When an incident occurs, do you shudder when either you or your team proceed to open multiple browser tabs for each of your monitoring tools? This is the picture painted by the “swivel-chair” effect, context-switching between tools to gather information needed to determine a path of resolution.
The key to choosing the best compensation plan is finding a solution that works well for your company but also recognizes the employees for their effort and time spent. If employees are well-cared for, they will, in turn, care about the business and contribute to its’ success. After choosing a method and confirming it abides by local laws, be sure to examine the following to confirm that compensation is competitive and fair and that your team can adequately share the load on-call requires.
In an ideal world, your DevOps toolchain would be highly automated for incident management and allow your teams to resolve issues at DevOps speed. An alert triggered by monitoring tools like Datadog or AWS Cloudwatch would notify on-call engineers, kick your collaboration tools into gear (ChatOps, StatusPage, etc), and automatically document the issue in ITSM and ticketing tools.
When incidents happen, many organizations have formalized processes for dealing with the issue. OpsGenie helps organizations manage their incident response processes smoothly from one single place. Now, as an addition to our Incident Management features, we are happy to announce Incident Response Roles!
Running your organization's infrastructure and understanding how services are performing a is key to ensuring every Dev and Ops team is running as efficiently as possible. The problem? Teams typically care about different metrics, so it can be hard to track the metrics you care about when they are not located on a central dashboard. Additionally, if these metrics are in central dashboard, it is often hard to dive deep and understand the root cause of your incidents and the performance of your team.
Announcing the following integrations: Workato, Jira Ops
AIOps is the application of analytics and machine learning to automate some aspects of DevOps and IT operations management. Like all new technologies, it may take time to discover the best ways to get practical results. However, AIOps is already showing a lot of promise in three key uses cases.
