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The Power of History: Using Past Alerts to Resolve On-Call Incidents Faster

Writer's picture: Sudeep ChaudhariSudeep Chaudhari

Being an on-call engineer is often like being a firefighter—you’re constantly reacting to incidents, putting out fires, and ensuring that systems stay up and running. Every time an alert comes in, you’re thrust into problem-solving mode, where quick, effective action is crucial. But what often separates a smooth, fast resolution from a stressful, drawn-out ordeal is the availability of historical alert details.


The Importance of Context

Let’s face it: no engineer likes the feeling of tackling an issue with no context. When an alert goes off, the first thing that runs through your mind is, Has this happened before? If you’re lucky enough to have detailed historical alert data, this question can be answered almost instantly. You can dive into the specifics of similar past incidents, identify patterns, and learn from previous resolutions—giving you a head start in solving the current problem.

Without this context, though, every alert feels like it's coming from a completely unknown source, even if it's part of a recurring problem. That’s where having historical alert details in a clear, accessible format can truly make a difference.


How Historical Alert Details Help


1. Faster Identification of Recurring Issues

When you're dealing with a complex distributed system, issues can often reappear in different forms. For example, a network latency spike might have been caused by an overloaded server during a high traffic period a month ago, and the same issue could pop up again today, triggered by a similar situation. If you can quickly check the alert history for recurring incidents of high latency, you can immediately identify that this isn’t a new issue but a recurring pattern.


Benefit: By recognizing recurring issues, you can apply a solution that has worked before, or

escalate faster if it requires a different fix.


2. Faster Root Cause Analysis

The more you know about past incidents, the faster you can pinpoint the root cause of a problem. For example, if a previous alert about high CPU usage was tied to a particular version of a microservice, you can start by investigating whether the current alert has anything to do with that same service or version.


Benefit: You avoid wasting time chasing unrelated problems, narrowing your focus and troubleshooting more effectively.


3. Quick Access to Proven Solutions

Historical alert data doesn’t just show the problem—it often shows the solution. If an alert for a service degradation happened a few weeks ago and the solution was as simple as rolling back a specific deployment, you don’t have to reinvent the wheel. You can confidently follow the same steps without needing to dive deep into every log and metric.


Benefit: You can resolve issues more quickly by reusing proven fixes from the past, reducing

mean time to recovery (MTTR).


4. Improved Alert Tuning

When you have visibility into past alerts, you can also identify patterns in false positives or overly sensitive triggers. Maybe an alert fires every time traffic spikes slightly, even when the system isn’t really under stress. By reviewing historical data, you can adjust thresholds and fine-tune your monitoring tools to avoid alert fatigue, which in turn helps you focus on real problems.


Benefit: You spend less time reacting to noise and more time solving critical problems.


5. Better Incident Documentation and Knowledge Sharing

When similar incidents happen over time, teams can build a knowledge base from historical alerts. By reviewing past incidents, you can document effective troubleshooting steps, common issues, and fixes, then share that information with your team. This shared knowledge makes it easier for future on-call engineers to address similar alerts quickly without starting from scratch.


Benefit: The more you document and share, the faster each engineer can resolve similar issues in the future, creating a self-reinforcing cycle of efficiency.



Access to historical alert data can transform how efficiently an on-call engineer handles incidents. It provides context, accelerates root cause analysis, and helps engineers apply proven solutions quickly. By learning from past incidents and continually refining monitoring systems, on-call engineers can reduce downtime, improve system reliability, and ultimately provide better service to users. As engineers, we know that time is often the most critical factor in resolving incidents. Having the right context, in the form of historical alert details, is like having a roadmap that guides us through the chaos and helps us find the quickest path to resolution.  


Based on our own experiences with on-call incident resolution, we at Next9  built the "Similar Alerts" feature, powered by our proven AI-based algorithm. This feature is designed to bring together all historically similar alerts, their occurrences, resolutions, and follow-ups, all seamlessly linked to the ongoing alert you’re handling. With "Similar Alerts," engineers can access all relevant historical data at their fingertips—empowering them to resolve issues faster and more efficiently. Many of our users have reported dramatic improvements in their Time to Resolution (TTR)—with some seeing their resolution time drop from hours to mere minutes!


We’d love to hear your thoughts on this experience. Do you agree with the value of having historical context so easily accessible, or do you have any other feedback on how we could make this feature even more effective? Try Next9 and see for yourself how it can drastically improve your on-call engineering productivity

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