Unify, Correlate and Visualize

All your observability data contextualized in one data fabric

Bring siloed telemetry data into StackState to create the shared observability data foundation you need to keep up with accelerating change.

StackState is purpose-built to integrate with many other technologies. It aggregates existing siloed telemetry data from other sources, correlates that data with StackState-collected telemetry data and delivers an integrated topology-powered data fabric.

Get a topology-based view of your end-to-end environment and “rewind the movie” frame by frame to understand exactly what was happening in your stack at every moment.

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Map relationships between all services and components

  • Aggregate siloed data from sources such as applications, data lakes, observability and infrastructure monitoring tools, virtualization and cloud platforms, incident management systems, existing APM solutions and Kubernetes.

  • Automatically discover and collect topology and telemetry data using your choice of dozens of pre-built agentless integrations plus optional lightweight agent-based alternatives.  

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Correlate telemetry and trace data at every point in time

  • Merge multiple topology sources into a unified view that provides unprecedented depth and insight. StackState's unique 4T® Data Model and versioned graph database provide essential underlying technology.

  • Use StackState’s time-series topology to show how changes propagate through your stack over time and affect dependent services. A change might be a new deployment, configuration change, change initiated by automation, lifecycle change, or even a change in behavior.

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Visualize your entire IT environment through a single pane of glass

  • Easily see context: What components does this service depend on? What is their lifecycle? For example, when did this container spin up? How does a change to this component affect customer-facing applications and the business?

  • Understand the cause and effect of change anywhere in your stack. Topology visualization shows dependencies between every component, with relevant metrics, events, logs and traces only a click away.

  • Jump from the present back through history and see the state of your stack at any point in time. Go directly to the change that created a problem and understand how that problem ripples through your environment.

  • Flexible, customizable lenses and dynamic screen updates – switch perspectives, focus at both high and low levels, from 50,000 feet to five feet, and view by role, layer, tag, domain and more. Visualize topologies of up to hundreds of thousands of components and show the user just the right slice to understand what is going on.

How StackState’s Data Unification, Correlation and Topology Visualization Helps You

Get a clear picture of full stack behavior at every point in time.

Get a clear picture of full stack behavior at every point in time.

Use detailed insight into cause and effect of issues to solve problems faster. See exactly what you need at a given time and filter out all the rest.

Move beyond observing siloed components to observing your stack as a whole

Move beyond observing siloed components to observing your stack as a whole

See how a change affects dependent components throughout your environment and ultimately how it affects customers. 

Share full stack data across your organization to foster better collaboration and more effective teamwork.

Share full stack data across your organization to foster better collaboration and more effective teamwork.

Democratize data to create a shared understanding of stack behavior for all teams. Everyone gets the specific view they need for their role and can also see the big picture across the entire environment. 

Protect your investments in existing tools

Protect your investments in existing tools

Integrate, operationalize and normalize data from all the monitoring and observability tools in your environment. Reduce the proliferation of tool-specific, unrelated dashboards and view everything in one place, with all data correlated and analyzed holistically.