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Causely for Cloud-Native Applications
Tour the productManaging cloud apps at scale is complicated
As DevOps and SRE leaders, you help your teams build and scale applications, and keep them running even when things break. And things break all the time.
With thousands of application microservices and related entities, the interactions between them and the underlying infrastructure are endless.
It’s a 24×7 reality – when application failures or slowdowns occur, they’re painful to troubleshoot and remediate. The tidal wave of metrics, logs, and traces can overwhelm you and your teams as you try to determine root cause, get services back up, and address end-user impact.
Causely is all you need to know
Causely for Cloud-Native Applications installs in minutes and provides real-time knowledge about your application environment – with a comprehensive view of causal relationships across all services and entities.
Causely leverages your existing monitoring, observability, and AI/MLOps tools as data sources to provide causality models, model-driven analytics, and automated orchestration.
Instead of constant noisy alerts, Causely tells you exactly what you need to know about all active and emerging application failures:
Why did it happen?
What was the root cause?
How can it be fixed?
120+ Causal Models provided out of the box
Applicable to any cloud-native environment, the Causal Models are paired with the Topology Graph to create a Causality Graph that’s specific to your environment.
Capture potential root causes in a broad range of entities, i.e. applications, databases, caches, messaging, load balancers, DNS compute, storage.
Describe how root causes will propagate across the entire environment and observed symptoms of each.
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Take the interactive, self-guided product tour to see Causely for Cloud-Native Applications first-hand.
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Causely for Cloud-Native Applications, built on our Causal Reasoning Platform, detects and remediates application failures in complex cloud-native environments.
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How does Causely work?
Learn more about Causal AI for DevOps