wu-sheng commented on code in PR #772: URL: https://github.com/apache/skywalking-website/pull/772#discussion_r1967541763
########## content/blog/2025-02-24-improving-alert-accuracy-with-dynamic-baselines/index.md: ########## @@ -0,0 +1,199 @@ +--- +title: "Improving Alert Accuracy with Dynamic Baselines" +date: 2025-02-24 +author: "Han Liu" +description: "This article explores how to leverage history metrics to generate dynamic baselines for a future period, thereby enhancing the accuracy of alerts." +--- + +## Background + +[Apache SkyWalking](https://skywalking.apache.org/) is an open-source application performance monitoring (APM) system +that collects various data from business applications, including metrics, logs, and distributed tracing information, +and visualizes them through its UI. +It also allows users to configure alerting rules by setting threshold values for specific metrics in the configuration file. +When a metric associated with a particular service exceeds the predefined threshold within a given period, an alert is triggered. + +However, in real-world scenarios, traffic patterns and invocation behaviors vary across different time periods. +For example, in a shopping system, the number of purchases is significantly lower during late-night hours compared to daytime. +As a result, system metrics fluctuate within different ranges depending on the time of day. +This makes it challenging to rely solely on static threshold values for accurate alerting. + +Therefore, dynamically generating thresholds for each time period based on historical data becomes crucial. + +## Skywalking Predictor with Alarm system + +Based on the above scenario, we developed the [SkyWalking Predictor](https://github.com/SkyAPM/SkyPredictor/) project to fix this issue. +SkyWalking Predictor periodically collects data from SkyWalking and generate dynamic baselines. +SkyWalking can then query the Predictor system to obtain predicted metric values for the recent period, enabling more precise and adaptive alerting. Review Comment: ```suggestion Meanwhile, SkyWalking queries from SkyPredictor to obtain predicted metric values for the recent period, enabling more precise and adaptive alerting. ``` ########## content/blog/2025-02-24-improving-alert-accuracy-with-dynamic-baselines/index.md: ########## @@ -0,0 +1,199 @@ +--- +title: "Improving Alert Accuracy with Dynamic Baselines" +date: 2025-02-24 +author: "Han Liu" +description: "This article explores how to leverage history metrics to generate dynamic baselines for a future period, thereby enhancing the accuracy of alerts." +--- + +## Background + +[Apache SkyWalking](https://skywalking.apache.org/) is an open-source application performance monitoring (APM) system +that collects various data from business applications, including metrics, logs, and distributed tracing information, +and visualizes them through its UI. +It also allows users to configure alerting rules by setting threshold values for specific metrics in the configuration file. +When a metric associated with a particular service exceeds the predefined threshold within a given period, an alert is triggered. + +However, in real-world scenarios, traffic patterns and invocation behaviors vary across different time periods. +For example, in a shopping system, the number of purchases is significantly lower during late-night hours compared to daytime. +As a result, system metrics fluctuate within different ranges depending on the time of day. +This makes it challenging to rely solely on static threshold values for accurate alerting. + +Therefore, dynamically generating thresholds for each time period based on historical data becomes crucial. + +## Skywalking Predictor with Alarm system Review Comment: ```suggestion ## Introduce SkyAPM SkyPredictor ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
