When it comes to serverless architectures using AWS Lambda, one of the major decisions is how to manage different execution environments such as development (dev), staging, and production (prod). You can either leverage the versatility of Lambda versions and aliases or opt for distinct Lambda functions tailored to each specific environment. Let’s explore the advantages and drawbacks of these methodologies.

Using Lambda Versions and Aliases

Lambda versions are an integral part of AWS Lambda’s versioning feature. When you publish a version of your Lambda function, AWS captures the code and configuration and assigns a unique version number. You can then create aliases, which are named pointers, to any of these versions.


  1. Version Control: Lambda versions enable you to snapshot your code, preserving a particular state. This configuration ensures that if a function works in the staging environment, it will work the same way in production as long as you promote the same version.

  2. Streamlined Resource Management: All versions of a function share the same AWS resources like IAM role, environment variables, VPC settings, etc. This can simplify configurations and permissions management.

  3. Smooth Promotion: With aliases pointing to different versions, it becomes easy to promote code from one environment to another. For instance, once testing on a dev alias is complete, you can update the prod alias to point to the latest version.

  4. Blue/Green Deployment: Using aliases and versioning, you can redirect some of the traffic to a new version, test it out, and then gradually increase the traffic to the new version. This ensures smooth transitions and reduces risks during deployments.


  1. Complexity: The versioning system can become complex, especially if multiple developers work and deploy. Tracking which version is associated with which alias can be challenging.

  2. Resource Contention: If environment configurations like databases or endpoints differ between environments, managing them within the same function can be cumbersome.

  3. Deployment Risks: If not managed carefully, there’s a risk of inadvertently updating a production version when you intend to update a dev version.

Separate Lambdas for Different Execution Environments

In this strategy, you have distinct Lambda functions for each environment (e.g., myFunction-dev, myFunction-staging, myFunction-prod).


  1. Isolation: Each environment is completely isolated, ensuring that changes or errors in one environment will not accidentally affect another.

  2. Simplicity: It’s straightforward. One function = one environment. There’s no need to worry about versions or aliases.

  3. Resource Segregation: Each function can have its own set of resources, environment variables, and permissions, tailored for its specific environment.

  4. Flexible Resource Allocation: If your production environment requires more resources or different settings, it will not affect your dev environment.

  5. Security: By using separate IAM roles and permissions for each Lambda function, you can ensure that development functions don’t have unnecessary access to production resources.


  1. Deployment Complexity: Deploying changes requires separate deployments for each environment which can be tedious and error-prone. Even though the source code can originate from the same repository or branch, you are deploying it as separate entities in AWS. This can lead to inconsistencies if not appropriately managed.

  2. Management Overhead: With multiple functions, you have more infrastructure to manage, which can increase the complexity of deployment and monitoring. This can complicate monitoring, logging, and tracing, especially if the functions aren’t named or tagged systematically.

The Hybrid Approach: Best of Both Worlds

In some scenarios, neither the strict Lambda versioning nor the entirely separate Lambda strategy fits the bill perfectly. Here, a hybrid approach can come to the rescue.

How It Works:

  1. Common Behavior Across Branches: Use Lambda versions and aliases for branches where the behavior is consistent. This leverages the benefits of unified codebase management and ease of environment switching.

  2. Distinct Environment Resources: For environments like ‘dev’, ‘staging’, and ‘prod’, where resource configurations are significantly different, deploy separate Lambda functions. This capitalizes on the benefit of strict isolation.


  1. Flexibility: You get the benefits of environment switching from versions and aliases while also ensuring strict resource isolation where needed.

  2. Efficient Management: Common behavior branches don’t multiply your management overhead, while distinct environments maintain their autonomy.


  1. Increased Complexity: The initial setup is more intricate, as you’ll manage both versions/aliases and separate functions.

  2. Monitoring: With this approach, monitoring strategies need to be more detailed to cater to both paradigms.

Implementation Tips

  1. Configuration Management: Use tools like AWS Systems Manager Parameter Store or AWS Secrets Manager to manage environment-specific configurations. This helps in keeping secrets and configurations out of the code.

  2. Infrastructure as Code (IaC): Tools like AWS CloudFormation or the Serverless Framework can be instrumental in managing a hybrid strategy. They allow you to define and deploy your infrastructure using code, ensuring consistent and maintainable environments.

  3. Branching Strategy: Clearly define a git branching strategy where specific branches align with the Lambda versions, and others are meant for distinct environments. This provides clarity to developers and ensures deployments go to the correct environment.


Choosing between Lambda versions/aliases and separate Lambdas for different environments largely depends on your team’s preference, the complexity of your application, and your release management process.

  • If you value streamlined deployments and have a sophisticated CI/CD process, using versions and aliases will suit you.
  • If you prefer complete isolation between environments or have distinct resource requirements for each, separate functions for each environment is the way to go.
  • If you have separate resources across a few environments but, most of the time, the same behaviour across multiple other branches, you can go with a hybrid approach.

Like many architectural decisions, there’s no one-size-fits-all answer. Consider your application’s unique requirements and the team’s workflow to make the best decision.