When in the course of technological evolution, it becomes necessary for engineers to break free from repetitive tasks and embrace innovation, a new approach is required. We hold these truths to be self-evident that all engineers deserve the right to meaningful, creative, and innovative work, free from the burdens of toil. Join the movement towards efficiency and freedom from toil.

Discover why many organizations choose Reservation Plans over Savings Plans in cloud financial optimization. Explore the benefits of cost predictability, higher discounts, enterprise agreements, and accounting advantages, even with minimal additional costs. Learn how Reservation Plans can impact your financial strategy and cloud usage effectively.

In a recent survey conducted by McKinsey with IT directors and IT organizations, one of the key takeaways was that FinOps is one of the most important and emerging practices that they have been adopting throughout their IT and technology organizations in the last couple of years.

While each organization’s approach is different let’s consider a journey through four stages of maturity from high-touch, manual processes to sophisticated, intelligent systems that enhance performance and cost-efficiency with minimal human intervention.

The development of autonomous vehicles as a solution to vehicle accidents provides parallels for the development of autonomous cloud management as a path to incident reduction. Explore key lessons on reducing human error, leveraging AI, incremental progress, phased rollouts, and building user trust to enhance system reliability and safety.

Traditional manual and rule-based automated systems struggle to keep up with the complexity of managing cloud environments leads to persistent issues with cost control and performance optimization. It's time to take the next step in cloud management—AI-driven autonomous cloud management platforms are solving the complexity challenge in modern cloud environments.

Amazon Simple Storage Service (Amazon S3) is a widely-used object storage service that offers industry-leading scalability, data availability, security, and performance. S3 has a variety of storage classes.

Key considerations when choosing Amazon S3 storage class include access frequency, performance (retrieval time), availability, durability, and cost. S3 Standard is ideal for frequently accessed data. S3 Standard-IA and One Zone-IA are cost-effective for infrequent access. Glacier, Glacier Flexible Retrieval, and Glacier Deep Archive offer substantial cost savings for long-term archival storage. Intelligent Tiering is beneficial for unpredictable access patterns, automating cost savings by transitioning data between tiers.

Discover AWS pricing models for ECS in this guide, covering On-Demand, Reserved Instances, Savings Plans, and Spot Instances. Learn how On-Demand instances offer a flexible pay-as-you-go model for fluctuating workloads, and explore the long-term discounts available with Reserved Instances and Savings Plans for predictable usage. Delve into Spot Instances, which provide steep discounts for fault-tolerant or stateless applications. This article also explains how to optimize costs and ensure availability by mixing On-Demand and Spot capacities, with a focus on ECS’s capabilities in automating Spot Instance lifecycle management and integrating with AWS Auto Scaling Groups. Perfect for optimizing your AWS spending strategy.

Explore four essential engineering optimizations for Amazon ECS - rightsizing, task placement, autoscaling, and scheduled shutdowns. Learn how to enhance ECS service performance and reduce costs with real-world examples of CPU optimization, memory efficiency, and task management. Discover the benefits of AWS Graviton instances for cost-efficiency and performance, strategic deployment through task placement, and cost savings with larger instance types. Understand how autoscaling adapts to traffic changes and how scheduled resource shutdowns during off-peak hours can further reduce expenses. Optimize your AWS environment for better performance and cost-effectiveness with these proven strategies.

Successful ECS optimization impacts financial performance including both cost savings through reduced overprovisioning and discount management, and revenue gains from application performance and latency gains. While ECS offers a range of controls and strategies, including rightsizing and utilizing spot instances, implementation is complex when managed with manual methods.

In this post we'll take a look at ECS vs other Amazon Compute models and some key concepts in Amazon ECS.

In environments where applications are not suitable for microservices architectures, rightsizing and in particular vertical scaling becomes a critical strategy to achieve cost-effective operations while meeting performance requirements.

In environments where applications are not suitable for microservices architectures, rightsizing and in particular vertical scaling becomes a critical strategy to achieve cost-effective operations while meeting performance requirements.

A technology company achieved a 25% cost saving across 1,400 Kubernetes services with Sedai's autonomous optimization technology by rightsizing Dev/Test environments. AI-powered autonomous optimization optimized Kubernetes requests and limits in Kubernetes workloads and optimized instance count and type. An AI driven approach was more effective than manual optimization, especially given the small spend on each individual service. Optimization is one key capability of Sedai's autonomous cloud management platform.

Keeping Amazon ECS development & testing environments workloads running when they're not actively used can lead to considerable expenses for teams.Implementing scheduled shutdowns of Amazon ECS cloud resources when not in use can lead to cloud cost savings with relatively little implementation effort.Four ways to achieve shutdowns for Amazon ECS include (1) manual shutdowns, (2) Lambda functions, (3) Cloudwatch templates and (4) schedules inside a platform such as Sedai.

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.

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.

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.

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.

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.

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.

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 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.

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.

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 will explore the reasons behind our adoption of Kubernetes, delve into the concept of autoscaling within Kubernetes, and specifically focus on cluster autoscaling. Throughout this article, we will examine the various tools that enable cluster autoscaling configuration

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 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.

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.

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.

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.

Failed Customer Interactions (FCIs) are a valuable metric measuring customer experience that accounts for the declining usefulness of time based measures such as uptime in microservice based architectures. It provides valuable insights into system availability from a customer-centric standpoint.

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.

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.

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.

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.

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.

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.

Performance & latency matter for B2B SaaS Applications, impacting user experience and ultimately retention and revenue.

We are proud to sponsor the DevOps Institute 2022 State of SRE report.

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!

From ensuring the highest levels of uptime availability to optimizing your code releases and cloud costs, learn how Sedai's autonomous cloud platform can become a staple in your SRE tool kit.

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

Announcing the availability of the Sedai Autonomous Cloud Management Platform. We welcome you to sign up for a free Sedai account and experience the future of site reliability engineering — autonomous.

Div Shekhar, AWS Solution Architect, shares how AWS customers Coca-Cola, Nielsen Marketing Cloud and Lego are driving agility, increasing performance and improving security with a serverless strategy. Suresh Mathew, founder of Sedai, also shares the benefits of continuous and autonomous management of Lambda environments.

Today we announced our Series A funding, and we are thrilled to announce we are opening a new product engineering division in Thiruvananthapuram to advance the autonomous movement.

Get all the benefits of serverless with provisioned concurrency when it’s intelligently managed for you. Sedai will adjust based on your seasonality, dependencies, traffic, and anything else it is seeing in the platform.

While the shift from monolith to microservices changed the game in regard to deployments and team velocity, it simultaneously introduced the monotony of daily repetitive work and manual tasks. SREs and DevOps now need to entirely rethink how teams manage their applications on a day-to-day basis.

In this post, we’ll take a look at another piece of the microservices puzzle — proactive actions and the role they can and should play in keeping your business operations running smoothly.

With so many microservices, how can DevOps teams effectively manage, measure, and take appropriate action on SLOs?

Managing and maintaining all of the microservices in your cloud environment can be costly, tedious, and time-consuming. But what if there were some way to simplify cloud management with always-learning, always-available technology?

How can DevOps teams continue to ensure release quality when releases are constantly occurring?