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Deploying AWS serverless APIs involves several steps. Here's a general guide to help you deploy AWS serverless APIs: AWS Account: Ensure you have an AWS account. If not, sign up for one at AWS Console. Set Up AWS CLI: Install the AWS Command Line Interface (CLI) on your local machine. Configure the CLI with your AWS credentials using the aws configure command. Code Your Serverless Functions: Write the code for your serverless functions using AWS Lambda. You can use the AWS Lambda Console, AWS SAM (Serverless Application Model), or your preferred IDE. Define API Gateway: If you haven't already, set up API Gateway to define the API structure, endpoints, and methods. You can do this through the AWS Management Console or by using the AWS CLI. Configure API Gateway Integration: Configure API Gateway to integrate with your Lambda functions. Define the API Gateway methods and link them to the corresponding Lambda functions. Authentication and Authorization: Implement authentication and authorization mechanisms if required. AWS Cognito, IAM roles, or API Gateway API keys are common options. Configure Environment Variables: Set any necessary environment variables for your Lambda functions, such as connection strings or API keys. Testing: Test your serverless functions and the API Gateway to ensure everything works as expected. Consider both unit tests and integration tests. Optimize for Cold Starts: Address cold start issues if necessary by optimizing dependencies and adopting strategies to reduce initialization time. Package Dependencies: If your functions have external dependencies, package them along with your code using AWS SAM or other packaging tools. Deploy Using AWS SAM (Optional): If you're using AWS SAM, create a template.yaml file describing your serverless application. Deploy the application using the sam deploy command. Deploy Using AWS Console or CLI: Use the AWS Management Console to manually deploy your Lambda functions and API Gateway. Alternatively, use the AWS CLI with commands like aws lambda create-function and aws apigateway create-rest-api. Monitor Deployment: Monitor the deployment process for any errors or issues. AWS CloudWatch logs provide valuable insights into the execution and errors of your functions. Configure Auto-Scaling (Optional): If needed, configure auto-scaling for your Lambda functions to automatically adjust the number of concurrent executions based on demand. Testing in Production: After deployment, perform additional testing in a production-like environment to ensure that your serverless API behaves as expected under real-world conditions. Monitor and Iterate: Regularly monitor the performance and usage of your serverless API using AWS CloudWatch and other monitoring tools. Iterate on your deployment as needed to optimize performance and address any issues. Always refer to the AWS documentation for the specific services you are using for detailed instructions and best practices.

Transform Your Development Workflow with AWS Serverless Services Harnessing the power of Amazon Web Services (AWS) Serverless Services can revolutionize your development workflow, enabling you to build and deploy applications faster and more efficiently. Here’s how AWS serverless solutions can empower your business and streamline your operations. AWS Lambda: Event-Driven Computing AWS Lambda lets you run code without provisioning or managing servers. Simply upload your code, and Lambda handles the rest, automatically scaling based on demand. This service is perfect for building event-driven architectures, microservices, and backend services. Amazon API Gateway: Secure and Scalable APIs Amazon API Gateway allows you to create, publish, maintain, monitor, and secure APIs at any scale. It acts as a front door for applications to access data, business logic, or functionality from your backend services. Amazon DynamoDB: Fast and Flexible NoSQL Database Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. It's ideal for applications that require low-latency data access at any scale. AWS Step Functions: Orchestration Made Easy AWS Step Functions allows you to coordinate multiple AWS services into serverless workflows, making it easier to build and update applications quickly. With Step Functions, you can design and run workflows that stitch together services such as AWS Lambda and Amazon ECS into feature-rich applications. Amazon S3: Scalable Object Storage Amazon S3 provides scalable, durable, and secure storage for any amount of data. It's designed to make web-scale computing easier by offering a simple web service interface to store and retrieve any amount of data from anywhere on the web. Amazon EventBridge: Building Event-Driven Architectures Amazon EventBridge is a serverless event bus that makes it easier to build event-driven applications by connecting application data from your own apps, SaaS, and AWS services. Conclusion AWS serverless services enable you to focus on writing code and innovating, without worrying about server management. These services automatically scale with your application, providing high availability and fault tolerance out of the box. By leveraging AWS serverless solutions, you can accelerate development, reduce operational overhead, and improve your application's scalability and resilience. 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 👉🏻   https://lnkd.in/e2sq98PN https://lnkd.in/e-9dJf8i 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤 👉🏻 https://lnkd.in/eWcXVwAt 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 👉🏻https://lnkd.in/ehA5ePqX #AWS #Serverless #CloudComputing #Lambda #DynamoDB #API #StepFunctions #S3 #EventBridge #DevOps #NoSQL LP754

