Answers. Not alerts.
AI-powered automated root cause analysis
Drop MTTR to minutes
Keep customers happy
Reduce operational overhead
Detect critical production issues and see the true root cause, determined by the Opas Causation Engine.
Engineers can go straight to resolving the root cause instead of spending time spotting, assessing, and analyzing issues from a sea of mostly-useless information.
Opas uses Artificial Intelligence and Machine Learning to eliminate time-intensive root cause analysis at scale.
Automating the root cause analysis lets you focus on fixing the issue, quickly resolve customer-facing issues that are often missed by aggregate metrics.
- Adaptive agents capture every interaction—within the application, between your application and data layer, and between each application across your IT environment—with the highest level of granularity.
- Causation models that employ two dualities to: A) Capture and model your most complex application environment as well as the intelligence and intuition of your best DevOps personnel; and B) Employ historical records as well as forward projections to determine the best solutions to the most vexing application performance problem.
- Predictive alerts. Our analysis engine filters and finds the most relevant metrics for the performance problem, creating predictive alerts and verifying root cause in real time.
Opas Digital Twin
Monitoring and logging solutions collect data, trigger alerts, and provide clues for where to look, but engineers must still perform tedious root cause analysis. The Opas Causation Engine provides definitive answers to production issues, not hints.
What does it do?
The Opas Digital Twin replicates your application’s performance based on the behavior of your various dependencies and components.
How does it do this?
Opas uses an ensemble of statistical and ML models – deep neural nets, random forest, support vector machines – to build a “digital twin” of your app/infra system. In AI language, we build a model of your system output given its inputs.
How do customers use it?
Once your system’s behavior in its environment is learned, we can predict with 98+% precision what the output will be, given the behavior of the inputs. The digital twin is a sandbox that automatically perturbs the inputs to isolate the one, or the combination of several, that are causing the problem.
The OPAS Promise
Our promise to our customers is both simple and bold: no matter how complex your application performance problem, we can find, diagnose and recommend a fix for it. Opas causation models capture both your entire application model as well as the insights of your best DevOps personnel, then employ past analysis and future projections to find and fix even the toughest application problems