Jira for ITSM is a DevOps Trap

In many companies, Jira is the go-to solution for IT Service Management (ITSM). Compliance teams are pleased with its structured approach, but this method often results in significant inefficiencies.

A common workflow illustrates this inefficiency well. Suppose a developer needs to run a query in a privileged environment. First, they create a Jira ticket and fill out a lengthy change management form. Much of the information required is already in context, leading to unnecessary time wasted. The ticket is then sent to the Database Administration (DBA) team for review and approval. This team could also include the Network Operations Center (NOC) or DevOps team, which typically have little context on the task at hand. Their main job becomes checking that the form was filled out correctly—a task Jira can already automate. They then connect to the database, copy the query from the Jira ticket, paste it into their client, run it, and copy the output back into the Jira ticket comments. Finally, they update the status to notify the developer of the results.

The developer then checks the Jira ticket to see if the query was successful or if there was an error, which could mean system downtime. This process is fraught with inefficiencies. Context switching alone can waste dozens of hours per developer each month. The DBA team, demotivated by repetitive copy-pasting tasks, is a massive resource waste, considering their skills could be applied to more challenging problems.

These inefficiencies extend beyond slow problem resolution. They lead to a worse reputation with customers, slower time to market, and poor employee retention.

Enter Hoop's Query Execution Engine

Hoop's query execution engine offers an optimized change management workflow for DevOps. Here’s how it works:

1. A developer tests their query in development and QA environments.
2. By toggling a switch in the client, they can prepare to execute it in production.
3. The query doesn't run immediately; a workflow is automatically prompted.
4. The user is asked for additional information, but the system uses context to track data it already knows, such as user, team, database profile, and environment. It also shows successful executions in other environments, proving the query passed tests, and generates an AI summary of the query.
5. The user is prompted only for essential inputs, similar to a Git pull request: the reason for execution and any additional description for the query.
6. The user submits the query like running any other SQL script. There's no need to learn ITSM workflows as everything happens transparently.
7. The DBA team receives a Slack notification with all the context needed to review the query, including the query itself, description, and team details.
8. From their mobile phone, any team member can trigger the approval by tapping a button in Slack. This process is 52 times faster than the previous workflow, allowing the team to focus on more significant tasks.
9. The developer is notified when the query is approved, maintaining autonomy and ownership. They execute the query, check the output, and handle any issues. If a problem arises, a rollback was pre-approved and can be triggered immediately.

Compliance Benefits

Hoop's approach enhances ITSM compliance. The automated process eliminates human errors from repeatedly inputting information that the system already possesses. Reports become more reliable, and audits are easier. Information synchronizes with Jira, so there’s no need to learn new reporting systems.

The Jira Integration

Hoop centralizes a lot of metadata, making it easy for compliance teams to use, but this data also needs to be accessible in Jira so compliance teams can track changes in their Jira-based reports. The integration between Hoop and Jira ensures that the transition to Hoop is seamless for audit purposes.

When a user runs a query in a privileged environment requiring approval, the process is as follows:

1. Metadata Collection: Hoop requests the mandatory metadata defined by compliance team, which is attached to Hoop's connections. Some of this metadata could be free-text inputs, while others might be selected from predefined options.
2. Contextual Information: Hoop gathers information provided by the user and contextual data it already has, such as the user’s team, the specific database, and the script. Hoop then creates a Jira card in the format currently used in the manual workflow.
3. Real-time Updates: For every state change in Hoop’s system, the information is sent to Jira in real-time. For example:

• Query Approval: Changes the card’s state to the appropriate status and adds the approver and any other relevant metadata.
• Query Execution: Changes the card state to "executed" and adds metadata about the execution, such as whether it was successful or failed, and any relevant context.

Two-way Integration

This integration can also be two-way, enhancing its functionality:

1. Approval in Communication Tools: Some teams may prefer to use Slack or Microsoft Teams to review and approve executions.
2. Jira Updates Hoop: In these cases, Jira can update Hoop with the execution status. For instance, when someone approves a card in Jira, the status is sent to Hoop, allowing the user to run the query.

The Outcome

The integration offers several key benefits:

1. Minimal Workflow Changes: Existing workflows for different teams within the organization remain largely unchanged.
2. Reduced Manual Errors: Fewer manual inputs and tasks reduce the likelihood of errors.
3. Consistent Compliance Views: Compliance teams can maintain their central ITSM views in Jira without disruption.
4. Focused Development Collaboration: Developers no longer need to use Jira card comments for collaborating on code, keeping the code within development environments.
5. Smooth Transition: Large organizations can transition to using Hoop seamlessly, with some teams barely noticing the change due to the transparent and smooth integration process.

The results speak for themselves: faster resolution of customer problems, happier teams, better employee retention, and skilled engineers focusing on more complex issues.