AWS Lambda is the backbone of many serverless applications because of its flexibility, cost efficiency, and scalability. But Lambda comes with limitations that can hold high growth tech teams back. The 250 MB deployment package limit forces engineers to constantly optimize dependencies. Repeated S3 calls slow down execution and drive-up costs. Large model files and shared libraries are difficult to manage efficiently.
These issues add up to longer cold starts, slower response times, and more expensive workloads. To solve these challenges, teams need a persistent and scalable storage layer that fits seamlessly into a serverless architecture. EFS for serverless applications provides the missing piece. By mounting Elastic File System to Lambda functions, teams gain a new level of performance and simplicity.
1. Reduced Deployment Size
With Lambda EFS integration, large dependencies no longer need to be packaged with each function. Instead, libraries, datasets, and even machine learning models can live in EFS. This dramatically reduces deployment size, accelerates updates, and allows developers to focus on innovation instead of constantly trimming packages.
2. Improved Dependency Management
When multiple Lambda functions rely on the same datasets or libraries, managing duplicates becomes a headache. By storing them centrally in EFS, redundancy is eliminated. Teams gain cleaner dependency management and faster deployment cycles while ensuring every function works with the most up-to-date resources.
3. Persistent Data Storage
Unlike Lambda’s temporary storage, persistent storage for AWS Lambda with EFS ensures data is retained between executions. This makes it possible to process files, run inference on machine learning models, or store session data without having to reload from S3 every time. Developers gain consistency across executions and smoother workflows for applications that need data persistence.
4. Scalable Serverless Storage
As applications grow, so do storage requirements. EFS is designed to scale, supporting thousands of Lambda functions that can read and write simultaneously. This scalability ensures performance stays consistent even as workloads expand. It is an ideal foundation for scalable, serverless storage solutions.
5. Cost Optimization
By reducing repeated S3 calls and improving Lambda efficiency, costs naturally decrease. Functions run faster, require less bandwidth, and eliminate unnecessary duplication of data. This results in a more cost-efficient serverless environment that scales smoothly with business growth.
Results Achieved
Teams that adopt AWS Lambda with EFS typically see reduced deployment size, simplified dependency management, and persistent storage across executions. Multiple functions share the same storage without conflict, improving scalability while also optimizing costs.
One client IAMOPS supported implemented this exact integration and experienced faster execution, improved efficiency, and a more predictable cost structure.
Best Practices for Lambda and EFS Integration
To get the most out of Lambda and EFS, IAMOPS recommends several best practices. Use EFS Access Points to enforce secure and isolated access per Lambda function. Track performance with CloudWatch to optimize latency and throughput. Keep functions warm for workloads that are sensitive to cold starts. Always enforce encryption at rest and in transit for EFS data and consider enabling AWS Backup for disaster recovery.
Why IAMOPS
At IAMOPS, we help high growth companies design serverless solutions tailored for scale and efficiency. Our experts implement serverless architecture with AWS Lambda and EFS using best practices for security and performance. Beyond deployment, we provide monitoring, cost tracking, and performance optimization to keep applications running at peak efficiency.
As part of our DevOps Consulting Services, IAMOPS ensures your infrastructure is built to support growth without unnecessary complexity. Whether it is serverless design, CI/CD automation, or cost optimization, our team works alongside yours to deliver long-term reliability and scalability.
