{"id":256240,"date":"2025-01-07T23:19:10","date_gmt":"2025-01-07T22:19:10","guid":{"rendered":"https:\/\/glosarix.com\/glossary\/metric-collection-en\/"},"modified":"2025-03-10T13:26:18","modified_gmt":"2025-03-10T12:26:18","slug":"metric-collection-en","status":"publish","type":"glossary","link":"https:\/\/glosarix.com\/en\/glossary\/metric-collection-en\/","title":{"rendered":"Metric Collection"},"content":{"rendered":"<p>Description: Metric collection is the process of gathering metric data from various sources, which can include applications, operating systems, hardware, and networks. This process is fundamental for analyzing the performance and health of systems, allowing development and operations teams to make informed decisions. Metrics can encompass a wide range of indicators, such as response times, error rates, resource usage, and other critical parameters that reflect the state of a system. Metric collection is carried out through monitoring and logging tools, which enable the capture and storage of data in real-time. This data is then analyzed to identify trends, detect anomalies, and optimize performance. The ability to effectively collect metrics is essential in agile and DevOps environments, where speed and efficiency are crucial. Additionally, metric collection is a key component of observability, which refers to the ability to understand the internal state of a system from its external outputs. In summary, metric collection is a critical process that provides visibility and control over the performance of technology systems.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Description: Metric collection is the process of gathering metric data from various sources, which can include applications, operating systems, hardware, and networks. This process is fundamental for analyzing the performance and health of systems, allowing development and operations teams to make informed decisions. Metrics can encompass a wide range of indicators, such as response times, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"menu_order":0,"comment_status":"open","ping_status":"open","template":"","meta":{"footnotes":""},"glossary-categories":[12216],"glossary-tags":[13172],"glossary-languages":[],"class_list":["post-256240","glossary","type-glossary","status-publish","hentry","glossary-categories-logging-and-observability-en","glossary-tags-logging-and-observability-en"],"post_title":"Metric Collection ","post_content":"Description: Metric collection is the process of gathering metric data from various sources, which can include applications, operating systems, hardware, and networks. This process is fundamental for analyzing the performance and health of systems, allowing development and operations teams to make informed decisions. Metrics can encompass a wide range of indicators, such as response times, error rates, resource usage, and other critical parameters that reflect the state of a system. Metric collection is carried out through monitoring and logging tools, which enable the capture and storage of data in real-time. This data is then analyzed to identify trends, detect anomalies, and optimize performance. The ability to effectively collect metrics is essential in agile and DevOps environments, where speed and efficiency are crucial. Additionally, metric collection is a key component of observability, which refers to the ability to understand the internal state of a system from its external outputs. 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