Getting started with Data Center monitoring

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This article features some basic guidelines on monitoring the health of your Data Center instance. There are two types of metrics you need to monitor:


These metrics reflect how your organization uses the Data Center product – number of users, amount of pages (in Confluence), number of issues (in Jira), etc. They also cover cases where your customizations can be quantified – for example, how many custom fields your Jira instance uses


Every action your users perform on the product adds load, and the effect of that load can be compounded by how you've customized and configured your Data Center product. Infrastructure metrics reflect how your load affects the environment on which your Data Center product is hosted.

In large organizations, the task of managing the Data Center application, its dependent components, and underlying infrastructure might be distributed across different roles. Understanding the difference between usage and infrastructure metrics can help you identify where each metric is tracked, along with who should be responsible for tracking and analyzing them. 

Usage metrics

Usage metrics can be tracked through a product's administrative user interface or database. This section provides some basic guidance for Jira and Confluence.

Track trends in usage and watch how they grow over time. Use these growth trends to help inform your predictions on how your load will look down the line. The lists below provide the fundamental metrics you should be tracking for both Jira and Confluence:


Application usage

Regularly track the total number of:

  • Issues
  • Attachments (including their total size)
  • Projects
  • Project artifacts
  • Workflows
  • Custom fields

You should also look out for sudden spikes in usage, as this can indicate a misbehaving plug-in or other problem (for example, if the total number of issues grows by 10% in the past 24 hours).


Application usage

Regularly track the total number of:

  • Existing pages
  • Attachments (including their total size)
  • All spaces
    • site spaces
    • personal spaces
  • All content items
    • current content items (pages, blog posts, etc)
    • previous (as in, earlier versions than current) content items

Database usage

  • Database table sizes
  • Content created per day
  • Content edited per day

For related information on how to retrieve this data, see:

Database usage

  • Content created per day (average number of pages created)
  • Content edited per day

For related information on how to retrieve this data, see:

See Tools for monitoring your Data Center application for related information.

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Other resources

Dynatrace also provides an overview of how to monitor Jira and Confluence on their platform. See Optimizing Atlassian JIRA and Confluence Productivity with Dynatrace for details. 

Infrastructure metrics

Infrastructure metrics generally require third-party tools to track, particularly if you're tracking the performance of multiple nodes in a cluster (as opposed to just a single host). Refer to Getting started with Data Center monitoring for examples of tools you can use.

The following infrastructure metrics are fundamental to any monitoring strategy. Track them regularly for each server in your deployment:

Application server

  • Average CPU load
    • Per minute
    • Per 5 minutes
  • RAM usage
  • Disk usage percentage (for all mounts)
  • Apache requests  per second (5-minute average)

Database server

The most important database metric to track is the number of open connections (5-minute average). A high number (like 50) can indicate that there is a bottleneck, and may need investigating.

You will also need to track the total number of the following database metrics at regular intervals (for example, every 4 hours):

  • Inserts
  • Updates
  • Locks
  • Commits
  • Deletes
  • Buffer hits

Assuming your database server is hosted on a dedicated server (as recommended), track the following as well:

  • Average CPU load
    • Per minute
    • Per 5 minutes
  • RAM usage
  • Disk usage percentage

Java Virtual Machine

As Atlassian applications are Java-based, you can use many of the monitoring points built into the Java Virtual Machine for insight into the health of your instance. The following metrics are of particular interest:

You can also use JMX (Java Monitoring eXtensions) to monitor your application in real-time. JMX uses objects called MBeans (Managed Beans) to expose data and resources from your application. The following articles provide more details on using JMX for specific products:

Trending and alerting

Once you collect enough data about your organization's usage and infrastructure load, seek out patterns that can help you identify:

  • Peak/non-peak hours of usage
  • Growth trends

Whenever possible, set alerts for metrics that need further investigation. For example:

  • the number of open database connections exceeds 50 over a 5-minute period
  • JVM heap space (as in, the amount of RAM used by Java) exceeds 80% of the available capacity

Use an alerting system that administrators and stakeholders can access easily. Your alerting system should also be compatible with your monitoring tool; for example, see Add apps (Stride) for information on how to integrate applications into a Stride room or direct message. 

We're here to help

This article features advice typically provided by Atlassian Technical Account Managers to customers on forming a performance monitoring plan. TAMs can provide strategic guidance to help you choose the right tools and methods to track the health of your instance.

Our  Premier Support team  performs health checks by meticulously analyzing your application and logs, to ensure that your application's deployment fully meets the needs of your users. If the health check process reveals any performance gaps, Premier Support will recommend possible changes to your deployment.

Last modified on Apr 23, 2019

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