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     Tags: AIOps


    The pace of change is increasing. Component sizes are shrinking. All the while monitoring solutions are bombarding us with log data, metrics, status reports and alerts. It all scales, but we don’t. How do we prevent from drowning in run-time data?

    A lot of companies are facing the same problem. They have such a huge amount of data, but can't get a total unified overview. When problems occur in their IT stack, they don't know where it originates. Was it a change? An overload? An attack? Or something else?

    Based on our experience, we created the monitoring maturity model. At which level is your company? Download the Monitoring Maturity Model whitepaper right here.

    The Monitoring Maturity Model

    Level 1 - Individual Component Monitoring

    At level one you have different components, but monitor solutions at this level only report if they are up or down. If something happens in your IT stack, you will see a lot of red dots and you will probably get a lot of e-mails which say there is something broken. So at level one you will only see the states and alert notifications per (single) component.

    Level 2 - In-depth monitoring on different levels

    Most of the companies we’ve seen are at level two of the Monitoring Maturity Model. At this level you are monitoring on different levels and from different angles and sources. Tools like Splunk or Kibana are used for log files analysis. Appdynamics or New Relic are used for Application Performance Monitoring. Finally we have tools like Opsview to see the component's states of different services. And that’s a good thing, because you need all this kind of data. The more data you have, the more insight you have on the different components. So at this level you are able to get more in-depth insight on the systems your own team is using.

    But what if something fails somewhere deep down in your IT stack, which affects your team? Any change or minor failure in your IT landscape can create a domino effect and eventually stop the delivery of core business functions. Your team only sees their part of the total stack. For this problem, we introduce level three of the Monitoring Maturity Model.

    Level 3 - Next-Generation Monitoring

    At level three we don’t only look at all the states, events and metrics but also look at the dependencies and changes. Therefore you need an overview of your whole IT stack, which will be created using existing data from your available tools. To create this overview you will need data from tools like:

    • Monitoring tools (AppDynamics, New Relic, Splunk, Graylog2)
    • IT Management tools (Puppet, Jenkins, ServiceNow, XL-Deploy)
    • Incident Management tools (Jira, Pagerduty, Topdesk)

    Re-use this existing data from different tools to create the total overview of your whole IT stack. At level three you are able to upgrade your entire organization. Now each team can view their team stack as part of the whole IT stack. So teams have a much easier job finding the cause of a failure.  Also teams are now able to find each other when this is needed the most. This level also helps the company to get a unified overview while letting teams decide which tools they want/need to use.

    Level 4 - Automated operations with AIOps 

    The final level of the monitoring maturity model is all about applying Artificial Intelligence for IT Operations (AIOps). AIOps is a new product category defined by Gartner and stands for “Artificial Intelligence for IT Operations”. AIOps is a natural evolution of IT Operations Analytics (ITOA) and involves the application of artificial intelligence (AI) and machine learning (ML) techniques.

    Using predictive analytics and continuous machine learning, monitoring at level 4 allows you to proactively detect anomalous behavior across your environments. Early warning signals get your operations teams out in front of upcoming issues and give them the opportunity to prevent the problem from impacting your business. The time gained will at least help them cut down on the issue’s remediation time.

    • Send alerts before there is a failure
    • Self-heal by for example scaling up or rerouting services before a service is overloaded
    • Abnormality detection
    • Advanced signal processing

    Curious to discover how mature your IT Monitoring is? Take the 1-minute test and download your personalized report!

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