Know When and Why Code Breaks and the Quality of Your Apps in All Environments

OverOps provides net new machine data from applications and services to help organizations effectively evaluate the reliability of their software, troubleshoot more efficiently and implement a culture of accountability. OverOps combines static and dynamic analysis to collect complete contextual data for every error and exception thrown –both caught and uncaught– in any environment, including production with minimal performance impact, securely and without any requirement to modify code.

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OverOps Data Platform

Implement Continuous Reliability


Investigate the overall quality of code and determine when it is safe to promote as part of a CI/CD workflow and provide feedback to dev about issues.

Create a Culture of Accountability


Create metrics dashboards that expose the overall quality of your applications and services across releases. Demonstrate quality trends over time.

Identify and Troubleshoot Errors More Efficiently


With complete context of an error including complete variable state across the execution stack, you spend less time investigating root cause.

About OverOps


OverOps captures unique code-aware insight about every error and exception––both caught and uncaught––in any environment, including production. This deep visibility into the functional quality of code helps developers more effectively troubleshoot issues and empowers operations to build metrics dashboards, implement continuous reliability and enhance their software supply chain.
PagerDuty Native Integration

Set alerts for error types and connect them easily with PagerDuty with preset integration setup

Anomaly Detection via PagerDuty

Anomaly Detection flags new issues and regressions in QA, Staging and Production.

Classify and Categorize Issues

Use the data API ad custom extensions to evaluate and classify events so they can be routed to the right person or process in PagerDuty.

Identify Every Issue

Gain insight into uncaught exceptions and issues that are not caught in log files across all environments, including production

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