INTEGRATION / FRAMEWORKS

LangChain observability, in production.

LangChain makes it easy to build agents and chains; Obsivara tells you how they behave once real traffic hits them. Trace every chain run and tool call, attribute cost per chain and model, and get predictive alerts before a degrading chain becomes an incident — framework-native, no rewrite required.

LangChainEXAMPLE
AGENT RUNS TRACED / 24H3,184
STEPS PER RUN (AVG)11.4
LOOPS FLAGGED / 24H6
ILLUSTRATIVE · EXAMPLE DATA
WHAT YOU GET

LangChain, fully observable.

Full chain & tool tracing

Every chain run, tool invocation, and LLM call captured as a span tree — with inputs, outputs, latency, and errors at each step.

Cost per chain and model

Token and dollar cost attributed to the chain, agent, and model that spent it — so you can see which parts of your LangChain app drive spend.

Health scoring & predictive alerts

Continuous health scores per chain plus predictive failure alerts that flag a degrading chain before it fails in production.

Works with LangGraph

Multi-step LangGraph agents are traced as full execution graphs, so you can debug where a run stalled, looped, or errored.

HOW TO CONNECT

Three steps. No code changes.

1STEP 01

Instrument with the SDK or OpenTelemetry

Add the Obsivara Python/JS SDK around your chains, or point any OpenTelemetry instrumentation for LangChain at Obsivara's OTLP endpoint.

2STEP 02

Run your app

Traces flow automatically as your chains execute — no code changes to the chain logic itself.

3STEP 03

See it in Obsivara

Chains appear in the inventory and knowledge map with health scores, cost, and traces within minutes.

WHAT WE MONITOR

Signals tracked out of the box.

  • Chain and tool-call traces
  • Tokens, cost, and latency per step
  • Error rates and failing steps
  • Health score per chain
  • Predictive failure alerts
INTEGRATION FAQ

Common questions.

Does Obsivara require changing my LangChain code?

No. You instrument via the SDK wrapper or OpenTelemetry; your chain and agent logic stays the same. Obsivara observes execution without altering behavior.

Does it support LangGraph?

Yes. LangGraph agents are captured as full execution graphs, so multi-step runs are traceable end to end.

How is this different from LangSmith?

LangSmith is deepest for LangChain development and evals. Obsivara is framework-agnostic and adds production operations — cost intelligence, health scoring, and predictive alerts. See our Obsivara vs LangSmith comparison.

Connect LangChain in minutes.

No credit card · 5-minute setup