Question 1

How much does Sedai cost? How does pricing work?

Accepted Answer

Sedai uses a simple, volume-based pricing model, designed to ensure our customers achieve a positive ROI. For example, we charge 1 Sedai Billing Unit (SBU) for each vCPU that our platform manages. There are no overage penalties — if you exceed your monthly commitment, you simply pay the same rate for the extra usage. You can also adjust your commitment, as your needs change over time. Please book a demo to discuss our specific pricing options & discounts.

Question 2

How does Sedai make sure that optimizations never cause availability issues or degrade performance?

Accepted Answer

Safe optimization is our secret sauce. When Sedai identifies a potential cost or performance improvement, our platform makes that optimization in gradual steps, while continuously validating the impact of the change on your environment. For example, if Sedai determines it can lower the memory limit of a container without impacting performance, it won’t make a big change all at once, from say 12 to 4 GB. Instead, Sedai will gradually lower the memory to achieve maximum cost savings, until the exact point where performance is impacted.

Question 3

Which cloud providers does Sedai support? And what specific services can Sedai optimize?

Accepted Answer

Sedai supports the widest range of cloud services & on-prem workloads in our industry. This includes all the major cloud providers: AWS, Microsoft Azure, Google Cloud Platform, & Oracle Cloud Infrastructure. We’re the experts at optimizing Kubernetes — think EKS, AKS, & GKE, as well as on-prem, self-managed clusters. But our platform is unique in going way beyond K8s. Sedai also optimizes storage, data platforms, and AI/ML workloads. Check out our integrations page for the full list.

Question 4

What makes Sedai different from competitors? Why choose Sedai?

Accepted Answer

Only Sedai deeply understands how your applications behave, which is why our platform can optimize safely without causing performance or availability issues. Most tools either stop at recommendations or make risky changes based on surface-level metrics like CPU and memory utilization. Sedai goes deeper. Our patented ML models learn what your applications actually need by analyzing traffic patterns, dependencies, and golden signals like latency, errors, traffic, and saturation. That application-aware approach is what makes Sedai safe in production. To date, Sedai has performed more than 25 million optimizations with zero incidents.

Question 5

Will I be able to control Sedai’s actions? What if we want to roll back a change?

Accepted Answer

Sedai offers three operating modes that give you full control. In Datapilot mode, Sedai provides read-only recommendations, for you to implement. In Copilot mode, Sedai lets your team approve optimizations with one click, which Sedai then safely executes. Once you trust the platform, you can turn on Autopilot mode for resources or environments that you select, which enables Sedai to make optimizations autonomously. Across the board, Sedai enables your team to instantly roll back a change, schedule maintenance windows, & pause optimizations for any reason.

Question 6

How does Sedai integrate with our CI/CD pipeline? Does it lead to IaC drift?

Accepted Answer

Sedai is built to work alongside your existing CI/CD & GitOps workflows. Whenever Sedai optimizes a resource, it automatically opens a pull request in your Git repository reflecting the changes, keeping your IaC in sync across Terraform, Helm, & Kustomize. If your pipeline would otherwise overwrite Sedai's changes, our built-in overwrite protection (including a Kubernetes Admission Controller for GitOps tools like Argo CD or Flux) ensures optimizations are preserved, without disrupting your workflow. The result: full auditability, no hidden drift, & no rip-and-replace required.

Question 7

What is the difference between an “automated” system and a truly “autonomous” system, like Sedai?

Accepted Answer

This is the #1 most important question to ask when you’re evaluating any system that will make changes in production, without a human in the loop. Automated systems follow rigid instructions & scripts: “if X, then do Y.” Meanwhile, autonomous systems make decisions in real time to achieve big-picture goals, like upholding your SLO for latency when your website traffic spikes. Sedai is able to make these intelligent, contextual decisions, because our platform uses ML to understand the behavior of your apps. For a deeper answer, check out this in-depth blog.

Question 8

How do you assess Sedai’s impact on application performance? What metrics does the platform look at?

Accepted Answer

Sedai uses a combination of metrics to paint a full picture of your application behavior. This includes the “golden signals” of latency, traffic, errors, & saturation — as well as seasonal trends. Our platform integrates with your existing APM tools, and then it applies patented machine learning to develop a thorough understanding of each app & microservice.

Question 9

Do we have to install agents for Sedai to work?

Accepted Answer

Sedai offers both agent-based and agentless deployment options, dependent on your use case. For most cloud resources, Sedai connects securely via IAM permissions, without requiring an agent. However, for Kubernetes clusters, we recommend using our Smart Agent for deeper integration. You can also choose agentless setups for AKS, EKS, & GKE clusters, if you prefer. Onboarding is quick — typically just 15 minutes.

Question 10

I have a technical question that isn’t answered here. Now what?

Accepted Answer

You can try asking our website chatbot. But the best way is to schedule a meeting with our team. This will be a 30-minute conversation with a technical expert, who can address any question about how Sedai works with your infrastructure and tools.

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