How AWS Helps BigBasket Manage 6x Traffic Spike During Lockdown

In 2021, BigBasket faced a massive surge in demand—daily orders skyrocketed from 250,000 to 400,000 in just 8 months due to the pandemic-driven boom in online shopping.

Here's how BigBasket, India’s largest online grocer, tackled this growth with AWS and maintained seamless performance while cutting costs:

What was the issue?

• With India under lockdown, BigBasket saw 6x traffic spikes, far exceeding pre-pandemic peaks.
• They needed to scale fast while maintaining 99.9% uptime and keeping response times under 350 milliseconds—no small feat with this much load.

How did they respond?

• BigBasket consulted AWS Enterprise Support and revamped its infrastructure. By fully containerizing operations and running 60 microservices on Kubernetes, they handled the surge without crashing.
• Database scaling was a major challenge. Using Amazon RDS for MySQL, they automated tasks, saving one week of engineering time per month, and kept costs at pre-pandemic levels, even with the spike in traffic.

What were the key fixes?

• Automated scaling features built into AWS containers helped BigBasket manage traffic spikes efficiently.
• The team kept databases optimized through quick scaling and avoided manual management, drastically reducing overheads.
• They leaned on AWS's flexibility, combining managed services and EC2 instances to design a scalable architecture.

The Data-Driven Edge

• BigBasket wasn’t just scaling—it was improving. By using Amazon Redshift and S3 for advanced analytics, they fine-tuned their recommendation engine to expedite shopping experiences for 10 million+ customers.
• Their BB Star loyalty program and Smart Basket features, powered by deep data insights, delivered personalized offers and faster checkouts, helping keep customer retention high.

Localized Efficiency

• Hyper-local data analysis using Amazon Elasticsearch allowed BigBasket to fine-tune warehouse stocking based on neighborhood demand, ensuring faster deliveries and satisfied customers.

Key Takeaways:

• Microservices and containers helped them scale quickly while cutting costs.
• Leveraging AWS tools, they saved significant time on database management and optimized their entire infrastructure.
• Personalized shopping and hyper-local inventory helped keep customers coming back, boosting both efficiency and growth.

In short, BigBasket rode the e-commerce wave during the pandemic and used AWS to ensure smooth operations, scaling effortlessly while keeping costs under control.