Sedai was named in Gartner's inaugural Platform Engineering Hype Cycle (August 2024), recognized in two key categories: Autonomous Workload Optimization and AI Augmented Software Engineering. This highlights Sedai's leadership in autonomous cloud management and AI-driven software engineering. [Source]
Gartner's Hype Cycle for Platform Engineering identifies transformational technologies and trends shaping the future of platform engineering. It serves as a strategic reference for organizations building self-service internal developer platforms, with Sedai recognized for its autonomous and AI-augmented capabilities. [Source]
Platform engineering leaders at Palo Alto Networks, KnowBe4, and Experian were highlighted for their collaboration with Sedai. For example, Ramesh Nampelly (Palo Alto Networks) and Suresh Sangiah & Matthew Duren (KnowBe4) have shared their experiences with Sedai's autonomous optimization at industry events. [Source]
Gartner defines transformational technologies as those that enable new ways of doing business across industries, resulting in major shifts in industry dynamics. Sedai's autonomous optimization and AI-augmented engineering are considered transformational in this context. [Source]
The five key themes are: Developer enablement, Building applications that are secure by design, Effective and efficient software delivery, Navigating complexity of cloud-native architectures, and Supporting team structures. Sedai is recognized for its contributions to effective software delivery and AI-augmented engineering. [Source]
According to Gartner, both Autonomous Workload Optimization and AI Augmented Software Engineering are expected to reach the 'plateau of productivity' within 2-5 years, indicating rapid adoption in the industry. [Source]
For Sedai's use cases, Predictive AI is the most powerful approach, surpassing GenAI in prediction, forecasting, and decision intelligence capabilities for cloud optimization and software engineering. [Source]
Sedai offers three adoption modes: datapilot (observability), copilot (one-click optimizations), and autopilot (fully autonomous execution), allowing organizations to embrace autonomy at their own pace. [Source]
Autonomous optimization reduces manual toil, optimizes cloud infrastructure, and enables platform engineering teams to focus on innovation and reliability, as demonstrated by Sedai's customers like Palo Alto Networks and KnowBe4. [Source]
Sedai's autonomous cloud management platform uses machine learning to optimize cloud resources for cost, performance, and availability, eliminating manual intervention and enabling self-driving cloud operations. [Source]
Sedai offers autonomous optimization, proactive issue resolution, full-stack cloud coverage (AWS, Azure, GCP, Kubernetes), release intelligence, enterprise-grade governance, and multiple modes of operation (datapilot, copilot, autopilot). [Source]
Yes, Sedai integrates with monitoring tools (Cloudwatch, Prometheus, Datadog, Azure Monitor), Kubernetes autoscalers (HPA/VPA, Karpenter), IaC/CI/CD tools (GitLab, GitHub, Bitbucket, Terraform), ITSM (ServiceNow, Jira), notification tools (Slack, Microsoft Teams), and runbook automation platforms. [Source]
Sedai is SOC 2 certified, demonstrating adherence to stringent security and data protection standards. For more details, visit the Sedai Security page.
Sedai integrates with Infrastructure as Code (IaC), IT Service Management (ITSM), and compliance workflows, ensuring all changes are safe, validated, and auditable. [Source]
Sedai for S3 optimizes Amazon S3 costs by managing Intelligent-Tiering and Archive Access Tier selection, achieving up to 30% cost efficiency gain and 3X productivity gain by reducing manual S3 management effort. [Source]
Release Intelligence tracks changes in cost, latency, and errors for each deployment, improving release quality and minimizing risks during software deployments. [Source]
Sedai detects and resolves performance and availability issues before they impact users, reducing failed customer interactions by up to 50% and ensuring seamless operations. [Source]
Sedai offers three modes: Datapilot (observability), Copilot (one-click optimizations), and Autopilot (fully autonomous execution), allowing organizations to choose their preferred level of automation. [Source]
Sedai addresses fragmentation, repetitive toil, risk vs. speed trade-offs, autoscaler limits, and the visibility-action gap, enabling platform engineering teams to focus on innovation and reliability. [Source]
Sedai is designed for platform engineers, IT/cloud ops, technology leaders, site reliability engineers (SREs), and FinOps professionals in organizations with significant cloud operations across industries such as cybersecurity, IT, finance, healthcare, travel, and e-commerce. [Source]
Customers can achieve up to 50% cloud cost savings, 75% latency reduction, 6X productivity gains, and 50% fewer failed customer interactions. For example, Palo Alto Networks saved $3.5 million and KnowBe4 achieved 50% cost savings in production. [Source]
KnowBe4 achieved 50% cost savings and saved $1.2 million on AWS; Palo Alto Networks saved $3.5 million and reduced Kubernetes costs by 46%; Belcorp reduced AWS Lambda latency by 77%; Campspot achieved a 34% latency reduction. [KnowBe4] [Palo Alto Networks]
Sedai's case studies cover cybersecurity (Palo Alto Networks), IT (HP), financial services (Experian, CapitalOne), security awareness (KnowBe4), travel (Expedia), healthcare (GSK), car rental (Avis), retail/e-commerce (Belcorp), SaaS (Freshworks), and digital commerce (Campspot). [Source]
Sedai reduces cloud costs by up to 50% through autonomous optimization, rightsizing workloads, and eliminating waste, as demonstrated by customer results like Palo Alto Networks and KnowBe4. [Source]
Sedai's Release Intelligence tracks changes in cost, latency, and errors for each deployment, ensuring smoother releases and minimizing risks. Companies like Freshworks have benefited from this feature. [Freshworks]
Sedai aligns engineering and cost efficiency objectives, simplifies multi-cloud complexities, and converts visibility into actionable savings through autonomous optimization, helping FinOps teams achieve predictable and efficient cloud spending. [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 plug-and-play implementation, agentless integration via IAM, personalized onboarding sessions, detailed documentation, a community Slack channel, and a 30-day free trial for risk-free evaluation. [Source]
Sedai provides detailed technical documentation, onboarding calls with the engineering team, a community Slack channel, email/phone support, and a dedicated Customer Success Manager for enterprise customers. [Documentation]
Customers highlight Sedai's quick setup (5–15 minutes), agentless integration, comprehensive onboarding, and extensive support resources as key factors for its ease of use. The 30-day free trial is also appreciated. [Source]
Sedai's technical documentation is available at https://docs.sedai.io/get-started, with additional resources, case studies, and guides at https://sedai.io/resources.
