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Reduce Alert Noise


When your ITOps teams are drowning in alerts, it can be hard for them to make sense of what is happening in their environment, much less find and fix issues. Your ITOps teams might be using event and incident management tools alongside monitoring tools. This accumulation of tools along with siloed teams and data creates an onslaught of alerts, many of which are duplicate, and makes it extremely difficult to understand signals from noise. This results in more unplanned downtime, reactive response, and staff burnout, all of which hinder ITOps’ ability to support and grow the business.

Continued exponential growth of IT and business systems data add to tool sprawl and make alert fatigue worse. For example, you might have implemented separate AIOps middleware, like BigPanda or Moogsoft, for event correlation and noise reduction. Typically, however, these tools are difficult to set up, are disconnected from monitoring workflows, and aren’t able to prioritize alerts based on business service impact. Teams spend their time jumping between tools and can't find and fix issues, all of which leads to frustrated teams, lost revenue, and higher costs.

How can Splunk ITSI help with reducing alert noise?

See all alerts in one place

The Splunk platform is data source agnostic and your ITOps teams can quickly onboard Splunk and third-party monitoring data into Splunk ITSI (ITSI) using the more than 2,800 data integrations and content packs available in Splunkbase. With Splunk ITSI, your teams can correlate and analyze telemetry data and alerts from monitoring, event, and incident management tools that are already in use today. You can enrich alerts with relevant context and and create custom alerts from any ingested data. This means you can see all your alerts in Splunk ITSI Event Analytics without having to jump between tools or replacing your existing investments.

Reduce alert noise and group related alerts

Reducing alert noise can happen in two ways: better alert hygiene, meaning more accurate alerts, and grouping related alerts. Your teams can achieve better alert hygiene through more accurate thresholding and, at times when it isn’t business as usual, through custom threshold and maintenance windows. Adaptive thresholding in ITSI dynamically adjusts baselines based on historical data so that alerts are more accurate. With the assistance of machine learning, you can create these adaptive thresholds in just a few clicks.

To proactively avoid false positives and unwanted alerts, you can use custom threshold windows to adjust KPI and service severity levels when you anticipate something unusual happening like an increase in web traffic due to a summer sales event or Black Friday.

Finally, ITSI can help detect and triage incoming alert storms and intelligently group alerts into episodes and prioritize them. This reduces the total number of alerts to actionable episodes and helps you make sense of the incident. Leveraging both machine learning and rules-based correlation, ITSI can help reduce alert noise by more than 90%.

Respond to incidents efficiently with directed troubleshooting

With alerts grouped and prioritized, your teams can see service impact and use Episode Review to find probable root cause on the event timeline. Links from the timeline that carry context into third-party monitoring tools and entity health help you zero in on root cause. Knowing how similar episodes were successfully resolved in the past means you don’t need to start from scratch. Episode Review in Splunk ITSI lets you look for similar episodes, see what actions were taken to resolve the issue, read any notes on how the problem was resolved, and review any linked tickets for even more context about the episode. You can also automate actions like sending email notifications, running a script, or sending to Splunk SOAR. Finally, you can accelerate incident response through bi-directional ticketing and creating custom instructions and runbooks.

Use case guidance