OverOps is a software reliability platform that applies machine learning to application code as its running to automatically identify anomalies, and provide code-level insights in QA, Staging and Production. By identifying when, where, and why the code breaks in real time, OverOps helps companies fix application issues before the customer is affected, as well as prevent these issues from ever being released. When anomalous failures – such as newly introduced issues, error regressions and slowdowns – occur in any environment, a complete picture of the code is provided, including: Execution stack, source code and complete variable state; previous 250 log statements (including DEBUG- and INFO-level, even in production); frequency and failure rate for ALL known and unknown errors and exceptions; classification of new versus reintroduced errors; which release or build is associated with each specific event; event analytics. This data allows organizations to create a culture of accountability, where every team has visibility into what went wrong, eliminating finger pointing. Not only does access to this information greatly reduce resolution time, it provides deep insight into the overall quality of new deployments and of the application as a whole. As more organizations aim to innovate faster and deliver a seamless experience for customers, OverOps helps avoid costly downtime with minimal performance impact and no code modification. The data collected by OverOps can easily be displayed on any other platform using OverOps native integration with tools like Splunk, AppD and Grafana for monitoring, alerting and visualization purposes.
Press and media coverage
All notable press coverage of OverOps is linked here: http://resources.overops.com/?resource=press&_ga=2.149472310.1829553038.1546877471-1112689513.1545923639