Community College District Deploys ERP System in AWS for Auto-scaling and DevOps Capabilities

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CLIENT SUCCESS |

COMMUNITY COLLEGE DISTRICT DEPLOYS ERP SYSTEM IN AWS FOR AUTO-SCALING & DEVOPS CAPABILITIES

About the Company

The Ventura County Community College District (VCCCD) is the college district serving all of Ventura County, California. The district is a member of the California Community College system that includes 113 community colleges statewide.

The Vision and Challenge

Ventura County Community College District (VCCCD) was already a Banner ERP solution user and needed a strategic service provider that could design and build out two Banner 9 ERP environments within the AWS Cloud. Both environments needed to be architected to allow for future growth and re-usability of automated build scripts as future AWS Cloud Banner 9 environments are created for test, pre-production, and production.

Steps required to ensure the smooth transition of Banner 9 ERP solution included:

  • Prepare the core servers and services according to VCCCD requirements
    Migrate databases
    Building servers
    Automate the Application Deployment pipeline
    Implement SSO with Banner 9
    Implement New Relic as the monitoring solution

The Outcome

VCCCD selected Infiniti, an InterVision Company to migrate its Banner 9 environment to AWS because of our extensive cloud services experience and validation in the education space. After  a successful migration of Banner 9 to AWS, VCCCD now benefits from fully automated, continuous integration and delivery pipelines for multiple applications. VCCCD now experiences zero-downtime deployments, autoscaling, and savings on technical costs. In addition to this, there is now enterprise wide, fully automated application and infrastructure performance monitoring built in. Infiniti will be working with VCCCD to support ongoing efforts to implement CIS Standards and NIST security standards.

AWS Cloud services utilized in this project:

  • EC2
    ECS
    Boto – AWS Python Library
    Route 53
    EFS Shared File System
    S3
    Cloudwatch
    Cloudtrail
    Cloud Formation Scripts
    Cloud9 – AWS Code IDE in the cloud to develop and test Python scripts.
    Application Load Balancers
    Auto-Scaling and load-balancing across AZs
    KMS – All data volumes are encrypted
    SSM – We follow best practices and store credentials in AWS’ Parameter Store.

3rd Party Products/Tools utilized in this project:

  • Docker
    New Relic
    Github
    Jenkins
    Rancher – Container Management