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Amazon Web Services > Case Studies > Edmunds Saves $100,000 in Year One by Going Serverless on AWS

Edmunds Saves $100,000 in Year One by Going Serverless on AWS

Technology Category

Infrastructure as a Service (IaaS) - Cloud Computing
Infrastructure as a Service (IaaS) - Cloud Storage Services

Applicable Functions

Discrete Manufacturing

Services

Cloud Planning, Design & Implementation Services

The Challenge

Edmunds, a company that helps consumers browse automobile dealer inventory, read vehicle reviews, and consume other automobile-related content, was planning a key update with better image quality and faster load times on the company's website and mobile apps. The company had a library of 50 million vehicle images that needed to be processed into several new aspect ratios and resolutions, resulting in more than half a billion new images. The company's existing image-handling solution, based on Cloudera MapReduce clusters, wasn't suitable for the job as it would have taken too long to develop and would have required the management of new clusters and incurred new monthly costs of at least $10,000.

About The Customer

Edmunds is a company that operates a website and mobile apps to help consumers browse automobile dealer inventory, read vehicle reviews, and consume other automobile-related content. The company's mission is to make car buying easy by providing a platform where consumers can complete the key steps in vehicle purchasing: identifying the right vehicle, evaluating trade-ins, analyzing price and financing offers, and finalizing the purchase. Edmunds considers its library of vehicle photos uploaded by auto dealers to be one of its most important assets. The company helps more than 20 million web and mobile users each month and is based in the United States with 700 employees.

The Solution

Edmunds decided to use a serverless solution on Amazon Web Services (AWS) for this project. The serverless solution uses Amazon Simple Storage Service (Amazon S3) for highly available object storage, with AWS Lambda functions triggered by an AWS API Gateway endpoint. It also includes Amazon Athena, a serverless, interactive service that uses standard SQL to query large data sets by taking advantage of the query-in place functionality of Amazon S3, avoiding the need to move the data to a separate analytics platform. By using Amazon S3 Standard storage, Edmunds achieves 99.999999999 percent data durability and replication across three AWS Availability Zones (AZs), so the company’s data would remain available even in the event of the destruction of an entire AZ’s AWS data centers.

Operational Impact

The project was completed on deadline for a one-time cost of $6,000, compared to the monthly charges of at least $10,000 that would have been incurred if new resources had to be purchased, provisioned, and configured.
The team was able to scale to thousands of AWS Lambda function invocations and increase the memory allocation with just a few clicks, processing all 50 million images into 700 million new images in just eight days.
The simplicity and flexibility of connecting services on AWS played a key role in how quickly the team was able to put the solution into production.

Quantitative Benefit

Saved $100,000 in the first year
Processed 50 million images in 8 days
Decreased photo storage from 60 to 40 terabytes

Edmunds Saves $100,000 in Year One by Going Serverless on AWS

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