Videos

Guidance on how to optimize Kubernetes costs and scalability with an AI-powered autonomous copilot

Get an overview of Sedai's autonomous optimization for AWS ECS.

Learn best practices and how to autopilot cost and performance optimization for AWS ECS.

See how to optimize Kubernetes for cost and availability with Sedai's autonomous cloud management platform.

See how to optimize AWS Lambda for performance, cost and availability with Sedai's autonomous cloud management platform. This demo shows multiple features for AWS Lambda including Autonomous Optimization, Autonomous Concurrency, Autonomous Availability, Release Intelligence and Smart SLOs.

This workshop shows how to bring powerful autonomous optimization capabilities to cut Kubernetes cost by up to 50% with significantly less effort than conventional automation. We cover why Kubernetes costs are a major driver for company success, the challenges of optimizing Kubernetes, and show how autonomous cloud management powered by AI/ML can achieve greater savings than can be achieved by moving away from static rules and threshold-based automation to modern ML-based autonomous operations. Using Sedai, Kubernetes users can achieve gains at the workload, node and purchase options levels.

Sedai is an autonomous cloud platform. This video gives a brief explanation of Sedai, followed by a demo of Sedai's autonomous availability capability, and a short interview with Sri Shivananda, SVP & CTO at PayPal about where autonomous systems fit into the pyramid of low, medium and high value work

Sedai is able to detect and address potential downtime threats autonomously. In this short video, Gremlin's chaos engineering solution is used to inject a potential availability problem. Sedai detects and addresses the issue

How can autonomous improve cost, availability and productivity? Experiences from RingCentral, Uber, Cato, fabric, Belcorp, Freshworks, and Norwest Venture Partners are brought together here in this panel discussion from autocon/22.

Is there a right path between Serverless or Kubernetes? Leaders with backgrounds at Paylocity, Inflection/GoodHire, Intuit, AWS, Tasq and Uncorrelated Ventures discuss modern architecture alternatives and their pros and cons in this panel discussion from autocon/22. They make the case that serverless is underutilized at many companies given its operational advantages.

Engineering leaders with backgrounds at Paypal, Topcoder, eBay, Ironclad and Sedai discuss how to optimize cloud costs and performance with Autonomous Cloud, including how Autonomous complements Kubernetes by taking care of choosing configuration, and enables teams to focus on applications not infrastructure.

Engineering & cloud experts from Paylocity, Palo Alto Networks, fabric and Norwest Venture Partners discuss the drivers behind the growth of autonomous cloud management in this panel discussion from autocon/22.

Siddharth RAM, Ex-CTO Inflection/GoodHire & Intuit Fellow, explains why FCIs (Failed Customer Interactions) are a better way to monitor customer experience than traditional availability metrics. At Goodhire, FCIs were reduced from 3.2% to ~0% through a range of initiatives including an autonomous system.

Prakash Muppirala, EVP Platform at fabric, explains how fabric achieved a 48% reduction in latency and a 6.7x gain in their customer/SRE ratio by implementing an autonomous cloud platform.

Manu Thapar, CTO of Mastercard, explains Mastercard's ML-based fraud detection system and gives his point of view on why going 100% autonomous helps meet application SLAs.

Sedai CEO Suresh Mathew explains the difference between an autonomous and automated system, why autonomous systems are safer, why the industry should "shift up", and the four ages of IT operational management approaches leading to the "a8s-ops" age we are moving into.

Existing Datadog users can easily add autonomous management capabilities, improving the performance, cost and availability of their applications while avoiding the time & cost of using traditional automation.

Lambda extensions offer a way to easily integrate Lambda with your favorite monitoring, observability, security, and governance tools. Shridhar Pandey of AWS outlines why extensions were built, how they work, and how to get started with them in this video from autocon/22.

Cold starts are the #1 performance problem for Lambda users. Autonomous concurrency provides a solution with fewer cold starts than warmup strategies, and lower cost than provisioned concurrency. Sedai VP of ML, Nikhil Gopinath explains the underlying challenge of cold starts and presents the autonomous concurrency solution and compares it to traditional solutions.

Combining serverless with autonomous is a path to NoOps. From a developer's perspective serverless expert Sam Williams of Complete Coding outlines the history of operations, the impact of serverless and the benefits of autonomous in a serverless environment.

This video covers the evolution of systems from mechanized to automatic to autonomous, and the five advantages of autonomous systems in this kickoff to the technical track of autocon/22.

Observability is a building block for autonomous systems. This session covers the problem with too many metrics, how Palo Alto Networks solved this problem and Sedai's approach to metric prioritization.

Kubernetes utilization is typically poor with only 20-45% of requested resources used. Kubernetes optimizations must meet application demands and minimizing idle resources. This video covers the potential to optimize at the pods and node/cluster level. The capabilities and limitations of Kubernetes HPA, VPA and Cluster Autoscaler are covered here.

In this session AWS container hero Dijeesh Padinharethil covers autoscaling in Kubernetes, cluster autoscaling, scaling tools and event-driven autoscaling.

Managing Kubernetes with current automated approaches makes it almost impossible to achieve optimal cost, performance and availability. Autonomous offers a path out of this complexity. Autonomous optimization and availability are outlined, the architecture used by Sedai to provide this capability, and how safety is addressed.

Most serverless functions are unoptimized resulting in unnecessary latency and/or cost. Serverless functions can be optimized for performance, cost or a balanced strategy without human effort using autonomous systems.