Guide to AWS Lambda: Understanding Serverless Computing for Your Career

Imagine being able to write code without worrying about how you’ll run it in the cloud. AWS Lambda lets you do this. Lambda is a serverless function that does away with provisioning, servers, and all the other requirements of running software in the cloud. 

In this guide, we’ll explain what AWS Lambda is and how it works. You’ll discover the benefits of serverless computing and how mastering it can help you develop a career in software engineering and DevOps. 

What Is AWS Lambda?

AWS Lambda is a cloud computing service that lets you run software code in the cloud in a serverless environment. It automatically organizes the infrastructure needed, such as by scaling services in response to demand. To get started, you upload your software code as a container image or ZIP file to the Lambda function. 

Since you don’t need to waste time setting up cloud infrastructure, it lets you focus on developing code. Other popular applications include running microservices and automating functions. 

A key attraction of Lambda is that you only pay for the compute time to run the code and the number of requests. The free tier provides you with one million requests and 400,000 GB seconds of compute time per month. 

How AWS Lambda Works

Each Lambda function runs in a stateless container that automatically allocates RAM and CPU capacity based on the function. The architectural design of the Lambda function means multiple instances can run concurrently. This feature allows the function to automatically scale to handle high demand. 

You can run AWS Lambda as a standalone function or combine it with other AWS services, and its functions are event-driven. Typical events that trigger Lambda include:

• HTTP requests received through Amazon’s API Gateway, such as when someone places an item in a shopping cart
• Changes to objects stored in Amazon S3 storage
• Data changes in Amazon’s DynamoDB NoSQL database

Lambda is user-friendly and easy to implement. The function code can be written in a range of programming languages, including: 

• Python
• Ruby 
• C#
• Java
• Node.js
• PowerShell
• Go

It also has a Lambda Runtime API that facilitates coding in additional programming languages. 

AWS Lambda automatically sends logs to AWS CloudWatch. This allows you to monitor how often the function is invoked and measure its performance metrics. CloudWatch also logs errors, including delivery failures, timeouts, and configuration errors. 

Benefits of Using AWS Lambda

If you want to develop a web application but don’t want to create a frontend and backend, then Lambda is the go-to solution. It’s largely intuitive and relatively easy to get started with. Some reasons developers and businesses use Lambda include:

• Cost-effectiveness. Lambda is an excellent low-cost solution for applications that respond to a trigger event. You only pay for what you use, and there’s no associated base charge or flat fee. It also has a monthly free tier, making it accessible to small developers. 
• Scales automatically. There’s no need to provision for a specific usage level. Lambda scales automatically and shuts down when not in use. This feature makes it ideal for projects where it’s difficult to predict usage, especially for start-ups and new users.
• No infrastructure management is needed. Because Lambda is serverless, you don’t have to think about infrastructure, and there are no set-up costs to consider. 
• Seamless integration with AWS services. As an integral component of the AWS environment, Lambda works seamlessly with most AWS services, including Amazon’s Simple Storage Services (S3), API Gateway, and DynamoDB. To integrate with other services, you’ll need the AWS software development kit (SDK) for your programming language. 
• Flexibility. With native support for many programming languages, Lambda is compatible with numerous programming runtimes and multiple software frameworks. 

Common Use Cases of AWS Lambda

AWS Lambda use cases are generally those where each task is self-contained and runs quickly. Tasks are typically triggered by an event or action. It’s a good choice for situations where the workload may scale up or down quickly, and it’s an effective way to automate multiple AWS services. 

