Last updated at Wed, 01 Nov 2017 19:51:56 GMT
Even the most non-technical audiences realize the business value in analyzing their log data. DevOps professionals are constantly being asked to monitor their application performance, and often rely on log data for troubleshooting, diagnostics and application systems monitoring. The challenge is that the amount of log data generated can be completely overwhelming.
Why log analysis is so difficult?
In one word — volume. Even relatively small applications, can generate millions, or billions of log events every day. So how can you efficiently comb through these log events to find the most important information; like application errors, exceptions, warnings, and other critical log events related to system performance?
Many companies have found success using a log analysis tool. But there are a few things you should know before you start evaluating options and choosing a solution to implement. You’ll want to make sure you have the right strategy for your business needs. So let’s talk about what you need to know, to use log analysis to successfully make important business decisions using billions of data points.
The facts…
Logentries conducted our own research on how data is being collected and analyzed across our user base, and found that of the data processed, 99.82% of log events are noise. We found that only about .18% of log events contain critical information for performance and reliability (like fatal events, critical events, warnings, and exceptions).
So if only .18% of log data is considered highly useful for a particular end user, and there are often millions or billions of log events, it is clear why this is one of the inherent industry challenges: big data gets most of the attention, but little data can be more important. You just need to find it.
How can log analysis tools find the needle in the haystack?
There’s a few different methods to find the information most important to your business. A common solution, that most log management tools highlight, is powerful search capabilities. Which is great, but if it isn’t easy, then it can become even more burdensome to try to search quickly.
Search, is great if you know exactly what you’re looking for.
However, for intermittent problems or abnormalities,you need different capabilities. Occasional errors and alerts can often go unnoticed for longer periods of time. You can’t search for something you’re unaware of. You need visualization, pre-processing of data, and the ability to plug-in intelligence from a variety of existing tools to help identify the data that matters most to your business.
The main challenge with log analysis, is not how to collect, scale, consume, and manage the data. The challenge is how to identify the information most important to your business, so you can react quickly and take action to prevent a bad user experience or system performance issues. So now that we know the main challenges, the next step is evaluating log analysis tools. Check out a free trial of Logentries log management and analysis here.
