Shifting From ITOps to AIOps: Introducing SL1 Colosseum

If your business is confronted with the onerous task of understanding and managing an explosion of variety, volume, and velocity (the 3 Vs) of operational data, then you‘re ready for SL1 Colosseum.

The latest release of the ScienceLogic SL1 platform (Colosseum) addresses this data challenge head-on by enabling IT teams to make the shift from ITOps to AIOps: from human-driven observability to machine-driven advisability and actionability.

Your AIOps journey starts with observability and building your SL1 Data Lake establishes a solid foundation. With this release, you can fortify that foundation by continuing to assimilate data from your ever-expanding IT estate via agent-based and agentless collection methods. SL1 Colosseum release expands your ability to quickly and easily monitor an even broader set of modern cloud, microservices-based, legacy, and unique infrastructure technologies and applications.

 

Moving Beyond Event Correlation: Anomaly Detection & Behavioral Correlation

When dealing with the sheer scope of data produced by modern IT environments, it is humanly impossible to sift through the noise and focus your efforts on critical service-impacting issues—before it’s too late. In truth, the industry has been trying to solve the ‘three Vs’ data problem with event correlation for decades—with limited success.

At ScienceLogic, we believe a more holistic understanding of business service performance and impact is needed. We help you achieve this holistic approach to service health via behavioral correlation—connecting the dots between events, anomalies, and topology relationships within and across your business service to quickly alert you to risks or issues impacting your business services. Why?

Event-Only Approach

  • Limited in scope
  • Not every piece of evidence manifests itself as an event
  • Learning event patterns to identify problems assumes problems are frequent
  • Places burden on humans to know/define events for all possible failure cases

Behavioral Approach

  • Evaluates numerous dimensions
  • Sometimes the best piece of evidence is something ‘weird’
  • Learning behavior will recognize problems the first time
  • Machines must reason over vast quantities of metrics to recognize ‘weird’ behavior

 

The SL1 Colosseum release leverages the power of artificial intelligence (AI) and machine learning (ML) to keep a pulse on your environment and identify any unusual or weird behavior (aka an anomaly). And SL1 automatically selects the best ML algorithm for the type of data being evaluated so there’s no data scientist required. When combined with ML-driven behavioral correlation, enhanced app and service views in SL1 Colosseum give you a 50K-feet-level view of your business services to help you quickly filter out the noise and automate root-cause analysis. And it doesn’t just alert you on the risks—it advises you on possible next steps that fit the needs of the minutewhich can be executed with the click of a button. SL1 Colosseum pulls a set of recommended actions from its vast library of industry best-practice troubleshooting and remediation actions, processes, and workflows.

Moving Fast With Automated Workflows

And now that you’re equipped with insights from across your IT environment, it’s time to take action by replacing pre-existing, error-prone manual workflows with the SL1 best-practice automation library, consisting of over 300 automated actions that enable both human and machine-driven workflows. IT workflow automation helps you keep pace with the rapidly evolving needs of your business as you move a step closer to actionability and attaining AIOps. Taking you a step further, the SL1 Colosseum introduces a drag-n-drop toolkit to accelerate your custom workflow development needs.

 

 

Want to learn even more about SL1 Colosseum? View this data sheet»


 

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