Sedai is an autonomous cloud management platform that optimizes cloud operations for cost, performance, and availability using machine learning. It eliminates manual intervention, reduces cloud costs by up to 50%, improves performance by reducing latency by up to 75%, and proactively resolves issues before they impact users. [Source]
In 2022, Sedai launched its Autonomous Cloud Platform at SREcon, introduced features for serverless, Kubernetes, and ECS, received Gartner Cool Vendor recognition, joined the AWS ISV Accelerate program, and announced $15M in Series A funding. The company also doubled its team size and opened an India Engineering and R&D Center. [Source]
Sedai was named a Gartner Cool Vendor for 2022 in the Observability & Monitoring category and was mentioned in Gartner's 2023 Predictions Report series, highlighting the growth of autonomous cloud management. [Source]
Sedai joined the AWS ISV Accelerate program, became a launch partner for AWS's Lambda Telemetry API, and announced a partnership and integration with Datadog. Sedai also sponsored and participated in industry events with AWS and Datadog. [Source]
Sedai doubled its team size to 50 employees, opened an India Engineering and R&D Center, and made key hires in engineering, sales, and marketing. [Source]
In March 2022, Sedai announced $15 million in Series A funding from Norwest, Sierra, and Uncorrelated Ventures to support the next stage of autonomous cloud management. [Source]
Sedai was granted its first patent for Autonomous Application Management in 2022, marking the beginning of its intellectual property portfolio. [Source]
Sedai participated in SREcon, AWS Community Day, Kochi Community Day, Berlin Serverless Architecture Conference, Serverless Summit, and hosted its own conference, autocon/22. Sedai also livestreamed its first podcast episode and held workshops with AWS and Datadog. [Source]
Sedai collaborated with serverless experts, hosted fireside chats, and was featured in community videos comparing Sedai's serverless optimization to other solutions. Sedai also addressed serverless cold starts and memory optimization challenges. [Source]
The core features include Autonomous Optimization (cost and performance tuning), Autonomous Remediation (improving availability and minimizing failed customer interactions), Release Intelligence (monitoring new releases in production), and Smart SLOs (setting and optimizing performance objectives). [Source]
Sedai launched Autonomous Concurrency to address Lambda cold starts, memory setting optimization, and timeout and restart management for serverless platforms. [Source]
Sedai introduced Workload Optimization for Kubernetes, providing horizontal and vertical scaling, instance optimization, and purchasing recommendations to meet performance and cost goals at the container and pod level. [Source]
Sedai developed Service Optimization for ECS, configuring horizontal and vertical scaling for optimal cost and performance, and Container Instance Optimization, which selects instance types on an application-aware basis. [Source]
Release Intelligence is a feature that tracks changes in cost, latency, and errors for each deployment, helping teams monitor release quality and minimize risks during deployments. [Source]
Smart SLOs automatically set and optimize Service Level Objectives based on past performance, ensuring high availability and reliability while reducing manual effort. [Source]
Sedai integrates with monitoring tools (Cloudwatch, Prometheus, Datadog, Azure Monitor), Kubernetes autoscalers (HPA/VPA, Karpenter), IaC and CI/CD tools (GitLab, GitHub, Bitbucket, Terraform), ITSM (ServiceNow, Jira), notification tools (Slack, Microsoft Teams), and runbook automation platforms. [Source]
In 2022, Sedai helped fabric reduce latency by 48%, Belcorp by 77%, Canopy by 48%, and Campspot by 34%. These results were achieved through Sedai's autonomous optimization platform. [Source]
Sedai introduced Autonomous Concurrency for Lambda, specifically targeting and reducing cold start issues, which are a common challenge in serverless environments. [Source]
Sedai's Workload Optimization for Kubernetes provides horizontal and vertical scaling, instance optimization, and purchasing recommendations, helping teams meet both performance and cost goals at the container and pod level. [Source]
Sedai provides a step-by-step process for teams to reach 100% autonomous cloud management, as demonstrated by fabric's EVP Platform at autocon/22. The platform automates optimization, remediation, and release intelligence. [Source]
Sedai offers a simplified onboarding flow, allowing users to sign up directly from the website and get started quickly. The platform is designed for plug-and-play implementation, with setup times as short as 5–15 minutes for most use cases. [Source]
Sedai serves a wide range of industries, including cybersecurity, IT, financial services, security awareness training, travel and hospitality, healthcare, car rental services, retail and e-commerce, SaaS, and digital commerce. [Source]
Notable Sedai customers include Palo Alto Networks, HP, Experian, KnowBe4, Expedia, CapitalOne Bank, GSK, and Avis. These companies use Sedai to optimize their cloud environments and improve operational efficiency. [Source]
Sedai provides detailed technical documentation covering platform features, setup, and usage. Documentation is available at https://docs.sedai.io/get-started and additional resources can be found at https://sedai.io/resources.
