Kube AIOps

Proactively predict anomalies and automate recovery with KubeAIOps.

KubeAIOps Approach

Not only does it detect anomalies, but it also offers direct troubleshooting and automatically handles failures.

Why KubeAIOps?

Alert-based anomaly detection and failover advisors enable fast and immediate operational adoption.

Immediate cloud operations

Alert-based anomaly prediction engine enables immediate adoption

NexClipper Observability-based integration service available

Streamline your cloud operations and operations teams

Collaborate on problem resolution with an intelligent incident manager

Reduce operational and automation costs

Proactive failure avoidance, lower MTTR

Avoid failures with proactive problem prediction

Reduce recovery time by automating outage handling

Operational tasks ,Failover automation

Automate repetitive failover tasks and more

Eliminate operational human error and minimize repetitive tasks

Multi Cluster

Alert Dashboard

Access Group

Easy Intagration

Business outcome

Why should customers adopt KubeAIOps?

0 %

Reduced MTTR

reduction in mean time to repair

0 %

Accelerate customer acquisition

reduction of new customers on board

0 X

Increased proactive troubleshooting

more proactive problem resoltion

0 %

Reduce the number of failures

reduction in the number of incidents


KubeAIOps is a structure that takes you from data collection to automating failure signaling and handling through analysis and learning.



Our AlertHub acts as a communicator for Prometheus alerts. Through a webhook, the hub receives the alerts and saves them with labels into a database. Users can access the alert depending on permissions for clusters, nodes, and services. Through communication channels, such as Slack, Email, or Webhook, alert notifications are sent to defined access groups.

  • Multi Cluster
  • Alert Dashboard
  • Access Group
  • Easy Intagration


Our anomaly detection system uses Prometheus alert rules and machine learning based on the Bayesian Belief Network for your selected monitoring targets. The engine calculates an anomaly probability and requests the creation of a new incident ticket.

  • ML model
  • Scored Anomaly
  • Alert rule based
  • Auto Incident ticket


Our incident manager takes care of incidents with system-generated or individually created actions or metrics. It manages severity, the status of the incident, and the resources in-charge of it while also helping system investigation.

  • Auto Ticketing
  • Trigger Redimation
  • Auto Attachemnt
  • Feedback


When the Anomaly Detector creates an incident ticket, the Resolution Advisor provides pre-defined actions based on alerts by monitoring target. These recommended actions are registered in the ticket. You can also pre-configure automatically executed actions that will be run as soon as they are attached to the ticket. And for the auto-execution we have our trusted sudoRy!

  • Build Knowledge
  • Scored Anomaly
  • Operation Insight
  • Auto Incident ticket


Our trusted executor of Kubernetes APIs, Helm commands, and Http services within Kubernetes clusters! Sudory can automatically execute actions using pre-defined service templates. The Sudory server outside the Kubernetes clusters requests the service, using the Sudory client within the targeted Kubernetes cluster. Through templates in the service catalogue, service requests are reusable.

  • Task Executor
  • Automation
  • Scheduling


MetricOps on NexClipper

  • NexClipper Observabiity Integration
  • Alert Hub
  • Incident Management
  • Anomaly detctor
  • Resolution advisor
  • Autonomous Redimation


  • Alerts Pipeline
  • Anomaly detctor
  • Resolution advisor
  • KubeAIOps workflow

Alert Noise Reduction

  • Alert Hub
  • Mertic Pipeline
  • Alert noise evalutor


Phone: +1 310 844 7260
400 Continental Blvd 6F El Segundo, CA 90245
4F, 125 Wangsimni-ro, Seongdong-gu, Seoul 04766