Day 7: AWS Lambda – Powering Serverless Computing 👋 Hello, Connections! Welcome to Day 7 of my AWS series! Today, we’re diving into one of the most innovative AWS services—AWS Lambda, the backbone of serverless computing. Let’s explore how you can run code without provisioning or managing servers! 🚀 🔹 What is AWS Lambda? • Imagine a world where you can focus solely on writing code, and the infrastructure worries vanish. That's AWS Lambda! Lambda lets you run code without provisioning or managing servers. Simply upload your code, and AWS Lambda takes care of the rest—from auto-scaling to running your functions in response to events. •It's serverless computing at its finest—just write code and let Lambda handle the execution whenever triggered. 🔹 Why Use AWS Lambda? AWS Lambda provides incredible benefits: ⚡ Cost-Efficient: Pay only for the compute time your code consumes, down to the millisecond. You’re not billed for idle time! 📈 Auto-Scaling: Lambda automatically scales based on the number of requests. No more worrying about server capacity! 🛠️ Simplified Operations: Focus on coding, not managing infrastructure. No server provisioning, patching, or scaling required. 🔹 Key Concepts: 📝 Functions: Your code logic. Upload your function in one of the supported languages (Node.js, Python, Java, Go, etc.), and Lambda will execute it based on defined triggers. 🚨 Event Sources: Lambda can be triggered by various AWS services such as: S3: Process objects when uploaded. DynamoDB: Trigger actions when data changes. API Gateway: Run functions on API requests. ⌛ Execution Duration: Lambda functions have a max execution time of 15 minutes. If your workload exceeds this, you can chain multiple Lambdas together or use Step Functions for orchestration. • Environment Variables: You can pass dynamic data (such as database connections or API keys) into your function at runtime using environment variables. • Layers: Lambda Layers allow you to manage and share code dependencies separately from your main function code, optimizing reusability. 🔹 Use Case: Imagine you’re running an eCommerce platform. You can use Lambda for: Image Processing: Automatically resize product images when uploaded to S3. Order Processing: Trigger order workflows based on customer purchases. Notifications: Send automated emails or push notifications when certain actions occur, like orders being placed. 🔹 Key Features: ⚡ Event-Driven: Lambda triggers based on defined events (S3 uploads, database changes, API calls). 📏 Highly Scalable: Automatically scales with the number of requests, whether it’s 1 or 1 million. 💸 Pay-Per-Use: Only pay for the time your function runs—no idle costs! 🌍 Fully Managed: No server management. AWS handles all backend operations. 🔹 When to Use AWS Lambda: • When you want to run code without managing servers. • When you have event-driven workloads (like file uploads, API requests, or database updates). #AWS #CloudInfrastructure #Serverless

Transform Your Development Workflow with AWS Serverless Services Harnessing the power of Amazon Web Services (AWS) Serverless Services can revolutionize your development workflow, enabling you to build and deploy applications faster and more efficiently. Here’s how AWS serverless solutions can empower your business and streamline your operations. 🌀 AWS Lambda: Event-Driven Computing AWS Lambda lets you run code without provisioning or managing servers. Simply upload your code, and Lambda handles the rest, automatically scaling based on demand. This service is perfect for building event-driven architectures, microservices, and backend services. 🌀 Amazon API Gateway: Secure and Scalable APIs Amazon API Gateway allows you to create, publish, maintain, monitor, and secure APIs at any scale. It acts as a front door for applications to access data, business logic, or functionality from your backend services. 🌀 Amazon DynamoDB: Fast and Flexible NoSQL Database Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. It's ideal for applications that require low-latency data access at any scale. 🌀 AWS Step Functions: Orchestration Made Easy AWS Step Functions allows you to coordinate multiple AWS services into serverless workflows, making it easier to build and update applications quickly. With Step Functions, you can design and run workflows that stitch together services such as AWS Lambda and Amazon ECS into feature-rich applications. 🌀 Amazon S3: Scalable Object Storage Amazon S3 provides scalable, durable, and secure storage for any amount of data. It's designed to make web-scale computing easier by offering a simple web service interface to store and retrieve any amount of data from anywhere on the web. 🌀 Amazon EventBridge: Building Event-Driven Architectures Amazon EventBridge is a serverless event bus that makes it easier to build event-driven applications by connecting application data from your own apps, SaaS, and AWS services. 🌀 Conclusion AWS serverless services enable you to focus on writing code and innovating, without worrying about server management. These services automatically scale with your application, providing high availability and fault tolerance out of the box. By leveraging AWS serverless solutions, you can accelerate development, reduce operational overhead, and improve your application's scalability and resilience. 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 👉🏻   https://lnkd.in/ezHXZv9G https://lnkd.in/eahN4sWH 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤 👉🏻 https://lnkd.in/encdeXKB 𝐅𝐨𝐥𝐥𝐨𝐰 𝐮𝐬 𝐨𝐧 𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦 👉🏻https://lnkd.in/eFQP-pRb #AWS #Serverless #CloudComputing #Lambda #DynamoDB #API #StepFunctions #S3 #EventBridge #DevOps #NoSQL LP711

