1. The basic definition of APM (from Baidu Encyclopedia)
APM is the abbreviation of Application Performance Management, application performance management, real-time monitoring of enterprise systems to achieve systematic solutions for application performance management and fault management.
Application performance management is a relatively new network management direction. It mainly refers to monitoring and optimizing key business applications of enterprises, improving the reliability and quality of enterprise applications, ensuring that users receive good services, and reducing IT total cost of ownership (TCO). The performance of an enterprise's business-critical applications is strong, can improve competitiveness, and achieve commercial success, therefore, strengthening application performance management (APM) can generate huge commercial benefits.
APM's coverage includes five levels of implementation: end-user experience, application architecture mapping, application transaction analysis, deep application diagnostics, and data analysis
2. Development of APM Technology in 2016
In 2016, Gartner's definition of APM was revised from the original 5-dimensional definition to 3 dimensions, namely Digital Experience Monitoring (DEM), Application Discovery, Tracking and Diagnosis (ADTD) and Application Analysis (AA), in which DEM replaced the Prior to End User Experience Monitoring (EUEM), the end user experience was always the most important task of APM. In terms of mobile application monitoring in 2016, the release of the latest versions of the two major mobile platforms, iOS 10 and Android 7, not only brought some new performance indicator monitoring interfaces, but also blocked many interfaces and methods that could be used in previous versions. Makes APM manufacturers need to look for new monitoring solutions.
In 2016, APM technology not only focused on application performance data, but also gradually began to pay attention to application user behavior and business data. Thanks to the automatic code embedding technology of APM probes, APM can collect and analyze user behavior and business data at a relatively low cost (compared to manual embedding), while providing correlation analysis between performance indicators and business indicators, such as How much business order volume will be affected when the responsiveness of a transaction process decreases. Through business analysis, APM suite products have also promoted the target user group from the operation and maintenance and R&D personnel of the pure technology line to the products and operation personnel of the business line, realizing a great increase in product value.
In 2016, the live broadcast industry showed explosive growth. According to statistics, there are more than 200 live broadcast platforms in China so far, with more than 24 million daily active users. Major e-commerce companies have also launched their own live broadcast channels. As the most effective tool for evaluating user experience from the perspective of end-users, APM suites from various technical aspects such as Active Monitoring (Synthetic Monitoring) and Real User Monitoring (Real User Monitoring), from RTMP, HLS, HTTP-FLV, etc. Live broadcast protocol support provides real-time user experience monitoring for the live broadcast platform from various performance indicators and multiple dimensions, and optimizes live broadcast and real-time scheduling through monitoring data to improve the user experience of live broadcast.
3. APM 2017 Future Outlook
In 2017, we will see big data and machine learning begin to play an important role in the APM field, because cloud computing, microservices and containerization have increased the amount of monitored data, and it is no longer suitable for humans to analyze data. , it's time to hand over the work of anomaly detection and root cause diagnosis to the machines. In addition, there are the challenges of IoT and microservice architecture, containers.
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