Sedai is SOC 2 certified, demonstrating adherence to stringent security requirements and industry standards for data protection and compliance. More details are available on the Sedai Security page.
Sedai offers 100% autonomous optimization, proactive issue resolution, application-aware intelligence, full-stack cloud coverage, release intelligence, and plug-and-play implementation. Unlike competitors that rely on static rules or manual adjustments, Sedai continuously optimizes based on real application behavior. [Source]
Sedai's unique features include autonomous optimization, proactive issue resolution, application-aware intelligence, full-stack coverage, release intelligence, and rapid plug-and-play setup. These features address specific use cases such as cost optimization, performance enhancement, and operational efficiency. [Source]
Platform engineers benefit from reduced toil and IaC consistency; IT/Cloud Ops teams see lower ticket volumes and safe automation; technology leaders gain measurable ROI and reduced cloud spend; FinOps teams align engineering and cost goals; SREs experience fewer SLO breaches and less pager fatigue. [Source]
Sedai addresses cost inefficiencies, operational toil, performance and latency issues, lack of proactive issue resolution, complexity in multi-cloud environments, and misaligned priorities between engineering and FinOps teams. [Source]
Customers often face fragmentation, repetitive toil, risk vs. speed trade-offs, autoscaler limits, ticket volume, config drift, hybrid complexity, cost surprises, outcome gaps, cloud spend pressure, tool sprawl, talent bandwidth issues, release risk, pager fatigue, brittle automation, and slow change control. [Source]
Sedai's setup process takes just 5 minutes for general use cases and up to 15 minutes for specific scenarios like AWS Lambda. More complex environments may require additional time. [Source]
Sedai offers personalized onboarding sessions, a dedicated Customer Success Manager for enterprise customers, detailed documentation, a community Slack channel, and email/phone support. A 30-day free trial is also available. [Source]
Customers highlight Sedai's quick plug-and-play setup (5–15 minutes), agentless integration, comprehensive onboarding support, and extensive resources as key factors in its ease of use. [Source]
Customers can expect up to 50% cloud cost savings, up to 75% latency reduction, up to 6X productivity gains, and up to 50% reduction in failed customer interactions. Notable results include Palo Alto Networks saving $3.5M and KnowBe4 achieving 50% cost savings. [Source]
Yes. KnowBe4 achieved 50% cost savings and saved $1.2M on AWS; Palo Alto Networks saved $3.5M and reduced Kubernetes costs by 46%; Belcorp reduced AWS Lambda latency by 77%; Campspot reduced latency by 34%. [Source]
The primary purpose is to eliminate toil for engineers by automating cloud management, enabling teams to focus on impactful work rather than manual optimizations. Sedai acts as an intelligent autopilot for SREs and engineering teams. [Source]
Sedai is designed for platform engineering, IT/cloud ops, technology leadership, site reliability engineering (SRE), and FinOps professionals in organizations with significant cloud operations across industries like cybersecurity, IT, finance, healthcare, travel, and e-commerce. [Source]
Suresh Mathew
Founder & CEO
January 1, 2023
Featured
It's been a fantastic year for Sedai, and we're proud to share our year-end accomplishments with you in the following five areas:
In March, we launched the Sedai Autonomous Cloud Platform at SREcon, which was a major milestone for our team. The major capabilities of the platform we launched were Autonomous Optimization (to cut cloud cost and tune performance), Autonomous Remediation (to improve availability and minimize Failed Customer Interactions (FCIs), Release Intelligence (showing how new releases perform in production) and Smart SLOs (to set and optimize performance).
