--- title: "Analytics" description: "Logs, metrics, traces and alerts, plus product analytics and ML workloads." url: https://railway.com/guides/topics/analytics guides: 18 last_updated: 2026-11-05T19:03:01.649Z --- # Analytics Logs, metrics, traces and alerts, plus product analytics and ML workloads. ## Get started 1. [Set Up Structured Logging for a Production App](https://railway.com/guides/structured-logging-production.md): Emit JSON logs from your Railway services so the Log Explorer can parse, color, and filter them by level and custom attributes. 2. [Ship Application Logs to a Third-Party Aggregator](https://railway.com/guides/ship-logs-third-party.md): Build a log drain on Railway with a Vector forwarder service. Apps send logs over private networking, and Vector fans them out to any aggregator. 3. [Self-Host Langfuse for LLM Observability](https://railway.com/guides/langfuse-llm-observability.md): Deploy Langfuse v3 on Railway with Postgres, ClickHouse, Redis, and object storage. Trace, debug, and evaluate your LLM applications on infrastructure you control. ## Build and deploy - [Deploy a Jupyter Server for Team Data Work](https://railway.com/guides/jupyter-server-team.md): Run a shared JupyterLab server on Railway with token authentication, a persistent volume for notebooks, and health checks for zero-downtime deploys. - [Run ClickHouse for Product Analytics](https://railway.com/guides/clickhouse-analytics.md): Deploy ClickHouse on Railway from the template or the official Docker image, size its volume for event data, and ingest and query analytics events from a Node.js service. - [Connect a Third-Party Observability Tool](https://railway.com/guides/third-party-observability.md): Send telemetry from your Railway services to third-party observability tools. Covers vendor SDKs (Datadog, New Relic, Sentry), OpenTelemetry (OTLP), and common deployment pitfalls. - [Set Up a Datadog Agent in Railway](https://railway.com/guides/set-up-a-datadog-agent.md): Learn how to set up a Datadog agent in Railway. - [Deploy Triton Inference Server on Railway](https://railway.com/guides/deploy-triton-inference-server-on-railway.md): Learn the benefits of using Triton inference server and how to deploy it on Railway - [Deploy Offen on Railway](https://railway.com/guides/offen-web-analytics.md): Offen is an open-source, lightweight, and free analytics solution. In this post, we’ll deploy an Offen instance connected to a PostgreSQL database on Railway! - [Self-hosted website analytics](https://railway.com/guides/self-hosted-website-analytics.md): In this post, we talk about self-hosted alternatives to Google Analytics, why you should be using them instead and how you'd go about deploying them on Railway! ## Run in production - [Self-Host Uptime Kuma for Uptime Monitoring](https://railway.com/guides/uptime-kuma.md): Deploy Uptime Kuma on Railway with a volume for persistent monitor history. Monitor public sites and internal services, and publish status pages. - [Debug a Production Incident with Logs, Metrics, and Traces](https://railway.com/guides/debug-production-incident.md): A step-by-step incident debugging workflow using Railway's built-in observability surfaces. Confirm scope with metrics, find the failure in HTTP and deployment logs, correlate requests, and mitigate with a rollback. - [Set Up Alerts for Crashes, Restarts, and Failed Deploys](https://railway.com/guides/alerts-crashes-failed-deploys.md): Configure Railway webhooks and monitors to get notified in Slack, Discord, or your own service when a deployment fails, crashes, or a resource threshold is crossed. ## More guides - [Instrument an App with OpenTelemetry](https://railway.com/guides/instrument-app-opentelemetry.md): Enable Railway's built-in tracing, follow requests from the edge into your service, and add OpenTelemetry spans from your code with automatic instrumentation or an SDK. - [Roll Back a Bad Deploy Fast](https://railway.com/guides/roll-back-bad-deploy.md): How to revert a broken deployment on Railway in under a minute. Covers rollback vs redeploy vs restart, image retention limits, and healthcheck-gated deploys that stop bad code before it goes live. - [Right-Size CPU and Memory from Real Metrics](https://railway.com/guides/right-size-cpu-memory.md): How to read the Metrics tab on Railway, translate real CPU and memory usage into a monthly cost, and set replica and usage limits that cap spend without crashing your service. - [Load Test an App Before Launch with k6](https://railway.com/guides/load-test-k6.md): Write a k6 load test, run it locally or as a Railway service, set realistic performance targets, and read Railway metrics while the test runs. - [Logs, Metrics, and Traces: What Does Each Signal Tell You?](https://railway.com/guides/logs-vs-metrics-vs-traces.md): Learn how logs, metrics, and traces work together to cut incident resolution time. See how each signal answers a different question. ## Related topics - [Containers and Hosting](https://railway.com/guides/topics/containers.md): Deploy from Docker and Compose, self-host open-source tools, and scale across replicas and regions. - [AI Agents](https://railway.com/guides/topics/ai.md): Host agents, MCP servers, RAG pipelines, model gateways and inference services. - [Storage](https://railway.com/guides/topics/storage.md): Run Postgres, Redis, MySQL and object storage on Railway: pooling, backups, migrations and vector search. - [Backend](https://railway.com/guides/topics/backend.md): APIs, background workers, queues, cron jobs and webhooks. - [Frameworks and Languages](https://railway.com/guides/topics/frameworks.md): Deploy apps in Python, Go, Rust, Ruby, PHP, Java, Elixir and more, with their frameworks. - [Comparisons and Migrations](https://railway.com/guides/topics/comparisons.md): How Railway compares with other platforms, what it costs, and how to move over from Heroku, AWS and others.