”Intellectuals solve problems, geniuses prevent them.” - Albert Einstein
StackState gives you innovative new capabilities to eliminate problems before they impact your users.
The best incident is the one that never happens. Use StackState’s Autonomous Anomaly Detector to spot the warning signs and prevent problems altogether.
Cut through alert noise, monitor telemetry streams and identify relevant events throughout your stack using StackState’s AIOps capabilities.
Apply AI-based insights to improve observability for your end-to-end environment.
Correlate AI-discovered anomalies with StackState’s comprehensive topology data. Use our 4T® Data Model to link suspicious behavior with probable root cause in the overall environment and to proactively predict issues.
Zero configuration required: works out of the box, trains itself in 2 hours.
Use StackState’s out-of-the-box monitoring and health checks, combined with your own custom health checks, to automatically alert you if metrics start to deviate from desired behavior.
Auto-discover and observe your environment. Perform automatic health checks with no need for manual threshold setting.
Automatically capture the golden signals of latency, traffic, saturation and error rate.
Create new monitors as code and deploy through your existing CI/CD pipeline.
Apply machine learning to find patterns and alert on warning states before they turn into failures using the Autonomous Anomaly Detector.
Automatically implement a multi-algorithm machine-learning model without sidecar deployments.
Self-tuning: adapt to changes in behavior patterns in your environment in real time with no manual intervention.
When deviations occur or failures are imminent, proactively notify teams who need to know so they can act to prevent failures from occurring.
How StackState’s Proactive Problem Detection Helps You
Improve reliability and performance by acting on potential issues before they become problems.
Armed with StackState’s early warnings, you can take immediate, proactive steps to address deviating behavior before it results in a failure. The result? Less downtime and fewer outages.
Create a better customer experience.
Customers are happiest when your system doesn’t go down and you consistently exceed SLOs. 😊
Increase the depth and scope of your observability capabilities. Let AIOps do the heavy lifting for incident prevention, root cause analysis, threshold-setting and more.
At today’s pace of change, especially in cloud and container environments, teams can monitor more effectively with AI-based insights. Reduce toil and free up time to focus on more productive activities.
Use StackState to set custom SLOs and SLIs, track performance and alert when commitments are not being met.
Central SRE or Platform teams can configure the SLOs and SLIs that are important to their organization; any components added to StackState by other teams will automatically adhere to the controls set by the central team.
Show tangible deliverables to make your AIOps vision real.
StackState works out of the box and delivers usable value in just a few hours. Don’t spend weeks or months on AIOps projects that take eons to show results.
Only Autonomous Anomaly Detection Scales· Lodewijk Bogaards6 min read
In this blog, Lodewijk - CTO at StackState - explains the difference between manual and autonomous AI and why only the later scales.
Why Predict When You Can Prevent?· Lodewijk Bogaards5 min read
How to Logically Determine Your Next Step on the Path to Proactive IT Monitoring (And Stop Wasting Your Money on Predictive Monitoring).
The Ultimate Guide to Telemetry21 min read
Telemetry data can give you amazing insights into the health and state of your system. No wonder it’s one of the most important data sources for observability.