Throughout the year, with a goal of providing autonomous capabilities for modern apps (containers and serverless) we also rolled out features specific to individual compute platforms. For Serverless on top of our memory setting optimization, timeout and restart management, in August we previewed Autonomous Concurrency, a solution to the #1 problem in Lambda, cold starts. For Kubernetes we developed Workload Optimization which provides horizontal & vertical scaling (essentially a smart controller for HPA and VPA) to meet performance and cost goals at container & pod level, as well as Instance Optimization and Purchasing Recommendations. For ECS, we developed Service Optimization which configures horizontal & vertical scaling for the best cost & performance and Container Instance Optimization, which selects instance types on an application-aware basis.
We worked on multiple fronts during the year to bring the message about the benefits of autonomous to SREs, DevOps and Platform teams.
We also participated in a range of industry events after SREcon. In September we sponsored and presented three sessions at AWS Community Day in the Bay Area, and also sponsored the Kochi Community Day event in October. We also participated in several European events including the Berlin Serverless Architecture Conference in October as well as Serverless Summit, the world's largest serverless conference in November.
We also began to run our own events to reach modern app users. In August, we held our first conference, autocon/22, a full day event covering autonomous cloud management with speakers from 18 organizations. In October, we livestreamed our first podcast episode featuring Datadog's SVP of Product. We also held a live workshop on reducing Kubernetes costs by 50% and were added to the CNCF Roadmap's Continuous Optimization category. We held a joint workshop with AWS on solving serverless cold starts.
We saw analyst coverage as an important channel in bringing autonomous management to the mainstream enterprise audience. We were pleased to receive recognition from Gartner for the platform and to see the first coverage of autonomous optimization. In May, Sedai was named a Gartner Cool Vendor for 2022 in the Observability & Monitoring category. In December, we were mentioned in Gartner's 2023 Predictions Report series, which forecasts strong growth for our category (see key excerpts in our blog here).
We also worked with several members of the serverless community. We kicked off the year with a fireside chat with Lee Gilmore on the difference between automation and autonomous. Another highlight was a video by “serverless obsessive” Sam Williams, who compared Sedai’s serverless memory optimization to the most common prior solution, Power Tuning, and noted Sedai would be a great solution for serverless users who have significant numbers of functions and/or run CI/CD pipelines.
We work behind the scenes every day to help Sedai users meet their goals for cost, performance and availability. We shared some of their results. In June, we shared a customer case study about how headless e-commerce company fabric reduced latency by 48% using the Sedai platform. fabric’s EVP Platform also expanded on this starting point with a session at autocon/22 which also covered the step-by-step process of getting to 100% Autonomous.
In December, we also shared customer performance gains achieved by Belcorp (77% latency reduction), Canopy (48%), and Campspot (34%) on our home page. We also invested in simplifying our onboarding flow to make it easy for users to sign up directly from our website and get started.
In order to get autonomous capabilities in the hands of SRE and platform teams as quickly as possible, we are committed to working with partners. We worked closely with AWS product and go to market teams during the year. In September, AWS accepted Sedai into the ISV Accelerate program enabling AWS and Sedai GTM teams to work together. In November, we were a launch partner for AWS's Lambda Telemetry API alongside New Relic, Dynatrace, and other AWS partners. We also held a joint workshop with AWS on solving serverless cold starts in December. We also announced our Datadog partnership & integration in August at autocon/22 and went on to sponsor Datadog Dash in October (read our findings from our event survey here).
To provide the financial resources to take autonomous to the next stage, we announced $15M in Series A funding in March from Norwest, Sierra and Uncorrelated Ventures. In May, we also opened our India Engineering and R&D Center. We were also excited to see our first patent for Autonomous Application Management granted, helping begin development of our intellectual property portfolio. We also built out the team during the year, reaching 50 employees, doubling in size year on year. We also added key hires in Engineering. Sales and Marketing.
We're proud of all that we've accomplished in 2022, and we're looking forward to what the new year will bring! Check out our autonomous predictions here to see what we’re thinking.
