AWS Partner Network (APN) Blog

How Signiant Uses AWS Lambda and Amazon DynamoDB to run its SaaS Solution on AWS

By Mike Deck, Partner Solutions Architect, AWS

When AWS Lambda was launched in 2014, it unlocked an ability for AWS customers and partners to implement full-featured, scalable solutions without the need to deploy or manage any servers. I work with many SaaS partners who are now leveraging the serverless model for various components of their architecture. The first step in this journey is often to re-engineer ancillary workloads that can be easily re-implemented without servers. This can afford immediate reductions in infrastructure costs and operational surface area as well as provide valuable experience in building and running systems using this new paradigm.

Signiant, an Advanced APN Technology Partner, Digital Media Competency Partner, and Storage Competency Partner, is a textbook example of a firm who has put this pattern into practice. Over time, Signiant has re-architected its solution on AWS that leverages the bounce and delivery notifications provided by Amazon Simple Email Service (Amazon SES), via an Amazon Simple Notification Service (Amazon SNS) topic. Each iteration of the company’s system has made improvements to the scalability and operational efficiency of the solution, culminating in a simple, Lambda-based serverless architecture. In this post, I will walk through how Signiant has re-architected its SaaS solution on AWS to take advantage of the capabilities of AWS Lambda and a serverless architecture.

Solution Overview

Signiant’s SaaS solution on AWS is called Media Shuttle. This product is used pervasively within the media and entertainment industry to quickly transfer very large files. Using a simple browser plugin or mobile app, users can send or share files of any size through a simple portal. Media Shuttle takes care of the transfer acceleration, security, scalability, elasticity, and resource management on the user’s behalf.

Architecture Evolution

One key feature of Media Shuttle is its delivery notification system, built on Amazon SES. When a file becomes available, the system will send an email to the user with a secure link for downloading the content. These notification emails will occasionally bounce or be caught in spam filtering systems which prevents users from retrieving their files, and generally results in a support call from the sender to figure out why the email was never received.

To improve the support team’s ability to resolve these issues while maintaining the privacy of the sender and email content, Signiant developed a simple system for tracking email bounces that has evolved over time. The initial solution, depicted below, was to subscribe an internal email distribution list to the Amazon SNS topic that received the bounce notifications. This provided simple alerts to the support team when emails bounced and was very easy to implement, but it presented scalability problems as adoption of the product grew. Pretty soon, there were thousands of notifications flooding the support team’s inboxes, and searching for a given customer’s email quickly became cumbersome.


In the next iteration of the solution, the email list was replaced by a database-backed web application running on Amazon Elastic Compute Cloud (Amazon EC2). The bounce notifications were delivered via the Amazon SNS topic to an Amazon Simple Queue Service (Amazon SQS) queue. The application would poll the queue and update a local database that the support team could then search through a simple web UI. Shortly after this version of the system was released, SES added the ability to capture notifications for deliveries in addition to bounces. Signiant added these notifications to the system as well, so that support engineers could see successful delivery statuses in addition to bounces.

The v2 architecture shown above worked well. It was more scalable than using an email distribution list, and the search capabilities were vastly improved. Despite these functional improvements, the new system required more maintenance than the team would have liked. They now had an additional server they were running just for this process, and the database they had chosen was having difficulties managing the increasing load. To optimize the system further, the team decided to re-engineer its solution to take advantage of the benefits of AWS Lambda and a serverless architecture.

The team designed a completely serverless architecture using Lambda to host the message processing logic and Amazon DynamoDB for its database. In the current architecture, instead of a PHP process polling a queue, they have a simple Lambda function written in Python subscribed to the SNS topics fed by SES. The Lambda function was easy to develop based on their existing PHP application that processed SQS messages. The relational database has been replaced by a DynamoDB table which is trivial to scale as the number of emails tracked continues to grow.

Signiant’s current architecture for capturing email status is depicted above. While this system captures delivery status of SES emails, the pattern being employed is extremely versatile and can be applied to any event-driven data processing workflow. By moving to a serverless architecture, Signiant not only decreased the direct cost of running this system, but also removed the operational overhead of managing a one-off server for this isolated task. “Porting our previous message processor to run on Lambda was really straightforward and the new design is much simpler and more robust than our previous server-based system,” said Dave North, the Director of DevOps at Signiant. The new architecture also eliminated the scaling concerns present in the other versions of the system. Using AWS Lambda, the message processors now scale seamlessly without any additional configuration or management, and the database’s throughput can be increased with a simple parameter update.


In this post, I’ve walked through how Signiant has evolved its architecture over time to take advantage of a serverless architecture design. Whether event data is delivered via an SNS topic as is the case here, sent directly to Lambda through a direct service integration as is the case with Amazon Simple Storage Service (Amazon S3), or generated from your own applications using the AWS SDK, you can build systems to capture, process and report on those events using this same basic architecture.