Download Case StudyFullBeauty Brands has some workloads running on the MuleSoft cloud: Anypoint Platform. These workloads are mainly used to synchronize data between different on-premises and SaaS data sources. They realized they were paying too much for an enterprise license for MuleSoft products. IO Connect Services assessed the migration effort, laid a roadmap for all the activities needed, and led the realization from re-design to development, testing, and production rollout. Moreover, these new re-designs accounted for all the lessons learned at FullBeauty Brands and implemented more robust and resilient mechanisms to support these business flows. All the new workloads were designed following a serverless, cloud-native approach to take advantage of PaaS services available in AWS.
FullBeauty Brands was spending almost $300,000.00 a year for an under-utilized MuleSoft license. Moreover, the renewal cycles of the MuleSoft licensing were hard due to the number of legal activities involved in reviewing all documentation and agreements.
FullBeauty Brands use an expensive and robust memory cache system in their previews on-premises implementation, which can be easily replaced for AWS DynamoDB tables to significantly reduce costs without impacting application performance.
All the new FullBeauty Brands workloads were designed following a serverless, cloud-native approach to take advantage of PaaS services available in AWS.
FullBeauty Brands requires that all IT assets be deployed in a secured, private VPC that establishes a point-to-point connection to the on-prem data center via a VPN. All the deployed API endpoints must be private too. Therefore, the deployed API Gateway has a VPC endpoint accessible through VPN only.
Two data access patterns were identified:
This pattern followed an event-driven architecture to ensure the business flows' reliability, resiliency, and fault tolerance. Because of the usage of SNS topics, the solutions are now prepared to accept more business flows using the pub-sub mechanism built into them, allowing flexibility to grow in other areas not accounted for initially.
AWS DynamoDB tables are used as a replacement for the memory cache system when the code runs in Lambdas. Using TTS (time to live) enabled in the Dynamo Table items, Lambdas can use them as cache without compromising performance, and this approach is extremely cheapest than other cache systems. All events going through the different pipelines can be traced thanks to the joint usage of AWS CloudWatch Logs and AWS X-Ray, whereas all the deployed services are audited with CloudTrail.
The serverless computing pricing model is pay-as-you-go. It costs for resources one consumes and nothing when the application doesn’t run. Also, AWS takes care of infrastructure maintenance and updates so developers can spend more time on software development.
A serverless architecture in AWS has the potential to scale up and down according to application workload.
Developers don’t need to worry about resource distribution, scaling, application deployment, and workload intensity. AWS handles these issues for serverless architecture. Developers should only compile their code, zip it, and upload it to the new serverless platform to deploy new functions.
AWS serverless platforms support multiple programming languages like Node, Java, Python, C#, Ruby, Go, etc., so developers can choose the most convenient option for themselves.
This Serverless approach provides a fast, resilient, and high-availability environment for the application.
Save money by replacing physical hardware with expensive license fees with AWS services and only pay for what you use.
Deployments are more efficient with fully managed resource provisioning, maintenance, and backup.
