Use Cases
Event Correlation & Noise Reduction

Event Correlation & Noise Reduction

Too much information noise

The monitoring system handles a large amount of data every day: tests, changes, events, queries and logs. It is impossible to manually combine all of these groups of data into clusters, which is why engineers work with each event individually. This poses a risk of losing critical information and has data engineers wasting their time.

Acure effectively collects big data from dozens of resources

No matter how many resources you use, Acure displays the state of the whole IT infrastructure and allows you to see the health of all its elements and connections between them in one screen. It makes the observability more effective.

How does it work?

1. To start, configure Data Streams. Utilize the connector for existing systems or create the custom connectors for the systems that don’t exist in Acure. Write tasks for integration and start the collection of data.

In the next steps, ensure no data is missing and collection is working properly.

2. Setup the mechanism of triggers. On the level of triggers and cases, the larger amounts of data are condensed into smaller processes.

3. The status of IT infrastructure (all services, virtual machines, and statuses over time) is displayed on one centalized screen. Monitor the IT infrastructure using the heat map or graph connection model.

There are three types of correlation in Acure:

Topology (graph)

Topology displays the whole IT environment like a tree with links between each configuration item. You can see the health and state of the IT complex and each CI individually.

Time (timeline)

In Acure you can easily filter all events by picking up the necessary timeline and sort by priorities. This allows you to see only important alerts without unnecessary information.

Context (rules)

Acure triggers allow to process events received via the monitoring system. It is possible to create a trigger from a template or write it from scratch using scripts written in the Lua language.

Note: The result of the event correlation is a noise reduction. You will see only the important alerts that are worth handling