The Complexity of Production Environments
In many organizations, about 30% of an engineer's time is tied up in production tasks, managing legacy code, babysitting multiple dashboards, and coping with notifications that may or may not be critical. Some alerts are minor, but the reality is that production also hosts significant issues needing prompt attention. Hours often slip away trying to figure out which problems should be tackled first.
Calmo is an AI Site Reliability Engineer (SRE) that behaves like a colleague, relying on existing infrastructure tools to manage the day-to-day turmoil. Instead of presenting yet another SaaS interface, this approach offers a form of SRE automation tools, bridging metrics from services like AWS or GCP, analyzing logs, and referencing code repositories to keep production stable. Handling automated incident response tasks means the main human role is making key decisions or deploying final fixes.
When something malfunctions, Calmo gathers system metrics, traces, and historical data to understand what went wrong.
Root Cause Analysis and Intelligent Investigation
Many failures can be traced back to a single root cause: a flawed code push, a database schema change, or a resource bottleneck. Calmo correlates different signals (metrics, recent deployments, incident histories) to identify that root cause quickly.
It also connects to metrics dashboards, tracing systems, and code repositories, along with Slack, Teams, or other collaboration channels. Access to logs, runbooks, and playbooks can be coordinated in one thread, minimizing the search for scattered documentation. Calmo consumes these resources to deliver a human-like output for each investigation, ultimately resulting in a workflow that's faster and more transparent.