In the middle of an alert storm, which alerts matter? What’s the signal and what’s the noise?
StackState’s Topology-Powered Observability understands the upstream changes that cause downstream problems. StackState uses that insight to logically group related alerts and prioritizes the ones that need your attention.
Use StackState to reduce alert noise. Get faster MTTR, more reliable systems, and a better experience for customers.
StackState automatically clusters alerts that are likely to be related, helping you sort through the noise to find the main issue.
Visualize groups of alerts and event progression over time to see exactly where the initial problem began and what components are affected.
Eliminate alert storms and immediately understand where to focus remediation efforts. Avoid duplicate incidents, false alarms and irrelevant alerts.
Correlate events across your stack for the most accurate insights. Know which teams to call.
Use StackState’s unified platform to relate different signals from different sources, from data lakes to monitoring tools to AWS to Kubernetes. Check out our many out-of-the-box integrations.
Use StackState's AI capabilities with the 4T® Data Model to analyze enterprise-wide telemetry data with self-training intelligence. StackState’s machine learning identifies and disregards irrelevant data—correlating events, reducing alert noise and detecting anomalies to generate increasingly insightful alerts.
Enrich tickets with probable root cause to further accelerate resolution.
Automatically consolidate incidents and normalize data before creating tickets in ITSM or triggering automated self-healing systems.
Group alerts to reduce the number of tickets created: the main ticket is updated rather than a new ticket being opened. StackState provides multiple pre-built integrations with common ticket handling systems.
Provide better input to power automated self-healing systems, which can do more harm than good when they try to remediate the wrong thing.
How StackState’s Alert Noise Reduction Helps You
Reduce time to find and resolve incidents. Repurpose the time spent on problem management to proactively make your entire system more robust.
Reduce toil and time spent troubleshooting an effect rather than a cause. Follow the right path with the right people.
Reduce number of tickets created – customers report reductions of 70% and higher.
Every ticket created causes more work to understand and triage. Save even more time (and money) with fewer tickets.
Provide more accurate data to incident resolution and self-healing systems.
Improve problem resolution efficiency for all downstream systems.
Connect disciplines and provide necessary insight to all teams.
Give development, SRE and support teams access to the same detailed information across the stack.
How APA-Tech Uses Observability to Make Sense of Tons of Monitoring Data With Georg Höllebauer3 min watch
In this video, Georg Höllebauer, Enterprise Metrics Architect at APA-Tech, explains how he and his team use topology-powered observability to make sense of tons of monitoring data and get a better overall picture of IT environments.
Accenture Achieves 85% Reduction in Problem Resolution Time with StackState3 min watch
Luke Higgins, Managing Director at Accenture, explains why Accenture's myWizard® platform applies StackState's observability solution to achieve up to 70% reduction in tickets and realize up to 85% reduction in problem resolution time.
Driving Business Performance With Observability in Financial Services60 min watch
Learn how one financial organization, Nationale Nederlanden Bank, gets better visibility from the volumes of data coming out of monitoring solutions, such as Splunk, to gain greater insights, faster root cause analysis and shorter MTTR.