Sedai is an autonomous cloud platform that optimizes cloud resources, reduces costs, and improves performance and availability. For Palo Alto Networks, Sedai provided a single control plane for their complex, multi-cloud environment, enabling both AI and human engineers to work together to achieve high availability and cost efficiency. Source
Unlike traditional automated tools that rely on fixed rules and scripts, Sedai uses patented deep reinforcement learning to understand the entire cloud environment and make context-aware, autonomous optimizations. This approach adapts to changes and avoids the pitfalls of static automation, which can break in complex, real-world scenarios. Source
Autopilot mode allows Sedai to take incremental, autonomous actions in production environments to achieve specific Service Level Objectives (SLOs) set by the engineering team. After building trust through recommendations, Palo Alto Networks enabled Autopilot mode, allowing Sedai to operate independently and optimize their cloud continuously. Source
Sedai employs multiple AI agents, each focused on objectives like cost, performance, or availability. For example, a cost-optimization agent can autonomously reduce resource allocation until another agent predicts a negative impact on performance or availability, ensuring optimal balance. Source
Human engineers set the strategic direction and SLOs for their cloud environment, while Sedai autonomously executes optimizations to achieve those goals. This collaboration allows engineers to focus on higher-value work and reduces manual toil. Source
Sedai provides a single control plane for managing resources across multiple cloud providers and internal data centers. This unified approach simplifies operations, reduces fragmentation, and enables consistent optimization across the entire cloud footprint. Source
Unlike monitoring tools that only provide visibility and alerts, Sedai goes beyond by autonomously executing optimizations and remediations in real time, directly impacting cost, performance, and availability. Source
Sedai starts by making recommendations that engineers can review and approve. As the platform demonstrates its effectiveness and reliability, teams can gradually enable autonomous actions (Autopilot mode) for greater impact. Source
Sedai's deep understanding of the cloud environment enables it to detect anomalies and potential availability issues in real time, allowing teams to react quickly and prevent customer disruption during major cloud provider outages. Source
99.999% availability ("five 9s") means only five minutes of downtime per year. Achieving this standard is critical for Palo Alto Networks due to the essential nature of their services. Sedai helps the team get closer to this goal by reducing manual toil and enabling real-time anomaly detection and remediation. Source
Sedai automates repetitive and time-consuming tasks, freeing engineers from 24/7 manual operations and allowing them to focus on more meaningful, high-value work. This shift reduces burnout and improves job satisfaction. Source
Sedai's platform continuously learns from the environment, adapting its optimizations as the cloud architecture and workloads evolve. This ensures ongoing improvements and resilience in dynamic, large-scale environments. Source
Sedai has saved Palo Alto Networks $3.5 million in cloud spend, before accounting for special discounts, by autonomously optimizing resource allocation and reducing waste. Source
Sedai provides visibility, actionable insights, and autonomous execution, allowing engineering leaders to set strategic goals and trust that the platform will optimize resources to meet those objectives. Source
Sedai's single control plane and autonomous optimization reduce the need for manual coordination across teams, streamline operations, and ensure consistent performance and cost management across the organization. Source
The process typically starts with Sedai making recommendations that engineers review. Once trust is established, teams can enable Autopilot mode for Sedai to autonomously execute optimizations in production. Source
Sedai's AI agents continuously monitor and optimize resources, making adjustments that maximize cost savings without sacrificing performance or availability. The platform stops optimizations at the point where further changes would negatively impact other objectives. Source
By automating repetitive tasks and reducing the need for 24/7 manual intervention, Sedai allows engineers to focus on strategic projects and reduces burnout, leading to a better work-life balance. Source
Sedai addresses challenges such as managing complex, multi-cloud environments, reducing cloud costs, improving availability, and minimizing manual toil for engineering teams. Source
Sedai provides latency reporting, out-of-the-box performance gains using machine learning, performance and cost optimization with cost caps, Smart SLOs, and Release Intelligence to track the impact of new releases. Source
Yes, Sedai integrates with AWS, Google Cloud, Microsoft Azure, IBM Cloud, Oracle Cloud, and tools like Slack, Microsoft Teams, Jira, ServiceNow, AppDynamics, DataDog, New Relic, Prometheus, GitHub, GitLab, Bitbucket, Terraform, and more. Source
Smart SLOs automatically set and monitor Service Level Objectives based on past performance, alerting teams to breaches and helping maintain reliability and latency targets. Source
Release Intelligence tracks the impact of new releases on latency, cost, and errors using scorecards, enabling teams to ensure quality and reduce deployment errors. Source
Sedai provides a comprehensive Getting Started Guide, Dataflow Optimization Documentation, and other resources to help users configure and utilize the platform effectively. Source
