👉Flipkart’s Bold Move: Production Databases on Kubernetes Explained
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Running Databases on Kubernetes? Flipkart Did It at Massive Scale
Flipkart’s Bold Move: Production Databases on Kubernetes Explained
Database-as-a-Service on Kubernetes | Flipkart’s Real Architecture
When companies adopt Kubernetes, they typically start with stateless workloads.
Flipkart went further.
In this high-impact session, Vaidyanathan S (Senior Engineering Leader at Flipkart) reveals how Flipkart built a Database-as-a-Service (DBaaS) platform on Kubernetes, running production databases reliably at massive scale.
This isn’t theory.
It’s based on 3+ years of real production experience.
🔥 What You’ll Learn:
✅ Why Flipkart chose Kubernetes for stateful workloads
✅ The engineering challenges of running databases on K8s
✅ Operational lessons from production-scale deployments
✅ Hybrid cloud strategy (Flipkart Cloud Platform + GCP)
✅ BCP-DR design for mission-critical systems
✅ Productivity, resilience, and cost tradeoffs
✅ What most teams get WRONG about databases on Kubernetes
If you design platforms, manage infrastructure, or run large-scale systems — this talk is packed with insights you can apply immediately.
📌 Subscribe to Perfology for weekly deep dives on:
#kubernetes #flipkart #database #cloudarchitecture #sre #devops #perfomance #distributedsystems #perfology
kubernetes databases, stateful workloads kubernetes, database on k8s, flipkart engineering, dbaas architecture, database as a service, hybrid cloud architecture, running postgres on kubernetes, scalable database infrastructure, sre architecture, cloud native databases, production kubernetes, distributed databases, platform engineering, high availability databases, devops architecture, perfology
Performance Engineering • Cloud • DevOps • Observability • AI in Testing • Distributed Systems
Here are the key timestamps and topics covered in the video:
Introduction to Hybrid Technology (0:00-1:02)
Big Billion Days: Hybrid Cloud Strategy (1:03-2:55)
Advantages of Hybrid Cloud (2:56-7:53)
Why Kubernetes? (7:54-10:32)
Stateful Workloads and Operators (10:33-14:55)
Challenges of Databases on Kubernetes (14:56-17:53)
Telemetry and Alert Fatigue (17:54-19:30)
Choosing the Right Storage (LAST vs. NAS) (19:31-22:27)
Resource Utilization and Cost Management (22:28-23:51)
Performance vs. Availability Tradeoffs (23:52-26:40)
Practical Example: Tidb Operator Setup (26:41-28:59)
Scaling Databases on Kubernetes (29:00-31:31)
Failure Management Scenarios (31:32-33:10)
Backups and Custom Operators (33:11-36:03)
Q&A and Summary (36:04-39:07)
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