Introduction
In the ever-evolving landscape of cloud computing, serverless architecture has emerged as a game-changer. It’s a paradigm shift that allows developers to focus on writing code without the burden of managing servers, infrastructure, or scaling concerns. At the forefront of this revolution stands AWS Lambda, a powerful and versatile service offered by Amazon Web Services (AWS).
In this comprehensive guide, we embark on a journey into the world of serverless computing with a specific focus on AWS Lambda. We’ll unravel the complexities, explore the intricacies, and provide you with a solid foundation to harness the capabilities of serverless computing for your projects and applications.
Our exploration will take us through the fundamentals of serverless computing, shedding light on serverless operational tasks and the AWS serverless platform. We’ll introduce the star of the show, AWS Lambda, and delve into its key features. Event-driven architectures will be demystified, and we’ll also gain a deep understanding of what Lambda functions are and how they work.
By the end of this guide, we’ll not only comprehend the concept of serverless computing but also be equipped with the knowledge to leverage AWS Lambda effectively, making our development process more efficient, scalable, and cost-effective.
So, let’s dive into the world of serverless computing and AWS Lambda, where innovation meets simplicity, and where our code takes center stage. Welcome to a future where the possibilities are endless, and the servers are nowhere to be seen.
Introduction to Serverless
One of the major benefits of cloud computing is its ability to abstract (hide) the infrastructure layer. This ability eliminates the need to manually manage the underlying physical hardware. In a serverless environment, this abstraction allows us to focus on the code for our applications without spending time building and maintaining the underlying infrastructure. With serverless applications, there are never instances, operating systems, or servers to manage. AWS handles everything required to run and scale our application. By building serverless applications, developers can focus on the code that makes business unique.
Serverless operational tasks
The following chart compares the deployment and operational tasks in a traditional environment to those in a serverless environment. The serverless approach to development reduces overhead and lets us focus, experiment, and innovate faster.
| Deployment and Operational tasks | Traditional Environment | Serverless |
|---|---|---|
| Configure an instance | YES | – |
| Update operating system (OS) | YES | – |
| Install application platform | YES | – |
| Build and deploy apps | YES | YES |
| Configure automatic scaling and load balancing | YES | – |
| Continuously secure and monitor instances | YES | – |
| Monitor and maintain apps | YES | YES |
AWS serverless platform
The AWS serverless platform includes a number of fully managed services that are tightly integrated with AWS Lambda and well-suited for serverless applications. Developer tools, including the AWS Serverless Application Model (AWS SAM), help simplify the deployment of your Lambda functions and serverless applications.
Review the following services. These services are part of the AWS serverless platform and are mentioned throughout the course.
AWS Lambda is the computing service for serverless.
The AWS serverless platform includes a number of fully managed services that are tightly integrated with Lambda. There are also developer tools including AWS SAM to simplify deployment of your serverless applications.
What is AWS Lambda?
AWS Lambda is a computing service. we can use it to run code without provisioning or managing servers. Lambda runs our code on a high-availability computing infrastructure. It operates and maintains all of the compute resources, including server and operating system maintenance, capacity provisioning and automatic scaling, code monitoring, and logging. With Lambda, we can run code for almost any type of application or backend service.
Some benefits of using Lambda include the following:
- We can run code without provisioning or maintaining servers.
- It initiates functions for us in response to events.
- It scales automatically.
- It provides built-in code monitoring and logging via Amazon CloudWatch.
AWS Lambda features
There are six main features of Lambda
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Bring our own code: we can write the code for lambda using languages we already know and are comfortable using. Development in Lambda is not tightly coupled to AWS, So we can easily port code in and out of AWS.
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Integrates with and extends other AWS services: with our lambda function, we can do anything traditional applications can do including calling and AWS SDK or invoking a third-party API, whether on AWS, in our datacenter, or on the internet.
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Flexible resource and concurrency model: Instead of scaling by adding servers, Lambda scales in response to events. We configure memory settings and AWS handles details such as CPU, network, and I/O throughput.
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Flexible permissions model: The Lambda permissions model uses AWS Identity & Access Management (IAM) to securely grant access to the desired resources and provide fine-grained control to invoke our functions.
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Availability and fault tolerance are built in: Because Lambda is a fully managed service, high availability, and fault tolerance are built into the service without needing us to perform any additional configuration.
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Pay for Value: Lambda functions only run when we initiate them. We pay only for the compute time that we consume. When the code is invoked, We are billed in 1-millisecond (ms) increments.
Event-driven architectures
In an event-driven architecture, events play a pivotal role in orchestrating actions and fostering communication among loosely-coupled services. An event, in this context, signifies a change in state, a user’s request, or an update—think of it as an item being added to a shopping cart on an e-commerce website. When an event takes place, the pertinent information is broadcasted, making it available for other services to consume. In essence, event-driven architectures rely on events as their core means of sharing information among services.
These events are characterized by their observability, akin to noticing a new message in a log file, rather than being directed with specific commands to perform explicit actions. This approach allows for flexibility and adaptability, making it easier for services to react to changing conditions and requirements.
Producers, routers, consumers
AWS Lambda is an example of an event-driven architecture. Most AWS services generate events and act as an event source for Lambda. Lambda runs custom code (functions) in response to events. Lambda functions are designed to process these events and, once invoked, may initiate other actions or subsequent events.
What is a Lambda function?
In the world of AWS Lambda, our code takes center stage in the form of what we call “Lambda functions.” Think of these functions as bite-sized, self-contained applications. The beauty of Lambda functions lies in their instant readiness. Once we’ve created one, it’s poised to run at a moment’s notice.
Each Lambda function packs our code along with some essential configuration details, like its name and resource requirements. But here’s where it gets interesting: these functions are entirely stateless, meaning they’re not tied to any particular piece of underlying infrastructure. In other words, Lambda can swiftly fire up as many copies of our function as required to keep up with incoming events.
