Blog

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.

We explore the key role of autoscaling in optimizing performance and cost within Kubernetes. Specifically, we delve into two critical autoscalers—Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA)—and shed light on their functionalities, benefits, and limitations.

A comprehensive overview of how Sedai addresses the challenge of cold starts through the implementation of autonomous concurrency. We explore the history of cold starts, their underlying causes, and their relationship with concurrency before showing how an AI based approach can resolve cold starts.

Learn strategies for enhanced system performance and reliability. See how observability metrics lay the foundation for autonomous systems, and how Palo Alto Networks approaches production metrics. Explore the potential problems associated with an overwhelming influx of data and metrics and how ML-driven correlation analysis can identify truly predictive metrics in an environment with multiple monitoring providers, multiple resource types, real-time data stress and predictive analytics. See how Palo Alto Network uses a multi-stage approach that includes a notice filter, aggregation, analysis, auto-remediation and notifications.

Datadog can be utilized to achieve autonomous cloud environments in just 15 minutes. We'll discuss the partnership between Sedai and DataDog, the integration they have developed, and how customers can leverage Datadog to automate manual processes. The goal is to guide customers towards a fully autonomous system. By following our guidance, you can transform your investment in Datadog into a self-driving engine. Stay tuned as we reveal the steps to unlock the full potential of Datadog and empower your cloud environments.

Today, we're going to explore the concept of running a software company without the need for an operations team or an SRE team. We'll discuss the evolving landscape of operations and its implications for developers. This discussion will be presented from a developer's perspective.

In this article, we will explore the world of optimization, with a special focus on serverless functions, particularly those leveraging Lambda. We will dive into how Sedai, a cutting-edge solution, helps in optimizing serverless functions. Sedai offers invaluable insights and tools that enable businesses to identify and address niche areas where optimization can make a significant impact.

In the past few years, we have seen a huge increase in adoption for Kubernetes. Kubernetes is an excellent platform, which provides you with all the facilities to fine-tune your application and run it the way you need. We at Sedai, use Kubernetes for deploying our applications along with surveillance and some other managed services from AWS. One question we get a lot is “Is there a need for another system or an autonomous system to manage Kubernetes?” Kubernetes is in fact a declarative system, an excellent one at which you can specify the needs of running your application, and Kubernetes will take care of the rest.

In this article, we delve into the reintroduction of autonomous infrastructure within the realm of large-scale systems, shedding light on the transformative changes that have taken place in infrastructure development over the past few decades. The insights shared here are the result of a collaborative effort involving multiple speakers who engaged in a thought-provoking discussion, comparing the distinctions between traditional monolithic systems and emerging paradigms such as Kubernetes and serverless environments. The focus lies on highlighting the advantages offered by enhanced flexibility and access to a diverse range of tools. As the conversation unfolds, we shift our attention towards the crucial role that autonomous systems play in this dynamic landscape and why relying solely on automation falls short of our aspirations. By embracing autonomy, we open up new possibilities to transcend the previously inevitable trade-offs that accompanied investment decisions, business choices, and market strategies. We reflect on the age-old dilemma where one must choose between something being good, fast, or cheap, realizing that achieving all three simultaneously has long been an elusive goal. However, our speakers firmly believe that with advancements in technology and the successful implementation of autonomy, these trade-offs can be overcome.

This article is my summary of an insightful panel discussion on the topic of Serverless versus Kubernetes. We will delve into the valuable perspectives shared by esteemed industry professionals during the panel. The discussion aims to shed light on the relationship between serverless architectures and Kubernetes, focusing on the logic behind utilizing Kubernetes for stateless applications. Through an exploration of different viewpoints, we aim to gain a better understanding of the merits and considerations surrounding these two approaches. You can watch the full video here.

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.

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.

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.

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.

Microservices architectures are rapidly becoming the new norm architects rely on when it comes to cloud computing. There has been a lot of debate whether it's best to shift left, or shift right. With Microservices, organizations must shift up, and manage their systems autonomously.

Sedai automatically discovers resources, intelligently analyzes traffic and performance metrics and continuously manages your production environments — without manual thresholds or human intervention. Try the autonomous cloud platform for free at sedai.io

We raised more than $15M in Series A funding led by Norwest Venture Partners. We are defining the future of SRE. Join us in the autonomous movement!