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Learn about five key differences between autonomous and traditional automated systems. These include 1. Intelligent Decision-Making, 2. Dynamic Adaptability and Context-Awareness, 3. Self-Correcting Capability, 4. Complexity and 5. Scalability and Limited Human Oversight.

KnowBe4's autonomous journey has led to 98% of their Amazon. ECS and Lambda services running autonomously, with a 27% cost reduction and over 1,100 autonomous actions in the past 3 months. KnowBe4 fhad aced an optimization challenge with their Amazon Elastic Container Service (ECS) services, leading them to adopt Sedai's autonomous optimization to reduce toil for engineers and improve efficiency. KnowBe4 implemented a three-part approach (Crawl, Walk, Run) to gradually adopt autonomous optimization, resulting in significant cost savings and performance gains.

In this post, we will cover how to master Amazon ECS optimization using autonomous techniques. The autonomous approach can help with both ECS cost optimization and performance optimization.

In this article which serves as a summary of a collaborative panel discussion on monitoring and optimization strategies for cloud-based systems, we delve into the exciting advancements in this rapidly evolving landscape. We focus on crucial aspects such as cost management, performance optimization, and the emergence of autonomous solutions. Join us as we explore insights from the panelists and gain valuable perspectives on these topics. You can watch the full video here.

To optimize AWS ECS costs, focus on workload optimization by right-sizing resources, configuring efficient infrastructure with the appropriate instance types and mix, and making strategic purchasing decisions such as leveraging Savings Plans or Reserved Instances.

Is Tesla known for building the safest car on earth? They made an interesting discovery regarding task division. By examining all operations, they identified two distinct segments: One that can be effectively performed by machines and another that is better suited for humans. When the first segment is completely handled by machines without any human intervention, it is referred to as an autonomous system. This means that the system operates autonomously.

In this article, we'll be exploring an important topic: Lambda Extensions. These extensions are a powerful feature that was introduced last year. So, let's jump straight into it and understand the details of this valuable addition.

This article, based on the kickoff session from the autocon/22 conference, sets the stage for the event by outlining the significance of autonomous systems in cloud management. It explores how autonomous systems have revolutionized various industries and highlights their transformative potential.

Cloud cost and time savings drive the "above the surface" benefits of autonomous cloud management, but "below the surface" benefits including customer experience gains, release quality, employee retention and adaptability contribute to the overall value realized from autonomous cloud management.

Your autonomous business case should consider cloud cost savings, performance gains, availability improvements and time savings. Operations teams looking to adopt autonomous optimization need to show business value to get buy-in from leadership.

Learn how to seamlessly integrate Infrastructure as Code (IaC) with autonomous systems for cloud cost & resource optimization. This guide explores strategies for maintaining DevOps best practices while leveraging AI-driven optimization in CI/CD pipelines, ensuring your IaC remains accurate and your cloud costs are minimized. Ci/CD tools mentioned include Jenkins, Argo CD, Circle CI and GitLab CD. IaC tools mentioned include Terraform, Ansible, AWS Cloud Development Kit (CDK), Puppet and Helm. A case study showing how Gitlab IaC is integrated with Sedai's autonomous optimization capability at KnowBe4, a leading cybersecurity platform is included.

Discover how Sedai brought AI-driven autonomous cloud management to SREcon23 Americas. Learn about our platform demos, magician entertainment, and special offers for conference attendees. Explore how Sedai can help SREs optimize resources, reduce costs, and prevent downtime

Hello everyone! In this article, we will discuss seven effective strategies to optimize costs for AWS ECS. This discussion is based on the joint webinar between Sedai and AWS, which you can watch here.

It's been a fantastic year for Sedai, and we're proud to share our year-end accomplishments with you in five areas.

Sedai CEO Suresh Mathew shares eight predictions for 2023 and explains what they could mean for the adoption of autonomous cloud management.

Our Datadog Dash 2022 survey found cost is the #1 challenge for Datadog users, that autonomous systems are on average expected to provide a 48% gain on these challenges, and that Datadog users are well down the path of running modern apps with 77% using containers and 36% using serverless.

Sedai is a launch partner for AWS for their new Telemetry API for AWS Lambda. Sedai uses the telemetry API to improve availability for Lambda users of Sedai’s autonomous cloud management platform by providing additional insights and signals on Lambda functions on a cost-effective basis.

Sedai has been accepted into the AWS Independent Software Vendor (ISV) Accelerate Program.

Walkthrough of Sedai's autonomous optimization for ECS showing ECS service optimization, instance optimization, and purchasing levers. An autonomous cloud-management platform designed to optimize performance, cost, and availability for your ECS (Elastic Container Service) clusters.

fabric is a modular and headless platform tailored for modern eCommerce applications, with a primary focus on Software-as-a-Service (SaaS) solutions. fabric's mission is to empower retailers to streamline their commerce operations across various channels by creating custom functions through interconnected components. Gone are the days of relying solely on prepackaged systems; they embrace a more flexible and adaptable approach to meet the evolving needs of their clients.

Manu Thapar, CTO of Mastercard discusses the application of AI/ML to credit card fraud detection systems and how moving from a rules based system to a system that can self-learn and operate autonomously was key to successfully keeping up with constantly changing credit card fraud risks. Manu spoke at autocon, Sedai's annual conference focused on autonomous cloud management.

In today's fast-paced and demanding IT world, professionals and individuals face increasing pressure to do more with less time for evaluation and beta testing. The focus on delivering value to customers is often overshadowed by flashy marketing gimmicks. However, customer satisfaction is crucial for business success. The realm of artificial intelligence (AI) and machine learning (ML) has shifted towards practical applications and collaborative autonomy, where autonomous systems work together with humans. This article delves into the practical aspects of autonomy, discussing the challenges and benefits of implementing autonomous cloud management in various industries. It highlights insights from industry experts on the transition to autonomy, practical approaches, building trust, and managing expectations. The article showcases real-world examples of organizations such as Palo Alto Networks, Paylocity, and Fabric that have successfully implemented autonomous systems to enhance productivity, efficiency, and customer satisfaction.