Today, we see that IT is awash in a sea of data. Data from monitoring tools, dashboards, apps and critical alert management platforms make it challenging at best for IT to ensure the data it gathers can define the problem. With so much data surrounding them, it becomes even more challenging to get the right I&O (Infrastructure & Operations) teams together to resolve the issues.
Gartner highlights a solution to this issue when they write:
Collaboration is critical to resolving problems quickly, but having multiple infrastructure monitoring tools often extends outages. I&O leaders can improve collaboration and improve resolution times by focusing on a data-driven approach.
It is no stretch to say that this data driven approach needs to be taken towards monitoring as well as critical alert management . Only through this dual approach can the data be used to tell a full story and a solution be properly implemented.
To that end, this blog will look into some ways to implement a data driven approach and (more importantly) how IT teams can use that data for achieving improved outcomes.
Fragmentation of monitoring tools makes it challenging to create data-driven decisions due to the diversity of business demands. Instead, leaders and managers need to prioritize what their objectives are and what are the needs of the IT teams consuming the data.
When everyone is aiming for speed of response and faster troubleshooting, having multiple tools that look at multiple points of the stack can become debilitating. Instead, teams need to prioritize their monitoring objectives to ensure that those endpoints that are tied to key metrics such as SLAs or MTTR.
IT monitoring and alerting are intertwined. When you have effective monitoring, your team is alerting on the right metrics at the right intensity. You don’t alert on events which are not actionable and you don’t alert on events which are redundant. You alert on IT events that have meaning and that meaning is defined by data. The ultimate goal of alerts is to raise awareness of underlying code or infrastructure problems.
Effective alerting is defined based on the way monitoring has been put in place. In a network management system, you always have latency. By definition a plain monitor is not calibrated to the events you want to receive alerts on.
In the beginning, every monitoring system will generate false positives because the system does not know the environment it is working in nor the infrastructure it is monitoring. It is only through the professional’s experience that an alerting system can be
Too many events and alerts (false positives) will reduce the effectiveness of IT operations. You’ll also start to overlook important events or alerts. Consequently, it is important to learn what the important statistics to keep track of are. Is it MySQL availability, aborted connections or error logs? Know which ones are important for your organization and alert on them.
An ideal alerting tool will enable you to ensure the following capabilities:
Conclusion
These insights highlight the necessity of teams creating a renewed commitment to data and staying with the data to determine its results. For the data to be effective though, teams need to make sure they have the proper forethought, the right tools and critical alert management platforms in place to effectively respond to incidents.
To read three more ways about how to adopt a data driven approach to monitoring and critical alert management, download our whitepaper.
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