About

Category

SaaS platform deployment ,

A SaaS-based platform from the UK helps businesses streamline operations with features like data import and video generation. However, its growing user base created scalability issues, while resource-intensive processes strained performance. They sought an AWS-based solution to ensure scalability, security, and operational efficiency for a seamless user experience.

Peerbits, with its deep expertise in AWS solutions, developed a custom deployment architecture, enhancing scalability, security, and automation to meet its unique challenges.

The Challenges

  • Scalability: As a SaaS platform,needed to handle unpredictable spikes in user activity. The existing infrastructure lacked auto-scaling capabilities, leading to performance bottlenecks during peak usage.
  • Data Import Handling: Bulk data imports caused high server loads, leading to system slowdowns and impacting the user experience.
  • Resource-Intensive Operations: Processes like PDF creation consume excessive CPU and memory, reducing overall system efficiency.
  • Secure Deployment: Ensuring data security while scaling requires a private and secure cloud environment.
  • Automated Deployment: Manual deployments caused downtime and increased the risk of errors during updates.

The Solution

  • Scalable architecture with ECS

    Deployed the platform on AWS Elastic Container Service (ECS) within a private VPC to ensure data security.

    Configured auto-scaling policies to handle fluctuating workloads, ensuring uninterrupted performance during peak usage.

  • Automated deployment pipeline

    Implemented a CI/CD pipeline with version control and automated deployment using ECR (Elastic Container Registry) and AWS CodePipeline.

    Achieved zero downtime by automating the deployment process, enabling updates without manual intervention.

  • Serverless data import with Lambda and SQS

    Re-architected the data import process using AWS Lambda and SQS (Simple Queue Service).

    Lambda functions processed data in chunks, reducing server load and ensuring a smooth import experience.

  • Serverless PDF generation

    Offloaded resource-intensive tasks like PDF generation to AWS Lambda, leveraging its ability to scale automatically based on demand.

    Used Lambda’s ephemeral compute model to reduce CPU load on the primary server.

  • Disaster Recovery and Rollback

    Enabled automatic recovery with AWS Backup and versioning to roll back to previous states during failures.

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Key features

  • Scalable SaaS platform: Seamless scaling with ECS auto-scaling and Lambda-based processing.
  • Secure private deployment: Isolated infrastructure within a private VPC for enhanced security.
  • Automated CI/CD: Fully automated deployment pipeline for zero-downtime updates.
  • Efficient resource management: Serverless architecture for heavy operations like data import, video, and PDF generation.
  • Data flow optimization: SQS-based queuing system to ensure smooth data handling without overloading servers.

Results

  • Improved scalability: Infrastructure handled traffic spikes without downtime.
  • Enhanced performance: Reduced server load with serverless processing for import and generation tasks.
  • Faster deployment: Automated CI/CD pipeline reduced deployment time by 70%.
  • Secure operations: Private VPC ensured compliance with data security standards.

  • Operational efficiency

    Improvements with the following :

    50% faster data imports

    3x improvement in task completion time for video and PDF generation.

    Zero downtime during updates.

Tech stacks we used

Compute

AWS ECS,EC2, AWS Lambda

Database

Amazon RDS, SQS

Storage

Amazon S3

Deployment Tools

AWS CodePipeline, ECR

Monitoring

Amazon CloudWatch, Datadog