Blind runtime behavior
When Ruby apps slow under real traffic, teams lack a reliable view into what the runtime is actually doing. Assumptions replace evidence, and fixes become guesswork.
Ruby Application Performance Monitoring
Get end-to-end visibility into your Ruby performance with application monitoring tools. Gain insightful metrics on performance bottlenecks with Ruby monitoring to optimize your application.
Challenges
The Hidden Cost of Ruby in Production
Unclear failure paths
Errors surface without context on what triggered them. Engineers see symptoms but not the execution path that led there.
Slow Root Causes
Incidents demand fast answers, yet teams burn hours stitching clues across systems. The delay increases blast radius and operational stress.
Scaling side effects
What works at low traffic breaks subtly at scale. Latency compounds, queues back up, and the root issue hides behind secondary failures.
Noisy signals
Production generates massive amounts of data, but little of it explains why things broke. Teams struggle to separate signal from background noise.
Environment drift
Behavior differs across staging, production, and regions. Bugs reproduce only under specific conditions that are hard to isolate.
Ownership confusion
Multiple teams touch the same Ruby services. When incidents happen, responsibility is unclear and response slows down.
Reactive firefighting
Without continuous clarity, teams operate in crisis mode. Engineering time shifts from building to chasing production issues.
Key Features
Gain Deep Observability into Ruby Application Performance
Real-time performance monitoring designed for Ruby that helps teams understand runtime behavior, catch issues early, and optimize production performance with clarity.
Follow Every Ruby Request Through Your Stack
Get complete end-to-end traces across web requests, background jobs, and database interactions to understand how each part of your Ruby application behaves in production.
Understand How Your Ruby Services Interconnect
See relationships between your Ruby processes, databases, caching layers, and external APIs so you can uncover latency patterns, failure trends, and inter-service bottlenecks.
Track High-Value Ruby Transactions
Measure key business flows like API endpoints, user sessions, and background jobs in real time to detect slow routes, rising error rates, and regressions before they impact customers.
Visibility into External Dependencies
Monitor third-party services, external APIs, and integrations your Ruby apps rely on to spot slowdowns or failures that could degrade overall application performance.
Why Atatus
Why choose Atatus for Ruby logs and metrics monitoring?
01
Built for Ruby production
Atatus ingests Ruby and Rails logs from real production workloads without invasive code changes.
02
Framework and job awareness
Atatus understands Rails request flows, ActiveRecord operations, and background job systems like Sidekiq.
03
Runtime performance context
Atatus combines logs with memory usage, garbage collection, and process-level metrics.
04
Faster incident resolution
Atatus correlates errors, slow requests, and worker events to speed up root cause analysis.
05
High-concurrency ready
Atatus scales across multi-worker Ruby servers and background jobs without performance impact.
06
Modern environment coverage
Atatus aggregates Ruby logs and metrics across VMs, containers, and cloud infrastructure.
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.
The Ruby performance monitoring tool helps developers to optimize the Ruby server performance.
A good Ruby APM solution answers the following two questions:
- Is an application broken or slow?
- What is issue that's causing the application broken or slow?
You can easily use application performance monitoring tools to answer, detect and resolve the above issues before they could impact the end users.
In general, there are two types of monitoring:
- Black-box monitoring - It allows you can monitor the external behaviour of your system such as CPU usage, disk usage, memory usage, load averages etc..
- White-box monitoring - It allows you to keep an eye on the applications running on your server. It requires an agent to enable white-box monitoring.
Every organization should have a well-implemented Ruby APM solution, which allows DevOps teams (and the organization as a whole) to resolve issues and performance bottlenecks efficiently and reduce Mean Time To Resolution (MTTR). This has a substantial impact on the bottom line of the business.
Now organizations do not have to deal with the unnecessary work involved in maintaining an extensive software analysis group.
Your Ruby performance monitoring tools should be easy to use, offer actionable insights, and be able to:
- Manage applications in the language(s) your apps use
- Track performance at the code level
- Keep an eye on end-user experiences
- Make use of artificial intelligence
- The ability to monitor the entire infrastructure
- Provides information that connects app performance metrics to business outcomes.
Technical Benefits:
- Increase application uptime and reduces downtime
- Code level diagnostics
- Avoid network outages
- Reduces MTTR
- Server metrics
- Alerts and notification on error information
Business Benefits:
- Higher conversion rate
- Improves SEO
- Better end-user experience
- Improves productivity
- Reduced operational costs
With the help of the database monitoring, you can easily identify the database performance bottlenecks.
- Understand who's using your databases.
- Track key performance metrics for DB performance tuning.
- Detect the slow and most-time consuming SQL queries to optimize it.
- Alerts on availability and performance issues.