StackState Launches Its Observability Solution for Cloud Native Applications and Environments
Hilversum, NL – June 7, 2021 – StackState, a leading provider of dynamic observability solutions, today announced that it has launched a version of its observability offering specifically for cloud-native applications and their environments. The solution helps Site Reliability Engineers (SREs) running applications on Amazon AWS and Kubernetes prevent and resolve problems by offering three key capabilities often lacking in other solutions. StackState’s solution delivers end-to-end visibility of the environment at any moment in time, makes locating the root cause of an issue as simple as one click, and delivers a zero-configuration anomaly detector to prevent problems before they impact end-user experience.
“Delivering reliable and performant applications in the cloud starts with being able to quickly identify issues and remediating the root cause before it impacts the business, but that’s a huge challenge for companies today,” said Lodewijk Bogaards, CTO and co-founder, StackState. “Our latest offering for companies running AWS and Kubernetes helps make that vision more of a reality, enabling them to better ensure the performance and reliability of their applications.”
Cloud environments that host business-critical applications, from online banking to streaming services and everything in between, are in a constant state of flux. Because of this, when performance and reliability issues arise, it can be incredibly difficult for SREs and DevOps teams to locate where the problem started or prevent it in the first place. What’s typically lacking is a comprehensive view of the entire environment, not only for the current moment in time, but also over time, as well as an easy way to pinpoint the exact change in the environment that triggered the issue.
StackState’s new observability solution for cloud-native applications uniquely offers the following capabilities:
End-to-end visibility: Leveraging StackState’s unique, unified Time-Traveling Topology, the solution maps service and application dependencies to supporting cloud and container infrastructure across all environments over time. It also automatically collects the four “golden signals” (response time, throughput, error count, and saturation) for all services and processes running in a Kubernetes environment. This is critical to ensuring application and infrastructure performance. StackState is the only vendor to offer this in one application. StackState’s end-to-end visibility is much broader than just a service map. It includes the full infrastructure, all cloud components and services including low-level components, like security groups, and higher-level services, like elastic load balancers and Lambdas. With this complete overview StackState automatically tracks any low-level changes and immediately shows the impact of that change at any point in time.
One-click root cause analysis: The ability to map changes to problems enables SREs to relate configuration and architecture changes to problems in real-time, at any point in time and identify the root cause of any issue in one-click.
Problem prevention: Traditionally, instrumenting AI to predict anomalies is resource-intensive and prone to failure. StackState’s zero-configuration anomaly detection removes the overhead and automatically detects performance anomalies and pinpoints their location within the stack before they become issues.
“Today, enterprises operating business-critical applications in cloud-hosted Kubernetes environments typically use either time-consuming-to-implement-and-maintain open source tooling, or APM products that are too expensive to deploy broadly across the entire environment,” said Bernd Harzog, CEO at APM Experts. “StackState breaks new ground by providing an Observability solution that is easy to implement, easy to maintain, that works well in modern cloud environments, and that is affordable to procure.”
StackState is an observability and AIOps platform that helps enterprises decrease downtime, prevent outages, and improve performance and reliability by breaking down the silos between existing monitoring tools and tracking changes in dependencies, relationships, and configuration over time. The system relates these changes to incidents, understanding the precise change that is the root cause of an issue. Our clients realize decreases in mean-time-to-repair (MTTR), fewer outages, and lower costs associated with incidents.