automations

Managing version releases across multiple Jira workspaces can be a manual and error-prone process. In our recent technical session, we explored a streamlined approach to automate this workflow, ensuring consistency across your product ecosystem.

Date calculations are essential for operational insights, such as tracking ticket age or due dates. Manual calculations fail to scale, making Jira Cloud automation a vital tool for business efficiency.

Setting Up Your First Automation Flow

To calculate date differences, start by configuring a trigger—such as a status transition—and pairing it with an "Edit Issue" action. Target a custom field to store the result, ensuring you have a clean setup for your data.

Every administrator knows the feeling: it's Monday morning, and suddenly, automation rules are failing across the board. The instinct is immediate—start debugging triggers, conditions, and smart values. But before you dive into the weeds of configuration, pause. The problem might not be your rule at all.

Automating Jira attachment cleanup is a powerful way to enhance storage efficiency and enforce strict compliance policies. This post explores how to leverage Jira Cloud automation to automatically delete attachments based on workflow transitions.

As your Jira instance scales, the number of automation rules can quickly grow from a handful to hundreds. While these automations are essential for efficiency, they can also become a burden if not managed correctly.

The Visibility Gap

Most administrators rely on audit logs to troubleshoot issues. However, audit logs often fail to answer critical performance questions: Which rules are running the most? Which ones are consuming the most processing time? Where are the inefficiencies hiding?

In many organizations, bridging the gap between Jira Service Management (JSM) and Jira Software creates a significant operational bottleneck. When a customer incident escalates into a software bug, support teams often find themselves trapped in manual data entry—copying descriptions, screenshots, and manually linking tickets. This post explores how to automate these processes to improve efficiency and traceability.

In our recent tutorial session, we explored the powerful yet frequently overlooked "Create Variable" action in Jira Cloud Automation. Understanding how to use these variables is a game-changer for administrators looking to create cleaner, more maintainable automation rules.

Automating Jira subtask creation can significantly streamline your workflow, especially when you need to maintain data consistency between parent issues and their child tasks. However, a common hurdle arises when dealing with cascading select lists. In this guide, we explore how to bridge this gap using Jira Cloud Automation.

In the realm of Jira Cloud, automation is often synonymous with event-driven triggers—actions that fire automatically when an issue is created, updated, or transitioned. However, manual triggers offer a powerful alternative for on-demand execution. Unlike their event-driven counterparts, manual triggers allow users to initiate specific automation rules with a single click.

Automation has become one of the most powerful features in Jira Cloud, allowing teams to eliminate repetitive tasks, improve workflow efficiency, and maintain consistency across projects. However, the automation experience we use today didn't always exist.

If you've been using Jira for only a few years, you've probably never encountered Legacy Automation. But understanding its history provides valuable insight into how Jira Automation has evolved into the feature-rich platform we rely on today.