AWS Lambda use cases include:

• Backend development for web and mobile applications. AWS Lambda is ideal for creating a behind-the-scenes backend for web and mobile applications. The backend manages data and helps applications run efficiently. Lambda backend tasks manage API requests between the application and application databases. 
• Data processing. Lambda can be triggered for real-time processing of changes in databases or data streams. This applies to AWS services, such as S3 cloud storage buckets, DynamoDB NoSQL databases, and Kinesis data streams.
• Workflow automation. You can use Lambda in conjunction with AWS Step Functions to automate serverless workflows. Other possibilities include orchestrating CI/CD pipelines to automate software development, machine learning, and running scheduled jobs. It also responds to CloudWatch Events, such as operational changes and alarms, and lets you automate scheduled tasks. 
• Machine learning and artificial intelligence. AWS Lambda is an ideal tool for the serverless deployment of machine learning models. This is typically done by packaging the model as a container image and using a Lambda function to trigger inference (predictions). The advantages of using Lambda for ML include a pay-as-you-go environment and the ability to scale almost instantly to run multiple processes in parallel. 
• Manage IoT applications. Amazon uses AWS IoT to connect IoT devices to the AWS Cloud. Using the AWS IoT rules engine, you can create a rule that triggers Lambda when certain conditions are met. This can invoke linked AWS services or third-party software to generate an appropriate action. 

Careers That Benefit From AWS Lambda Knowledge

If you’re going to work in the AWS ecosystem, Lambda knowledge is a prerequisite for success. Lambda skills are in high demand and can help you succeed in your chosen career. 

Let’s look at some careers where having Lambda skills and certifications can make a real difference.

Cloud Engineer

Cloud engineers build and manage infrastructure in the cloud. This includes developing cloud applications from scratch using public clouds, such as AWS, and the development of private clouds. Cloud engineers need to have practical and theoretical knowledge of serverless applications. 

These professionals are expected to know how to use tools such as AWS Lambda to automate applications and develop cost-effective applications that readily scale. 

DevOps Engineer

DevOps is an abbreviation of developer operations and refers to the procedures and practices used to automate software processes. DevOps engineers are often IT generalists with advanced technical and team-building skills. They coordinate software development and the migration of applications to the cloud as serverless applications. 

These engineers commonly use AWS Lambda as part of a CI/CD automation pipeline. They also use it to create serverless computing solutions. 

Software Developer

Software developers are in high demand. They design and create computer applications, programs, and serverless solutions in the cloud. 

These solutions include backend services that support cloud applications. You can also use Lambda to create event-driven applications, such as responding to user requests. It’s especially useful for linking multiple software applications to create an automated software solution.

Data Engineer

Access to data is a key ingredient to business success. Data Engineers are responsible for creating systems for collecting structured and unstructured data and converting it into usable information. They typically use, extract, transform, and load (ELT) pipelines to modify and manage this data. 

AWS Lambda is a key tool for actioning ELT pipelines. Data engineers use Lambda to automate the movement of data to and from S3 and DynamoDB storage. It’s also compatible with Amazon’s petabyte-capable Redshift data warehouse.

Security Engineer

A security engineer’s primary task is to build and maintain security systems that keep the organization’s applications, systems, and data safe. This includes the provision of strong security solutions that protect against malicious attacks. Key to this is automated security monitoring capabilities driven through AWS Lambda triggers. 

Security engineers are responsible for implementing and managing security monitoring solutions to detect and respond to security threats in the cloud. 

Getting Started With AWS Lambda

It’s easy to get started and experiment with Lambda. While there are many approaches, the following steps can help you get certified:

1. Learn the concepts of serverless computing. Familiarize yourself with serverless computing and AWS Lambda. Once you’re ready, consider taking one of our AWS Lambda and serverless computing courses. These courses teach you how to write and deploy Lambda serverless functions.
2. Gain hands-on experience with Lambda functions. Open a free account with AWS, experiment with writing Lambda functions, and take advantage of AWS Lambda’s free tier. This gives you a million free requests each month and a significant amount of free compute time. 
3. Explore AWS services that integrate with Lambda. Discover and experiment with various AWS services, such as the API Gateway, S3 storage, and DynamoDB. Read the AWS Lambda developer guide to learn more about Lambda-based applications.
4. Work on real-world Lambda projects. Use the knowledge gained in your course to develop expertise with real-life projects. Experiment with AWS Lambda tutorials and discover Lambda layers on GitHub. Join the AWS Lambda Community for new ideas and help. 
5. Earn AWS Certifications. Open up future job opportunities by gaining AWS certifications, such as AWS Certified Developer – Associate or AWS Certified Solutions Architect – Associate. You may need to take further Udemy courses and enroll in an AWS Exam Prep course for the qualification you’re seeking. 

