{"@attributes":{"version":"2.0"},"channel":{"title":"Time series on Docs","link":"https:\/\/redis.io\/docs\/latest\/develop\/data-types\/timeseries\/","description":"Recent content in Time series on Docs","generator":"Hugo","language":"en","item":[{"title":"Configuration Parameters","link":"https:\/\/redis.io\/docs\/latest\/develop\/data-types\/timeseries\/configuration\/","pubDate":"Mon, 01 Jan 0001 00:00:00 +0000","guid":"https:\/\/redis.io\/docs\/latest\/develop\/data-types\/timeseries\/configuration\/","description":"<h2 id=\"redis-open-source---set-configuration-parameters\" class=\"group relative\">\n  Redis Open Source - set configuration parameters\n  <a href=\"#redis-open-source---set-configuration-parameters\" class=\"header-link opacity-0 group-hover:opacity-100 transition-opacity duration-200 ml-1 align-baseline\" aria-label=\"Link to this section\" title=\"Copy link to clipboard\">\n    <svg class=\"inline-block w-4 h-4 align-baseline\" fill=\"currentColor\" viewBox=\"0 0 20 20\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n      <path fill-rule=\"evenodd\" d=\"M12.586 4.586a2 2 0 112.828 2.828l-3 3a2 2 0 01-2.828 0 1 1 0 00-1.414 1.414 4 4 0 005.656 0l3-3a4 4 0 00-5.656-5.656l-1.5 1.5a1 1 0 101.414 1.414l1.5-1.5zm-5 5a2 2 0 012.828 0 1 1 0 101.414-1.414 4 4 0 00-5.656 0l-3 3a4 4 0 105.656 5.656l1.5-1.5a1 1 0 10-1.414-1.414l-1.5 1.5a2 2 0 11-2.828-2.828l3-3z\" clip-rule=\"evenodd\"><\/path>\n    <\/svg>\n  <\/a>\n<\/h2>\n<p>Before Redis 8 in Redis Open Source (version 8.0), all time series configuration parameters are load-time parameters.\nUse one of the following methods to set the values of load-time configuration parameters:<\/p>"},{"title":"Out-of-order \/ backfilled ingestion performance considerations","link":"https:\/\/redis.io\/docs\/latest\/develop\/data-types\/timeseries\/out-of-order_performance_considerations\/","pubDate":"Mon, 01 Jan 0001 00:00:00 +0000","guid":"https:\/\/redis.io\/docs\/latest\/develop\/data-types\/timeseries\/out-of-order_performance_considerations\/","description":"<p>When an older timestamp is inserted into a time series, the chunk of memory corresponding to the new sample\u2019s time frame will potentially have to be retrieved from the main memory (you can read more about these chunks <a href=\"https:\/\/redislabs.com\/blog\/redistimeseries-ga-making-4th-dimension-truly-immersive\/\">here<\/a>). When this chunk is a compressed chunk, it will also have to be decoded before we can insert\/update to it. These are memory-intensive\u2014and in the case of decoding, compute-intensive\u2014operations that will influence the overall achievable ingestion rate.<\/p>"},{"title":"Use cases","link":"https:\/\/redis.io\/docs\/latest\/develop\/data-types\/timeseries\/use_cases\/","pubDate":"Mon, 01 Jan 0001 00:00:00 +0000","guid":"https:\/\/redis.io\/docs\/latest\/develop\/data-types\/timeseries\/use_cases\/","description":"<p><strong>Monitoring (data center)<\/strong><\/p>\n<p>Modern data centers have a lot of moving pieces, such as infrastructure (servers and networks) and software systems (applications and services) that need to be monitored around the clock.<\/p>\n<p>Redis Time Series allows you to plan for new resources upfront, optimize the utilization of existing resources, reconstruct the circumstances that led to outages, and identify application performance issues by analyzing and reporting on the following metrics:<\/p>\n<ul>\n<li>Maximum CPU utilization per server<\/li>\n<li>Maximum network latency between two services<\/li>\n<li>Average IO bandwidth utilization of a storage system<\/li>\n<li>99th percentile of the response time of a specific application outages<\/li>\n<\/ul>\n<p><strong>Weather analysis (environment)<\/strong><\/p>"}]}}