Customers can expect significant cost savings (e.g., KnowBe4 achieved up to 50% savings, Palo Alto Networks saved $3.5M), productivity gains (over 2 million autonomous remediations in a year), improved performance (up to 77% latency reduction), and enhanced availability. Source
Sedai is ideal for Site Reliability Engineers, Platform Engineers, DevOps teams, Engineering Leaders, CTOs, and organizations of all sizes managing cloud operations in industries like cybersecurity, SaaS, financial services, e-commerce, and more. Source
Customers like KnowBe4, Palo Alto Networks, Belcorp, Campspot, Inflection, and Freshworks have achieved major cost savings, performance improvements, and operational efficiency using Sedai. For example, Palo Alto Networks saved $3.5M and KnowBe4 achieved 50% savings in production. Source
Sedai's case studies cover cybersecurity, information technology, information services, financial services, SaaS, supply chain solutions, insurance software, scientific research, e-commerce, and online travel. Source
Sedai's plug-and-play implementation takes just 5 minutes for general setup and 15 minutes for specific use cases like AWS Lambda, ensuring minimal disruption to workflows. Source
Sedai offers live onboarding support, comprehensive documentation, a Slack community for real-time help, and the option to schedule personalized onboarding calls. Source
To get started, you need cloud access (via IAM), a monitoring source, and for Kubernetes clusters, integration via Sedai's Smart Agent. Security team assistance may be required to provide sufficient access. Source
Sedai is designed for ease of use, with quick setup, live onboarding, comprehensive documentation, and a supportive Slack community, making adoption straightforward for new users. Source
Palo Alto Networks evaluated Cast AI and Kubecost but chose Sedai for its autonomous optimization, continuous learning, and ability to enhance production safety in complex environments. Sedai provides a single control plane and goes beyond recommendations to autonomous actions. Source
Sedai is 100% autonomous, optimizes across multiple platforms, uses AI-driven insights, proactively resolves issues, and tracks release quality, offering advantages for enterprises, DevOps teams, and startups. Source
Sedai offers autonomous optimization, comprehensive platform coverage, AI-driven insights, proactive issue resolution, and proven ROI, making it a superior choice for organizations seeking efficiency and reliability. Source
Yes, Sedai is SOC 2 certified, demonstrating adherence to stringent security and compliance standards for data protection. Source
Sedai's customers include Palo Alto Networks, HP, Experian, KnowBe4, Capital One, Flex, Guidewire, Oak Ridge National Laboratory, and Freshworks. Source
Sedai
Content Writer
September 25, 2025
Featured
Palo Alto Networks needs no introduction. Its customers include nine of the Fortune 10, eight of the ten biggest US banks, and all ten of the world’s largest utilities. Simply put, the company protects our planet’s most critical infrastructure from cyber attacks.
Suresh Sangiah is responsible for keeping its cloud online — no matter what.
“Palo Alto Networks is the preeminent cyber security company in the world,” he said. “We have the responsibility to make sure that our cloud is always on. Because if ever our service goes down, it would mean the companies that we serve are not able to get their work done.”
Suresh Sangiah delivering the keynote presentation at autocon 25
As Senior Vice President of Engineering, Suresh oversees Prisma SASE, the industry-standard cloud service that provides networking and security to distributed workforces around the globe. Under the hood, Prisma SASE runs on a huge array of its own cloud-based resources. Each of these resources requires careful management and constant optimization.
The result is a job that sounds impossible. Somehow, Suresh needs to control a cloud that is hosted by third-party vendors, configured by dozens of engineering teams, and stressed by millions of end users. And of course, he also faces pressure to lower costs — by eliminating every source of wasted spend.
Ultimately, the Palo Alto Networks team went looking for a new way to handle the complexity and costs of its cloud.
This is the part of the case study where we tell you that Palo Alto Networks got Sedai — which solved every challenge with its cloud operations, overnight.
But that’s not the truth.
The reality of enterprise software is much more nuanced, especially when you’re dealing with such complex environments. Automated tools fail precisely because they ignore the nuance of the real world. These automated tools use fixed rules and scripts, without understanding context or adapting to change, which means things inevitably break.
The Palo Alto Networks team evaluated the leading solutions to manage its cloud, including automated tools like Cast AI and Kubecost. It decided to partner with Sedai, the first autonomous cloud management platform. The team found that only Sedai could “enhance production safety” at Palo Alto Networks, through “continuous learning.”
Sedai didn’t start making autonomous changes to the company’s cloud, right away. Instead, our patented deep reinforcement learning technology began by understanding how its cloud functioned: from the overall architecture, down to individual microservices. This big-picture perspective is critical to manage a complex, multi-cloud environment like Palo Alto Networks’. Whereas the cloud is often fragmented by provider or by team, Sedai provides a single control plane for the company’s entire cloud footprint.
