For years, reliability discussions have focused on uptime and whether a service met its internal SLO. However, as systems become more distributed, reliant on complex internet stacks, and integrated with AI, this binary perspective is no longer sufficient. Reliability now encompasses digital experience, speed, and business impact. For the second year in a row, The SRE Report highlights this shift.
It was the time of Novell networks, RG58 cables, and bulky tower PCs. It was also a time before the telemarketer's IT department employed specialists. Carter and his two colleagues - boss Mike and part-time student Stefan - therefore handled tasks ranging from programming to support, and everything in between.
Once an issue is detected, AI agents will automatically address security, configuration, and optimization issues without any manual intervention required. In the event the updates applied create another issue, Codenotary Trust also provides an automated rollback capability that restores the IT environment to its previous state.
Support for distributed systems. Check how well the tool handles microservices, serverless, and Kubernetes. Can you follow a request across services, queues, and third-party APIs? Does it understand pods, nodes, clusters, and autoscaling events, or does it treat everything like a static host? Correlation across metrics, logs, and traces. In an incident, you shouldn't be copying IDs between tools. Look for the ability to pivot directly from a slow trace to relevant logs,
