How We Reduced Infrastructure Costs By 40 Times for an LMS System

One of the leading LMS systems hired us to improve their security model and reduce infrastructure costs.

The client is one of the leading LMS systems in the US with over 300+ customers having hundreds of active users. Initially, the platform was built for teachers to build exams and assessments for their students. Then the project was pivoted: fully rethought and adjusted for the first paid enterprise-level client.

The client’s software platform is utilized across a range of organizational areas such as learning and training, survey research, human resources, leadership, corporate strategy, marketing, and content licensing and delivery.

The client initially contacted us to help improve its security model and reduce infrastructure costs. After a project discovery phase, we have prepared a list of technical issues and technology solutions that would help solve them.

Keep reading the LMS case study to know how we:

  • Reduced infrastructure costs for the client
  • Introduced the AWS multitenancy architecture
  • Improved the client’s multi tenant security model
  • Implemented automated deployment pipelines.
Client Profile
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Location
Ponte Vedra, FL, US
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Industry
Learning Management System
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Services
Security Model Redesign, AWS Infrastructure Improvement, Micro-Services Architecture Design, Monitoring System Setup
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Team Size

10

Challenges

Design & Implement Security Model

The client’s existing platform security model didn’t have user entities and this issue generated lots of complexity in managing system’s permissions. Also, LMS system users experienced multiple challenges in sharing data within the platform due to the scalability limits.

AWS Infrastructure Re-Deployment & Redesign

The client had many organizations (>300) that required frequent system deployments held on the platform’s side. It means that each deployment procedure should have been processed with a separate version of the system per each organization manually. This scenario required several weeks of manual deployment activities to serve >300 companies that led to high maintenance costs for a client.

Single Sign On Implementation

Multiple companies using the LMS system wanted to utilize their own credentials to log in to the system. The platform had no such functionality due to the absence of SSO features that provided organizations with additional difficulties.

Setup Monitoring System

The platform had no monitoring tools to track current and potential technical issues and inform the internal client’s team about the existing problems. This means the client had no real-time metrics to validate the LMS system’s production health and find the root causes of performance issues.

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Solutions

1
Multitenancy Architecture Setup
Multitenancy Architecture Setup

We introduced multitenancy to help the client reduce AWS infrastructure costs and minimize the deployment cycle per each organization. A multi tenant security model means there is only one version of the LMS system capable to handle requests from different organizations simultaneously.

This way, we helped the client significantly minimize maintenance efforts as now there is no need to deploy multiple different tenants separately. System re-deployment currently takes a few minutes compared to several weeks of manual work before which allows the client to save a bill.

Multitenancy Architecture Setup
2
AWS Infrastructure Optimization
AWS Infrastructure Optimization
AWS Infrastructure Optimization

We optimized and improved the client’s AWS infrastructure by utilizing AWS Lambdas – a serverless offering by Amazon. This allowed to change the infrastructure model and start using a pay-per-usage option which means that AWS bills for actual work only.

Infrastructure optimization with AWS Lambdas helped us minimize maintenance costs for multiple LMS system components as currently there are server idle periods the client should pay for.

3
Infrastructure AutoScaling Implementation
Infrastructure Auto-Scaling Implementation

We implemented the auto-scaling approach for the platform to utilize resources efficiently and optimize the bill. This solution means that the LMS system automatically tracks and validates incoming traffic.

If the system detects the lack of resources needed to perform an operation, it automatically creates additional instances of the servers. And vice versa, in case the system detects inefficient usage of resources, then it automatically disposes extra servers.

So, auto-scaling approach helped the client to improve and optimize usage of platform resources thus minimizing total infrastructure costs.

Infrastructure AutoScaling Implementation
4
Automated Deployment Implementation
Automated Deployment Implementation
Automated Deployment Implementation

As a part of multitenancy, we optimized the platform deployment process by implementing automated and deployment pipelines. They transform manual deployment operations into automated which allows to deploy the system on any environment. This approach minimizes the deployment cycle and eliminates any errors caused by the human factor during operations.

Additionally, we adopted the “infrastructure-as-code“ principle. It also brought high automation to the infrastructure setup process, including adjusting servers, databases, network configurations, etc. This solution helped minimize the deployment time required to set up additional testing environments.

5
transparent monitoring system
Transparent Monitoring System Setup

The client’s platform had no monitoring tools that would allow tracking current and potential errors and technical issues to ensure the system’s health status. We introduced the monitoring functionality that automatically collects metrics of the system in real-time. They include performance, CPU/memory utilization, number of requests, and other crucial logs.

The implemented monitoring system helps the client’s technical team to find root causes for the issues and perform system health checks to ensure the system works error-free. In case of any alerts on production environment, the tool automatically notifies the internal team so it can address challenges in a timely fashion.

transparent monitoring system

Results

256 roi boost

256% ROI Boost

Our technical solutions allowed to minimize the deployment cycle by 40x times thus boosting ROI by 256%.

For example, the old approach meant manually deploying 40 clients which took 40 hours * $45 (i.e. an average DevOps rate) = $1800. In contrast, the new model implies auto-deployment of 40 clients periodically = 1 hours * $45 = $45.

What’s more, the client is planning to move 260 LMS system organizations to a new platform version, and here is the bill comparison:

Old approach: Manual deployment 260 clients = 260 hour * $45 = $11700.

New approach: Auto deployment 40 client periodically = 7 hours * $45 = $315.

256 roi boost
40x-Time Infrastructure Costs Savings

40x-Time Infrastructure Costs Savings

Most of our technology solutions helped the client minimize the AWS infrastructure and maintenance costs.

Automated deployment pipelines, multitenancy and micro-services architecture, an auto-scaling approach, and the AWS infrastructure as code principle summarily allowed the client to decrease infrastructure costs by 40 times.

Tech Stack

AWS Cognito
Amazon SQS
AWS EKS
AWS RDS
AWS Lambda
VueJS
.NET Core

The project is not completed yet but we are tracking to schedule. Although the complete requirements were not flushed out, the team has been flexible and providing recommendations/suggestions on design and user experience.

- Client