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In this video series, the process of using DataDog's log pattern matching to discover Grok parsing rules and drive exclusion filters is explained. The first video focuses on identifying suitable Grok parsing rules for dotnet logs to prevent indexing logs with minimal operational value, ultimately reducing log costs. The second video covers setting up exclusion filters to prevent these logs from being indexed. The process involves using pattern matching to extract useful information and storing it as metrics in pipelines. By filtering logs in the Logs Explorer, the focus is on net logs to effectively index them.
