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Runtime Code Analysis in
Test and Production
OverOps provides previously unavailable insights to
identify, prevent and resolve Code-Level Errors
Runtime Code Analysis in Test and Production
Identify, Prevent and Resolve
Get Reliable Code >OverOps is the industry’s first Software Data Optimization platform, merging continuous code analysis and machine learning in test and production. OverOps helps organizations identify when code changes introduce critical issues, prevent them from impacting customer experience and resolve them 10x faster.
Know When and Why Code Breaks
Identify Issues >Identify all errors, regressions and slowdowns, even those not detected by APMs and logs. Leverage AI to get a reliability score for every microservice, deployment and infrastructure component to prioritize critical issues.
Never Promote Bad Code Again
Prevent Issues >Prevent poor quality code from being pushed to production. Integrate with Jenkins to add code quality gates, and ensure faulty releases never get shipped.
Reproduce in Minutes With Code-Level Visibility
Resolve Errors >Reproduce every issue in just a few clicks. Get the source code and variable state across the entire stack for each error that occurred.
One Suite for
All Your Needs
All Your Needs
DevOps
Detect All Critical Issues
Developers
One Click to True Root Cause
QA
Don't Promote Bad Code
Executives
Advance Business Roadmap
Integrates Seamlessly
with
Over 100 Technologies
with
Over 100 Technologies
Consume the Data
Through Your Existing Platforms
View All Integrations
Through Your Existing Platforms
“OverOps turned days of work into minutes. Short of attaching a debugger in production, OverOps is the next best thing.”
”OverOps is the time-saver we’ve been looking for in other tools, that gives detailed analysis without accessing servers directly.”
“We use OverOps to monitor our flagship X1 XFINITY platform. With it, we are able to stay on top of every new error.”
“OverOps improved our development team productivity significantly by giving us the root cause to every error.”