![]() ![]() Typically, an APM tool will be able to distinguish between the application and external services automatically. Additionally, you will need to determine if the slowdown of the application is due to problems with the application or the external dependencies. Therefore, it is critical to assess the performance of these backend services to determine if there is a need for reconfiguration. While developers may have no control over the code of these backend services, developers can manage the configurations of these services. The external dependencies may be legacy systems, caching layers, databases, queue servers, or web services. When measuring user-facing latencies, you need to monitor all aspects of the user interface, including:Īll applications interact with some form of external or backend services, and these interactions can have a profound effect on the overall performance of your application. The progression accounts for the evolution of the user-facing application and reflects the user experience more than any other metric you can use. The data gathered during this measurement will affect subsequent baselines for that time of day and day of the week. The user-facing metric may shift depending on the time of day and day of the week in which measurement occurs. The excessive deviation indicates abnormal behavior on the part of the application. For instance, you find that the response time is more than the two standard deviations from the average response time for that user transaction. With a Node.js API, the entry point is typically an HTTP request, although it could be a WebSocket connection or a service call, depending on the infrastructure.Īfter identifying the entry point, you can now measure the performance across the app ecosystem to assess if it is performing within normal parameters (baseline + 2 standard deviations). If any Node.js performance measurement goes beyond that, then your API is behaving abnormally.Īfter establishing the baseline, you can start assessing transaction performance by identifying the entry point or the interaction that begins the user transaction. Anything within two standard deviations from the baseline is normal. The goal of measuring user-facing latencies is to ensure the API is behaving normally.īefore you can measure the performance of the application, you must establish a baseline. You want to avoid unnecessary latencies or delays during user interactions. Therefore, ensuring that the API is performing as expected from the user perspective is critical. The function of any API is to relay information from one interface, such as a mobile app, to another. This post is about the top five Node.js performance metrics you should regularly monitor, namely: However, if you want behind-the-scenes knowledge, read on. Retrace provides complete Node.js monitoring in one tool. Tools such as Retrace for Node.js automate the monitoring of critical metrics for your application. Without regular application performance management, dynamic typing can lead to unacceptably slow Node.js performance and memory leaks. This model restricts CPU-thread utilization. Another part is JavaScript uses dynamic typing, which means Node.js assigns types to variables for each use of the application. One part of the reason is the Chrome V8 engine it’s built on tends to slow down when encountering CPU-intensive processes. However, getting Node.js applications to run just right is tricky. These characteristics also means Node.js dispenses with thread-based networking protocols, saving CPU usage and making the application more efficient overall. Node.js is asynchronous and event-driven, which means the application can handle multiple connections at the same time. Here are the top metrics you should monitor for Node.js performance measurement analysis.Īpplication programming interfaces or APIs that use the Node.js runtime environment are scalable. However, it requires significant maintenance to keep it working as expected. Sys.Using Node.js as a JavaScript runtime has its advantages. ![]() You begin to explore the query performance counters in this object using this T-SQL query on the sys.dm_os_performance_counters dynamic management view: SELECT * FROM sys.dm_os_performance_counters ![]() Indicates the total amount of memory the server has committed on this node. Specifies the ideal amount of memory for this node. Specifies the amount of memory the server is using on this node for purposes other than database pages. Specifies the amount of memory the server is not using on this node. Specifies the amount of non NUMA-local memory on this node. Specifies the amount of memory the server is currently using on this node for database pages. This table describes the SQL Server Memory Node counters. The Memory Node object in Microsoft SQL Server provides counters to monitor server memory usage on NUMA nodes. ![]()
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