Automating Infrastructure for Memorizz using AWS CloudFormation
Problem Statement
Memorizz is a dynamic web and mobile application designed to help users create, manage, and share personalized events, media files, and photobooks. As the product scaled and integrated advanced capabilities such as AI-powered captioning using AWS Bedrock and Lambda-based image processing, the existing manual infrastructure setup led to the following challenges:
• Difficulty in managing consistent environments (Dev, Stage, Prod) with uniform configurations. • Error-prone manual provisioning leading to discrepancies across deployments. • Time-consuming infrastructure updates and scaling tasks. • Limited visibility and version control over infrastructure changes. Memorizz required a fully automated, repeatable, and auditable infrastructure provisioning approach that could help them scale reliably while maintaining performance, compliance, and cost-efficiency.
Solution Offered by HabileLabs
HabileLabs partnered with Memorizz to transform their AWS infrastructure deployment process by leveraging AWS CloudFormation and aligning with Infrastructure as Code (IaC) best practices. The core objective was to standardize deployments across multiple environments, eliminate manual interventions, and enforce security and scalability principles using CloudFormation templates and AWS-native automation tools.
Key Solution Highlights:
Infrastructure Automation with CloudFormation
All core infrastructure components were defined as modular CloudFormation templates, including:
- VPCs, subnets, route tables, internet gateways
- ECS Fargate clusters and services (for Beta, Stage, and Production)
- ALB, target groups, listeners
- S3 buckets for original and resized image storage
- DynamoDB tables and RDS MySQL database configuration
- CloudWatch Logs, Metrics, and Alarms for monitoring
- IAM roles, policies, and secrets management
CI/CD Integration
A CodePipeline and CodeBuild-based deployment pipeline was defined via CloudFormation, enabling automated build and deployment of container images to ECS from the source repository (Bitbucket).
- Each stage (Source → Build → Deploy) was codified for transparency and auditability.
Multi-Environment Support
- Separate CloudFormation stacks were created for Beta, Stage, and Production environments.
- Parameterized templates enabled environment-specific configurations (e.g., CPU/memory, subnet mappings, image tags, scaling policies).
Monitoring, Logging, and Alerting
CloudFormation templates provisioned:
- CloudWatch Alarms for ECS, Lambda, API Gateway, and RDS metrics.
- Log Groups for ECS and Lambda to centralize logs.
- X-ray tracing enabled for monitoring user flows.
Security & Compliance Automation
- Automated provisioning of IAM roles with least privilege, Secrets Manager entries, and KMS encryption keys via CloudFormation.
- Configured security groups and NACLs with strict inbound/outbound rules as per NETSEC-001 guidelines.
Business Outcomes & Benefits
- Consistency & Repeatability: Each environment now mirrors the other exactly, reducing bugs and deployment mismatches.
- Rapid Recovery: In the event of a failure, entire stacks can be re-deployed within minutes using CloudFormation templates.
- Scalability: Integrated Auto Scaling policies and containerized ECS workloads scale seamlessly based on load.
- Audibility & Governance: All changes to infrastructure are tracked and version-controlled through Git-based CloudFormation templates.
- Operational Efficiency: Deployment time reduced by over 60% across environments with standardized templates.
Conclusion
Through the use of AWS CloudFormation and other native DevOps tools, Habilelabs Pvt. Ltd. successfully delivered a fully automated, secure, and scalable infrastructure deployment solution for Memorizz. This engagement not only modernized their operations but also aligned them with AWS Well-Architected best practices and CloudFormation Service Delivery expectations.
