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Distributed Video Management at Tesco Scale with Edge Compute and Kubernetes
Retail enterprises are increasingly relying on edge computing to deploy critical applications across thousands of distributed locations. Among the most demanding of these is the CCTV video platform, which must stream and process high-resolution footage in real time while navigating constraints like network bandwidth, latency, and compute limitations.
This session dives into a real-world architecture that supports over 200,000 cameras in a major retail deployment, achieving sub-second latency and robust video storage using Kubernetes and open-source tools. We’ll explore how a hybrid edge-to-cloud strategy enables localized compute, real-time filtering, and scalable storage—all while ensuring high availability, compliance, and performance.
From system design to deployment, learn how to architect and optimize edge-native video platforms that are secure, resilient, and cost-efficient. We’ll walk through edge cluster design, stream processing pipelines, storage tiering, and operational strategies that make this scale possible.
Key Takeaways
- Edge Computing – Learn how Kubernetes clusters at the edge reduce latency and cloud dependence by enabling local compute and dynamic video processing.
- Video Platform Optimization – Reduce cloud dependency via edge filtering, open-source streaming pipelines.
- Retail-specific Outcomes – Understand architectural trade-offs to meet compliance, storage efficiency, and operational needs across thousands of locations.
Target Audience
- Edge Infrastructure Engineers – Designing and deploying distributed video workloads across edge clusters.
- Video Platform Developers – Optimizing CCTV systems for real-time analytics, low latency, and hybrid cloud storage.
- Retail IT & Technology Leaders – Scaling intelligent video analytics across stores, warehouses, and digital ecosystems.
- Kubernetes Architects – Managing persistent, stateful workloads in edge environments with limited resources.
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About the speaker
Balaji Murugesan
Senior Software Development Engineer, Tesco Technology
Balaji is a Senior Software Engineer at Tesco with over 17 years of experience, specializing in distributed computing and edge compute technologies. He designs scalable, reliable, and high-performing systems, optimizing both hardware and software integration.
With expertise in distributed computing, Balaji creates systems that address challenges like latency, fault tolerance, and scalability, ensuring operational efficiency under high demand. He also specializes in edge compute, building real-time video processing systems that reduce latency and deliver high-quality, low-latency video streaming in bandwidth-constrained environments across various devices.
Balaji stays at the forefront of emerging trends in distributed computing and edge technologies, integrating the latest advancements to develop next-generation solutions.
