Observability for AI Agents and Backends

Axonpush provides a unified observability platform designed to bridge the gap between your AI agents and their underlying backends. It consolidates data from your agents, backend services, and OpenTelemetry spans into a single, coherent timeline, all linked by a common trace ID. This allows you to pinpoint failures that occur in the complex interactions between different components of your AI systems.

• Unified Timeline: Visualize agent behavior, backend requests, and model calls on a single record, even while the process is active.

• Drop-in SDKs: Easily integrate with popular frameworks like LangChain, LangGraph, OpenAI, Anthropic, CrewAI, Vercel AI, Mastra, Google ADK, and LlamaIndex with minimal code changes.

• Auto-instrumentation: Supports Python and TypeScript, automatically instrumenting frameworks and logging libraries such as Pino, Winston, loguru, and structlog.

• OpenTelemetry-Native: Seamlessly integrates with existing OpenTelemetry collectors.

• Sentry-Compatible: Utilizes your existing Sentry DSN for compatibility.

• Agent-Native Spans: Captures crucial spans for tool calls, handoffs, and LLM tokens.

• Real-time Updates: Leverages WebSockets for real-time data fan-out, eliminating polling and batch lag.

• Self-hosted Option: Deploy the stack within your own AWS account, ensuring your trace data remains within your cloud environment.

• Learning Loop: Transforms recurring failures into automated regression tests.

Axonpush simplifies debugging by presenting all relevant information in one place, making it easier to identify and resolve issues that are often missed by separate APM and agent-specific tools.