VictorOps is now Splunk On-Call! Learn More.
Modern IT operations and DevOps-centric organizations are required to find new ways to maintain resilient applications and infrastructure without slowing delivery speed. Highly complex, integrated systems, alongside CI/CD, containerized applications and DevOps adoption are leading to more complicated production environments. So, software developers and IT professionals alike are constantly searching for ways to continuously deliver features and services in a reliable fashion.
DevOps is leading to shorter feedback loops and tighter relationships between IT and software engineering teams – leading to more collaboration and transparency in the release management and software delivery process. But, teams are finding that the only surefire way to maintain reliable systems is through an established plan for on-call incident management and response. DevOps and IT teams are learning how to notify on-call responders faster and more appropriately while providing more applicable alert context – helping them fix issues faster.
To move incident response and on-call operations into the future, VictorOps is leveraging automation and machine learning. In a highly collaborative, centralized solution for incident management and response, you can automatically route alerts through the proper channels and use machine learning and ChatOps to quickly remediate problems. Below, you’ll learn more about making on-call suck less with our latest machine learning capability – suggested responders:
As VictorOps ingests more alerts from multiple monitoring tools, the system learns more about the way your team responds to incidents. As the team resolves more incidents, VictorOps better understands who has the ability to fix certain problems. For new on-call responders, suggested responders can help them quickly understand who can handle certain issues on the team. Or, if you’re somehow alerted for a feature or service you’re not equipped to look into, you can quickly add the right responder to the incident.
Over time, you can optimize your alert routing keys and escalation policies to make alerts more actionable – getting them to the right person the first time. And, even if you find it hard to get the time to update your alerts, it’s as easy as clicking one button to add the right responders to an issue.
Many incidents in DevOps and IT are not isolated to one single server, system or application. Because of the nature of CI/CD and continuous integration between applications and services, it’s likely that multiple alerts are related to each other. In VictorOps, you can combine alerts into a single incident and leverage suggested responders to make sure you get the right people working on the issue. Then, in the same tool, you can automatically start up a conference call or a Slack channel so the team can work together in real-time to triage the incident and resolve the problem.
Suggested responders and a collaborative tool for on-call incident management and response breaks down silos. No longer will the sysadmin team receive an alert without context for which they’re not equipped to fix. In seconds, they’ll know exactly which person or team on the software engineering team can jump in and help them fix the issue. Accountability for service resilience is spread across the entire organization, driving more robust software, higher revenue, happier customers and happier employees.
It’s really just the tip of the iceberg for machine learning functionality in DevOps and IT. The ability to learn from previous incidents and the vast amounts of monitoring data ingested by alerting systems is leading to efficient incident management. Machine learning in incident management isn’t eliminating the need for on-call teams but it’s reducing alert fatigue and helping people understand their services more quickly.
Think about the amount of time it can take to ramp up an engineer to the intricacies of your software and infrastructure. Then, when a new engineer encounters their first major incident while on-call, they’ll be confident that they have the tools and resources they need to fix the issue. Being on-call can feel like you’re alone in the dark. Suggested responders not only helps you find the right person to help you, but it helps you not send an alert to the wrong person at 3 AM.
Teams of all kinds (DevOps, SRE, SysAdmins, NOCs, etc.) are already using VictorOps to reduce alert noise and create an efficient system for collaborative on-call incident response. With VictorOps, you can manage the incident lifecycle from beginning to end within one tool for all engineering and IT teams. Machine learning in incident management and our latest suggested responders functionality is just one of the many ways you can reduce downtime, improve MTTA and MTTR, mitigate alert fatigue and make end-users happier.
Sign up for a 14-day free trial or request a free personalized demo with our sales team to learn more about suggested responders and the numerous ways we improve incident management and make on-call suck less for DevOps and IT operations.