Now, here’s where the magic truly happens. After we’ve uploaded our code to AWS Lambda, we get to configure what’s known as an “event source.” This source could be anything from an Amazon Simple Storage Service (Amazon S3) event, an Amazon DynamoDB stream, an Amazon Kinesis stream, to an Amazon Simple Notification Service (Amazon SNS) notification.
Whenever this event source detects a change or triggers an event, AWS Lambda steps in. It executes our function and takes care of all the necessary computing resources to handle incoming requests.
In essence, AWS Lambda and its Lambda functions make our code come alive, reacting to events in real time without we having to worry about the infrastructure behind the scenes. Its code execution is made brilliantly simple.
How AWS Lambda Works?
To understand event-driven architectures like AWS Lambda, we need to understand the events themselves. So, During this section dives into how events initiate functions to invoke the code within.
Invocation models for running Lambda functions
Event sources can invoke a Lambda function in three general patterns. These patterns are called invocation models. Each invocation model is unique and addresses a different application and developer needs. The invocation model you use for your Lambda function often depends on the event source you are using. It’s important to understand how each invocation model initializes functions and handles errors and retries.
These three Invocation models are :
- Synchronous invocation
- Asynchronous invocation
- Polling invocation
For a more in-depth exploration of each invocation model, please refer to the following sections:
Synchronous invocation
When we invoke a function synchronously, Lambda runs the function and waits for a response. When the function completes, Lambda returns the response from the function’s code with additional data, such as the version of the function that was invoked.
Synchronous events expect an immediate response from the function invocation.
With this model, there are no built-in retries. We must manage our retry strategy within our application code.
The following diagram shows clients invoking a Lambda function synchronously. Lambda sends the events directly to the function and sends the function response directly back to the invoker.
List of AWS Services
| AWS services supported by Synchronously Invocation |
|---|
| Amazon API Gateway |
| Amazon Cognito |
| AWS CloudFormation |
| Amazon Alexa |
| Amazon Lex |
| Amazon CloudFront |
Asynchronous invocation
When we invoke a function asynchronously, events are queued and the requestor doesn’t wait for the function to complete. This model is appropriate when the client doesn’t need an immediate response.
The following diagram shows clients invoking a Lambda function asynchronously. Lambda queues events before sending them to the function.
List of AWS Services
| AWS services supported by Asynchronous Invocation |
|---|
| Amazon SNS |
| Amazon S3 |
| Amazon EventBridge |
Polling invocation
This invocation model is tailored for seamless integration with AWS streaming and queuing-based services, completely eliminating the need for manual code or server management. AWS Lambda takes on the role of polling or watching these services, identifying and capturing relevant events, and then initiating the execution of our functions.
List of AWS Services
| AWS services supported by Polling Invocation |
|---|
| Amazon Kinesis |
| Amazon SQS |
| Amazon DynamoDB Streams |
Summarize Error Behavior of Invocation Models
| Invocation model | Error behavior |
|---|---|
| Synchronous | No retries |
| Asynchronous | Built-in – retries twice |
| Polling | Depends on the event source |
Lambda execution environment
When Lambda triggers a function, it operates within an execution environment—a secure and self-contained space. This environment takes care of all the necessary resources needed for our function’s execution. Moreover, it offers essential lifecycle support for our function’s runtime and any external extensions linked to it.
Execution environment lifecycle
When we create our Lambda function, we provide configuration details, including memory allocation and the maximum permissible execution duration. AWS Lambda leverages this information to establish the execution environment.
Within this environment, the function’s runtime and any associated external extensions operate as separate processes. They share essential elements such as permissions, resources, credentials, and environment variables to facilitate seamless execution.
Step 1: Init phase
In this phase, AWS Lambda orchestrates the creation or reactivation of an execution environment, aligning it with the preconfigured resources. During this process, Lambda downloads the function’s code along with any associated layers, initializes any extensions, sets up the runtime environment, and proceeds to execute the function’s initialization code—typically the code outside the main handler function.
The Init phase unfolds either during the initial invocation or before subsequent invocations if you’ve opted for provisioned concurrency.
Breaking down the Init phase further, it comprises three distinct sub-phases:
- Extension init: This step launches all extensions.
- Runtime init: Here, the runtime environment is bootstrapped.
- Function init: Finally, the function’s static code is executed.
These sub-phases are meticulously designed to ensure that extensions and the runtime complete their setup tasks before the core function code comes into play.
Step 2: Invoke phase
In this phase, Lambda invokes our function handler. After the function runs to completion, Lambda prepares to handle another function invocation.
Step 3: Shutdown phase
When a Lambda function remains idle without receiving any invocations for a certain duration, the Shutdown phase is triggered. During this phase, AWS Lambda takes steps to gracefully conclude the execution environment.
In the Shutdown phase, Lambda performs the following tasks:
- Shutdown of Runtime: The runtime environment is shut down gracefully.
- Extension Notifications: Extensions are alerted to prepare for a clean stop.
- Environment Removal: The execution environment is removed from the infrastructure.
As part of this process, Lambda sends a shutdown event to each extension, signaling that the environment is slated for shutdown. This ensures that all resources are gracefully managed before the environment is taken offline.
Conclusion:
In this comprehensive guide, we’ve delved into the realm of serverless computing, focusing on the powerful AWS Lambda service. we’ve gained insights into serverless operational tasks, explored the AWS serverless platform, and deep-dived into Lambda functions and event-driven architectures. With this newfound knowledge, we’re well-equipped to harness the capabilities of serverless computing for your projects and applications. Embrace the future of cloud computing with AWS Lambda and make our development process more efficient and scalable.