Signeasy is a number one eSignature firm that gives an easy-to-use, cross-platform and cloud-based eSignature and doc transaction administration software program as a service (SaaS) answer for companies. Over 43,000 firms worldwide use Signeasy to digitize and streamline enterprise workflows. On this weblog, you’ll be taught why and the way Signeasy used AWS Serverless to create a SaaS dashboard for his or her tenants.
Signeasy’s SaaS tenants requested for a neater strategy to get insights into tenant utilization information on Signeasy’s eSignature platform. To deal with that, Signeasy constructed a self-service utilization metrics dashboard for his or her SaaS tenant utilizing AWS Serverless.
Utilization experiences
What was it like earlier than the self-service dashboard expertise? Previously, tenants requested Signeasy to share their utilization metrics by way of assist channels or emails. The Signeasy assist staff compiled the experiences after which emailed the report again to the tenant to service the request. This was a repetitive handbook job. It concerned querying a database, fetching and collating the outcomes into an Excel desk to be emailed to the tenant. The turnaround time on these handbook experiences was eight hours.
The next desk illustrates the report format (with instance information) that the tenants obtained by way of e-mail.
The design
Signeasy deliberated quite a few elements and arrived on the following design issues:
- Improve tenant expertise — Present the experiences to tenants on-demand, utilizing a self-service mechanism.
- Scalable aggregation queries — The experiences ran aggregation queries on utilization information inside a time vary on a relational database administration system (RDBMS). Signeasy thought of transferring to an information retailer that has the scalability to retailer and run aggregation queries on hundreds of thousands of data.
- Agility — Signeasy needed to construct the module in a time-bound method and ship it to tenants as shortly as potential.
- Scale back infrastructure administration — The load on the experiences infrastructure that shops and processes information will increase linearly in relation to the depend of utilization experiences requested. This meant a rise within the undifferentiated heavy lifting of infrastructure administration duties comparable to capability administration and patching.
With the design issues and constraints known as out, Signeasy started to search for the acceptable answer. Signeasy determined to construct their utilization experiences on a serverless structure. They selected AWS Serverless, as a result of it gives scalable compute and database, utility integration capabilities, computerized scaling, and a pay-for-use billing mannequin. This reduces infrastructure administration duties comparable to capability provisioning and patching. Confer with the next diagram to see how Signeasy augmented their current SaaS with self-service utilization experiences.
Structure of self-service utilization experiences

Determine 2. Structure diagram depicting the info stream of the self-service utilization experiences
- Signeasy’s tenant customers log in to the Signeasy portal to authenticate their tenant identification.
- The Signeasy portal makes use of a mixture of tenant ID and person ID in JSON Internet Tokens (JWT) to differentiate one tenant person from one other when storing and processing paperwork.
- The paperwork are saved in Amazon Easy Storage Service (Amazon S3).
- The customers’ actions are saved within the transactional database on Amazon Relational Database Service (Amazon RDS).
- The person actions are additionally written as messages into message queue on Amazon Easy Queue Service (Amazon SQS). Signeasy used the queue to loosely couple their current microservices on Amazon Elastic Kubernetes Service (Amazon EKS) with the brand new serverless a part of the stack.
- This permits Signeasy to asynchronously course of the messages in Amazon SQS with minimal modifications to the present microservices on EKS.
- The messages are processed by a report author service (Python script) on AWS Lambda and written to the experiences database on Amazon Timestream. The experiences database on Timestream shops metadata attributes comparable to person ID and signature doc ID, signature doc despatched, signature request obtained, doc signed, and signature request cancelled or declined, and timestamp of the info level. To view utilization experiences, the tenant directors navigate to the Studies part of the Signeasy portal and choose Utilization Studies.
- The utilization experiences request from the (tenant) Internet Shopper on the browser is an API name to Amazon API Gateway.
- API Gateway works as a entrance door for the backend experiences service operating on a separate Lambda perform.
- The experiences service on Lambda makes use of the person ID from login particulars to question the Amazon Timestream database to generate the report and ship it again to the net consumer by way of the API Gateway. The report is instantly out there for the administrator to view, which is a big enchancment from having to attend for eight hours earlier than this self-service function was made out there to their SaaS tenants.
Following is a mock-up of the Utilization Studies dashboard:
So, how did AWS Serverless assist Signeasy?
Amazon SQS persists messages as much as 14 days, and permits retry performance for message processed in Lambda. Lambda is an event-driven serverless compute service that manages deployment and runs code, with logging and monitoring by way of Amazon CloudWatch. The combination of API Gateway with Lambda helped Signeasy simply deploy and handle the backend processing logic for the experiences service. As utilization of the experiences grew, Timestream continued to scale, with out the necessity to re-architect their utility. Signeasy continued to make use of SQL to question information throughout the experiences database on Timestream in a price optimized method.
Signeasy used AWS Serverless for its performance with out the undifferentiated heavy lifting of infrastructure administration duties comparable to capability provisioning and patching. Signeasy’s assist staff is now extra targeted on higher-level organizational wants comparable to buyer engagements, quarterly enterprise critiques, and signature and cost associated points as a substitute of managing infrastructure.
Conclusion
- Going from eight hours to on-demand self-service (0 hours) response time for utilization experiences is a big enchancment of their SaaS tenant expertise.
- The AWS Serverless providers scale in and out to fulfill buyer wants. Signeasy pays just for what they use, they usually don’t run compute infrastructure 24/7 in anticipation of requests all through the day.
- Signeasy’s assist and buyer success groups have repurposed their time towards larger worth buyer engagements vs. capability, or patch administration.
- Growth time for the Utilization Studies dashboard was two weeks.
Additional studying