Motadata AIOps

Open the console, connect your telemetry, and let the platform map your environment. In a few minutes you can link cloud accounts, hypervisors, Kubernetes clusters, network gear, applications, and log streams. Auto-discovery builds a live topology while baselines establish dynamic thresholds from day one. Create notification rules by service priority, set maintenance windows, and tag owners so the right people get the right alerts. Finish setup by selecting which external tools to sync with—ServiceOps or your preferred ITSM—so incidents and changes flow without manual handoffs.

When something breaks, start in the service view. Related events are grouped automatically and unusual patterns are flagged, cutting down noise so you can focus. The dependency map shows blast radius and likely root causes. Enrich the alert with metrics and logs in one timeline, then send an incident to ServiceOps with a click—routing, assignment, and escalation policies apply instantly. The system proposes runbooks based on history and context; approve an action to restart a service, roll back a deployment, scale pods, purge a queue, flush DNS, or adjust a firewall rule. Close the loop as health recovers; ticket status updates and evidence are pushed back to the service desk for a clean audit trail and faster MTTR.

Between incidents, use the analytics workspace to answer day-to-day questions. Query live logs to spot trends, compare current traffic to baseline, and visualize throughput by site or app. Track host and container resources—CPU, memory, I/O—alongside availability and SLA adherence. Maintain an IP/DNS inventory with quick lookups for MAC and hostname, and set simple policies for acceptable web usage to safeguard the network. Build a performance baseline for key services, watch deviations in real time, and publish weekly reports to stakeholders covering uptime, response times, bandwidth consumption, and capacity headroom.

Automate routine tasks so the team can focus on higher-value work. Chain diagnostics and fixes into workflows that run on schedule or in response to signals. Expose actions via API and webhooks to fit into CI/CD, change management, and paging tools. Keep runbooks versioned with approvals and rollback. Typical patterns include: scale out when CPU anomalies persist, raise QoS for critical paths when congestion appears, or trigger deep endpoint checks when an API slows. With shared dashboards for NOC, SRE, and service desk, everyone sees the same truth, incidents resolve faster, and operating costs drop while reliability improves.