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Onboarding requires permission to access your cloud resources as well as a monitoring source to inform Sedai's analysis and build models. Sedai uses Identity and Access Management (IAM) to securely connect to cloud accounts without an agent, however for Kubernetes clusters we recommend integrating via Sedai's Smart Agent.

Cloud Access

Sedai is thoughtfully engineered to help your team save time by safely acting on your behalf. The system will only act when given permission, which is controlled via three different modes: Datapilot, Copilot, and Autopilot (learn more).

While you control permissions within Sedai, these permissions are ultimately defined during the integration process. You can choose to provide either read-only or read-write access:

• Read-only: Allows Sedai to analyze monitoring data, however the system can only predict low-confidence opportunities for cost/performance savings and flag potential availability issues. With read-only access, Sedai can only operate in Datapilot mode. It's important to note that read-only access significantly limits Sedai's features and capabilities. We recommend a Crawl-Walk-Run approach (learn more) to build confidence with the system and gradually allow Sedai to make changes to your resources.

• Read-write: Allows Sedai to build advanced models based on reinforcement learning for maximum savings; the system will ask for your permission to make changes on your behalf. With read-write access, Sedai can operate in any mode. It's important to note that by default all integrations run in Datapilot mode, which simulates read-only access. Sedai will ask for permission to act in Copilot mode, or act autonomously in Autopilot mode. You can update modes from the Settings page (learn more).

We recommend connecting dev resources first to explore Sedai and its different modes. However, keep in mind that dev resources typically have low usage and traffic, both of which inform Sedai's machine learning (ML) models. As a result, Sedai's opportunities, recommendations and savings for these types of resources will not be significant. To experience Sedai's full capabilities and see realistic savings, we recommend integrating a production account or cluster once you're ready.

Monitoring Data Access

Each cloud account or Kubernetes cluster integration requires read-only access to at least one monitoring data source in order to learn and analyze resource behavior. Sedai automatically imports the Golden Signals: latency, traffic, errors, and saturation.

Sedai builds monthly, weekly, and daily seasonality models for each of your resources. When you integrate monitoring data, the system will enhance its predictions over the course of 2 to 3 weeks. Alternatively, you can backfill metric data to expedite the learning process.

For Sedai to be most effective, it needs sufficient traffic and high quality metric data.

Requirements

Select from the list below to view connection requirements and access details:

AWS | ECS, EC2, Lambda, RDS, S3, EBS

Azure | Virtual Machines, Managed Disks

Kubernetes | Managed or self-hosted cluster

Monitoring | Datadog, Prometheus and more