AWS Serverless: An In-Depth Guide for 2023



Cameron Barrie


June 21, 2023

AWS Serverless: An In-Depth Guide for 2023

AWS Serverless opens up a whole new world of possibilities for deploying applications that help save money and time.

Your company has a brilliant idea for an application. Still, to build it, you need a scalable backend environment that supports your idea and can grow with your business. That’s why it’s essential to choose the right infrastructure from the very beginning.

In our experience, whether you are working on a personal or professional project, this process takes much longer than expected, and often you can get stuck in some of the small details. In addition, even when you do get something working, you can’t help but think about all the things you have done or not done that could put the application at risk. Such as:

  • Are there security vulnerabilities?
  • What if someone discovers one of them and exploits the application?
  • What happens when users start using the application?
  • What if it becomes popular and suddenly thousands of people are using it?
  • How do you make sure that the user experience is always positive?

The good news is that AWS has a solution for all of these problems: AWS Serverless.

AWS Serverless is one of the hottest topics in cloud computing today. We have seen many enterprises adopting serverless architecture on AWS and reaping its benefits in the past few years.

This post will help you understand what AWS Serverless is and how you can use it to help you achieve your business goals.

Let’s get started.

What Is AWS Serverless?

AWS Serverless is a subset of Amazon Web Services (AWS) that enables you to build applications and services without managing server infrastructure.

Serverless is a cloud execution environment that removes the infrastructure layer and manages all operational tasks, like server and operating system maintenance, capacity provisioning, etc.

Serverless platforms like AWS Serverless provide auto-scaling and high availability out of the box. The prospects are enticing, so much so that Gartner predicts that half of all global enterprises will have deployed one type of serverless service or another by 2025, which would be a significant jump from only 20% in 2020.

However, it is essential to note that there’s no such thing as “serverless” in a true sense. When you build a serverless application, you generally don’t have to think about these servers. You provide the code, and the cloud provider takes care of everything required to run and scale your code with high availability.

Why Go Serverless? The Key Benefits

The truth is that serverless architecture is pragmatic and provides benefits for companies that don’t have the resources or expertise to maintain a server farm. Therefore, according to a Harvard Business Review study, it is not surprising that the adoption rate is high among smaller organisations and startups. It is commonly used in conjunction with cloud computing to enable high-performance functions as-a-service, thus making it a growing resource for companies that want to handle their business quickly and easily.

The benefits include:

No Server Management

You do not need to provision and manage server resources. Instead, AWS handles all of the infrastructures for you. Your application still runs on servers; however, AWS manages all the server management tasks.

You no longer need to:

  • Provision of virtual machines (VMs)
  • Scale compute resources up or down based on demand
  • Deploy your code on the VMs
  • Instead, you upload your application code to AWS Lambda. The service automatically runs the code on high-availability compute infrastructure and performs all the administration of the resources for you.

Some of the functions include:

  • Provisioning capacity
  • Monitoring fleet health and availability
  • Patch management for security updates
  • Performing automatic scaling.

No Fixed Pricing Model

You only pay for the compute time used in your application. There is no charge when your code is not running.

Easier To Build Microservices Based Architecture

Serverless components are easier to deploy and manage compared to traditional applications. It, therefore, becomes easier to build Microservices using serverless components.


AWS services have built-in security features, so you don’t have to worry about it. The different layers of security that AWS manages include identity and access management (IAM), encryption at rest and in transit, penetration testing by third parties, and much more.

Bottom line:

Serverless allows software development teams to focus on writing code instead of managing servers or infrastructure. As a result, serverless can help them deliver functionality to the market faster.

The Components Of AWS Serverless

The AWS serverless offering consists of many components (referred to as services) that function in harmony to deliver a serverless computing experience.

Let’s take a look at each of the main components:

Compute Services

AWS Lambda

A serverless compute service that runs your code in response to events and automatically manages the compute resources, making it easy to build applications that respond quickly to new information.

AWS Fargate

AWS Fargate is the latest addition to AWS Serverless Compute services. The technology allows developers to reduce or eliminate the need to manage servers or clusters when using Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). With AWS Fargate, you can run containers eliminating the need to spend time provisioning, configuring, or scaling virtual machines – now you can forget about which servers to use, scaling, and cluster packing.

Application Integration

Application integration services are useful in situations where you need to connect different applications and systems for them to collaborate on a business process. Users can use these services to connect systems from the same or different vendors.

