Palo Alto Networks was motivated by the need to scale efficiently, integrate acquisitions, and deliver reliable cloud-native security solutions. Under Suresh Sangiah's leadership, the company transitioned from manual workflows to sophisticated autonomous systems to support rapid growth and operational agility, especially during the pandemic. Source
The company encountered challenges such as merging acquisitions into a unified platform, transitioning from manual to autonomous workflows, and convincing experienced staff to embrace automation without compromising quality. Training engineers in new skills was also essential for success. Source
They focused on transforming the workforce by training engineers in new skills and fostering a culture that values automation as a pathway to scale. The company worked to overcome skepticism and gradually adapted teams to autonomous workflows. Source
Palo Alto Networks needed to overcome the mindset that autonomy reduces the need for human expertise. They created structured pathways for teams to adapt, ensuring confidence in new systems while maintaining operational integrity. Source
The company unified its offerings under a single platform, requiring all services to meet a standardized five-nines (99.999%) reliability. Rigorous backend integration ensured seamless and dependable service across acquisitions. Source
Security layers include URL filtering, DNS security, and continuous latency management to protect users accessing remote resources and prevent performance slowdowns. Source
The company prioritizes continuous latency management to ensure immediate, secure access to critical applications, balancing high-level security with real-time efficiency. Source
Telemetry data is used to predict and preload resources based on user patterns, optimizing application access and reducing wait times. Network optimization manages packet delays for smooth connectivity. Source
Copilots interpret natural language queries, analyze backend information, and provide summaries, automating support processes and improving resolution speed. User feedback refines AI effectiveness. Source
Internal AI applications are used for backend automation and insights, offering flexibility for experimentation. External applications undergo rigorous testing to ensure data security and reliability, minimizing customer risk. Source
Palo Alto Networks partners with Sedai to develop systems that proactively detect issues and trigger automated resolutions. This collaboration leverages advanced telemetry and AI-driven alerts to minimize manual interventions and enhance operational reliability. Source
The end goal is to minimize human intervention while maintaining security and reliability, equipping teams with robust tools for scalable, sustainable growth. Autonomy is seen as a partnership between human expertise and machine intelligence. Source
The company instills confidence in new systems through structured adaptation, maintaining operational integrity by balancing automation with human oversight. Source
Palo Alto Networks uses a five-nines (99.999%) reliability standard across its unified platform, ensuring uninterrupted service for customers. Source
The company uses telemetry analysis to predict and preload resources, optimizing application access and reducing wait times for frequently accessed resources. Source
Copilot automation enables faster, more accurate support, freeing human agents to focus on complex tasks and improving the speed of resolutions. Source
External AI applications are rigorously tested to ensure data security and reliability, maintaining customer trust and transparency. Source
Suresh Sangiah, SVP at Palo Alto Networks, guided the company through acquisitions, platformization, and the shift to autonomous operations, driving 80% of the company's revenue and shaping its direction. Source
The company views autonomy as a partnership, equipping teams with robust tools while maintaining operational integrity and leveraging human expertise for scalable growth. Source
Sedai is the only cloud optimization platform patented to make safe, autonomous optimizations in production without causing incidents or breaching SLOs. Unlike risky optimizers that make all-at-once changes, Sedai performs gradual optimizations with continuous validation checks, ensuring operational safety. Source
Sedai customers typically achieve a 30% reduction in cloud costs, 75% fewer failed customer interactions, and 50% reduction in engineering toil. For example, KnowBe4 reduced response time from 18.5 seconds to 80 milliseconds—a 99.5% duration reduction. Source
Sedai integrates with monitoring tools (Prometheus, Datadog, Cloudwatch, Azure Monitor), Kubernetes autoscalers (HPA/VPA, Karpenter), CI/CD platforms (GitHub, GitLab, Bitbucket, Terraform), ITSM (ServiceNow, PagerDuty, Jira), notification tools, runbook automation, and serverless platforms (AWS Lambda, AWS Fargate). Source
Sedai offers a Getting Started Guide, Kubernetes Optimization Guide, and a Platform Overview. These resources are available at docs.sedai.io/get-started and 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 Sedai's Security page.
