Grafana v7.5 has been released! This is the last stable release before we launch Grafana 8.0 at GrafanaCONline in June. Register for free now, so you won’t miss the great sessions we’re planning around all things Grafana. And if you’re doing something special with Grafana that you’d like to share with the community, the CFP for GrafanaCONline is open until 06:59 UTC on April 10! Now, back to 7.5.

When you send alerts, work orders or service requests to your workers in the field, on the shop floor or campus it is essential to provide them with all relevant information necessary to solve the task. This prevents misunderstandings, avoids waste work, time for searching information and thus increases productivity and facilities an effective, timely incident resolution.

On-call planning is one of the most popular features in Enterprise Alert and is widely used by users, team managers and administrators. However, in our discussions we keep finding that it is not simply done with 5 minutes of planning. Scheduling often depend on external systems. This can range from a simple excel form provided to HR all the way to a comprehensive billing system such as SAP. As a result, it takes a quite a bit of time to transfer the planned shifts to third-party systems.

Apple announced some time ago that the Apple Push Notification (APN) will be deactivated for sending push messages as of March 31, 2021. To continue to ensure the sending of push messages to iOS devices, we have already implemented push shipping via Firebase in Enterprise Alert 2019. Unfortunately, the change could not be done automatically and requires manual intervention.

We’re excited to present a feature update to the OnPage platform. The new update will bring more flexibility and resiliency to a team’s on-call management workflow. With the new scheduling capabilities, OnPage system administrators can create exceptions to configured, recurring on-call schedules.

Finding relationships between disparate events and patterns can reveal a common thread, an underlying cause of occurrences that, on a surface level, may appear unrelated and unexplainable. The process of discovering the relationships among data metrics is known as correlation analysis. For data scientists and those tasked with monitoring data, correlation analysis is incredibly valuable when used for root cause analysis and reducing time to remediation.