Using the Rovo Ops agent
Rovo Ops is an agent designed to help you manage alerts and incidents more efficiently by providing historical context and recommending actions, thereby streamlining your on-call duties. Leveraging both Atlassian apps and connected third-party apps as knowledge sources to gather relevant information, it offers guidance to help you mitigate the impact of incidents, seeking to reduce the time you need to detect, respond to, and recover from them.
Run queries for alerts and alert data
Rovo Ops processes your queries in natural language into corresponding AQL syntax and fetches alerts and incidents you have access to.Gather context and resolve incidents faster
Quickly access past and ongoing incidents that may be similar to yours, related articles, and related people to better understand the underlying issues.Create PIR
Post-incident reviews are essential for defining actionable steps and guiding future work item resolution. Integrate Rovo Ops with your post-mortem process to create post-incident review reports (PIR) in a Jira work item or on a Confluence page.
Find alerts and incidents
You can input queries in plain English, such as "show all P1 alerts that came in the last 24 hours”. Rovo Ops processes the natural language input and converts it into the corresponding AQL syntax. The converted AQL query is executed to fetch the relevant alert and incident data that you have access to.
Triage incidents
Whether you're new to the team, returning after a break, or simply need a refresher, Rovo Ops is here to streamline your incident triaging process. By surfacing historical data and insights from knowledge sources you’ve connected Rovo to (that is, based on what you already have access to) such as Confluence (related articles, runbooks, post-mortem reports), Jira (past work items), Jira Service Management (past incidents and alerts), Microsoft Sharepoint docs, Google docs, and historical chats from Slack, Rovo Ops empowers you to quickly understand and address incidents, minimizing reliance on other team members.
Even seasoned experts can benefit from Rovo Ops’s ability to recall and gather details about past incidents, ensuring you have the context you need right at your fingertips. For a previous incident, Rovo Ops provides a concise summary of the details captured in a shared Post-Incident Review (PIR). This feature helps provide a clear understanding of the incident's context and previous resolutions, allowing you to make informed decisions quickly.
For example, Rovo Ops can help you with anything along these lines:
Are there ongoing incidents?
What are some past similar incidents?
Find me knowledge-base articles, runbooks, or PIRs related to an incident
Are there people related to an ongoing incident that can help me?
Summarize an incident (needs an ID or a URL pointing to the incident)
Suggest incidents fields and the creation of a problem ticket
Help with root cause analysis
Update the incident’s priority, severity, or major incident tag.
Create post-incident reviews
Rovo Ops takes your incident management to the next level by integrating with your post-mortem process. Post-incident reviews (PIR) are crucial for defining actionable next steps and serving as living documents that guide the resolution of similar incidents in the future.
Invoke Rovo Ops directly within Confluence to assist in generating comprehensive PIRs.
Create PIR in a Slack channel based on the incident history and other details present in that channel.
Generate an incident timeline by aggregating data from various sources, such as Slack and incident details in Jira Service Management.
Suggest actionable next steps and integrate them into your Confluence pages.
Update incidents
Rovo Ops also helps you update the severity and priority of incidents and update the Major incident tag.
Start and use Rovo Ops
The following articles will provide more details to help you get started. Find out how to access Rovo Chat, select Rovo Ops, and have your conversation:
How to | Article URL |
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Start Rovo Chat | |
Select Rovo Ops from a list of Rovo agents | |
Start Rovo Ops from the Incident work item view (in Jira Service Management) |
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Chat with Rovo Ops |
Conversation starters
Rovo Ops presents three conversation starters to help you get started. You can use any of these or use your own prompts.
Help me resolve an incident (will need you to enter the incident ID or URL)
Create a post-incident review (PIR) (\will need you to enter the incident ID or URL)
Are there any ongoing incidents?
Read more about conversation starters.
Skills
Skills are how Rovo Ops takes action and turns responses into concrete outcomes when working with alerts and incidents.
Rovo Ops skills
These skills are provided directly by Rovo Ops and are designed specifically to support alert and incident management workflows.
Skill | Description |
Find alerts | Find alerts and their related data for an Operations team in Jira Service Management. Suggested prompts:
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Create PIR | Create a post-incident review (PIR) for a given incident. This skill uses incident details and incident slack channel data via Jira Service Management’s Slack integration. Suggested prompts:
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Find similar incidents | Find similar incidents in a given Jira Service Management space based on content similarity. Suggested prompts:
You must provide the incident's ID or URL if you're not already on the page. |
Suggest related people | Suggest people or teams that can help resolve incidents faster. Suggested prompts:
You must provide the incident's ID or URL if you're not already on the page. |
Summarize incident | Create a comprehensive summary of a given incident. Suggested prompts:
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Find incidents | Find incidents in a given Jira Service Management space and their related data. Suggested prompts:
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Find cause of incident | Find the root cause of an incident based on historical data. Suggested prompts:
You must provide the incident's ID or URL if you're not already on the page. |
Suggest problem ticket | Suggest creating a problem ticket if an incident is identified as recurring. Suggested prompts:
You must provide the incident's ID or URL if you're not already on the page. |
Suggest incident fields | Suggest values for severity, priority, and affected services for an incident, or mark it as major based on historical data. Suggested prompts:
You must provide the incident's ID or URL if you're not already on the page. |
Working with MCPs (Model Context Protocol)
Model Context Protocol (MCP) enables Rovo to securely connect to external systems and tools, allowing it to retrieve context-specific data and take action using those systems. MCP-based integrations let Rovo work with third-party observability, monitoring, and operational tools as part of alert and incident investigation and response. Read how to add an external MCP Server from Atlassian Admin.
MCP | Description |
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Use New Relic tools | Use the tools provided by New Relic to access and analyze observability data. Suggested prompts:
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Other Rovo agent skills
These skills are provided by other Rovo agents, but can also be used alongside Rovo Ops to complete related tasks such as creating content or updating work items. Explore all Rovo agents.
Skill | Description |
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Create charts | Create charts that visualize data using any context. Suggested prompts:
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Create page | Create new content in a Confluence space. Suggested prompts:
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Create work item | Create a new work item in a Jira project Suggested prompts:
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Update work item severity | Update the severity of a Jira work item. Suggested prompts:
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Update work item priority | Update the priority of a Jira work item. Suggested prompts:
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Update major incident tag | Update the major incident tag on a Jira work item. Suggested prompts:
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Find out how to write instructions for your custom Rovo agent.
Though Rovo Ops is accessible within Jira, Jira Service Management, Jira Product Discovery, and Confluence, it generates higher-quality output in the context of alerts and incidents within Jira Service Management. The agent also continuously learns from past incidents and alerts and improves its recommendations over time. Regularly review the agent's suggestions and use thumbs-up 👍 or thumbs-down 👎 to provide feedback to enhance its accuracy and usefulness.
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