🚀 Deploying to AWS Lambda Using Containers: The Future of Serverless Applications 🛳️ Why Use Containers with AWS Lambda? -Language Flexibility: Build your Lambda functions in any language, not just those natively supported by Lambda. Have a specialized runtime? No problem—just containerize it! -Dependency Management: Package your application and all its dependencies into a single container image. This is especially useful for applications with complex dependencies that are tricky to manage in traditional Lambda deployments. -Portability: Easily move your workloads between environments—whether on-premises, other cloud providers, or AWS Lambda—without needing to refactor your code. -Standardized Development: Use your existing Docker tooling, CI/CD pipelines, and development workflows to build and test Lambda functions. How It Works: -Build Your Container Image: Use Docker to package your application code, dependencies, and custom runtimes into a container image. This image is essentially your Lambda function. -Push to Amazon ECR: Once your container image is ready, push it to Amazon Elastic Container Registry (ECR), a fully managed container registry that integrates seamlessly with AWS Lambda. -Deploy to Lambda: Configure your Lambda function to use the container image stored in ECR. AWS Lambda takes care of provisioning, scaling, and managing the underlying infrastructure, just like with traditional Lambda functions. Benefits of Lambda with Containers: -Seamless Integration: Continue using the same AWS Lambda triggers and event sources you're familiar with, but with the added flexibility of containers. -Effortless Scaling: Automatically scale your containerized applications in response to incoming traffic, without worrying about infrastructure management. -Cost Efficiency: Enjoy the same cost model as standard Lambda functions—pay only for the compute time you consume. Real-World Use Cases: -Legacy Applications: Easily lift-and-shift legacy applications into AWS Lambda by containerizing them. -Machine Learning Inference: Deploy machine learning models with complex dependencies or custom runtimes in a containerized Lambda function. -Polyglot Environments: Run functions written in multiple programming languages within the same environment by containerizing each one. Why It Matters: By combining the flexibility of containers with the simplicity of AWS Lambda, you can modernize your applications, reduce operational overhead, and accelerate your development process. Whether you’re dealing with complex dependencies, custom runtimes, or simply looking for a more standardized way to manage your serverless applications, deploying Lambda with containers is a powerful option to consider. #AWS #Serverless #Containers #Lambda #CloudComputing #DevOps #Docker #CloudDeveloper #opentowork

🖥️ What I have learned about AWS Lambda so far... AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS) that lets you run code without provisioning or managing servers. Lambda automatically scales your application by running code in response to triggers, such as changes to data in an S3 bucket, updates to a DynamoDB table, or custom events. 🌟 Key Features: ⚡ Event-driven Execution: Lambda executes your code in response to various triggers such as HTTP requests via API Gateway, file uploads in S3, updates in DynamoDB, and more. 📈 Scalability: Automatically scales up and down based on the number of incoming requests. There’s no need to manage server infrastructure. 💰 Cost-effective: Pay only for the compute time you consume – there’s no charge when your code is not running. The first 1 million requests per month are free. 🔄 Flexibility: Supports multiple languages including Node.js, Python, Ruby, Java, Go, and .NET Core. You can also bring your own libraries. 🛠️ Integrations: Seamlessly integrates with other AWS services like S3, DynamoDB, Kinesis, CloudWatch, SNS, and more, allowing you to build complex serverless applications. 🏗️ How does it Work: When you create a Lambda function, you define a trigger, write the code, and set the execution role that grants necessary permissions. Once deployed, Lambda takes care of everything required to run and scale your code with high availability. 🔍 Use Cases: 📧 Data Processing: Handle real-time streaming data, such as from IoT devices or social media feeds, using services like Kinesis and Lambda. 🌐 Web Applications: Create backends for web applications using Lambda, API Gateway, and other AWS services to build a fully serverless architecture. 🔔 Event Handling: Automate tasks like log analysis, data transformation, and alerting by connecting Lambda with AWS CloudWatch and other monitoring tools. 🧰 DevOps Automation: Use Lambda to automate CI/CD pipelines, manage infrastructure as code, and handle custom deployment tasks. 🛡️ Security: AWS Lambda runs in a secure VPC, providing network isolation. You can further secure your functions using IAM roles and policies, allowing granular control over permissions and access to resources. 📊 Monitoring and Logging: AWS Lambda is integrated with Amazon CloudWatch, providing detailed logs and performance metrics. You can set up alarms and notifications to monitor the health and performance of your functions in real-time. 🎯 Getting Started: To get started with AWS Lambda, use the AWS Management Console, AWS CLI, or AWS SDKs to create your first function. AWS provides extensive documentation, tutorials, and a free tier to help you explore serverless computing. AWS Lambda enables you to focus on writing code and solving business problems without worrying about the underlying infrastructure. Its flexibility, scalability, and cost-efficiency make it a powerful tool for modern application development.