Learn AWS Lambda With Udemy Courses

Udemy offers online technical education courses across the globe. We have more than 250,000 courses available and a network of over 75,000 expert instructors. Our courses include interactive question-and-answer sessions with your instructor. 

We also offer certification prep courses and practice tests. Reasons to choose Udemy include:

• Comprehensive selection of courses. We provide a comprehensive range of courses covering everything from the basics of Lambda and serverless architectures to advanced developer courses. 
• Hands-on projects. We offer a selection of hands-on projects where you can practice building serverless web applications with AWS Lambda. Udemy provides a wide range of associated projects to help you gain experience.
• Learn from industry experts at your own pace. Our instructors are all experts in their fields. They provide up-to-date lectures and study materials while allowing you to work at your own pace. 
• Expert preparation for AWS Certifications. We offer a range of specialized courses to help you prepare for AWS Certification exams. All AWS Certification courses include on-demand video tutorials and practice exams.

Master AWS Lambda Today

If you want a career focusing on the AWS ecosystem, mastering Lambda is crucial. Lambda is key to developing serverless cloud services on AWS. Its unique design allows you to create scalable and efficient applications that are fully automated. 

By successfully mastering AWS Lambda, you’re opening the door to a rewarding career in fields such as cloud design, DevOps, and data and software engineering. Obtaining full AWS Certification means your skills are validated and internationally recognized. 

Start learning AWS Lambda by signing up for one of our top courses today. Working at your own pace, you’ll learn how to use Lambda to develop serverless applications on AWS. You’ll also receive individual guidance and feedback from the instructor and a certificate on the completion of the course. 

Glossary of AWS Lambda & Cloud Computing Terms

1. Serverless Computing – A cloud computing model where developers can run code without managing servers. The cloud provider automatically handles infrastructure, scaling, and maintenance.
   
2. AWS Lambda – A serverless compute service from Amazon Web Services (AWS) that runs code in response to events, automatically managing resources and scaling.
   
3. Function (Lambda Function) – A small, self-contained piece of code that AWS Lambda executes in response to an event.
   
4. Event-Driven Architecture – A software design pattern where code is triggered by specific events, such as a file being uploaded or a database entry being modified.
   
5. Cold Start – A delay that occurs when AWS Lambda initializes a function for the first time or after a period of inactivity.
   
6. Scaling (Auto-Scaling) – The process of automatically adjusting computing resources based on demand to ensure efficient performance.
   
7. Infrastructure – The underlying technology (servers, storage, networking) that supports cloud applications and services.
   
8. Microservices – A software development approach that breaks applications into small, independent services that communicate with each other. AWS Lambda is commonly used to run microservices.
   
9. API Gateway – An AWS service that allows developers to create, publish, and manage APIs that connect with backend systems, including AWS Lambda functions.
   
10. S3 (Amazon Simple Storage Service) – A storage service in AWS used to store and retrieve data. It can trigger AWS Lambda functions when files are added or modified.
    
11. DynamoDB – A fully managed NoSQL database service by AWS that can trigger AWS Lambda functions when data changes occur.
    
12. CI/CD (Continuous Integration/Continuous Deployment) – A development practice that automates the process of testing and releasing software updates. AWS Lambda is often used in CI/CD pipelines.
    
13. IAM (Identity and Access Management) – AWS’s system for managing permissions and access to cloud resources, including AWS Lambda.
    
14. Compute Time – The amount of time a cloud provider spends executing code. AWS Lambda charges based on compute time rather than fixed server costs.
    
15. AWS Certification – Official credentials from AWS that validate cloud computing skills, including knowledge of AWS Lambda and other AWS services.