Jama Performance In Enterprise Recommendations for System Administrators
Information Moved to the Knowledge Base in January 2024
Jama Connect® Performance In Enterprise Recommendations for System Administrators
Introduction
Jama Connect is a platform that is successfully used at scale for many different use scenarios. By design, Jama Connect can be configured and used in many ways. The fact that the platform is so configurable makes it difficult to provide “hard” guardrails and performance recommendations. Instead, the purpose of this document is to:
- Define “typical” usage profile of Jama Connect
- Provide a matrix where performance may be affected during specific usage scenarios
- Provide recommendations to mitigate performance risks
Assumptions
This article assumes your Jama Connect instance is in our Cloud environment or, if Self-Hosted, the application is installed correctly utilizing supported software and hardware. We require that the application server be on a dedicated system with no other applications running, with a separate dedicated system for databases. It is acceptable to share the database server with databases for other applications.
Typical Usage Profile
A typical data usage profile is where users should not see any performance or scalability issues in typical day-to-day use of Jama Connect. There is always a small risk of performance impacts in any environment, though. Jama engineering teams extensively test Jama for performance, and you can read more about our performance testing approach here: Jama Connect Performance Whitepaper
When describing the typical usage profile, it is important to understand that Jama Connect differentiates “active” vs “inactive” items. Inactive items may be old versions of requirements or entire archived projects. These inactive items are not included in search index and do not materially impact performance of the system. All the numbers below reference “active” aka current version of items. So while a particular project may have 50,000 active requirements, there might be 5x inactive items for the project due to old versions of those items.
Category | Count (active) | Notes |
Total items in database | 10 million | No hard system limit but upper limit recommendation of 10 million active items, with much higher # of inactive items in database. |
Average concurrent user sessions over course of single day | 2500 | Jama supports many more total licensed users in systems. 2500 concurrent users means 2500 users performing application functions within a 5-minute window. |
Average items per project tree | 50,000 | No hard-upper limit but above typical usage, users may encounter more performance issues moving items or doing project-wide actions like whole project baseline. |
Average items per container (e.g. set/folder) | 250 | No hard upper limit but recommend upper limit of 1000. Set and folder containers are meant to help organize data. |
Average relationships per item | 5 | Average # of relationships per item across all items. No hard-upper limit in system. |
Average Test Plans per project | 10 | No hard-upper limit, many more Test Plans may exist in archived state. |
Average Test Cases per Test Plan | 2,500 | No hard-upper limit, recommend upper limit below 5,000. |
Average Cycles per Test Plan | 5 | No hard-upper limit, Recommend upper limit below 10 cycles per plan as each cycle creates a new Test Run item for each test case. |
Average attachments/images per project | 5,000 | Typically these are image files stored on application server and will impact HD space needed for self-hosted customers. No hard-upper limit for Jama Cloud customers. |
Performance Impact Matrix
Below is a summary of what functions may lead to performance issues in certain data profile situations.
- Green: expect no performance issues
- Yellow: may encounter rare performance issues depending on usage
- Orange: more likely to see performance issues as # of concurrent users or volume of active items used exceeds the “typical usage” profile
The more complex and linked your data structure, the more related items you will pull into memory, and the more processor-intensive it will be to manage.
If you believe your organization usage of Jama will likely fall above “typical usage” profile and frequently utilize these functions, consider installing multiple Jama instances to split the data and load.
Typical Profile
If you are operating Jama Connect within our description of “typical usage” profile, the application will be very performant and reliable. Some functions, such as reusing very large # of items, will create a high load on the system. Jama Connect has built-in threshold warnings for users in these scenarios. For example, if a user plans to reuse 1000 items, they will get a pop-up warning that the batch reuse may affect performance. It is not a hard limit. Jama will still complete the task but it’s a guardrail to encourage users to do complex functions in smaller batches.
Concurrent Users Exceeds Typical Usage
If you are operating Jama Connect within our description of a “typical” profile but you have a higher # of concurrent users (greater than 2500 performing multiple actions within 5-minute window.)
Jama may still perform well in many usage scenarios, but you may encounter more performance issues or slowness as a higher volume of users are performing high-load actions on the system concurrently. For example, a higher number of users may concurrently create complex filter queries across entire system or export large documents with thousands of items which may stress the system.
Volume of Items Exceeds Typical Usage
If you are operating Jama Connect beyond the volume of items defined in the “typical usage” profile, you are more likely to see performance issues with specific functions. This is especially true if multiple users are performing high-load actions concurrently. Please carefully review the performance recommendations section. If you believe your organization usage of Jama will likely fall above “typical usage” profile and frequently utilize functions that may lead to performance issues, consider installing multiple Jama instances to split the data and load.
Performance Risks and Recommendations By Function
Periodic Performance Issues: If you find that your users are reporting that Jama periodically seems to ‘slow down’ and the issues do not appear to relate to any specific area.
Troubleshooting: Monitor the CPU/Memory utilization to see resources are being consumed by large operations. Talk to your power users and see if any of them are creating Reviews, Baselines or generating reports on large numbers of items.
Recommendations: Break large operations up into smaller operations. Run large operations at the end of the day when less users will be on the system. Increase system resources to reduce impact of periodic large operations.
Function-Specific Performance Issues
# |
Function |
Performance Issues |
Troubleshooting |
Recommendations |
1 |
Viewing Items |
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2 |
Comment on item
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3 |
Create / Edit Item |
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4 |
View traceability |
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5 |
Search for item(s) |
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6 |
Batch edit/delete items |
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7 |
Move item(s) in tree |
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8 |
Participate in a review |
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9 |
Reuse items |
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10 |
Create Test Cycles & Runs |
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11 |
Create baselines |
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12 |
Export data to documents |
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13 |
API scripts / integrations |
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14 |
Dashboards |
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