Sedai provides an autonomous cloud platform for optimizing cloud operations—cost, performance, and availability—using machine learning. Solutions include Application Performance, Cloud Cost Optimization, Cloud Operations, FinOps, and SRE automation. Supported technologies: AWS EKS, Kubernetes, AWS ECS, AWS Lambda, EC2, AWS EBS. Source
Customers can expect up to 50% cloud cost reduction, 75% latency reduction, 50% fewer failed customer interactions, and up to 6X productivity improvements. Typical ROI is greater than 400%, with financial payback in under six months. Source
Sedai's customers include KnowBe4, Palo Alto Networks, Belcorp, Campspot, Inflection, and Freshworks. These companies have achieved measurable results in cost savings, performance improvements, and operational efficiency. Source
Industries include cybersecurity (Palo Alto Networks, KnowBe4), financial services (Experian), healthcare, e-commerce (Wayfair, Campspot), IT and technology (HP, Freshworks), consumer goods (Belcorp), and digital commerce (Informed). Source
Sedai uses a volume-based pricing model, charging based on resources optimized (Kubernetes pods, ECS tasks, VMs, etc.). Pricing is transparent, flexible, and includes a free tier and 30-day free trial. For Kubernetes, a demo is recommended to determine the best pricing structure. Source
Initial onboarding takes approximately 15 minutes for agentless or agent-based deployment. Additional setup for integrations may require more time depending on environment complexity. Sedai offers plug-and-play implementation and seamless integration with existing tools. Source
Key features include autonomous optimization, application-aware intelligence, proactive issue resolution, full-stack cloud coverage, safety-by-design, release intelligence, and plug-and-play implementation. These address cost optimization, performance enhancement, and operational efficiency. Source
Sedai offers 100% autonomous optimization, application-aware intelligence, proactive issue resolution, full-stack coverage, safety-by-design, and release intelligence. Unlike competitors, Sedai continuously executes real-time optimizations with patented safety checks, making it ideal for enterprises needing compliance and reliability. Source
Sedai is designed for IT/cloud operations, FinOps, technology leadership, platform engineering, and site reliability engineering (SRE) roles in organizations focused on infrastructure, compliance, cost efficiency, and operational reliability. Source
Sedai addresses cost inefficiencies, operational toil, performance and latency issues, lack of proactive issue resolution, complexity in multi-cloud/hybrid environments, and misaligned priorities between teams. Source
KnowBe4 achieved 50% cost savings and saved $1.2 million on AWS. Palo Alto Networks saved $3.5 million in cloud costs. Belcorp reduced AWS Lambda latency by 77%. Campspot achieved a 34% reduction in AWS Lambda latency. Inflection and Freshworks improved platform performance and user experience. Source
Suresh Mathew
Founder & CEO
November 1, 2024
Featured
As enterprises push the boundaries of technology, Palo Alto Networks stands out as a leader in cybersecurity transformation, innovating toward an autonomous operations future. Steering this transformation is Suresh Sangiah, Senior Vice President at Palo Alto Networks, who has brought his deep expertise and strategic vision to guide one of the most significant transformations in the company’s history. At the PM 5 Talk, Sangiah spoke candidly about the journey of transitioning from traditional operations to a sophisticated, autonomous system—an endeavor rooted in both technological prowess and human adaptability.
Sangiah’s experience spans several acquisitions and integrations of new services, each of which has been pivotal in shaping the current capabilities of Palo Alto Networks. His insights shed light on the layered complexities of building autonomous systems in cybersecurity, highlighting both the technological advancements and cultural shifts required. Join us as we dive into the journey Palo Alto Networks has undertaken, moving from cloud beginnings to a unified, AI-driven autonomous operation, with insights from Suresh Sangiah’s expertise and vision.
Watch the full talk here.
Palo Alto Networks, once recognized primarily as a firewall company, has since redefined itself as a leader in cloud-native security solutions. Under Suresh Sangiah’s guidance, the organization has accelerated its cloud services while also leading multiple acquisitions to reinforce its mission. Sangiah’s team now drives 80% of the company’s revenue—a testament to its influence and responsibility in shaping the company’s direction.
