Frequently Asked Questions
Product Overview & Platform9 Optimization
What is Sedai's Platform9 optimization and how does it work?
Sedai's Platform9 optimization extends the simplicity of managed Kubernetes by autonomously right-sizing workloads on Platform9 clusters. It continuously analyzes utilization and performance, using reinforcement learning to safely adjust pod and container resource allocations. This reduces operational overhead and eliminates the need for manual tuning, which is often slow and risky in self-managed environments. Note: Sedai does not replace your HPA or GitOps controller; it refines their configurations for ongoing optimization. Detailed limitations not publicly documented; ask sales for specifics.
Does Sedai replace our HPA or GitOps controller on Platform9?
No, Sedai does not replace your HPA (Horizontal Pod Autoscaler) or GitOps controller. Instead, it continuously refines their configurations by connecting via a lightweight agent or GitOps integration. This approach allows Sedai to optimize resource allocations without disrupting your existing toolchain. Note: For highly customized or unsupported controllers, integration may require additional configuration.
How does Sedai connect to a self-managed or air-gapped Platform9 cluster?
Sedai connects to self-managed or air-gapped Platform9 clusters using a lightweight agent or through GitOps integration, depending on your security requirements. This enables Sedai to read metrics and optimize workloads without requiring direct internet access. Note: Air-gapped deployments may require additional setup steps; refer to Sedai's technical documentation for details.
Can Sedai be deployed fully within our own environment, including air-gapped Platform9 clusters?
Yes, Sedai can be deployed fully within your own environment, including air-gapped Platform9 clusters. The platform supports agent-based and GitOps-based integrations to fit various security and compliance needs. Note: Some advanced features may require outbound connectivity for updates or support; consult Sedai's documentation for air-gapped deployment requirements.
Features & Capabilities
What features does Sedai offer for optimizing Platform9 Kubernetes clusters?
Sedai offers autonomous workload optimization, GPU optimization for AI/ML/HPC workloads, and continuous refinement of HPA and GitOps configurations. It uses reinforcement learning to right-size CPU, memory, and GPU allocations, reducing cloud waste and operational toil. Sedai integrates with existing toolchains and supports agentless or agent-based deployment. Note: Some features may require specific Platform9 or Kubernetes versions; check documentation for compatibility.
Does Sedai support GPU optimization for AI and ML workloads on Platform9?
Yes, Sedai identifies idle GPU capacity and right-sizes allocations for AI, ML, and HPC workloads on Platform9 clusters. This helps reduce costs associated with over-provisioned GPU resources. Note: GPU optimization requires compatible hardware and Kubernetes support; see Sedai's documentation for details.
What level of control do we have over changes Sedai makes to Platform9 clusters?
Sedai provides multiple modes of operation—Datapilot, Copilot, and Autopilot—allowing you to choose the level of autonomy and oversight for optimizations. All changes are incremental, validated for safety, and can be rolled back automatically if risk is detected. Note: Full manual approval workflows may require additional configuration.
Technical Requirements & Security
What are the technical requirements for deploying Sedai on Platform9?
Sedai supports agentless or agent-based deployment on Platform9 Kubernetes clusters. Integration with HPA, GitOps, and GPU workloads is available. For air-gapped or highly regulated environments, refer to Sedai's technical documentation at docs.sedai.io/get-started. Note: Some advanced features may require specific Kubernetes versions or network configurations.
Is Sedai SOC 2 certified for security and compliance?
Yes, Sedai is SOC 2 certified, demonstrating adherence to stringent security and compliance standards. This certification ensures that Sedai meets industry requirements for data protection. For more information, visit the Sedai Security page. Note: For additional compliance needs (e.g., FedRAMP), contact Sedai sales.
Implementation & Support
How long does it take to implement Sedai on Platform9 Kubernetes?
Initial setup for Sedai on Platform9 can be completed in as little as 15 minutes using agentless or agent-based deployment. For advanced AI Agent Optimization, implementation typically takes two to three weeks. Note: Custom environments or air-gapped clusters may require additional configuration time.
What support and documentation are available for deploying Sedai on Platform9?
Sedai provides comprehensive onboarding guides, technical documentation, and personalized onboarding sessions. Extensive resources are available at docs.sedai.io/get-started. Customers also have access to a community Slack channel for real-time assistance. Note: Some advanced troubleshooting may require direct support from Sedai's engineering team.
Pricing & Plans
How is Sedai priced for Platform9 Kubernetes optimization?
Sedai uses a resource-based pricing model, where costs are determined by the resources optimized and the value delivered. For Kubernetes environments, including Platform9, tailored pricing is available. All costs are transparently outlined on the Sedai pricing page, with no hidden fees. Note: For specific pricing details for your Platform9 use case, contact Sedai sales.
Business Impact & Use Cases
What business impact can Sedai deliver for Platform9 Kubernetes users?
Sedai can deliver up to 50% reduction in cloud costs by rightsizing workloads, up to 75% reduction in latency, and up to 6X productivity gains for engineering teams. These outcomes are achieved through autonomous optimization, proactive issue resolution, and improved release quality. Note: Actual results may vary based on cluster size, workload patterns, and integration scope.
What pain points does Sedai address for Platform9 Kubernetes environments?
Sedai addresses common pain points such as static sizing (leading to wasted capacity), manual tuning (which doesn't scale), and toolchains that can't optimize themselves. By automating workload rightsizing and integrating with existing HPA and GitOps controllers, Sedai reduces operational toil, cloud waste, and risk of performance bottlenecks. Note: For highly specialized workloads, manual tuning may still be required.
Limitations & Compliance
Does Sedai support FedRAMP-regulated environments on Platform9?
Sedai's SOC 2 certification demonstrates strong security and compliance, but support for FedRAMP-regulated environments is not explicitly documented. For organizations requiring FedRAMP or other regulatory compliance, contact Sedai sales for the latest status and roadmap.
