Issue page revamp for NRAI #19790
Issue page revamp for NRAI #19790
Conversation
Created this for NRAI integrations on issue page.
|
Hi @mlakshmiharita 👋 Thanks for your pull request! Your PR is in a queue, and a writer will take a look soon. We generally publish small edits within one business day, and larger edits within three days. We will automatically generate a preview of your request, and will comment with a link when the preview is ready (usually 10 to 20 minutes). |
✅ Deploy Preview for docs-website-netlify ready!
To edit notification comments on pull requests, go to your Netlify site configuration. |
Updating Issue page for AIML
Typo Corrections
WIP. Please do not merge.
WIP. Do not push.
WIP. Do not merge.
src/content/docs/alerts/incident-management/Issues-and-Incident-management-and-response.mdx
Outdated
Show resolved
Hide resolved
src/content/docs/alerts/incident-management/Issues-and-Incident-management-and-response.mdx
Outdated
Show resolved
Hide resolved
| ### How does the engine work? | ||
| The causal analysis engine uses distinct analysis categories, such as deployment events, infrastructure resource limits, and more. Each category is designed to address various potential sources of anomalies and performance issues. These categories focus on specific data types and metrics, enabling precise analysis and more accurate identification of causal relationships. | ||
|
|
||
| At the moment, we’re primarily focused on APM entity causal analysis. In the near term, our plan is to include infrastructure, Browser, among other entity types. |
There was a problem hiding this comment.
Do we want to commit to this in docs?
src/content/docs/alerts/incident-management/Issues-and-Incident-management-and-response.mdx
Outdated
Show resolved
Hide resolved
src/content/docs/alerts/incident-management/Issues-and-Incident-management-and-response.mdx
Outdated
Show resolved
Hide resolved
src/content/docs/alerts/incident-management/Issues-and-Incident-management-and-response.mdx
Outdated
Show resolved
Hide resolved
src/content/docs/alerts/incident-management/Issues-and-Incident-management-and-response.mdx
Outdated
Show resolved
Hide resolved
src/content/docs/alerts/incident-management/response-intelligence-ai.mdx
Show resolved
Hide resolved
| Many IT issues tend to reoccur. Knowing if an issue has happened before, why it occurred, and how it was resolved can save first responders valuable time during an incident. To support this, customers can use the widget to link their existing retrospective or postmortem documents. By leveraging retrieval augmented generation (RAG), the New Relic AI platform will index and store this information for future contextual reference. Once configured, first responders will see a summary of similar past issues, along with links to the retrospective documents for detailed analysis. | ||
|
|
||
| ## What to check? | ||
| First responders often need contextual guidance on immediate actions to mitigate an issue. This widget provides customized steps to help them quickly restore services to normal operational levels. Additionally, the Potential causes tab identifies likely causes through causal analysis, covering a range of possible anomalies and performance issues. For more information, refer to casual analysis. |
There was a problem hiding this comment.
After this pararaph, please add the following:
Overview
The causal analysis engine identifies potential symptoms that might have triggered an alert event and suggests immediate mitigating actions to address them.
Consider a scenario where a PHP application encounters a memory leak, leading to a failure in the throughput SLI and triggering an alert. Our engine investigates by moving from the service level to the APM application and then to the infrastructure container to detect the symptom.
How does the engine work? The causal analysis engine uses distinct analysis categories, such as deployment events, infrastructure resource limits, and more. Each category is designed to address various potential sources of anomalies and performance issues. These categories focus on specific data types and metrics, enabling precise analysis and more accurate identification of causal relationships.
At the moment, we’re primarily focused on APM entity causal analysis. In the near term, our plan is to include infrastructure, Browser, among other entity types.
Mitigating actions & visualizations
For every identified potential cause, the engine offers tailored mitigation actions that guide users through the necessary steps to quickly restore services and entities to their normal operational states. We recognize that many of our customers typically rely on NRQL to analyze significant queries, hence we provide relevant visuals alongside the underlying query for each cause.
New Relic AI generated analysis
In some scenarios, our causal engine may not identify an algorithm-driven cause. However, we have insights that can be utilized with LLMs to offer you actionable steps. Customers interested in this capability must have the New Relic AI entitlement enabled.
Incorporating Vinay's edits Co-authored-by: Vinay Payyapilly <[email protected]>
Created this for NRAI integrations on issue page.
WIP content, please do not merge. Thank you.