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The Request Tracing Service helps detect application slowness and performance degradation by logging requests that exceed a given threshold. The trace data from long-running requests gives insight to solving bottlenecks and other performance issues. The service is very lightweight and doesn’t impact performance when enabled. Therefore it provides authentic information about what’s going on in the application and how long it takes to finish. It’s compatible with the MicroProfile OpenTracing specification so you can use any data generated in any OpenTracing tool (such as Zipkin and Jaeger).
Payara Server includes capabilities to detect and log slow SQL queries executed via a connection pool. The Slow SQL logger monitors all queries executed on the connection pool and if they exceed a configurable execution time in seconds, a warning message is logged into the server log. The warning message logs the SQL query and the stack trace to the code executing the query to enable rapid diagnosis, pinpointing the exact lines of code to investigate.
Develop custom auditing, error handling, and monitoring components with SQL Trace Listeners. Payara Platform SQL Trace Listeners track calls to the database and can be enabled globally on a data source if the class implementing it is on the server’s classpath, or they can be enabled on application-specific data sources by including them in the application’s WAR or EAR file.
SQL Tracing in the Payara Platform gives you a detailed look at what the application is doing to identify the cause of issues and a view of all queries performed.
After you’ve got familiar with administering Payara Server, having configured your domain and deployed your applications, you might find it useful to get some more information on features supporting maintenance and diagnostics of your domain in the longer term.
Download the Guide which summarises some very useful maintenance features of Payara Server:
The guide features a demo on Application Versioning in Payara Server and lists some useful references to the detailed documentation material for Payara Server.
Once an application is running on Payara Server, it’s important to know when something is not working as expected, or if you’re experiencing performance issues. To find out what is going on and what could be improved, Payara Server provides several monitoring options.
Once you have developed applications on Payara Server and moved these applications into a production environment, control will pass over to your operations teams. This guide introduces some features of Payara Server that you may not know about, which are especially useful for the operations teams.
Request tracing has been a feature in Payara Platform for a number of years now, and over time it has evolved and changed in a number of ways. The crux of what the feature is remains the same, however: tracing requests through various parts of your applications and the Payara Platform to provide details about their travels.
RMI calls to an EJB hosted on Payara Server from a Java SE client have the active Span Context automatically propagated to the server, with a counterpart server-side span being created as a child of this client call.
As previously reported on this blog, the Request Tracing Service was improved drastically in release 18.104.22.168 and implemented the configuration of a historic trace record storing for increased productivity purposes. In addition to these changes, we also made the configuration on the Request Tracing Service in Payara Micro for the same release. These changes to Payara Micro make it simpler to configure the Request Tracing Service when starting a new instance!
Since being introduced as a technical preview, the Request Tracing Service has been improved and polished to meet production quality requirements. In the latest Payara Server version 171, it was extended to allow tracing of more request types and more events that happen during the requests. It can also remember traces of the slowest 20 requests for viewing them later, though the number stored can be increased or decreased.
Have you ever wondered whether your application is slow to respond to requests? Which requests take the longest to respond to? And what you can do about it? Payara Server aims to provide the best tooling you would need to identify performance issues, identify their causes and help you solve them. One part of this tooling is the new Request Tracing service, available in Payara Server and Payara Micro from version 163 as a technical preview.
In this recorded webinar we explore how Payara Monitoring Console helps you streamline your Jakarta EE and MicroProfile application monitoring, troubleshooting, and management. Discover how the Payara Monitoring Console streamlines monitoring workflows, improves application performance, and enables faster incident response for your organisation.
Within Payara Server, the JMX system is used to store all the data that the monitoring service captures of the modules within the runtime. You can use any tool that can connect to the JMX system to collect these data and monitor the environment. Besides this direct access, the notifier service can send this information to various channels so that the data can be integrated with external systems. The Notifier service is modular since October 2020 with version 5.2020.5 so that you can include only those notifiers that you are interested in and use within your environment. These notifiers cover a wide range of channels, from typical destinations like email, JMS Queues, over APM tools like DataDog and NewRelic to communication platforms like Teams, Slack, and Discord. In this blog, we take a look at enabling JMX Monitoring for the JVM Heap Size, monitoring the process Heap Size, and then sending that information to a Discord channel.
What happens when an application designed for a small user base needs to be scaled up and moved to the cloud? It needs to live in a distributed environment: responding to an appropriate number of concurrent user requests per second and ensuring users find the application reliable. Though Jakarta EE and Eclipse MicroProfile can help with reliable clustering, there is no standard API in Jakarta EE that defines how clustering should work currently. This might change in the future, but in the meantime, this gap must be filled by DevOps engineers. In this blog, we will cover 10 technical strategies to deal with clustering challenges when developing Jakarta EE and MicroProfile for cloud environments.
嬉しいお知らせです。Payara Platform 5.194から、Payara Serverにはサーバーの状態を可視化できる組み込みの監視コンソールが搭載されます。
We are happy to announce that from the Payara Platform 5.194 release onwards Payara Server ships with a built-in monitoring console that allows a visual peek under the hood of the server.
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