Deploying Serverless Applications: The What and How

When it comes to developing and deploying modern applications, you have a lot to consider. In the past, traditional monolithic applications were often the go-to choice. But today, more and more businesses utilize serverless architectures to build scalable, cost-effective applications that can meet the demands of their users. But what exactly is a serverless application? And what are some of the best ways for deploying serverless apps?

In this article, we'll answer those questions and more. We'll discuss the benefits of serverless architectures and walk through some best practices for deploying serverless applications.  So let's get started!

What is a Serverless Application?

First, let's define what we mean by "serverless." A serverless architecture lets you build and run applications without worrying about provisioning or managing servers. Instead, the application runs on a function-as-a-service (FaaS) provider, such as AWS Lambda, Google Cloud Functions, or Azure Functions.

The provider takes care of running and scaling your code. And because you only pay for the resources your code uses, serverless can be a more cost-effective way to run your applications than setting up servers.

When it comes to deployment, serverless architectures offer a few benefits. First, as already mentioned, you don't need to provision or manage servers; the deployment process is more straightforward. Additionally, because your application is broken down into small pieces (i.e., functions), you can deploy them incrementally, which can be helpful if you're working with a large codebase.

Now that we've answered the question, "What is serverless?" let's discuss some of the best ways to deploy serverless applications.

Best Practices for Deploying Serverless Applications

Deploying serverless applications is a great way to reduce your overhead and improve efficiency. However, you should follow some best practices when deploying serverless architectures.

Develop Using a Serverless Framework

Frameworks can be a great way to build serverless applications. They provide a library of templates and reusable components that make it easy to get started. And since most frameworks are open source, you can customize them to fit your needs. While using a framework has benefits, it can be hard to know which one to choose. You can choose from many different frameworks, and they all have their pros and cons.

AWS SAM and Functions Framework are popular for building serverless applications. Let’s now look at both these frameworks and explore the pros and cons of each.

AWS Serverless Application Model (SAM)

SAM is the perfect choice for those looking to build serverless applications on AWS. It is easy to use and has all the features you need to get started quickly. It includes support for Lambda functions, API Gateway, DynamoDB, and others. SAM is open source and maintained by the community as part of this GitHub project.

SAM is based on AWS CloudFormation, and you can use it to define your serverless application resources in a template file. You can then use SAM to package, deploy, and test your application. SAM provides a set of tools to manage your serverless applications, including the SAM CLI and the AWS Serverless Application Model (AWS SAM) service.

SAM has a few drawbacks. First, it can be difficult to know which template to use for your application. Second, SAM can be slow to deploy applications. Lastly, it’s not compatible with all AWS services.

Functions Framework

The open source Functions Framework allows you to write serverless functions, and provides a set of tools that make it easy to write, test, and deploy your functions. Based on the Cloud Functions programming model, it supports Node.js, Python, PHP, Ruby, .NET, C++, Dart, R, Deno, Java, and Go. The Functions Framework lets you write standardized functions that you can run on any cloud provider that supports the Functions Framework.

The Functions Framework is available here on GitHub. Despite its many benefits, one drawback of the Functions Framework is that it can be difficult to configure and use on some cloud providers. In addition, the Functions Framework can be challenging for beginners to learn and use.

The Serverless Framework

The Serverless Framework is a framework for building applications that you deploy and run on various next-gen serverless infrastructures. With the Serverless Framework, you can define your application's infrastructure as code and deploy and manage your application using a simple, declarative syntax in YAML format. The Serverless Framework is open source and available under the MIT license.

The Serverless Framework contains two components:

1. The Serverless Framework CLI: This is a command-line tool that you can use to create and manage your serverless applications.
2. The Serverless Framework Core: This is a library of templates and functions that you can use to create your serverless applications. It includes support for the most common programming languages (JavaScript, Python, and Node.js) and cloud providers (AWS, Azure, and Google Cloud Platform).

You can get started quickly by installing it using npm.

Drawbacks of the Serverless Framework is that it has a steep learning curve and it lacks good documentation and support.

Use a CI/CD Pipeline

When deploying an application, you should have a continuous integration/continuous delivery (CI/CD) pipeline in place. A CD/CI pipeline ensures automatic testing and deployment and that you can quickly roll back changes if necessary.

For serverless applications, you can use a tool like AWS CodePipeline, AWS CodeBuild, or Azure DevOps Services to create your CI/CD pipeline, depending on your cloud provider. These tools will help you automate your code's build, testing, and deployment.

You should to include all of the following components or steps in your pipeline:

1. Source: This is where you store your code. You can use any source code repository, like AWS CodeCommit, GitHub, or Cloud Source Repositories.
2. Build: You build and package your code in this stage; you can use AWS CodeBuild or a Linux-based cloud server instance with Node.js runtime for npm builds. Usually, you’d write build specifications using a YAML file format (with the .yml file extension).
3. Test: You test your code in this step, before deploying it in the production environment.
4. Approve: At this point, you can approve or reject changes to your code before deploying it.
5. Deploy: In this step, package your code for deployment in cloud services like AWS Lambda, Google Cloud Functions, or Azure Functions.

The AWS CodePipeline ties all the above steps together. After creating the pipeline, you can view the status of the different stages here.

Manage Your Cloud Resources Using an Infrastructure-as-Code Service

As an infrastructure-as-code service, AWS Cloud Formation lets you provision, manage, and update your AWS resources in a predictable and repeatable way. You can use CloudFormation to create a template that describes your desired AWS resources and their dependencies, and then use the template to provision and update those resources. CloudFormation enables you to implement version control for your templates so you can track changes and roll back to previous versions if necessary.

Deploy & Test in Multiple Environments in Stages

When deploying serverless applications, it's important to deploy to multiple environments, such as development, staging, and production. Testing your code in the development and staging environments is a safe way to test before deploying it to production.

Secure Access to Your Environments

It is also critical to provide secure access to your cloud environments. You'll need to set up authentication and authorization for each environment to ensure that only authorized users have access to the resources they need.

For example, let’s say you’re working in AWS. First, create and configure a new identity and access management (IAM) profile. Then attach appropriate policies like AmazonS3FullAccess, AWSCodePipelineFullAccess, and AWSCodeBuildAdminAccess, as required by your project. Lastly, to configure the access, copy the Access Key ID and Secret key for the new user.

Monitor Your Applications

After deploying your serverless applications,  monitor them so that you can quickly identify and fix any issues that arise. You'll want to set up monitoring and logging for your applications, and you should also consider using a tool like AWS CloudWatch or Azure Monitor to help you keep an eye on your resources. You can also generate critical insights about application usage data using the Traceable AI Platform.

Conclusion

In this post you learned that you can use serverless applications as a cost-effective way to build scalable applications that meet your users’ needs. However, be sure to follow best practices when deploying serverless architectures.

We recommend the following best practices:

• Develop using serverless framework
• Use a CI/CD pipeline
• Deploy to multiple environments in stages
• Secure access to your environments
• Manage resources using an infrastructure-as-a-code service like AWS Cloud Formation to monitor your applications

You can deploy serverless applications more successfully if you use these best practices. Please also have a look at the Traceable AI platform, which may can give you critical insights about your serverless apps and help ensure cloud security.

This post was written by Tarun Telang. Tarun is a software engineering leader with over 16 years of experience in the software industry with some of the world’s most renowned software development firms like Microsoft, Oracle, BlackBerry, and SAP. His areas of expertise include Java, web, mobile, and cloud. He’s also experienced in managing software projects using Agile and Test Driven Development methodologies.