10 Must-Know AWS Serverless Services for Developers 1. AWS Lambda Well, well, well...if it isn't the star of the serverless show! Lambda lets you run code without worrying about servers. It's like having a team of tiny robots doing all the heavy lifting for you. Just toss your code over the wall, and Lambda will handle the rest with its event-driven magic and automatic scaling superpowers! 2. Amazon API Gateway API Gateway is the bouncer at the front door of your serverless applications. It makes creating, deploying, and managing APIs a breeze. It'll seamlessly integrate with Lambda, Cognito, and all the other AWS services in your toolbelt. 3. Amazon DynamoDB DynamoDB is a fully managed NoSQL database that's faster than a cheetah on a rocket-powered skateboard. It scales like a boss, making it the perfect fit for serverless apps with traffic patterns more unpredictable than a toddler's mood swings. Just be prepared for a bit of a learning curve – it's like learning a new language, but way more rewarding! 4. Amazon S3 Simple Storage Service (S3) is the ultimate storage locker for all your data needs. It's durable, scalable, and perfect for storing everything from serverless app data to static websites and data lakes. 5. AWS Step Functions Step Functions simplifies the coordination of distributed applications and microservices by providing a visual workflow service that manages and orchestrates Lambda functions and other AWS services. 6. Amazon EventBridge EventBridge is that guy who can introduce you to everyone at the party. It's a serverless event bus that enables you to react to a variety of events from AWS services, SaaS applications, and your own applications, making it a powerful tool for building event-driven architectures. 7. AWS CloudWatch CloudWatch is the all-seeing eye that keeps a watchful gaze over your AWS resources, applications, and services. It collects logs, metrics, and events, visualizing them in a way that would make even the most seasoned data analysts swoon. Plus, it lets you set alarms, so you'll never miss a beat (or a performance issue). 8. Amazon Cognito Cognito is the bouncer for your serverless app's users. It simplifies user authentication, authorization, and data management, providing a secure and scalable solution for managing user identities. 9. AWS Fargate Fargate is a serverless compute engine for containers, allowing you to run containers without managing servers or clusters, making it a perfect fit for running containerized serverless workloads. If you've got a stable workload and are looking to save on your Lambda bill, Fargate is a great way to go. 10. AWS X-Ray AWS X-Ray is the detective service that helps you analyze and debug your distributed applications. It's like having a team of private investigators profiling your services, pinpointing performance bottlenecks, and solving mysteries faster than Sherlock Holmes on a caffeine binge! #aws #serverless #software

🚀 DEVELOPING MY PLATFORM. PART 5: SERVERLESS FRAMEWORK So far in this series about building a platform on AWS Serverless services, we have: - Discussed CloudFront and Route 53 as the foundation for delivering assets to users - Highlighted API Gateway as the connection between these services and our Lambda functions - Implemented authentication using Cognito Hosted UI and JWT tokens In the first article, we distinguished between manually and automatically configured resources (see Screenshot 1). I won’t go into detail about the Serverless Framework here, because once it's set up on your desktop or integrated into your CI/CD pipeline, all you need to do to create resources in the cloud is run the following command: serverless deploy Instead, I'm going to show how it works in our use case, the tourists in transit platform, to show you how simple, enjoyable, and powerful it is to include IaC (Infrastructure as Code) in your projects. Note: I’m using this framework, but CloudFormation, AWS CDK, or any IaC tool will work just as well. In my serverless.yml I've declared the following ( see Video Recording 2 in the comments): - Cloud provider-specific information, focussing on runtime configuration - My Lambda functions, so far we've talked about two of them: Auth and Refresh - A DynamoDB table Note: The DynamoDB table is not a core part of the platform. It is disposable scaffolding to test and ensure secure CRUD operations throughout the stack. The provider section in the serverless.yml file defines key settings for the AWS environment, such as the Node.js runtime version, memory allocation, and function timeout limits. In screenshot 3, you can see a side-by-side comparison of the code from the serverless.yml file and the actual Lambda configuration in the AWS Web Console, showing how the settings are applied. The section where I spend more time (not so much time) is the Functions section. To create a Lambda function that listens in https://myapp_url/auth I need to specify, - the handler, to point to the code the Lambda function will run - the endpoint to be exposed by API Gateway Screenshot 4 illustrates the interconnected nature of our declarative Infrastructure as Code (IaC), Lambda functions, and API Gateway. I’ve added Video Recording 5 in the comments to further demonstrate how IaC simplifies the creation of complete CloudFormation stacks. This stack is generated from the same serverless.yml file we discussed earlier in this post. ⏭️ Next article about GITHUB ACTIONS: https://lnkd.in/dgXWgi9Q ⏪ Previous article about how to REFRESH JWT TOKENS: https://lnkd.in/dfnPsXHb #Serverless #CloudComputing #InfrastructureAsCode #ServerlessFramework #APIGateway #Lambda #DynamoDB #Cognito #AWSLambda #CI/CD #NodeJS #DigitalTransformation #TechCommunity #SoftwareDevelopment

