I want to extend a special thank you to Ryan Booz for his fantastic work organizing and hosting the event, and to Gilles Darold for his tireless efforts in creating and maintaining the incredibly powerful pgBadger tool. The 'Top' and 'Events' tabs are also key in identifying time-consuming queries and monitoring for any warnings or errors. I share how I interpret these reports, spot irregularities, and adjust settings to optimize performance. I deep-dive into different sections of the pgBadger report, focusing on the 'VACUUMS' and 'Temp Files' tabs that have proven most useful. These elements enable me to efficiently resolve most issues I encounter. When troubleshooting, I rely on four main components: system views snapshots, OS level metrics, basic instance data, and pgBadger itself. I recount my first encounter with pgBadger at my debut IT job and its valuable assistance in solving Postgres issues ever since. Despite her personal preferences, she recommends pgBadger for DBAs who need an overview of their system's performance.Īlicja Kucharczyk – In my own blog post, I discuss how pgBadger has transformed my approach to Postgres troubleshooting. This approach allows her more control over her log analysis. She prefers using a CSV output for Postgres logs and querying them as tables using Foreign Data Wrapper (FDW). Laetitia Avrot - While she recognizes its utility for routine monitoring, she finds it lacks flexibility for the complex problems she often encounters. I particularly loved his delightful reference to the "Very Hungry Caterpillar" book. Despite these, he strongly recommends pgBadger for PostgreSQL performance analysis, as its effectiveness depends on the quality of the logs it parses. He also acknowledges a few limitations, including potential performance issues and limited chart functionality. Anthony points out that pgBadger is beneficial for giving high-level overviews, managing lengthy log files, and visually presenting data, which aids in communication with non-technical individuals. Finally, Hettie expresses a wish for a feature in pgBadger to track repeating sequences of SQL statements, which would aid in understanding an application's behavior.Īnthony Nowocien - Anthony appreciates how it turns raw log data into an understandable web report and provides insights on statistics, events, sessions, and query performance. pgBadger can highlight these multiple database calls, enabling Hettie to identify queries that are executed quickly but too frequently. She argues that slow performance often results from suboptimal database access patterns due to the use of ORM (Object-Relational Mapping), leading to an excessive number of database calls. Henrietta (Hettie) Dombrovskaya - Hettie notes how pgBadger has been pivotal in diagnosing slow database performance, focusing on metrics such as the frequency and duration of queries. You will find a brief summary of all these insightful blog posts below. I extend my heartfelt gratitude to all who participated. It was an enjoyable experience seeing the entries come in over the week. A few weeks back, I initiated a call for blog posts about pgBadger for the tenth installment of the monthly PGSQL Phriday series.
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