BigBasket Grows Bigger with 400,000 Daily Orders on AWS
Traffic Spikes Sixfold during Lockdown
BigBasket, India’s largest online grocery, has been in business since 2011. Customer retention is at the heart of its strategy, as well as a hyper-local approach to inventory. BigBasket is available in 21 cities and runs its infrastructure on the Amazon Web Services (AWS) Cloud. The business had been growing 20–30 percent each year, but when COVID-19 struck and India went into lockdown, BigBasket faced unprecedented demand. Daily traffic was suddenly six times higher than pre–COVID-19 peaks.
Chief Technology Officer, BigBasket
Microservices and Containers Boost Efficiency
The company had already begun shifting to asynchronous work queues in 2018, isolating workloads into containers and breaking up its monolithic architecture. However, the onset of the 2020 lockdown shifted this process into high gear. By mid-2020, the company was fully containerized with 60 microservices running on Kubernetes.
Automated scaling features that come with a containerized approach has helped BigBasket accommodate the extreme spikes in traffic the site now experiences. Daily order volume was averaging 250,000 in 2019 and had risen to 400,000 each day by late 2020. Even during its transition to containers, BigBasket maintained 99.9 percent uptime on its website, with response times under 350 milliseconds for its customer-facing APIs.
Scaling Up While Keeping Costs Down
Furthermore, due to efficiencies gained with containers and automation, BigBasket managed to bring the monthly cost of Amazon RDS down to pre–COVID-19 levels, even though its database was serving a much higher volume of traffic.
“With AWS, we can focus our energy in areas that are ripe for optimization. We can understand costs in a very clear way and can take advantage of various AWS tools to move to a different architecture quite seamlessly,” Daga says. “The fact that it’s a very open environment allows you to tap into services at multiple levels, so we can decide to go with a managed service or operate with simple Amazon Elastic Compute Cloud [Amazon EC2] instances for each application. This gives us a lot of flexibility in defining and designing our own architecture.”
Data-Driven Loyalty Program and Recommendation Engine
The fundamental aim of BigBasket’s data and analytics activities is to make the online shopping experience more intuitive. Online grocery shopping appeals to customers who are short on time, so the ability to log on, make the day’s purchases, and check out seamlessly is key to gaining repeated customers on BigBasket.
A feature called Smart Basket, for example, makes recommendations that help customers quickly navigate to the products they want, largely drawing on past purchase data and on shopping trends in the area they reside in. A year and a half ago, BigBasket introduced its BB Star loyalty program, powered by insights on a city level, to offer members discounts on delivery as well as preferred delivery slots, among other benefits.
Hyper-Local Approach to Product Selection
“A core value proposition of our business is being hyper-local,” Daga says. “We’re able to customize to very small geo-polygons within cities to strategize demand-based inventory.” Data also informs BigBasket’s decisions when setting up new warehouses based on customer density, helping drive the right product assortment for the area.
Out-of-the-Box Functionality on the Cloud
“The comfort of operating on AWS is there are certain aspects of our infrastructure that we don’t have to think about,” says Daga. “In an on-premises infrastructure, we would have to consume a large bandwidth of our engineers’ time, but on AWS we get new capabilities straight out of the box. With AWS, we have all the pieces of the puzzle to smoothly run a large ecommerce architecture.”
Benefits of AWS
- Scales from 250,000 to 400,000 daily orders in 8 months
- Maintains 99.9% site uptime with latency of 350 milliseconds
- Saves 1 weeks’ worth of staff time per month on database maintenance
- Frees up engineering time with managed services
- Recommends products to expedite shopping experience
- Develops loyalty program to reward repeat shoppers
- Achieves high degree of geo-segmentation with data tools
AWS Services Used
Amazon RDS for MySQL
MySQL is the world's most popular open source relational database and Amazon RDS makes it easy to set up, operate, and scale MySQL deployments in the cloud. With Amazon RDS, you can deploy scalable MySQL servers in minutes with cost-efficient and resizable hardware capacity.
No other data warehouse makes it as easy to gain new insights from all your data. With Redshift, you can query and combine exabytes of structured and semi-structured data across your data warehouse, operational database, and data lake using standard SQL.
Amazon Simple Storage Service
Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. This means customers of all sizes and industries can use it to store and protect any amount of data for a range of use cases, such as data lakes, websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics.
AWS Enterprise Support
AWS Enterprise Support provides you with concierge-like service where the main focus is helping you achieve your outcomes and find success in the cloud.
Companies of all sizes across all industries are transforming their businesses every day using AWS. Contact our experts and start your own AWS Cloud journey today.