Hybrid and multi-cloud inventory, health analytics, drift intelligence, workload placement and governed remediation.
Talk to a CloudOps AIOps Specialist
Each service can be taken alone. They share telemetry, policy and runbooks when combined.
One operations layer for AWS, Azure, GCP and private-cloud inventory, health, incidents, changes and automation.
Example scenario
Show several provider environments in one control plane and run one cross-cloud workflow.
Detect unhealthy cloud resources and recover them under policy control.
Example scenario
Simulate unhealthy compute or application infrastructure and demonstrate recovery.
Compare cloud state with desired IaC and policy and safely reconcile drift.
Example scenario
Create console drift and restore the intended state through Git and IaC.
Recommend placement from capacity, latency, availability, policy and cost inputs, with reasons.
Example scenario
Submit a workload profile and compare placement options across private and public cloud.
Map applications to cloud dependencies, correlate provider events and estimate blast radius.
Example scenario
Fail a shared dependency and show every affected application and the contingency actions.
Every service is built as a local-first lab, then extended to your private cloud and to AWS, Azure or GCP.
Ingestion health, processing latency, decisions, automation success and failure, overrides and false positives where measurable.
Validated, allowlisted actions with approval rules and least-privilege identities.
Healthy, false-positive, policy-blocked, automation-failure, rollback and telemetry-source-failure cases, all exercised.
Retained evidence for every decision, a short demo script, and setup, troubleshooting and cleanup documentation.
Rules every AIOps action follows, in every track.
AI output never goes straight to a shell, cloud API or cluster. It selects from validated runbooks.
Disruptive actions wait for a person. Low-risk, reversible steps can run on their own once you agree the rule.
Every action is followed by a health check, with rollback or compensation when the check fails.
Signals, scores, model or rule versions, approvals and results are retained and reviewable.
Adapted to the tools you already run.
Combine tracks to share telemetry, policy and runbooks.
Tell us what you run and where operations hurt most. We will suggest where to begin.
Talk to an AIOps Specialist