Watch the best sessions from autocon/22, the autonomous cloud conference ūüöÄ

Autonomous Kubernetes Management

Sedai autonomously improves your application's cost, performance and availability in production using machine learning, without manual thresholds or human intervention. It's like adding a team of SREs looking for improvements on your behalf, 24/7




Cut Kubernetes Costs by >50%

Reduce Kubernetes costs by deploying an autonomous system to rightsize applications, optimize nodes,  and maximize purchasing options. Using an autonomous platform gets savings faster while eliminating manual effort

Right size applications

Discover and implement the lowest cost configuration leveraging Sedai's  application behavior & seasonality insights, using both horizontal and vertical scaling

Optimize nodes

Optimize the mix of instance types and node grouping that minimizes cost while meeting application performance needs

Maximize purchase options

Optimizes the instance purchasing options provided by public cloud providers including spot and reserved instances


Optimize Kubernetes performance

Use an autonomous system to reduce Kubernetes latency by up to 95% at a service level by finding the optimal parameters for memory and CPU, and placing the application in the optimal node group.

Auto-discover the highest performing configuration

Reinforcement learning is used to discover the best memory & CPU combinations for your application; no more pre-release guesswork

Predictive scaling based on seasonality

Seasonality predictions based on traffic patterns are used to scale proactively reducing performance risks

Balance app performance and cost

Set priorities to maximize performance, balance performance and cost or minimize cost


Improve Kubernetes availability

Sedai also watches to see if services are experiencing common problems such as high CPU usage resulting in throttling, or out of memory errors Sedai safely acts in production on your behalf to ensure your resources avoid availability issues and run optimally at all times.


Prevents issues before they impact your customers with early detection at the onset of symptoms.

Escalation based remediation

Sedai attempts multiple remediations based on the learning from past application behavior

Safety checks built in

Sedai safely acts in production on your behalf to ensure your resources avoid availability issues and run optimally at all times


Cut Operational Toil

Spend more time on value added tasks and scale applications faster than the operations team as  Sedai autonomously takes care of tasks on behalf of the operations team

End alert overload

Overcome the stress & chaos of alert fatigue and reactive troubleshooting by leveraging an autonomous co-pilot who takes on operations tasks on behalf of the team

Delegate routine activities

Sedai performs thousands of optimization and remediation tasks daily that would normally require human intervention

Focus on higher value tasks

Operators can be less concerned with low level details and instead focus on new deployments, site enhancements and other priorities


Accelerate Release Cycles

Get intelligence on how each release performed and share the insights with your team to improve how they code and raise release quality and velocity

Release scorecards

At-a-glance understanding of code deployments based on detection, analysis and grading of performance so you can release confidently.

Trend analysis

Compares releases’ saturation, duration, and error metrics for an overview of how code has evolved between releases.

Improve configurations

Evaluates how code changes between releases and recommends & acts on configuration changes to optimize performance.


“Having autonomous managing applications complements Kubernetes capabilities. Kubernetes is great for managing clusters but it can't solve the problem of managing complex applications by itself"

Kumar Rethi

CTO, Topcoder & ex-eBay, speaking at autocon/22 (watch here)

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