Ruby Logs Monitoring & Observability
Effortlessly track Ruby logs, gaining instant insights into errors and refining logging for a more efficient and reliable application.
Monitor Ruby application logs and runtime metrics in production environments
Centralize Ruby application logs
Collect logs emitted by Ruby applications running on Rails, Sinatra, or custom frameworks, including request handling, middleware execution, and application-level warnings.
Inspect Rails request lifecycle
Analyze Rails controller and middleware logs to understand request routing, view rendering time, and database interaction timing.
Track background job execution
Capture logs generated by background workers such as Sidekiq, Resque, and Delayed Job to investigate retries, failures, and long-running jobs.
Observe Ruby process behavior
Monitor Ruby process metrics including memory usage, object allocation pressure, and garbage collection activity to identify runtime bottlenecks.
Detect memory and exception issues
Surface Ruby exceptions, segmentation faults, and memory growth patterns visible in logs before they impact application availability.
Correlate logs with runtime metrics
Link Ruby log events with request duration, job execution time, and process-level metrics to understand performance degradation under load.
Monitor application server logs
Ingest logs from Puma, Unicorn, and Passenger to analyze worker restarts, request queuing, and concurrency limits.
Debug production traffic patterns
Use Ruby logs and metrics together to investigate traffic spikes, slow responses, and backend saturation in live environments.
Centralize and Analyze Ruby Logs With Real-Time Visibility
Collect, structure, and explore Ruby log data in Atatus so you can search efficiently, spot patterns quickly, and correlate logs with performance context for faster insights.
Raw Logs Do Not Reveal Patterns
Unprocessed Ruby log lines make it difficult to spot trends across requests or sessions, and parsing them into structured fields surfaces meaningful events and attributes.
Manual Searches Are Inefficient
Searching through log files across servers slows troubleshooting, and centralized ingestion with fast search enables instant access to relevant entries.
High Volume Obscures Key Signals
Large volumes of logs can bury important context, and filters with custom pipelines help focus on the log attributes that matter most.
Switching Contexts Slows Debugging
Jumping between raw logs and other tools breaks investigation flow, and saved views let you revisit filtered contexts without reapplying rules.
Logs Lack Insight Without Traces
Log entries alone do not show full request behavior, and correlating Ruby logs with traces ties log lines back to specific execution paths.
Why choose Atatus for Ruby logs and metrics monitoring?
Production-grade visibility into Ruby application behavior, background jobs, and runtime performance
Built for Ruby production workloads
Designed to ingest Ruby and Rails logs generated in real-world production environments without requiring invasive code changes.
Rails and job system awareness
Understands log patterns emitted by Rails controllers, ActiveRecord operations, and background job processors such as Sidekiq.
Application and runtime context
Combines Ruby log data with process-level metrics to provide context around memory usage, garbage collection, and request handling.
Faster root cause analysis
Correlates errors, slow requests, and worker restarts across logs and metrics to reduce investigation time during incidents.
Handles high-concurrency servers
Scales with multi-worker Ruby application servers and background job systems without impacting application throughput.
Works across modern deployments
Aggregates Ruby logs and metrics from virtual machines, containerized services, and cloud-hosted production environments.
Unified Observability for Every Engineering Team
Atatus adapts to how engineering teams work across development, operations, and reliability.
Developers
Trace requests, debug errors, and identify performance issues at the code level with clear context.
DevOps
Track deployments, monitor infrastructure impact, and understand how releases affect application stability.
Release Engineer
Measure service health, latency, and error rates to maintain reliability and reduce production risk.
Unified Logs Monitoring & Observability Across Different Platforms
Frequently Asked Questions
Find answers to common questions about our platform