Posts tagged Monitoring
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.
This is an updated blog of the original which was published in May 2016
Payara Server provides the Health Check Service for automatic self-monitoring in order to detect future problems as soon as possible. When enabled, the Health Check Service periodically checks some low level metrics. Whenever it detects that a threshold is not met, it triggers alert notifications that allow to detect undesired behavior and predict possible failures. All of these automatic checks are very lightweight and run with a negligible impact on performance.
Payara Server provides many metrics within JMX beans. The most interesting metrics are the statistics around pools for HTTP threads and JDBC Connection pooling.
On the other hand, Payara Server also implements the MicroProfile Metrics specification. The retrieval of useful metrics from the running instance in the areas of CPU, memory, Class loading, and other MicroProfile specifications (like Fault Tolerance), are possible through the implementation of the MicroProfile Metrics in Payara Server.
(This is an update of this blog written in 2016: Making Use of Payara Server's Monitoring Service)
Payara Server has for a while now included a JMX Monitoring Service which can be used to log information from MBeans to the server log. Using the JMX Monitoring Service, you can monitor information about the JVM runtime such as heap memory usage and threading, as well as more detailed information about the running Payara Server instance. The information is logged as a series of key-value pairs prefixed with the string PAYARA-MONITORING:, making it easy to filter the output using tools such as Logstash or fluentd.
JConsole is a useful tool for monitoring Java processes. You can collect data from a Java process such as: heap memory usage, thread count, CPU usage, classes loaded and MBean data. This allows you to gauge whether any Java process is using too much system resources. This guide will show you how to monitor Payara as a local process (on the same machine), or a remote process. This blog will assume that you've got a valid JDK and Payara install.
In the fourth part of our continuing series on alternatives for commercial Oracle GlassFish features we are looking at the JMX Monitoring Service & the Payara HealthCheck Service as possible replacements for Oracle's Monitoring Scripting Client.