraries, and wrap your app with opentelemetry-instrument. No code changes required.

Install opentelemetry-distro, run opentelemetry-bootstrap to detect your libraries, then wrap your app with opentelemetry-instrument. Works with any WSGI or ASGI server.

The Dash0 Operator auto-instruments Python pods on Kubernetes with zero code changes. Or configure via environment variables in your Dockerfile for any deployment target.

Open-source skills for Claude Code, Cursor, Windsurf, and 38+ other AI coding agents. Correct resource attributes, span status codes, and Collector patterns from the first commit.
No proprietary agents and no vendor-specific code in your repo, just standard OpenTelemetry from instrumentation to export to query.
Dash0 is designed as an OpenTelemetry-native observability platform. Your instrumentation uses the official OTel Python SDK — semantic conventions and resource attributes preserved as-is, enabling standardized data collection across distributed systems.

Import your existing Prometheus alerts and query traces, logs, and metrics with PromQL or SQL.

Perses-compatible dashboards, PromQL alert rules, and OTel Collector configs. Everything Dash0 produces is an open-standard artifact you can commit to git.
The definitive guide to Python’s built-in logging module. Covers handlers, formatters, filters, hierarchical loggers, and integrating with OpenTelemetry for trace-correlated logs.
A practical comparison of the standard logging module, Logure, structlog, and python-json-logger. When to use each, performance benchmarks, and OpenTelemetry integration patterns.
How to configure structured JSON logging in Python for production. Covers python-json-logger setup, field customization, and integrating with OpenTelemetry for centralized observability.