PTP Solves: Migrating AWS Lambda Runtimes for Secure, Compliant Biotech Applications
As biotech and pharmaceutical research organizations increasingly adopt cloud-based solutions to accelerate data processing and analysis, the tools that support these workflows must evolve to meet growing demands for performance, security, and scalability. For many businesses relying on AWS Lambda to run lightweight, event-driven applications, these changes can have a significant impact on operations. In particular, AWS regularly announces the end of support for older Python and Node.js runtimes, which means companies need to be aware of deprecations and have a plan of action.
In this post, we’ll explore the key reasons why migrating away from these outdated Lambda runtimes is crucial and how you can smoothly transition to newer, supported versions to ensure your serverless applications remain reliable, secure, and performant.
What Does AWS Lambda’s End of Support for Older Runtimes Mean?
AWS Lambda allows code to run without the need for provisioning or managing servers, supporting multiple programming languages, including Python, Node.js, Java, and more. Each of these languages has an associated runtime, which includes the programming language and the associated libraries and dependencies Lambda requires to execute the code. However, like any technology, languages evolve, and older versions eventually reach their end of life.
AWS has announced that it will stop supporting several older versions of Python and Node.js in Lambda. This means that Lambda functions running on these runtimes will no longer receive security patches, performance updates, or bug fixes, potentially leaving serverless workloads vulnerable or less efficient.
Key Risks of Using Outdated Runtime
1. Security Vulnerabilities
In the biotech and pharmaceutical industries, data security and patient confidentiality are of utmost importance. Once a runtime is deprecated, it no longer receives critical security updates. Research organizations processing sensitive data—whether related to clinical trials, genetic research, or drug discovery—may expose themselves to data breaches and compliance issues by continuing to rely on deprecated runtimes. Security vulnerabilities can lead to unauthorized access, data loss, or damage to research integrity.
2. Decreased Performance and Efficiency
In research environments where large datasets are analyzed and processed frequently, performance is critical. Older runtimes are not optimized for the latest AWS infrastructure, which can result in inefficient execution of Lambda functions. Biotech and pharma organizations that rely on Lambda for time-sensitive applications—such as real-time analytics, data pipelines, or simulations—may experience delays and increased compute costs if their functions are running on outdated runtimes. Migrating to a newer runtime ensures that Lambda functions run with the latest performance improvements, enabling faster processing and more efficient use of cloud resources.
3. Compatibility Issues with New Technologies
The pharmaceutical and biotech sectors often leverage cutting-edge technologies like machine learning, artificial intelligence, and high-performance computing. As new AWS features are released, older runtimes are not updated and, therefore, may not be compatible. This could limit the ability to integrate Lambda functions with emerging technologies and best practices. Updating runtimes ensures seamless integration with new AWS services, providing better support for complex research workflows and data pipelines.
4. Increased Operational Complexity
Biotech and pharmaceutical research organizations must comply with strict regulatory standards, such as 21 CFR Part 11, HIPAA, and GDPR. Operating Lambda functions on unsupported runtimes can create additional complexity, as troubleshooting and patching vulnerabilities will no longer be managed by AWS. Additionally, after a time specified by AWS, organizations will not be able to update or maintain the code in Lambda functions with very out-of-date runtimes. This greatly increases the likelihood of errors, downtime, and regulatory compliance risks. Migrating to a supported runtime simplifies operations and ensures that Lambda functions remain secure and compliant.
Benefits of Migrating to Supported Runtimes
1. Access to New Language Features and Enhanced Security
Migrating to newer Python and Node.js versions unlocks access to new language features and improvements that can be critical for modern research workflows. Newer releases of Python, for example, have offered improved support for asynchronous programming, which is essential for efficiently processing large amounts of data. Node.js has introduced new features like optional chaining and nullish coalescing in their updates, which enhance the ability to handle complex logic in research applications. Moreover, these newer versions receive regular security patches, which ensures that sensitive research data remains secure.
2. Improved Integration with AWS Services
AWS Lambda functions often serve as a core component of larger research systems that integrate with other AWS services like Amazon S3, DynamoDB, AWS Batch, Sagemaker, HealthOmics, and HealthLake. Newer runtimes are better optimized for these integrations, making it easier to build efficient, scalable research workflows. For example, AWS Step Functions, which is used to coordinate Lambda functions and other AWS services, works more effectively with the latest runtimes, enabling the creation of robust, automated research pipelines.
3. Better Compliance and Regulatory Alignment
In highly regulated industries like pharmaceuticals, maintaining compliance with industry regulations is crucial. Using outdated runtimes can create security and data integrity gaps that may violate compliance requirements. Newer runtimes are supported by AWS’s security framework, ensuring that Lambda functions remain in line with industry regulations and standards, reducing the risk of non-compliance during audits or inspections.
4. Enhanced Performance and Cost Efficiency
In the research space, optimizing the performance of Lambda functions can lead to research acceleration. Newer runtimes are more efficient in terms of execution speed and resource utilization. For example, functions running on these updated runtimes are able to process data faster, which reduces compute costs and time. In biotech and pharmaceutical research, where large volumes of data are processed regularly, these savings can quickly add up.
How to Migrate to Newer Runtimes
1. Evaluate Current Lambda Functions
The first step in migrating is identifying which Lambda functions are still running on outdated runtimes. This can be done by reviewing the AWS Lambda console and checking the runtime settings for each function.
2. Update Code for Compatibility
After identifying the functions to update, assess the codebase for compatibility with the newer runtime versions. This might involve:
- Updating dependencies to newer versions that are compatible with the most current Python or Node.js version
- Refactoring code to take advantage of new language features
- Testing the updated functions to ensure they perform as expected in the new runtime environment
3. Test, Deploy, and Monitor
Testing is crucial to ensure that Lambda functions work correctly after migration. Biotech and pharmaceutical companies can use AWS CloudWatch for logging and monitoring to track the performance of the updated functions. Once testing is complete, the updated functions can be deployed into production.
4. Optimize and Scale
After migrating, organizations should monitor the performance of Lambda functions and look for opportunities to optimize. AWS CloudWatch metrics and AWS X-Ray can help track function execution times, resource usage, and error rates, ensuring the system runs smoothly as research needs scale.
Benefits of Well-Architected Framework Review
A Well-Architected Framework Review (WAFR) is a valuable process for identifying issues that may exist in an AWS Lambda environment. By conducting a review, organizations can assess their cloud infrastructure against AWS’s best practices across five key pillars: operational excellence, security, reliability, performance efficiency, and cost optimization. As part of this review, an evaluation of the Lambda functions is performed, ensuring Lambda functions are operating within a VPC, using encrypted environmental variables, and following the principle of least privilege. This proactive assessment helps pinpoint areas that may be a security risk or cost liability. A Well-Architected Review also offers recommendations on how to neutralize these issues, ensuring the organization’s environment is aligned with the latest AWS standards and best practices. For more information about conducting a Well-Architected Framework Review with PTP, including options to fully fund the project, fill out the form at the bottom of this page or contact info@ptp.cloud.
Conclusion
The end of support for older Python and Node.js runtimes in AWS Lambda presents a significant challenge for biotech and pharmaceutical research organizations relying on Lambda to power their critical applications. However, migrating to newer runtimes is essential for maintaining security, performance, and regulatory compliance. By updating to supported runtimes, research organizations can improve the efficiency and scalability of their workflows, ensure better data protection, and reduce operational complexities.
Taking proactive steps to migrate to the latest supported versions will ensure that Lambda functions remain secure, cost-effective, and capable of supporting the next generation of scientific breakthroughs.