The following AWS Serverless services support application integration:

Amazon SNS

Amazon SNS (Simple Notification Service) is a notification service that provides developers with the capability to publish messages from an application and immediately deliver them to subscribers or other applications. It is a highly scalable, flexible, and cost-effective way to send messages between applications or from app to person.

AWS AppSync

AWS AppSync is a managed service that uses GraphQL to make it easier for applications to obtain the exact data they require. AWS AppSync can connect to your data sources, including AWS Lambda functions, Amazon DynamoDB tables, Amazon ElastiCache, or any HTTP endpoint, and then automatically update web and mobile applications data in real-time when that data changes.

Amazon SQS

Amazon SQS (Simple Queue Service) allows you to work smarter, not harder. It is a reliable and scalable queuing service that enables you to quickly process and route messages at any volume with no software or hardware installation. Amazon SQS makes it simple and cost-effective to decouple the components of a cloud application. You can use Amazon SQS to transmit any volume of data, at any level, without losing messages or requiring other services to be available always.

AWS Step Functions

When building a new application or updating an old one using AWS solutions, you must coordinate things. But this can slow you down. AWS Step Functions solves this problem by harmonising multiple AWS services into seamless workflows allowing users to build and update apps faster with less hassle. You can design and run workflows that stitch together services such as AWS Lambda and Amazon ECS into feature-rich applications using Step Functions. Workflows are made up of steps, with the output of one step acting as input into the next.

AWS EventBridge

An enterprise-wide event bus service that makes it easy to connect applications using data from your apps, integrated Software-as-a-Service (SaaS) apps, and AWS services.

Amazon API Gateway

Amazon API Gateway is a fully managed service that does all the heavy lifting relating to creating, publishing, maintaining, monitoring, securing, and managing APIs effortlessly at any scale. Amazon API Gateway is an easy way to expose your service’s functionality to the outside world without building and maintaining backend infrastructure.

Serverless “Datastore” Services

Datastore services allow you to create a database without managing the underlying infrastructure, including provisioning storage space, installing security software, and deploying instances.

Amazon S3

Amazon S3 (Simple Storage Service) is a storage solution in the cloud that offers high scalability and availability.S3 provides a simple interface that you can use to store and retrieve any amount of data, at any time, from anywhere on the web. It is ideal for storing static files like images, videos, PDFs, and documents.

Amazon DynamoDB

Amazon DynamoDB is a fully managed NoSQL database service designed for mission-critical applications that require single-digit millisecond latency at any scale. It delivers this performance at a meager cost with comprehensive security and compliance capabilities that meet the requirements of even the most security-sensitive organisations.

Amazon RDS Proxy

Amazon RDS Proxy is a fully managed and highly available database proxy for Amazon Relational Database Service (RDS) that makes applications more scalable and resilient to database failures. Amazon RDS Proxy can significantly simplify the code required to access your databases by handling connections, network failover, retries on failure, credential management, and audit logging. Applications using Amazon RDS Proxy benefit from improved failure isolation and increased performance.

Amazon Aurora Serverless

Amazon Aurora Serverless is a MySQL and PostgreSQL compatible relational database built for the cloud. It automatically starts, scales, and shuts down database capacity based on your application’s demands.

AWS Serverless Services For Analytics

Data can be a powerful tool for your business. These AWS solutions help provide data-driven insights that can help you optimise costs, improve efficiency and increase productivity.

Amazon Kinesis

Amazon Kinesis is a fully managed service for the real-time processing of streaming data at a massive scale that provides actionable insights in just seconds.

Amazon Athena

Amazon Athena is a serverless query service that allows you to analyse data using standard SQL commands.

Putting It All Together: How Does The AWS Serverless Model Work?

The problem with conventional server-in-the-box cloud computing is paying for idle servers. Serverless offers the promise of on-demand scaling – in other words, you only pay for the servers you need when you need them.

Let’s take a look at a hypothetical model of how you can use AWS Serverless:

First, you write your code and add the required configuration. For example, you can configure AWS Lambda to run your code in response to events such as object uploads to Amazon S3 buckets or messages arriving in Amazon Kinesis streams. Each time an event triggers your function, Lambda then executes it.

Next, you deploy your application code to AWS Lambda as a function. You also define what triggers that function, such as an HTTP request arriving via API Gateway or an object uploaded to an S3 bucket.

Lastly, AWS Lambda both provisions and manages the infrastructure needed to run the function in response to new events. It also monitors the resources used by your processes and scales them up or down automatically based on demand. You only pay for the compute resources you use while your functions are running.

Challenges of Using AWS Serverless Computing

While the above might sound like it is all rainbows and unicorns, some challenges are associated with using AWS serverless computing.

