text: EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerDatadog TracingOn this pageDatadog Tracingddtrace is a Datadog application performance monitoring (APM) library which provides an integration to monitor your LangChain application.Key features of the ddtrace integration for LangChain:Traces: Capture LangChain requests, parameters, prompt-completions, and help visualize LangChain operations.Metrics: Capture LangChain request latency, errors, and token/cost usage (for OpenAI LLMs and Chat Models).Logs: Store prompt completion data for each LangChain operation.Dashboard: Combine metrics, logs, and trace data into a single plane to monitor LangChain requests.Monitors: Provide alerts in response to spikes in LangChain request latency or error rate.Note: The ddtrace LangChain integration currently provides tracing for LLMs, Chat Models, Text Embedding Models, Chains, and Vectorstores.Installation and Setupâ€‹Enable APM and StatsD in your Datadog Agent, along with a Datadog API key. For example, in Docker:docker run -d --cgroupns host \              --pid host \              -v /var/run/docker.sock:/var/run/docker.sock:ro \              -v /proc/:/host/proc/:ro \