Frequently Asked Questions

Product Features & Capabilities

What is Sedai's VMware Tanzu Optimization and how does it work?

Sedai's VMware Tanzu Optimization autonomously right-sizes both Kubernetes container requests and the underlying vSphere nodes running in Tanzu environments. It continuously analyzes utilization and performance, using reinforcement learning to safely adjust pod and container resource allocations, and right-sizes VMs serving as Kubernetes nodes. This approach reduces over-provisioning and manual tuning, helping teams optimize on-prem Kubernetes clusters as if they were cloud-native. Note: Detailed limitations for highly customized or unsupported environments are not publicly documented; ask sales for specifics.

Does Sedai replace our HPA or GitOps controller?

No, Sedai does not replace your HPA (Horizontal Pod Autoscaler) or GitOps controller. Instead, it refines their configurations continuously by connecting via a lightweight agent or GitOps integration, ensuring your existing toolchain remains in place while Sedai optimizes for cost and performance. Note: Sedai requires integration with your existing toolchain for optimal results; environments without HPA or GitOps may require additional setup.

How does Sedai connect to a self-managed or air-gapped cluster?

Sedai can connect to self-managed or air-gapped clusters using a lightweight agent or through GitOps integration, depending on your security and operational requirements. This allows Sedai to operate within highly controlled environments without requiring direct internet access. Note: Some advanced features may require outbound connectivity; consult technical documentation for air-gapped deployment specifics.

What level of control do we have over changes Sedai makes?

Sedai offers multiple modes of operation—Datapilot, Copilot, and Autopilot—allowing organizations to choose their preferred level of autonomy. You can review, approve, or automate changes based on your risk tolerance and governance requirements. All actions are safety-checked with continuous health verification and automatic rollbacks. Note: Full automation may not be suitable for organizations with strict manual change control policies.

Can Sedai be deployed fully within our own environment, including air-gapped?

Yes, Sedai supports deployment fully within your own environment, including air-gapped setups. The platform can be installed using agent-based or GitOps integration, ensuring compliance with strict security requirements. Note: Some integrations or features may require additional configuration in air-gapped environments; consult Sedai's technical documentation for details.

Does Sedai support FedRAMP-regulated environments?

Sedai is SOC 2 certified, demonstrating adherence to stringent security and compliance standards. However, detailed support for FedRAMP-regulated environments is not publicly documented; please contact Sedai sales or support for specifics regarding FedRAMP compliance. Note: Organizations with FedRAMP requirements should validate compatibility before deployment.

What types of workloads can Sedai optimize in VMware Tanzu environments?

Sedai optimizes both general Kubernetes workloads and specialized AI, ML, and HPC workloads running on VMware Tanzu. It right-sizes CPU, memory, and GPU allocations, identifying idle GPU capacity and adjusting resources to match real demand. Note: Optimization for highly specialized or unsupported workloads may require custom configuration; consult Sedai for details.

What integrations does Sedai support for VMware Tanzu optimization?

Sedai integrates with 12+ APMs (including Prometheus, Datadog, AWS CloudWatch, Azure Monitor, Google Cloud Monitoring), Kubernetes autoscalers (HPA/VPA, Karpenter), IaC and CI/CD tools (GitHub, GitLab, Bitbucket, Terraform), ITSM tools (ServiceNow, PagerDuty, Jira), notification platforms, and runbook automation. This ensures compatibility with most enterprise toolchains. Note: Some integrations may require additional setup in air-gapped or highly restricted environments.

Business Impact & Use Cases

What measurable business outcomes can Sedai deliver for VMware Tanzu users?

Sedai delivers up to 50% reduction in cloud costs by rightsizing workloads and eliminating waste, up to 75% reduction in application latency, and up to 6X productivity gains for engineering teams by automating repetitive tasks. These outcomes are based on real customer deployments and case studies. Note: Actual results may vary depending on workload and environment; detailed limitations not publicly documented.

Who can benefit from Sedai's VMware Tanzu optimization?

Sedai's VMware Tanzu optimization is designed for IT/cloud operations managers, FinOps leads, technology leaders (CTO, CIO, VP Engineering), SREs, and platform engineers in organizations running Kubernetes on vSphere. It is especially valuable for teams seeking to reduce operational toil, optimize resource utilization, and improve cost efficiency in on-prem or hybrid environments. Note: Organizations with highly unique or unsupported infrastructure may require custom evaluation.

What pain points does Sedai address for VMware Tanzu users?

Sedai addresses common pain points such as static sizing (leading to wasted capacity), manual tuning (which is slow and risky), and toolchains that do not optimize themselves. It automates rightsizing, reduces operational toil, and proactively resolves performance issues before they impact users. Note: Some pain points may persist in highly customized or unsupported environments; contact Sedai for a tailored assessment.

Implementation & Technical Requirements

How long does it take to implement Sedai for VMware Tanzu optimization?

Initial setup for Sedai 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: Complex or highly regulated environments may require additional time for integration and validation.

What technical documentation is available for deploying Sedai with VMware Tanzu?

Sedai provides comprehensive onboarding guides, Kubernetes optimization documentation, and GPU optimization instructions at docs.sedai.io/get-started. These resources support both standard and advanced deployments. Note: Some advanced topics may require direct support from Sedai's technical team.

Pricing & Plans

How is Sedai priced for VMware Tanzu optimization?

Sedai uses a resource-based pricing model, where costs are determined by the resources optimized and the value delivered. For Kubernetes environments, including VMware Tanzu, tailored pricing is available. All costs are transparently outlined on Sedai's pricing page. Note: For a custom quote or to discuss specific requirements, contact Sedai sales.

Security & Compliance

What security and compliance certifications does Sedai have?

Sedai is SOC 2 certified, demonstrating adherence to industry standards for data protection and compliance. For more details, visit Sedai's Security page. Note: Additional certifications or attestations may be required for certain regulated industries; contact Sedai for specifics.

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VMware Tanzu Optimization

Optimize Kubernetes Nodes Running on vSphere

Tanzu runs Kubernetes on top of vSphere infrastructure. Sedai optimizes both container-level requests and the underlying nodes — right-sizing the VMs serving as your Kubernetes nodes.

Cloud Resource UI - Tanzu.png
Background

On-Prem Kubernetes Wasn't Built to Tune Itself

Rightsizing self-managed clusters still relies on static estimates and manual effort — with no cloud elasticity to absorb the guesswork.

Static Sizing Wastes Capacity

Workloads run on worst-case CPU and memory requests that are set once and rarely revisited.

Manual Tuning Doesn't Scale

Rightsizing by hand is slow, guesswork-driven, and risky at the pace modern clusters change.

Toolchains Don't Optimize Themselves

HPA and GitOps controllers execute configs but can't tune themselves for cost or performance.

How We Help

Autonomous Workload Optimization

Sedai continuously analyzes utilization and performance to safely adjust pod and container resource allocations — using reinforcement learning to move workloads toward their optimal state.

GPU Optimization

For AI, ML, and HPC workloads, Sedai identifies idle GPU capacity and right-sizes allocations to match real demand, cutting a major cost driver.

Works With Your Existing Toolchain

Sedai doesn't replace HPA or your GitOps controller — it refines their configurations continuously, connecting via a lightweight agent or GitOps integration to fit your security needs.

Optimize On-Prem Kubernetes Like It's Cloud-Native.

Frequently Asked Questions