Flentas helps FinTech Company Migrate from Azure to AWS

Client Profile

Cassbana is a technology solution company that builds financial identities for underserved communities in Egypt through micro-lending, building a behavior-based scoring system, and making them the future data-based financial advisory collective.

Key Requirement

Cassbana was looking for a technology partner who could help migrate their Azure Cloud infrastructure to AWS Cloud concisely without downtime. They planned to control their overall cost, improve security, and scale their operations with fast deployment strategies.

High-level Challenges:

On-demand scale to meet the business growth Streamlined Infrastructure operations and security Establishment of a private connection from Cassbana to the vendor company While migrating their mission-critical Application to the AWS cloud, below are things to be considered,

AWS EC2 – To run the web services consumed by the Web Application
MYSQL database backup to be taken during non-business hours
RDS to be used for MYSQL databases
Databricks setup for ETL workloads
ECR is to be used to store all the container-based images
Application to be deployed behind the load balancer
EKS cluster setup for the deployment of microservices
API Gateway deployment to meet business requirements

Solution

Flentas provided a solution to Cassbana's need to migrate its Azure Cloud infrastructure to AWS Cloud quickly without downtime. Flentas proposed to engage with Cassbana to define the roadmap, plan, design, and execute the implementation plan, and work closely with them to deploy it on the AWS cloud.

The proposed solution for setting up the Application on AWS includes the following services:
- AWS EC2 – To run the web services consumed by the Web Application
- Load-Balancer – To load balance on multiple EC2 Instances
- RDS MYSQL – To Setup the MYSQL database on RDS with read replicas in AWS by migrating them from Azure
- Amazon VPC – To segregate the network between multiple environments and application tier
- ECR – To store container images
- EKS Cluster – To run and deploy several micro-services applications
Modernization of the Application to leverage object storage services by using fully managed AWS services like S3
The migration of Cassbana's existing API and business logic was carried out with the help of API Gateway and Lambda Functions, allowing for increased efficiency and cost-effectiveness
Migration of Data lakehouse using Databricks cluster setup in AWS for ETL workloads
We set up Cassbana's Data Analytics platform using various AWS services such as DynamoDB, Amazon Quicksight, Athena, and Glue. It allowed for better data analysis and insights
Planned the cutover for Cassbana applications and migrated their workload from Azure to AWS
Establishing site-to-site connectivity with respective vendors
Set up of basic monitoring system to alert the critical thresholds and Identify workload patterns

Components and Services

AWS EC2
Amazon Load Balancer
DynamoDB
ECR
EKS
Lambda
Glue
Amazon S3
Quick Sight
API Gateway
Databricks (Marketplace)
Application Load Balancer
CloudTrail
CloudWatch

Our Approach

The decision was made to use the AWS Ireland Region for hosting all AWS infrastructure resources
Each tier was further segregated into multiple subnets residing in each AZ available in the region for high availability setup
All the applications that support Active-Active setup were placed behind a load balancer
Azure Database dump has been taken and restored on the newly created RDS instance. Database users were created accordingly. A replica of the RDS instance was also created
Site-to-Site VPN connectivity setup was done, which is used for Applications calling the partner APIs and databases
Required docker images were also migrated from the Azure container registry to AWS ECR
AWS CloudWatch was used for monitoring and setting up alerts and logs for all metrics of the infrastructure
Databricks cluster setup was done from the AWS marketplace
To set up an Amazon EKS cluster for microservices applications, created an EKS cluster and launched worker nodes into it. Then configured the worker nodes to join the cluster and deployed microservices applications using Kubernetes Helm charts
Deployed a suite of AWS services to support data analytics use cases. It included AWS Glue, which is used for ETL (extract, transform, load) jobs to move and transform data into AWS data stores
We also used Amazon Quicksight as our business intelligence tool for data visualization and reporting. We utilized Amazon S3 as our primary data lake to store and manage our data. We leveraged Amazon Athena for querying data stored in S3 using SQL queries

Cutover Approach

API gateway was set up for all B2B applications, which allowed for forwarding the traffic to Azure endpoints
After the Infra setup was completed, a DB pipeline was created to migrate the data from Azure to AWS
After the App server setup got completed along with the necessary VPN connectivity, the Application was exposed via ALB
In the Maintenance window, the Backend URL was changed to AWS in the API gateway to ensure no downtime was required
For K8s services, cluster setup was completed first, and then one by one Application was deployed into the K8s cluster
After deploying the Application, the respective application database was migrated to AWS
Databricks cluster was setup from the marketplace, and Object storage data migrated to S3
DB – DMS Pipeline created for migrating data from Azure to AWS
EC2 – Application deployed manually on EC2, and data restored via S3
K8s – Services deployed in cluster manually
Jenkins - Pipelines were migrated separately, as it wasn't impacting migration

Measuring Success

Cloud Migration in less than two months Cassbana workloads were migrated to AWS and are live within two months.

Seamless Infrastructure Deployment Successfully deployed infrastructure components such as networking, database, compute, EKS cluster, and AWS services (S3, Lambda) using Terraform in a Non-Prod and Prod environment.

Databricks on AWS Successfully deployed all remaining Databricks components manually.

Rearchitected the data lakehouse solution Flentas had helped them rearchitect their data lakehouse solution to Databricks, data analytics solution using glue, Athena, quick sight, and SObject storage solution to S3.

Application and Infrastructure Monitoring AWS CloudWatch dashboards are made available to monitor all the applications. And SNS Subscriptions were created to notify the System of changes.