Key Challenges:
This transformation illustrates the depth of Palo Alto Networks' adaptability, especially when faced with the rapid market changes spurred by the pandemic, which demanded operational agility to support a surge in demand for remote security.
Sangiah’s vision for autonomy at Palo Alto Networks recognizes that the journey is far from complete. Autonomy may define the future, but it’s not yet a universal reality across every function. Sangiah notes that building autonomy requires not only tools and technologies but also transforming people’s approach to work and redefining traditional processes.
Human-Centric Challenges:
This journey toward autonomy highlights the company’s commitment to evolving its workforce and fostering a culture where employees embrace new methods to achieve efficiency and resilience.
The path to autonomy involves reshaping not only the technology stack but also the people and processes behind it. Sangiah emphasized that getting the operations team, who are used to manual, hero-driven approaches, to trust in automated workflows is one of the biggest challenges.
Cultural and Operational Adjustments:
Transitioning from traditional operations to an autonomous model is a significant shift, one that relies on instilling confidence in new systems while maintaining operational integrity. Sangiah’s focus is on transforming Palo Alto Networks’ culture and operations to see autonomy as a partnership with technology, not a replacement.
One of Palo Alto Networks' major undertakings has been unifying its offerings under a single, highly reliable platform, requiring every acquired company and new service to integrate seamlessly. This platformization journey means establishing a standardized five-nines (99.999%) service reliability across the entire system, a crucial metric in ensuring uninterrupted service for customers.
Backend Unification Efforts:
Achieving such a high degree of reliability across diverse systems speaks to the company's commitment to operational excellence. Each new service must meet the same stringent standards, ensuring that customers experience seamless and dependable service.
For Palo Alto Networks, security is paramount, and delivering it in real-time is essential. Sangiah explained that their service’s purpose is to maintain the security of SaaS applications, private networks, and remote work access without compromising on latency, as customers rely on immediate, secure access to critical applications.
Security Layers:
Balancing high-level security measures with real-time efficiency requires precision, as any delays can affect users’ productivity. Sangiah’s approach ensures that security remains robust without becoming a barrier to seamless operations.
Using telemetry data, Palo Alto Networks enhances user experience by predicting and preloading resources based on user patterns. This preemptive approach, supported by their advanced cloud infrastructure, optimizes application access and reduces wait times.
Optimized Access & Performance:
This level of user-centered optimization not only improves customer satisfaction but also demonstrates the company’s commitment to leveraging data for a more intuitive experience.
Palo Alto Networks' support teams are now empowered by "copilots," AI-driven assistants designed to automate support processes. Copilots interpret queries, analyze backend information, and provide summaries, freeing human agents to focus on more complex tasks and improving the speed of resolutions.
Automated Support Process:
These copilots enable faster, more accurate support, which enhances the customer experience while helping the team handle a higher volume of cases.
Sangiah notes the distinct approaches needed for internal versus external AI applications. While internal applications offer flexibility for experimentation, external use cases must meet rigorous standards to prevent any risks that could affect customers.
Differentiated Approaches:
The company’s commitment to responsible AI underscores its dedication to maintaining trust and transparency with its customers.
The end goal for Palo Alto Networks is an advanced, autonomous system that minimizes human intervention while maintaining security and reliability. Sangiah and his team have partnered with AI companies like Sedai, collaborating to build systems that proactively detect issues and trigger automated resolutions.
Core Components of Autonomy:
Sangiah sees autonomy as a collaborative journey between human expertise and machine intelligence. For his team, autonomy doesn’t imply replacing humans; instead, it means equipping them with robust tools for scalable, sustainable growth.
Palo Alto Networks’ journey towards autonomy is a bold leap, a fusion of technological innovation and human resilience. Under Suresh Sangiah’s guidance, the company has embraced a path of gradual yet impactful change, implementing AI to automate processes, reduce latency, and enhance customer experience. With partnerships, like the one with Sedai, they are not only setting a foundation for autonomy but also creating an environment where human expertise is amplified by intelligent systems.
The future of cybersecurity is autonomous, and Palo Alto Networks is at the forefront of making it a reality. Their journey reminds us that autonomy is as much about empowering people as it is about advancing technology, ensuring that every layer of operations is resilient, reliable, and ready for the future.
