OpenLIT vs PetalTrace

OpenLIT is an open-source platform for tracing and evaluating LLM activity, managing prompts, and tracking costs. Built on OpenTelemetry, it can capture model calls, tool use, and retrievals, with filters for user, session, cost, latency, and metadata. Evaluations can use an LLM judge, heuristics, or human review on production traffic or experiments. Prompt Hub provides versioning, dynamic variables, API retrieval, unlimited prompt fetching, and AI-assisted improvement. OpenGround supports side-by-side model comparisons for latency, tokens, and cost, including comparisons using a user’s own key. Coding agent monitoring covers sessions, costs, tokens, repository activity, and code impact. The site lists more than 56 integrations across LLMs, agent frameworks, vector databases, and GPUs. OpenLIT accepts OTLP data and can be self-hosted with Docker Compose or Kubernetes Helm. Its Apache 2.0 license and site description note that self-hosting keeps prompts, traces, and secrets in the user’s environment. The OSS plan costs nothing and includes unlimited self-hosted usage, users, projects, and environments.

PetalTrace is an open-source observability platform for developers examining AI agent workflows. It captures prompts and completions, tool calls, token use, costs, and execution timelines, with a React web interface plus CLI, HTTP API, and MCP server access. Full prompt capture can include system prompts, message history, tool definitions, and model responses. Users can search prompt and completion text, compare runs for structural, content, and cost differences, and replay runs with changed models or temperatures or in mocked mode. The platform accepts standard OpenTelemetry traces, including from applications that do not use PetalFlow. PetalFlow integration adds graph topology, node inputs and outputs, and replay-capable snapshots. Trace data is documented as stored in SQLite, and the software can be built from source or run from a release binary as a local daemon. Authentication is described as future functionality and disabled by default. The public repository identifies an MIT license; no commercial pricing or usage limits are stated.