Managing the logs in a centralized repository is one of the most common best practices in the DevOps world. Application logs, system logs, error logs, and any databases logs also will be pushed into your centralized repository. You can use ELK stack or Splunk to visualize the logs to get better insights about it. But as a SQL guy, I wanted to solve this problem with Bigdata ecosystem(use SQL). As a part of that process, we can relationalize unstructured data in AWS Athena with the help of GrokSerDe.
Here S3 is my centralized repository. I know it will not scale like ElasticSearch, but why should I miss this Fun. For this use case, Im going to rationalize the SQL Server Error log in AWS Athena. Let’s take a look at the SQL server’s error log pattern.
2019-09-21 12:53:17.57 Server UTC adjustment: 0:00
2019-09-21 12:53:17.57 Server (c) Microsoft Corporation.
2019-09-21 12:53:17.57 Server All rights reserved. …
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