In this article, we will explore how serverless computing can transform software development. We will compare the traditional approach with serverless.
Transforming traditional software development with serverless computing involves moving away from a monolithic architecture (self-contained and independent from other applications) or traditional server-based models to a more modern, flexible, and scalable approach.
What is Serverless?
Though the name is Serverless, it doesn’t mean that there is no server being used. It will be there, it’s just kind of a use-and-throw scenario. A temporary server will execute your code and then all the resources will be deallocated. Basically, Serverless computing allows developers to build and run applications and services without having to manage infrastructure. The cloud provider automatically handles the provisioning, scaling, and management of servers.
Key characteristics
Event-Driven Execution: Code is executed in response to events such as HTTP requests, database changes, or message queue triggers.
Microservices Architecture: Applications are decomposed into small, independent services that can be developed, deployed, and scaled separately.
Automatic Scaling: The infrastructure automatically scales up or down based on demand
Key benefits
Reduced Operational Overhead: Developers can focus on writing code instead of managing servers.
Scalability: Serverless platforms automatically handle scaling based on traffic and workload.
Cost Efficiency: Pay-per-execution model ensures you only pay for what you use.
Faster Time-to-Market: Simplified deployment processes lead to quicker releases and iterations.
High Availability: Built-in fault tolerance and redundancy provided by cloud providers.
Now that we know what serverless computing is, let’s discuss how to transform traditional software development.
Basic steps include:
Assessment and Planning
In this step, we should analyze the current platform and the serverless platform that we are planning to use. Please note that we are not talking about moving the entire application to the cloud. It can be a hybrid scenario where some components stay on-premise and some can be achieved using serverless.
Evaluate Application Architecture: Identify components that can be decoupled and moved to a serverless model. For example, we may have a nightly job that fetches data and prepares a file for export. As this is a nightly job, we can decouple and move to a serverless approach.
Choose the Right Serverless Platform: AWS Lambda, Azure Functions, Google Cloud Functions, etc. This can be organization-specific, but the overall approach is similar.
Assess Workload Characteristics: Determine which parts of the application are suitable for serverless based on their usage patterns and performance requirements. For example, we can have multiple nightly jobs, but some may not be suitable for serverless as they require very little computing power or memory allocation, etc.
Migrating to Serverless
Once we have finalized components, we should start migrating them to a serverless computing approach.
Refactor Monolithic Applications: Break down monolithic applications into smaller, manageable microservices. Ideally, this should have already been done, but doing this exercise will greatly benefit in the future.
Develop Serverless Functions: Write functions to handle individual tasks or services. For example, a function to process an image upload or handle a user registration.
Utilize Managed Services: Replace traditional components with cloud-managed services (e.g., databases, authentication, storage). Note that you can still keep these components as it is, but this step will make your application more cloud-compatible.
Database: Use services like AWS DynamoDB or Azure Cosmos DB.
Authentication: Use services like AWS Cognito or Azure AD B2C.
Storage: Use services like AWS S3 or Azure Blob Storage.
Implementing Event-Driven Architecture
Event Sources: Identify events that trigger functions (HTTP requests, database changes, message queues, or just the time of the day). This is essential to run our component.
Message Queues and Pub/Sub: Use services like AWS SNS/SQS, Azure Service Bus, or Google Pub/Sub for decoupling services and handling asynchronous tasks. This will bridge the gap between the existing application and the component running as serverless.
CI/CD Integration
Automate Deployments: Use tools like AWS CodePipeline, Azure DevOps, or GitHub Actions to automate the deployment of serverless functions. This is a no-brainer as even a monolithic application should leverage this approach.
Version Control: Make sure that code versions are properly managed and changes are tracked.
Monitoring and Logging
Monitoring Tools: Use cloud-native monitoring tools like AWS CloudWatch, Azure Monitor, or Google Stackdriver. This is essential as your component is in isolation, and monitoring will help track the status and outcomes.
Logging: Implement structured logging using services like AWS CloudWatch Logs or Azure Log Analytics. This will benefit from tracking the history and troubleshooting any post queries about the data or outcome of the serverless component.
Let’s take a look at an example of migrating a traditional web application to Serverless using Amazon Cloud Infrastructure.
Traditional Architecture
A traditional architecture mostly consists of the following components:
Web Server: Hosting a monolithic application.
Database: SQL database hosted on a VM.
Authentication: Custom-built authentication service.
Serverless Architecture
Below are the individual components of the Serverless scenario:
API Gateway: AWS API Gateway or Azure API Management to handle HTTP requests.
Serverless Functions: AWS Lambda or Azure Functions to handle business logic.
Managed Database: AWS DynamoDB or Azure Cosmos DB for data storage.
Authentication: AWS Cognito or Azure AD B2C for user authentication.
Storage: AWS S3 or Azure Blob Storage for static content.
Conclusion
Transforming traditional software development with serverless computing involves a strategic shift towards microservices, event-driven architecture, and managed cloud services. This transformation leads to reduced operational overhead, cost efficiency, scalability, and faster time-to-market, ultimately enabling developers to focus on delivering business value rather than managing infrastructure.