Here is a list of potential problems to consider before you go ahead and implement Serverless.

The Cold Start Problem

Even though you are not paying for the server time between requests, you are still paying in latency when your service is idle (and, therefore, not warm). The amount of data that needs to be fetched from S3 or elsewhere can be significant and may result in 10 seconds or more delays.

Vendor Lock-in

All major cloud providers offer Serverless services, but migrating that architecture in the future can be very difficult if you rely heavily on them for your application architecture.

More Complex Debugging Processes

Debugging serverless applications is more complex than debugging traditional ones because developers can’t easily replicate production environments when testing.

Less Control

Less control over the infrastructure. You are trusting AWS to keep things running smoothly. Additionally, your choice of third-party apps is at the mercy of AWS’ discretion.

Examples Of Practical AWS Serverless Uses For Businesses

Creating Software Applications

AWS Lambda can be an excellent choice for business logic and backend processing when creating a new web application or moving a legacy application to the cloud. The AWS Serverless Application Repository provides templates that allow you to build applications using serverless technologies and deploy them through GitHub, AWS CodeCommit, or directly from your IDE.

Backend processing: For example, if someone enters their credit card information into your website, you can send it to a Lambda function for validation.

Mobile apps development: Many organisations turn to microservices and often need a way to deploy them to support mobile apps. Amazon API Gateway allows you to quickly create RESTful APIs that connect to business logic code without worrying about everything that happens in between.


AWS has a serverless service called Amazon Polly to turn text into lifelike speech. The core idea is this: Instead of maintaining a server, users will upload the text, which will convert into an audio file in S3, which will trigger a Lambda function that carries out the conversion using Polly.

You can use it to build various applications, like IVR systems, or provide live updates about changing conditions. Amazon Polly can support multiple languages and is even capable of pronouncing many unusual words.

Image Recognition

Image recognition is detecting objects and faces in a photo or video. With the AWS serverless stack, we can use Amazon Rekognition to do this programmatically and at a low cost. Image recognition is already pretty standard – we’re all familiar with automatic tagging on Google Photos. But Amazon Rekognition can be used to automate other processes that require image recognition.

For example, an eCommerce company might have hundreds of product images they need to tag automatically for search purposes. Amazon Rekognition allows you to add image analysis to your apps quickly. With Rekognition, you can detect objects, scenes, and faces in images. Plus, it can recognise text within the photos that you provide.


A chatbot is a conversational agent that utilises natural language processing and machine learning algorithms to understand what the user is asking and thus responds accordingly. A chatbot can be programmed to answer questions related to a specific topic by retrieving information from a knowledge base.

Data Processing

You can use AWS Lambda to transform and process data in the following ways:

  1. Create a Lambda function that takes Amazon Simple Storage Service (Amazon S3) data.
  2. Create a Lambda function that uses Amazon Kinesis to process streaming data in real-time. For example, users can use it to ship data from multiple sources. The function can process each record and store it in an Amazon DynamoDB table updated as and when new records come in.
  3. Create a Lambda function that listens to changes made to an Amazon DynamoDB table and triggers downstream operations based on them. For example, this could be a customer review site that allows users to rate products they bought. In this scenario, your Lambda function can update the product metadata when new reviews come in and then send an email alert to product managers.

Data Archiving

You can also use AWS Lambda to create an automated backup system.

For instance, an object uploaded to an S3 bucket triggers a Lambda function that copies it to a second S3 bucket in another region. So, if anything happens to one of your buckets (e.g., a natural disaster), your data will still be safe and accessible in another region.

Real-time File Processing

One of the most common uses for serverless is real-time file processing. Supposing you are a gaming company. You might have users uploading files related to their game activities. As a retailer, you might want to process images uploaded by your customers. AWS Lambda can trigger new files in an S3 bucket and automatically resize images or transcode videos.

Batch Processing

Other impactful use cases for serverless computing are batch processing and data analysis. In this case, a business could use AWS Lambda to create a scheduled event that runs once a week or once a day. The function can then take the files in an S3 bucket and process them. For example, if the company wanted to analyse recent sales data in a NoSQL database like DynamoDB, it could pass all the relevant data through an AWS Lambda function.

Transactional Emails

You can use SES to send emails from your systems, such as password resets or purchase receipts. And this is just one example of how you can automate business processes by going serverless. Also, you could use Step Functions to create a workflow that sends text messages with SNS if an invoice is overdue.

