You're facing performance degradation. How do you navigate conflicting opinions on the root cause?

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When your application suddenly hits a snag and starts crawling, it's like a red alert for any software engineer. Performance degradation can be a silent killer, often sneaking up without warning and leaving you scrambling to pinpoint the culprit. As you dive into the murky waters of logs, metrics, and user complaints, you encounter a sea of conflicting opinions on what's causing the slowdown. Everyone from your database admin to the intern seems to have a theory. But fear not; there's a method to this madness. Navigating these choppy waters requires a blend of technical know-how, patience, and a systematic approach to troubleshooting.

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Vadivelraja Shanmugam

DBA Tech Lead at Tata Consultancy Services

1 Gather Data

Before you wade into the debate, equip yourself with hard data. Performance metrics can be your compass in the storm, guiding you toward the root cause. Monitor system resources like CPU usage, memory consumption, and I/O operations. Examine application logs for errors or slow-executing queries, and don't overlook user reports which can provide valuable insights. This data forms the foundation of your investigation, offering objective evidence that can validate or refute the various opinions you're juggling.

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Vadivelraja Shanmugam

DBA Tech Lead at Tata Consultancy Services
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Th performance issue investigation starts with understanding the issue first. Hear the customer experience on their own terms, then start probing to get more clarity and this in turn reassures customer that they are in right hands. This article right away jumps on a wild hunt of data collection. Now from what customer told you and from your experience you make some assumptions or list down possible causes. Next all performance issue investigation goes through “PDCA” cycle; so based on your list,start collecting data as this article guides you, but not limited only to them.

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2 Analyze Trends

Once you have your data, it's time to play detective. Look for patterns and anomalies in the performance metrics. Did the degradation coincide with a recent code deployment or a spike in user traffic? Correlating these events can reveal if the issue is code-related, infrastructure-based, or due to external factors. Your goal is to narrow down the possibilities by connecting the dots between what the data shows and the timeline of events leading up to the performance drop.

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Vadivelraja Shanmugam

DBA Tech Lead at Tata Consultancy Services
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Continued from data collection… Based on the data you collected you start your analysis without bias now. Your have a bias on the possible causes, but your analysis should go by evidence without bias or self opinion. This will kill all your biased choices and leave them with narrow set of causes. Now is your turn to go back in history to see if there is any difference, if so since when and then your close to the cause.

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3 Review Changes

Software is an ever-evolving beast, and changes are a constant. Whether it's a new feature, a patched library, or a configuration tweak, any alteration can be the butterfly that caused the hurricane of slowness you're facing. Review recent changes with your team to see if performance degradation aligns with these updates. Rollbacks might be necessary for a quick fix, but don't stop there; delve into the specifics to understand why the change had such an impact.

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Vadivelraja Shanmugam

DBA Tech Lead at Tata Consultancy Services
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Continued..As soon as you know when the deviation was observed, you go chase all the changes went live since then. The data you have collected can guide you here, ideally if you have config data stored, the job is easy. Especially with devops routine, it is easy to know what changed and when. Then you can work on a mitigation measure.

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4 Engage Experts

Sometimes you need to call in the cavalry. When performance issues become too enigmatic, reaching out to experts within your team or community can provide fresh perspectives. These individuals often have specialized knowledge that can shed light on obscure parts of your system. Be open to their insights and consider how their expertise aligns with the data you've collected. Remember, it's about finding the truth, not just being right.

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Vadivelraja Shanmugam

DBA Tech Lead at Tata Consultancy Services
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Continued… if the issue occurs on a vendor product, at times it’s hard to tell what is the cause and fix, you by now know which product caused issue and you don’t know in which part of the code stack your facing issue and why. Since you don’t own the code. So talk to the experts in vendor, it is mostly likely an edge case untested or a limit we hit in the vendor code.

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5 Test Hypotheses

Now that you've gathered opinions and data, it's time for experimentation. Formulate hypotheses based on your findings and set up tests to validate them. This might involve tweaking configurations, optimizing queries, or simulating traffic loads. Each test should be designed to prove or disprove a specific theory about the performance degradation. Through this scientific approach, you'll inch closer to identifying the real issue.

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Vadivelraja Shanmugam

DBA Tech Lead at Tata Consultancy Services
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Hmm.. Yes your in the phase of validating your hypothesis which you framed when you started the data collection. You already draw the fix and if the fix works. You know your cause is correct and fix too. So hurray stop here.

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6 Iterate Quickly

In the fast-paced world of software engineering, time is of the essence. Use an agile approach to iterate quickly on your findings. If a test doesn't yield answers, pivot and try another angle. Keep communication open with your team and update them on your progress. With each iteration, you refine your understanding of the problem and move closer to a solution. Remember, performance issues are puzzles waiting to be solved, and with persistence, you'll piece together the right combination.

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You're facing performance degradation. How do you navigate conflicting opinions on the root cause?

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1 Gather Data

2 Analyze Trends

3 Review Changes

4 Engage Experts

5 Test Hypotheses

6 Iterate Quickly

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