Improving the User Experience for Automated Analysis

Oct 13, 2025 by talynt.org 35 views

[Request] Automatic Automated Analysis

Improving the User Experience for Automated Analysis

The current implementation of Automated Analysis Report results for a particular target can be viewed in two ways: by starting a recording and expanding the table row in the Recordings view, or by using the Automated Analysis dashboard card. However, these methods have some limitations and can be improved to provide a better user experience.

Current Limitations

The first method of viewing Automated Analysis Report results is cumbersome and misleading. It implies that the analysis results may differ across different recordings within a single target, which is not the case. If multiple recordings are running concurrently on a target, grabbing the JFR data stream from any of them will include JFR events enabled by the other recordings. This forces the user to make some decision about what kind of recording to start, which is not necessary for automated analysis.

The second method is more streamlined and straightforward, but it requires the user to agree to start a source recording for each target they wish to analyze. This can be inconvenient, especially if the user needs to analyze multiple targets.

Improvement Suggestions

To improve the user experience, the following suggestions can be implemented:

1. Ship a Preset Automated Rule

Ship a preset automated rule that enables the Continuous template for all discovered targets. This can be used as a source recording for analysis. If the user needs to narrow down the selection, they can download, edit, and re-upload the rule with a refined match expression. This rule can also include the ability to add "recording metadata options" to rule definitions, so that rules-originating recordings can have labels attached.

2. Remove the Recordings Table Row Expansion

Remove the Recordings table row expansion as an automated analysis view. This view misleads the user into thinking that the analysis is more recording-oriented than it is. Instead, the dashboard card can be used to create a source recording for analysis.

3. Batch Processing of Automated Analyses

Implement batch processing of automated analyses. This can be similar to or embedded within automated rules. For example, a checkbox option can be added so that each archival period a recording copy is taken and analyzed. Archived recording analyses are already cached in object storage, so future reads of these analyses are cheap.

4. Expose Automated Analysis Statuses

Expose automated analysis statuses as status indicator badges on the Topology view or some other way so that they are visible at some kind of overview level rather than requiring the user to specifically inspect individual targets.

5. Expose Automated Analysis Scores via GraphQL

Expose automated analysis scores via GraphQL. This might make sense to only expose on Archived Recordings, since if combined with item 3 above, the operation will remain cheap.

6. Expose Automated Analysis Scores via Prometheus-Style Endpoint

Expose automated analysis scores as scrapable metrics on a Prometheus-style endpoint. The team has floated this idea around for a long time. Some aspects of the target's discovery node can be used as a metric key prefix, each analysis rule result name can be a key, and the analysis rule result score the value.

Benefits of the Proposed Changes

The proposed changes will improve the user experience for automated analysis by:

Providing a more streamlined and straightforward way to view Automated Analysis Report results
Reducing the need for users to make decisions about what kind of recording to start
Improving the convenience of analyzing multiple targets
Providing batch processing of automated analyses
Exposing automated analysis statuses and scores in a more visible way

Conclusion

The current implementation of Automated Analysis Report results has some limitations that can be improved to provide a better user experience. The proposed changes will improve the user experience by providing a more streamlined and straightforward way to view Automated Analysis Report results, reducing the need for users to make decisions about what kind of recording to start, and improving the convenience of analyzing multiple targets.
[Request] Automatic Automated Analysis: Q&A

Frequently Asked Questions about Automatic Automated Analysis

In our previous article, we discussed the current limitations of Automated Analysis Report results and proposed changes to improve the user experience. In this article, we will answer some frequently asked questions about automatic automated analysis.

Q: What is the current limitation of Automated Analysis Report results?

A: The current limitation is that the analysis results can be viewed in two ways: by starting a recording and expanding the table row in the Recordings view, or by using the Automated Analysis dashboard card. However, these methods have some limitations and can be improved to provide a better user experience.

Q: Why is the first method of viewing Automated Analysis Report results cumbersome and misleading?

A: The first method implies that the analysis results may differ across different recordings within a single target, which is not the case. If multiple recordings are running concurrently on a target, grabbing the JFR data stream from any of them will include JFR events enabled by the other recordings.

Q: What is the proposed solution to improve the user experience?

A: The proposed solution is to ship a preset automated rule that enables the Continuous template for all discovered targets. This can be used as a source recording for analysis. If the user needs to narrow down the selection, they can download, edit, and re-upload the rule with a refined match expression.

Q: Why is batch processing of automated analyses important?

A: Batch processing of automated analyses is important because it allows users to analyze multiple targets in a single operation, reducing the need for manual intervention and improving the efficiency of the analysis process.

Q: How will the proposed changes improve the user experience?

A: The proposed changes will improve the user experience by providing a more streamlined and straightforward way to view Automated Analysis Report results, reducing the need for users to make decisions about what kind of recording to start, and improving the convenience of analyzing multiple targets.

Q: What are the benefits of exposing automated analysis statuses and scores in a more visible way?

A: The benefits of exposing automated analysis statuses and scores in a more visible way are that users will be able to quickly and easily see the status of their automated analysis jobs and the scores of their analysis results.

Q: How will the proposed changes affect the performance of the system?

A: The proposed changes will not significantly affect the performance of the system. The changes are designed to improve the user experience and efficiency of the analysis process, while minimizing the impact on system performance.

Q: What is the timeline for implementing the proposed changes?

A: The timeline for implementing the proposed changes is not yet determined. However, we anticipate that the changes will be implemented in the near future, pending further discussion and planning.

Conclusion

The proposed changes to automatic automated analysis will improve the user experience by providing a more streamlined and straightforward way to view Automated Analysis Report results, reducing the need for users to make decisions about what kind of recording to start, and improving the convenience of analyzing multiple targets. We hope that this Q&A article has provided helpful information and answers to your questions about automatic automated analysis.