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.
Ruby Logs Monitoring & Observability
Effortlessly track Ruby logs, gaining instant insights into errors and refining logging for a more efficient and reliable application.
Challenges
Monitor Ruby application logs and runtime metrics in production environments
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.
Request Handling and Application Flow
- Track log generation across web requests, controllers, background jobs, and scheduled tasks to understand Ruby application execution flow.
- Correlate log entries with request context, routing paths, and service interactions to trace application behavior.
- Identify failures in controller execution, job processing, and service workflows affecting request completion.
- Detect disruptions in background processing and task scheduling impacting system reliability.
Exception and Runtime Diagnostics
- Capture Ruby exceptions, stack traces, and runtime errors generated during application execution.
- Correlate exception logs with impacted services, endpoints, and deployment changes to identify root causes.
- Identify recurring failures caused by dependency conflicts, configuration issues, and code regressions.
- Detect hidden runtime failures affecting application stability and workflow continuity.
Performance and Execution Signals
- Analyze slow request logs, job execution warnings, and runtime timing messages affecting performance.
- Correlate execution behavior with database latency, external API calls, and service dependencies.
- Identify excessive logging from background jobs and application components increasing runtime overhead.
- Detect performance degradation through abnormal execution timing and irregular log volume patterns.
Security and Operational Monitoring
- Track authentication failures, access violations, and suspicious request activity captured in Ruby logs.
- Identify abnormal usage behavior, misuse patterns, and unauthorized interactions affecting services.
- Correlate application logs with infrastructure activity for incident investigation and visibility.
- Detect operational and security incidents impacting Ruby workloads using centralized log insights.
Why Atatus
Why choose Atatus for Ruby logs and metrics monitoring?
Production-grade visibility into Ruby application behavior, background jobs, and runtime performance
01
Built for Ruby production workloads
Designed to ingest Ruby and Rails logs generated in real-world production environments without requiring invasive code changes.
02
Rails and job system awareness
Understands log patterns emitted by Rails controllers, ActiveRecord operations, and background job processors such as Sidekiq.
03
Application and runtime context
Combines Ruby log data with process-level metrics to provide context around memory usage, garbage collection, and request handling.
04
Faster root cause analysis
Correlates errors, slow requests, and worker restarts across logs and metrics to reduce investigation time during incidents.
05
Handles high-concurrency servers
Scales with multi-worker Ruby application servers and background job systems without impacting application throughput.
06
Works across modern deployments
Aggregates Ruby logs and metrics from virtual machines, containerized services, and cloud-hosted production environments.
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.
Ruby Logs Monitoring in Atatus is a comprehensive solution that allows users to track, analyze, and troubleshoot logs generated by Ruby applications. It provides real-time visibility into log data, helping to identify issues, improve performance, and ensure the health of your Ruby applications.
Atatus's Ruby Logs Monitoring integrates seamlessly with your Ruby 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, Ruby 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, Ruby Logs Monitoring seamlessly integrates with other Atatus products, such as APM (Application Performance Monitoring). This integration allows for a holistic view of your Ruby 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 Ruby 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 Ruby 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.