Monitors your infrastructure 24/7, detects anomalies before they become incidents, and auto-remediates common issues. Reduces MTTR from hours to minutes. All on your infrastructure.
"We had a runbook for everything. Literally everything. 147 pages of documented procedures. But when the alert fired at 3 AM, the on-call engineer still had to wake up, read the runbook, and manually execute each step. Average time to resolve: 47 minutes. For issues we'd seen hundreds of times. It was insane."
โ VP of Engineering, SaaS Platform (400 engineers)
Deploy an AI SRE that monitors your systems 24/7, detects anomalies before they become incidents, and automatically remediates common issuesโwithout waking anyone up.
Correlates signals across metrics, logs, and traces. Learns your system's normal behavior. Detects anomalies before they trigger traditional thresholds. Catches issues 10-15 minutes earlier than static alerts.
Executes runbooks automatically for known issues. Scales infrastructure, restarts services, clears caches, rotates credentialsโwhatever the playbook says. Human approval for anything risky.
Only pages humans for novel issues or when auto-remediation fails. Provides full context: what happened, what was tried, what's recommended next. Engineers wake up informed, not confused.
CPU, memory, disk, network. VMs, containers, Kubernetes clusters. Auto-scaling triggers.
Response times, error rates, throughput. APM integration. Distributed tracing.
Query performance, connection pools, replication lag. Slow query detection.
Latency, packet loss, DNS. Load balancers, CDN, edge locations.
Unusual access patterns, certificate expiry, credential rotation. Compliance drift.
AWS, GCP, Azure. Service health, quota limits, cost anomalies.
Signups, transactions, conversions. Correlate technical issues with business impact.
Third-party APIs, SaaS services, payment processors. External health tracking.
Memory leak in payment service causes crashes every few days. On-call gets paged, restarts the service, goes back to sleep. Same runbook. Same 3 AM page.
Static thresholds miss subtle changes. Latency jumps from 50ms to 150msโno alert fires, but something's wrong.
Production incident. Multiple alerts firing. On-call spends 20 minutes just understanding what's actually broken.
Traffic spikes are predictableโMonday mornings, end of month. But someone has to remember to scale up, and they're always 10 minutes late.
Combines metrics, logs, and traces. Understands relationships between services. Finds root cause, not symptoms.
ML-based baseline learning. Detects deviations before thresholds breach. Seasonal pattern recognition.
Executes runbooks automatically. Scales, restarts, reroutes. Human approval for destructive actions.
Consolidates alert storms into single incidents. Reduces noise by 90%+. Only pages when it matters.
Converts existing runbooks into executable automation. Learn from manual responses.
Understands service dependencies. Calculates blast radius. Prioritizes by business impact.
Learns traffic patterns. Scales before spikes hit. Optimizes cost during quiet periods.
Auto-generates incident reports. Timeline, root cause, actions taken. Blameless by design.
Routes to the right person. Includes full context. Integrates with PagerDuty, Opsgenie, Slack.
Monitor infrastructure 24/7, detect anomalies before they become incidents, and auto-remediate common issues while routing complex problems to humans with full context
Inputs: Metrics, logs, traces from observability stack, service dependency maps, runbook definitions, escalation policies, historical incident data
Outputs: Correlated alerts, auto-remediation actions, incident reports, escalation notifications, postmortem data, capacity recommendations
Escalate to on-call when: novel issue with no matching runbook, auto-remediation fails after 2 attempts, P1/P2 severity incident detected, customer impact exceeds threshold, security concern identified
Pay once. Own the asset. Full source code on Google ADK. Deploy, modify, extend.
Metrics, logs, and traces never leave your infrastructure. Runbooks and remediations stay internal.
New monitoring integrations, security patches, and remediation patterns. You own agents; you subscribe to safety.
Configure runbooks, escalation policies, and remediation boundaries for your environment.
Deploy the Site Reliability Agent on your infrastructure. 24/7 monitoring. Auto-remediation. Engineers who actually rest.
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