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High Load Cloud Adaptive Learning Solution

Challenge
Client, Startup company with adaptive learning solution for K1-6 from Europe, came to ENBISYS with initial request to maintain their system while rapidly scaling up their Product. Ensuring stable performance for existing users (more than 10 000) was crucial. Additionally, Client opted for integrating Elo rating system and/or IRT algorithms for predicting student's performance and automated content generation and supply. Later on, new requirements for the Product were defined and updated version of Product like new Android and iOS application and enhanced Student's dashboard are supposed to be released in 2018.
Approach
Since Client's MVP experienced immediate tremendous success and was distributed in schools in several European countries it was absolutely necessary to provide reliable maintenance of the system. ENBISYS started with recovering of running Product and providing stable performance for Client's existing users. To support more than 700 000 users we apply all High-load instruments and technologies such as AWS, Mongo DB and Redis. After securing reliable performance we continued to develop the Product deploying and testing new features in real time applying all the newest UI/UX trends. We created highly efficient distributed team to augment Client's IT experts group.
After 3 years a decision to convert the whole architecture to microservices was made, as well as IRT algorithms implementation.
Solution
ENBISYS faced a unique challenge to support continuous growth of a High-load complex system. Forecasts that number of users will be 10 times bigger than at the beginning set the pace of work and responsibility to be very high. We created 3 SCRUM teams for support, testing and new features deployment. DevOps and back-end are completely secured by ENBISYS experts. Algorithms to further enhance system's adaptivity for every scholar are being explored and implemented.
Technologies
  • .NET Core 2.1
  • ASP.NET Core
  • .NET 4.7
  • ASP.NET MVC 5
  • MS SQL Server 2016
  • Mongo DB
  • Redis
  • KnockoutJS
  • Angular 6
  • AWS EC2
  • AWS Lambda
  • AWS S3
  • AWS CloudFront
  • AWS CloudFormation
  • AWS SQS
  • AWS SNS
  • NodeJS

High Load Cloud Adaptive Learning Solution

Challenge
Client, Startup company with adaptive learning solution for K1-6 from Europe, came to ENBISYS with initial request to maintain their system while rapidly scaling up their Product. Ensuring stable performance for existing users (more than 10 000) was crucial. Additionally, Client opted for integrating Elo rating system and/or IRT algorithms for predicting student's performance and automated content generation and supply. Later on, new requirements for the Product were defined and updated version of Product like new Android and iOS application and enhanced Student's dashboard are supposed to be released in 2018.
Approach
Since Client's MVP experienced immediate tremendous success and was distributed in schools in several European countries it was absolutely necessary to provide reliable maintenance of the system. ENBISYS started with recovering of running Product and providing stable performance for Client's existing users. To support more than 700 000 users we apply all High-load instruments and technologies such as AWS, Mongo DB and Redis. After securing reliable performance we continued to develop the Product deploying and testing new features in real time applying all the newest UI/UX trends. We created highly efficient distributed team to augment Client's IT experts group.
After 3 years a decision to convert the whole architecture to microservices was made, as well as IRT algorithms implementation.
Solution
ENBISYS faced a unique challenge to support continuous growth of a High-load complex system. Forecasts that number of users will be 10 times bigger than at the beginning set the pace of work and responsibility to be very high. We created 3 SCRUM teams for support, testing and new features deployment. DevOps and back-end are completely secured by ENBISYS experts. Algorithms to further enhance system's adaptivity for every scholar are being explored and implemented.
Technologies
  • .NET Core 2.1
  • ASP.NET Core
  • .NET 4.7
  • ASP.NET MVC 5
  • MS SQL Server 2016
  • Mongo DB
  • Redis
  • KnockoutJS
  • Angular 6
  • AWS EC2
  • AWS Lambda
  • AWS S3
  • AWS CloudFront
  • AWS CloudFormation
  • AWS SQS
  • AWS SNS
  • NodeJS

High Load Cloud Adaptive Learning Solution

Challenge
Client, Startup company with adaptive learning solution for K1-6 from Europe, came to ENBISYS with initial request to maintain their system while rapidly scaling up their Product. Ensuring stable performance for existing users (more than 10 000) was crucial. Additionally, Client opted for integrating Elo rating system and/or IRT algorithms for predicting student's performance and automated content generation and supply. Later on, new requirements for the Product were defined and updated version of Product like new Android and iOS application and enhanced Student's dashboard are supposed to be released in 2018.
Approach
Since Client's MVP experienced immediate tremendous success and was distributed in schools in several European countries it was absolutely necessary to provide reliable maintenance of the system. ENBISYS started with recovering of running Product and providing stable performance for Client's existing users. To support more than 700 000 users we apply all High-load instruments and technologies such as AWS, Mongo DB and Redis. After securing reliable performance we continued to develop the Product deploying and testing new features in real time applying all the newest UI/UX trends. We created highly efficient distributed team to augment Client's IT experts group.
After 3 years a decision to convert the whole architecture to microservices was made, as well as IRT algorithms implementation.
Solution
ENBISYS faced a unique challenge to support continuous growth of a High-load complex system. Forecasts that number of users will be 10 times bigger than at the beginning set the pace of work and responsibility to be very high. We created 3 SCRUM teams for support, testing and new features deployment. DevOps and back-end are completely secured by ENBISYS experts. Algorithms to further enhance system's adaptivity for every scholar are being explored and implemented.
Technologies
  • .NET Core 2.1
  • ASP.NET Core
  • .NET 4.7
  • ASP.NET MVC 5
  • MS SQL Server 2016
  • Mongo DB
  • Redis
  • KnockoutJS
  • Angular 6
  • AWS EC2
  • AWS Lambda
  • AWS S3
  • AWS CloudFront
  • AWS CloudFormation
  • AWS SQS
  • AWS SNS
  • NodeJS

Let's discuss your Case!
Let's discuss your Case!
Let's discuss your Case!