Products like Prisma SASE require complex interactions across many cloud resources.
“Our cloud is extremely complicated,” Suresh said. “We’ve got hundreds of services interacting with each other to deliver the outcome our customers expect. The only way to make sure our cloud is available all the time is for humans and AI to work together.”
That’s exactly what happened. Sedai began making recommendations to reduce costs, improve performance, and fix availability issues across Palo Alto Networks’ cloud — recommendations that its engineers would review and approve. At the same time, Sedai’s platform continued to build its understanding of the company’s environment.
The result was greater and greater trust in the platform.
Importantly, Sedai is not another monitoring tool, and it goes beyond recommendations. Once the Palo Alto Networks team had established trust, it enabled Sedai to operate in Autopilot mode, in its production environment. In this mode, Sedai takes incremental, autonomous actions to achieve the team’s specific SLOs.
In other words, Suresh’s team sets the “directions” for its cloud, and Sedai drives it there.
“As you can imagine, we’ve got a very, very large volume of alerts coming in from our monitoring tools, which is simply impossible for humans to process,” Suresh said. “This is where AI becomes critical. Sedai [performs] autonomous actions that we wouldn’t be able to handle without it.”
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Sedai is a single optimization plane for Palo Alto Networks’ cloud environment.
Sedai’s unique approach relies on multiple AI agents, each focused on a specific objective such as cost, performance, or availability. For example, when Sedai detects an overprovisioned resource, the cost-optimization agent can autonomously reduce the memory allocated to that resource. It stops at the precise point where other agents predict that further reduction would impact performance or availability.
Sedai thinks like an expert engineer — but acts on a scale that is only possible with AI.
“The cost is really on us,” Suresh said. “We’re responsible for making sure we run our service in an optimal way. But as the scale goes up, it becomes harder and harder to balance optimal costs with performance and availability. The conventional, human-centered approach just doesn’t work.”
The results of autonomy have been remarkable — and that’s not just marketing speak. Sedai has already saved Palo Alto Networks a staggering $3.5 million in cloud spend (before accounting for special discounts). And at the same time, Sedai has freed its engineers from thousands of hours of manual toil. The company can now redirect these resources, away from managing back-end systems and toward creating a better experience for customers.
You can probably guess why we led with $3.5 million in savings: It’s the type of big, flashy number that you’d love to show your CEO. But for Suresh, the most important number is 99.999%.
That is the availability standard that the entire engineering team at Palo Alto Networks works hard to deliver.
“To reach 99.999%, we can only afford five minutes of downtime per year,” Suresh said. “It’s an audacious goal, and we don’t always get there. But we’re getting better and better by using Sedai, which works alongside our engineers. It’s this combination — engineering smarts and AI — that we need to handle issues.”
“Five 9s” availability is difficult for any organization. But it’s particularly challenging for Palo Alto Networks, given that the company uses all major public clouds, manages its own data centers, and runs tens of thousands of microservices. For Suresh, the recent AWS and Google outages have made this problem very real:
“How do you respond when a major cloud provider has an outage? Because disaster does strike. We need to design our cloud to be resilient. So when there is a failure, we’re able to react right away and prevent disruption for customers.”
Ramesh Nampelly, Senior Director Of Cloud Infrastructure and Platform Engineering, said that the sheer size of this environment had become overwhelming for his team:
“The engineers who managed our production operations were dealing with a huge amount of toil,” Ramesh remembered. “They were working 24 by 7 to provide five 9s availability, which caused a lot of burnout. Our SREs were doing the same thing — again and again — without the ability to automate it. And we can’t grow our SRE team linearly, as the number of customers and workloads increases.”
Since then, Sedai has helped Palo Alto Networks truly take control of its availability. Because our platform has developed such a deep understanding of the company’s cloud, it is able to detect anomalies in its typical behavior, including potential availability issues. This enables its SREs to spend their time on critical, meaningful work.
"Sedai has helped us save millions of dollars by optimizing and managing our own back-end services,” Suresh said. “But most importantly, what Sedai has done very well is allow us to respond in real time when anomalies are detected."
For Palo Alto Networks, Sedai is more than just a fancy AI tool that reduces its costs. Sedai is the platform that allows engineering leaders like Suresh to understand, manage, and optimize its cloud — putting them in command.
“We’ve gone from what used to be automated, deterministic workflows to autonomous, with Sedai,” Suresh said. “The human element is indispensable, and it always will be. But more and more engineering toil is being done by AI, so as humans, we can move up the value chain. That’s how we can deliver what our customers expect of us.”