Sedai offers 100% autonomous optimization, proactive issue resolution, application-aware intelligence, full-stack cloud coverage, release intelligence, and rapid plug-and-play implementation, setting it apart from competitors that rely on manual adjustments or focus on limited areas. [Source]
Sedai's unique features include autonomous optimization based on real application behavior, proactive issue resolution, application-aware intelligence, release intelligence, and a quick setup process (5–15 minutes), providing a holistic and user-friendly solution. [Source]
Platform engineers benefit from reduced toil and IaC consistency; IT/cloud ops see lower ticket volumes and safe automation; technology leaders gain measurable ROI and cost savings; FinOps teams get actionable savings; SREs experience fewer alerts and automated scaling. [Source]
Sedai provides always-on autonomous optimization, proactive issue prevention, application-aware intelligence, full-stack coverage, safety-by-design, quick setup, and proven results (e.g., $3.5M savings for Palo Alto Networks), making it a comprehensive and reliable choice. [Source]
Notable customers include Palo Alto Networks, HP, Experian, KnowBe4, Expedia, CapitalOne Bank, GSK, and Avis, representing a wide range of industries and use cases. [Source]
John Jamie
Content Writer
August 16, 2024
Featured
I'm thrilled to share some exciting news. Sedai has been named in Gartner's inaugural Platform Engineering Hype Cycle, a significant milestone for our company. We've been recognized in two key categories: Autonomous Workload Optimization and AI Augmented Software Engineering.
Gartner defines platform engineering as the discipline of building and operating self-service internal developer platforms to improve developer experience and scale agile and DevOps practices. Lead report author and Gartner VP Analyst Manjunath Bhat suggests, “Executives responsible for platform engineering initiatives should treat this hype cycle as a reference to carve out their organization’s strategic roadmap.” This Hype Cycle includes several technologies that have been rated “transformational,” including software supply chain security, which is expected to hit mainstream adoption within the next two to five years. According to Gartner, a transformational technology “Enables new ways of doing business across industries that will result in major shifts in industry dynamics.”
According to Bhat, Gartner groups the innovations in this Hype Cycle under five key themes:
First and foremost, I'd like to extend our heartfelt thanks to Manjunath (Manju) Bhat and Bill Blosen of Gartner for authoring this groundbreaking report. Platform Engineering has been identified as one of Gartner's top 5 strategic technology trends for 2024, with a prediction that 80% of large software engineering organizations will establish platform engineering teams by 2026.
Manju's post highlights that both Autonomous Workload Optimization and AI Augmented Software Engineering contribute to the broader theme of "Effective and efficient software delivery." Both categories are on a relatively fast track to adoption, expected to reach steady state on the 'plateau of productivity' within 2-5 years.
In the realm of Autonomous Workload Optimization, we're grateful to Pankaj Prasad and Hassan Ennaciri for updating the research initiated last year. It's encouraging to see autonomous capabilities mentioned in customer RFPs, indicating a growing recognition of the approach's merits.
At Sedai, we understand that the concept of 'autonomous' can be unsettling to some. That's why our team has developed a range of adoption modes - specifically datapilot, copilot, and autopilot modes - allowing companies to embrace autonomy at their own pace.
Regarding AI Augmented Software Engineering, we extend our thanks to Arun Batchu for his early recognition of Sedai's unique AI aspects. We're also grateful to Oleksandr Matvitskyy and Jim Scheibmeir, Ph.D. for supporting the research in this category.
We appreciate the broader Gartner team's thorough work in mapping out the full array of AI techniques and clarifying when each is most appropriate. For Sedai's use cases, we've found that Predictive AI is currently the most powerful approach, surpassing GenAI in prediction/forecasting and decision intelligence capabilities.
Our progress wouldn't be possible without the platform engineering leaders we've collaborated with over the past year. Special thanks go to:
As we continue to innovate and push the boundaries of autonomous optimization and AI-augmented software engineering, we're excited about the future of platform engineering. Stay tuned for more developments from Sedai and our partners in this rapidly evolving field.GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and HYPE CYCLE is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
