Native Node.js stream log capture
Instrument process.stdout/stderr streams and async logger calls to capture unhandledRejection events, assertion failures, and module load errors from production Node.js processes.
Node.js Logs Monitoring & Observability
Effortlessly track Node.js logs, gaining instant insights into errors and refining logging for a more efficient and reliable application.
Challenges
Achieve full visibility into Node.js application logs across Express, NestJS, and distributed runtime environments
Async operation log correlation
Parse structured logs from Winston, Pino transports, and custom async_hooks domains. Track Promise chain failures, EventEmitter memory leaks, and callback hell scenarios across distributed clusters.
Node.js cluster & worker insights
Monitor logs across primary/worker processes, PM2 instance groups, and Docker container fleets. Surface inter-process communication failures and load balancer health issues from Node.js runtime logs.
Event loop delay & heap analysis
Detect event loop lag warnings, V8 garbage collection pauses, heapdump triggers, and max-old-space-size exceeded conditions logged by Node.js diagnostics.
Database driver & queue failures
Capture Mongoose connection drops, Redis pub/sub disconnects, BullMQ job timeouts, and Prisma query failures embedded in Node.js application logs with full stack context.
Source map error resolution
Transform minified production stack traces back to original TypeScript/ESM source files. Link Node.js log entries directly to controllers, middleware functions, and service implementations.
Dependency version conflict alerts
Track npm audit warnings, peer dependency mismatches, and package-lock.json drift logged during Node.js startup and hot reload cycles across CI/CD deployments.
Microservices inter-service tracing
Correlate logs across NestJS microservices, Express API gateways, and GraphQL resolvers using traceparent headers and OpenTelemetry context propagation standards.
Request and Asynchronous Execution Flow
- Track log generation across API requests, middleware execution, and asynchronous job processing to understand request handling behavior in Node.js services.
- Correlate log entries with request IDs, service interactions, and execution paths to trace event-driven workflows across the application.
- Identify delays and failures in asynchronous execution, callback chains, and background job processing affecting service responsiveness.
- Detect breakdowns in request routing, middleware logic, and handler execution impacting API reliability.
Runtime Errors and Promise Rejection Tracking
- Capture runtime exceptions, unhandled promise rejections, and application errors generated during execution.
- Correlate stack traces with impacted endpoints, service interactions, and deployment changes to identify failure sources.
- Identify recurring runtime failures caused by dependency issues, memory leaks, or asynchronous execution conflicts.
- Detect silent runtime failures affecting API stability and transaction completion.
Event Loop and Execution Performance Signals
- Analyze slow request logs, event loop delays, and execution warnings affecting responsiveness.
- Correlate Node.js execution behavior with database operations, external APIs, and service-to-service communication latency.
- Identify excessive logging from middleware, background workers, and asynchronous tasks increasing CPU and I/O overhead.
- Detect performance degradation through irregular execution timing and sudden log volume changes.
Security and API Access Monitoring
- Track authentication failures, rate-limit violations, and unauthorized API access attempts captured in logs.
- Identify suspicious traffic behavior, misuse patterns, and abnormal request activity affecting service stability.
- Correlate logs across microservices to investigate cascading failures and operational disruptions.
- Detect incident patterns and response gaps using centralized Node.js log visibility.
Why Atatus
Why Choose Atatus for Node.js Logs Monitoring?
01
Built for Node.js scale
Atatus ingests and structures Pino and Winston logs automatically for high-traffic JavaScript applications.
02
Zero-config log parsing
Atatus detects popular Node.js log libraries without requiring code changes or reconfiguration.
03
Unified cluster visibility
Atatus combines logs across PM2 clusters, containers, and Kubernetes pods into a single timeline.
04
Non-blocking ingestion
Atatus forwards logs asynchronously to prevent backpressure during traffic spikes.
05
Minimal performance impact
Atatus maintains event loop responsiveness even under heavy concurrent workloads.
06
Cost-efficient retention
Atatus preserves critical Node.js logs long-term without runaway storage costs.
Teams
Unified Observability for Every Engineering Team
Atatus adapts to how engineering teams work across development, operations, and reliability.
Developers
Debug errors and slow paths with the full context of what happened.
Atatus for developersDevOps
Track deployments and see how each release affects stability.
Atatus for DevOpsRelease engineers
Watch latency and error rates to ship with less production risk.
Atatus for release engineers
FAQ
Frequently Asked Questions
Pricing, deployment, data and the agent. If something is missing, a person will answer it on a demo call.
Node.js Logs Monitoring in Atatus is a comprehensive solution that allows users to track, analyze, and troubleshoot logs generated by Node.js applications. It provides real-time visibility into log data, helping to identify issues, improve performance, and ensure the health of your Node.js applications.
Atatus's Node.js Logs Monitoring integrates seamlessly with your Node.js applications, capturing log data and centralizing it for easy analysis. The solution offers powerful search and filter capabilities, making it simple to pinpoint specific events or issues within your logs. It also provides alerting features to notify you of critical events.
By offering real-time log streaming and advanced search capabilities, Node.js Logs Monitoring enables quicker issue identification and resolution. The ability to correlate logs with performance metrics provides a contextual understanding, streamlining the troubleshooting process.
Yes, Atatus provides powerful log filtering and searching capabilities. Users can filter logs based on specific criteria, such as log level, timestamp, or custom keywords. The search functionality allows for efficient navigation through large log datasets.
Yes, Node.js Logs Monitoring seamlessly integrates with other Atatus products, such as APM (Application Performance Monitoring). This integration allows for a holistic view of your Node.js applications, combining logs with performance metrics such as Distributed Traces to provide a comprehensive understanding of your application's health.
Log data parsing prioritizes customer security by meticulously anonymizing Personally Identifiable Information (PII) data. Sensitive fields can be completely excluded during the parsing process, ensuring the privacy and compliance of customer information.
In Node.js Logs Monitoring, log pipelines are customizable workflows that allow users to filter, parse, and fine-tune log data based on specific criteria.
Log pipelines can be customized by using diverse filters and defining custom parsing rules. Users have the flexibility to configure pipelines to meet their specific monitoring requirements, ensuring that log data is processed and organized according to their preferences.
Yes, log pipelines can be configured to filter log data based on various attributes such as log source, severity, timestamp, or any custom field. This customization allows users to focus on specific aspects of log data that are most relevant to their monitoring goals.
Saved Views in Node.js Logs Monitoring enable you to create and save custom configurations for different troubleshooting scenarios. This feature simplifies collaboration, allows for quick context switching, and automates repetitive tasks, significantly improving overall efficiency.
If you exceed your log ingestion limits, we would contact you to discuss on stopping further processing new log data or upgrade your subscription.
You can choose to store logs in Atatus for a limited time (e.g., 7 days) or export them to external storage solutions like Amazon S3 for long-term retention.
To access historical log data beyond the retention period, you can rely on log data exports from Amazon S3, where you can push the logs into Atatus for further analysis.
Yes, Atatus provides users with the flexibility to customize log retention settings. Users can adjust retention periods based on their specific needs, aligning with compliance standards or internal data management policies.