The Complete GitHub Logging Research: How the World’s Top Companies Choose How and What to Log
We all use log files to monitor our applications in production. Some of us prefer using log management tools like Splunk or ELK, while others sift through raw logs on their notepad or terminal. It doesn’t matter if you choose the former or the latter; logs contain the same information in both options.
That’s why we’ve set out to find out how developers use logs. What goes in? What’s left out? And how to tie it all together.
We’ve gathered the top 400,000 repositories on GitHub according to the number of stars they were given in 2016, sprinkled some BigQuery magic, added a pinch of SQL and started crunching the data. The results, conclusions and best practices are waiting for you in our new eBook.
Chapter outline
1. ERROR, WARN or FATAL? – In this chapter, we’ll understand how GitHub’s top Java projects use logs and see the log level breakdown use for the average Java application
2. Is Standard Java Logging Dead? – In this chapter, we’ll explore the data set from another angle and put the focus on the use of standard java.util.logging levels versus more popular frameworks like Log4j, Log4j2, and Logback.
3. Over 50% of Java Logging Statements Are Written Wrong – After finding out that production logs can’t help you find the real root cause of your errors, we’ll try to understand why that happens and how you can improve your production logs.
4. What’s the Top Java Logging Method on GitHub? – Parameters, concatenations or both; which logging method do developers use, and which method is the right one for you?