User Authentication

The AWS platform provides a serverless authentication service called Amazon Cognito (AWS Cognito). This service allows you to authenticate users without writing any authentication code. AWS Cognito also lets you authenticate and support sign-in via social media providers such as Facebook, Google, and Amazon.

Real-time Notification

We have all seen this in action: A notification instantly pops up when a friend likes or comments on your Facebook post. Or, when someone follows you on Twitter, another notification appears. But how do they do it?

Serverless applications are great for delivering real-time notifications about backend events to the browser or mobile device. Amazon’s Simple Notification Service (SNS) is an excellent tool for building this application. Developers can use it to create a highly scalable messaging system that lets you push notifications to browsers, mobile devices, and other services like SMS, HTTP, and email endpoints.

Best Practices

You can also use best practices to save costs, increase performance, and improve the developer experience.

Here are some best practices for getting the most from serverless:

Adopt Event-driven Workflows

It is generally better to build applications composed of discrete components responsible for a specific task that can communicate asynchronously using events/messages instead of synchronous/blocking calls between components.

Applying Security Practice

Just because you use serverless doesn’t mean that you can ignore security. For example, you can use Amazon Cognito to authenticate users calling your Lambda functions and Amazon API Gateway to protect your API endpoints by restricting access only to authenticated callers who have permission to access resources hosted on those endpoints. Use IAM (Identity and Access Management) policies that define what actions authenticated users can perform against specific resources.

Additional security tips when using AWS Serverless:

  • Ensure log files are monitored for suspicious activities
  • Ensure that the applications and the AWS services used by them are encrypted with appropriate encryption keys
  • Ensure that session states are not maintained in serverless applications
  • Ensure that HTTP requests do not contain user credentials like passwords.

Design For Scale

The most important thing to keep in mind when designing a serverless application is building it with scalability in mind. It thus means avoiding any single point of failure. A serverless function is designed to scale horizontally. You need to create your application and its data access patterns carefully such that they can scale automatically. For example, rather than relational databases, you can use Amazon DynamoDB or Amazon ElastiCache with Lambda functions to ensure that your data access layer can scale out with your compute function.

Monitoring and Logging

Since you don’t have access to the underlying machine, monitoring and logging are critical factors.

Use AWS X-Ray to monitor Lambda functions: X-Ray gives you a visualisation of your whole application with performance statistics for each component. It is beneficial for diagnosing function errors, especially since you can’t just ssh into your instances and run a trace.

Logging should be enabled on all Lambdas by default: Logs help users understand the application’s behavior and will provide additional information for monitoring. Users can access logs from CloudWatch, which is the default logging mechanism for AWS Lambdas.

To find problems before your users do, you should log as much information about your application. In particular, every time your serverless function responds to an event, make sure that you log the following:

  • The event that triggered the function
  • The parameters passed to the function
  • The name of the event source (e.g., DynamoDB table name, S3 bucket name)
  • The status code of the response and any error messages
  • The data the request contained if any
  • The time it took to process the request
  • Any errors that occurred.

Be Careful With Third-party Software

There is a considerable amount of third-party software that you can use to help with your development process. But when it comes to security and privacy, there are two things you should always keep in mind: “With great power comes great responsibility” and “Trust but verify.” The same goes for any third-party software or libraries you add to your application.

Avoid Using a Large Number Of Parallel Executions

AWS Lambda has a concurrency limit of 1,000 executions per use. To ensure that your Lambda functions are reliable, AWS recommends that you limit the number of parallel executions to 1,000.

How Much Does It Cost To Use AWS Serverless?

The pricing for AWS Serverless is based on the following three factors:

  1. Compute time: This is charged at a rate of $0.0000166667 or $0.0000133334 per GB-second for x86 and Arm architecture, respectively.
  2. Requests: AWS charges $0 for the first 1 million requests made to your Lambda functions each month and then charges $0.20 per million requests after that (prices correct at time of writing).
  3. API calls: The total number of API calls to manage your functions included in the free tier – up to 1 million calls per month for REST API and HTTP API calls, plus 1 million messages and 750,000 connection minutes per month for up to 12 months.

After that, for paid pricing:

  • HTTP API – $1.00/million for the first 300 million and $0.90/million for 300+ million for calls you receive and the amount of data transferred out.
  • REST API – $3.50/million for the first 333 million, $2.80/million for 667 million, $2.38/million for 19 billion, and $1.51/million for 20 billion for calls you receive and the amount of data transferred out.
  • Caching  – Pricing ranges from $0.02/hour for 0.5GB cache memory to $3.80/hour for 237.0GB cache memory.
  • WebSocket APIs – The cost of the first 1 billion requests/month is $1.00/million, and for requests over a billion, $0.80/month.
  • Connection Minutes – $0.25/million connection minutes.

