
Optimisation and growth of a new, scalable version of the client’s app managed internally in AWS Cloud
Executive summary
Challenge: To plan and modernise an existing solution which was unable to auto-scale and needed more flexibility and interconnectivity with third-party APIs.
Approach: Our team conducted bespoke Discovery and Product Design phases to pinpoint all areas for improvement and optimisations. The new version of the app is managed in AWS Cloud internally.
Result: The streamlined processes and automations in AWS Cloud offer more scalability, availability, and overall security of the system. The improvements enable faster business growth.
Table of contents
About the client
Our client is a leading provider of virtual data room solutions (VDR) – fully protected online information repositories for storing and distributing documents.
Business challenge
The client was searching for an IT technology consultant to plan and create a modernised version of the existing legacy application in AWS Cloud. The client’s developers’ team continued to maintain the original application in the Cloud managed by a third-party company and thus lacking flexibility and generating higher costs.
The challenge was to gather data about the performance of the application – the users’ feedback, already known issues – and use it to create a more scalable, more efficient version with reduced costs and improved design. Streamlined usability, responsiveness and integrity of the interface also became a key focus to our team.
Beginning with high-level workshops
The first step was to conduct a bespoke Discovery phase, which consisted of the initial workshops and the product design phase.
During the workshop phase, together with the client’s representatives we worked for a couple of days using a hybrid model – in person at Future Processing’s headquarters as well as online with other people engaged in the project.
Our comprehensive approach to the solution covered the client’s requirements presented in the framework. Our work spanned from business and technical analysis, through designing new system architecture, to gathering data concerning current users’ issues with the existing app.
Results of the Discovery phase
The workshop brought us tangible results:
- all factors currently influencing the client’s product were mapped by means of Future Processing’s Product Context Canvas,
- the map of the whole process covered by the VDR application was prepared,
- the proto-personas of the current end users with their goals and issues were created, which enabled us to use them while working on the new solution – this ensures the needs will be met and the risk of the problems reoccurring eliminated,
- the business needs and the new users’ potential problems were defined,
- the goals and priorities for the next couple of months were planned with a clear picture of the product’s future design and development path.
After it finished, the workshop paved the way for the further Product Design phase.
The Product Design phase
During the product design phase, Future Processing’s specialists prepared and delivered all the materials essential for the implementation stage. Our team members were in constant contact with the client’s decision-making representatives, the client’s internal end users of the solution as well as the technical team maintaining the current product. The close collaboration resulted in delivering the detailed plan for the development and implementation.
The plan consisted of:
- the technical architecture – the conceptual design,
- the backlog for the first 2 sprints,
- the project of the new interface – the visuals for the most important screens and guidelines.
Our specialists also refreshed the old solution so that it resembles the new one during the transitional period. This ensured that the end users are already getting used to the new interface and the changes that the client wants to implement after the finished MVP.
The collaboration between the client and the design team continued in an iterative Continuous Discovery model. During the implementation stage, Future Processing’s specialists worked closely with our client while specifying and prioritising the application’s functionalities in terms of business value and purpose.
AWS Cloud expertise for automation and optimisation
The improved solution created with best practices allows cost reduction because the client manages their AWS Cloud internally, without using a third-party orchestrator.
The new version of the app is built based on Microservices and runs in Kubernetes (AWS EKS). It is possible to use several instances at once, which is cost-effective and secures smooth workflow for end-users.
The solution enables dynamic scalability depending on the client’s current needs. The system also uses AWS S3, which is a storage service providing more data availability, security, and better performance.
All services that we chose are the most fitting for our client’s solution and leverage the great potential of AWS.
New version of the application
Our DevOps Engineers and Solutions Architects stay in close collaboration with the client to design and implement further improvements to the system.
What differentiates the application from the competition is a new Q&A and document review process. This is significant for the client, as it allows the end-users to work on shared documents in a coherent and streamlined way.
Our work saves time and our client’s internal resources, reducing the risk of possible mistakes in the processes.
We modernised the front-end of the application, which is continuously improving and allows the client’s platform to be updated more easily in the future. Our experts improved, among other things, a bulk rename feature through automation, which was previously done by exporting and importing Excel files – now it will be possible to do it in the app itself.
We resolved some of our client’s problems that hindered the organisation’s smooth growth.
In the old version of the system, the client could only scale up the application’s server to a certain degree and used a server with a manual recovery system. Additionally, they encountered problems with the individual server’s license that had to be retrieved every time a server stopped working. What’s more, prior to the migration, the client stored their data in virtual machines with limited possibilities.
Technologies used in the project




