Topology Discovery

AIMS uses machine learning and artificial intelligence to learn the behavior of all your performance metrics across your IT environment and identifies critical correlations and dependencies.

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Automated Topology Discovery

A key capability in AIMS is understanding dependencies across your IT environment simply from observing the behavior in real-time.

AIMS empowers you with a hyper scalable correlation engine that analyzes dependencies to let you understand the assets your business relies on.

Systems view application dependency mapping

Apply Machine Learning

AIMS automatically builds thousands to millions of patterns that represent your business behavior and continuously monitors actual performance against the patterns to identify deviations and anomalies.

AIMS auto-detects changes and deployments to applications and automatically includes them into your monitoring.

Introducing automated application dependency detection and mapping

With the new release of the AIMS Correlation Topology, you can now automatically discover your systems and application dependencies. 

Using AIMS Correlation Topology, you don't have to instrument anything, neither you have to do any manual setup. It basically takes all the data coming from the agent and based on that, we can access the visualization of any relationships and dependencies on a specific node or system, or application, which means that there's no need for a massive project or involvement of a great number of employees, because it is completely automated.

application dependency mapping physical view

Introducing Correlation Topology

What if the technology dependencies and relationships could be surfaced and kept up-to-date without a massive project and ongoing maintenance? That is what AIMS is solving with the Correlation Topology. 

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Gain critical insights in real-time

AIMS' modern IT monitoring solution leverages machine learning and AI to automate installation, configuration, insights and alerting while delivering time-to-value in hours and days - not weeks and months.

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Feed any time-series data

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Data normalization

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Anomaly detection

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Dashboards and analytics