In addition to these costs, AWS also charges for any other AWS components used by your application, such as S3, DynamoDB storage, or network traffic across VPCs. It is essential to take these into account when planning your project.

Getting Started With AWS Serverless

Amazon Web Services provides an open-source framework called AWS Serverless Application Model (AWS SAM) that lets developers quickly build serverless applications. AWS SAM’s shorthand syntax makes defining functions, APIs, databases, and event sources easier – just a few lines can zap the hard work out of determining an application and modeling it in YAML.

Getting started with building serverless applications requires using the AWS SAM CLI.

The following are some steps to help you get started with AWS SAM:

Installing the AWS SAM CLI

For Linux OS

AWS SAM CLI supports 64-bit versions of recent releases of CentOS, Fedora, Ubuntu, and Amazon Linux 2.

Step 1

  • Create an AWS account if you don’t already have one.
  • Choose “Create an AWS Account” and follow subsequent prompts and instructions to set up your account.

Step 2

Configure your identity and access management (IAM) permissions and your Amazon Web Services (AWS) credentials.

Step 3

Install Docker. You can get Docker from the official website. However, this step is optional.

Step 4

Download the appropriate AWS SAM CLI file.

  • Verify integrity and authenticity of installer files, unzip, install, and then verify the installation.
  • An example of a successful structure: SAM CLI, version 1.18.0.
  • You can start development.

For Windows

Step 1

  • Create an AWS account if you don’t already have one.
  • Choose “Create an AWS Account” and follow subsequent prompts and instructions to set up your account.

Step 2

Configure your identity and access management (IAM) permissions and your Amazon Web Services (AWS) credentials.

  • Set up AWS Access Role and ensure you grant administrator privileges to get sufficient permissions for AWS service calls.
  • Next, set up AWS credentials. You can use this guide to do so.

Step 3

Install Docker. (As with Linux, this is optional). You can get Docker for Windows 10 from the official website.

Configure shared drives and verify the installation.

Step 4

To install AWS SAM CLI for Windows, you’ll have to use the MSI file.

  • Download the appropriate AWS SAM CLI file. Next, install and verify the installation.
  • Install Git to download sample applications using the “sam init” command

For macOS

Step 1

Create an AWS account if you don’t already have one.

  • Choose “Create an AWS Account” and follow subsequent prompts and instructions to set up your account.

Step 2

Configure your identity and access management (IAM) permissions and your Amazon Web Services (AWS) credentials.

  • Set up AWS Access Role and ensure you grant administrator privileges to get sufficient permissions to AWS service calls.
  • Next, set up AWS credentials. You can use this guide to do so.

Step 3

Install Docker (Optional if you are using macOS). You can get Docker for macOS Sierra 10.12 and above from the official website.

Configure shared drives and verify the installation.

Step 4

Instalment of Homebrew.

  • First, install Git (For help installing Git for mac, visit this resource). Next, run the following to install Homebrew:

/bin/bash -c “$(curl -fsSL”

  • Verify installation

Step 5

Using the command below, install the AWS SAM CLI using Homebrew:

brew tap AWS/tap

brew install AWS-sam-cli

Finally, verify the installation.

What Next?

There is no better time than now to get started with AWS Serverless. Use this guide to get started and enhance your development experience by using serverless technologies. It will change everything regarding developer productivity and services’ scalability for the better.

Build Your Next App With Confidence

Not all businesses have the expertise required to take full advantage of AWS’s capabilities. To help fill this gap, AWS has certified select partners who can provide customers with custom solutions that leverage AWS technology for various business needs.

Our certified experts have demonstrated their technical proficiency and success with AWS, enabling them to deliver low-cost, scalable, and secure apps that quickly drive business results.

Suppose you are in the process of building a mobile app for your business. In that case, you must work with a trusted AWS Certified Partner that can help you deliver exceptional user experiences (UX), optimise for performance and security, and support your go-to-market strategy.

It is a fantastic opportunity because it can translate into guaranteed savings on both time and money, allowing you to focus on innovation and growth.

Get in touch with us now, and we will walk you through everything you need to know.

Book a free consultation

If you would like to meet us to talk through a project or find out more, we'd love to hear from you.

Cameron Barrie

Founder and CEO of Bilue

Cameron Barrie

I help companies uncover opportunities and solve problems using Web, Mobile, APIs, and Emerging Technologies.

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