I’ve been working on a project that leverages serverless architecture to create an automated Image Recognition Pipeline powered by some of the best AWS services! 💡📸 Check out the video attached to see how the app works. Also, check the architecture diagram in the comments section. 🔍 What I built: • A fully automated pipeline that processes images uploaded by users. When an image is uploaded, Amazon Rekognition is used to detect objects, text, and even celebrities in the image. 🖼️✨ • Users interact with the system via a secure CloudFront distribution, which connects to S3 for storing uploaded images. • AWS Lambda is triggered by each upload, calling Amazon Rekognition and saving the resulting metadata (labels, celebrities, texts) into DynamoDB for easy retrieval. • An API Gateway facilitates smooth communication between the front-end and back-end. 🌟 What is Amazon Rekognition? Amazon Rekognition is an AWS service that uses machine learning to analyze images and videos. With just a few API calls, you can detect objects, scenes, celebrities, and even text within an image. It’s incredibly powerful for building intelligent applications, and best of all—it requires no machine learning expertise to use. 🛠️ The Power of Simplicity in a Serverless Approach: I love how simple the architecture is, thanks to serverless technologies: • No servers to manage or scale. AWS services like Lambda and S3 scale automatically as needed. • Each component (storage, processing, and API) is fully managed, reducing overhead and complexity. • The solution is highly cost-efficient, as I only pay for what I use. No need for running servers 24/7—Lambda functions only run when triggered! 🔗 Key AWS Services Used: • Amazon S3: For scalable, secure image storage. • Amazon Rekognition: For extracting image metadata, including objects, texts, and even celebrity recognition! • AWS Lambda: To handle image processing and invoking Rekognition. • Amazon API Gateway: For managing API requests and responses between the client and server. • Amazon DynamoDB: For storing image metadata with fast, scalable performance. • CloudFront: For fast and secure content delivery to users. 💡 What I Learned: This project demonstrated how powerful and accessible AWS services are, especially when combined in a serverless architecture. Building an intelligent image-processing solution without having to manage any servers or complex infrastructure is a game-changer! 💪 Next Steps: I’m looking forward to further refining this project and possibly expanding its capabilities for real-time face analysis and reporting! I would love to mention some amazing individuals who have inspired me and who I learn from and collaborate with: Neal K. Davis Steven Moran Ali Sohail Eric Huerta Prasad Rao Azeez Salu Mike Hammond Teegan A. Bartos Maria Christidi Noble #AWS #CloudComputing #AmazonRekognition #Serverless #S3 #Lambda #API #DynamoDB #CloudFront #SolutionsArchitect #MachineLearning

What is AWS Lambda? AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS) that allows you to run code without provisioning or managing servers. Here's an overview of AWS Lambda: 1. Serverless Computing: Lambda follows the serverless computing model, where you can execute your code without worrying about underlying infrastructure management. You upload your code and define the events that trigger its execution, and AWS Lambda takes care of the rest. 2. Event-driven Execution: Lambda functions are triggered by various AWS services, such as Amazon S3, Amazon DynamoDB, Amazon API Gateway, Amazon SNS, Amazon SQS, and more. You can also trigger Lambda functions based on custom events using AWS SDKs. 3. Pay-per-Use Pricing: With Lambda, you pay only for the compute time your code consumes and the number of requests it handles. There are no upfront fees or ongoing commitments. This makes it cost-effective, especially for applications with varying workloads. 4. Support for Multiple Programming Languages: Lambda supports several programming languages, including Node.js, Python, Java, Go,.NET Core, and Ruby. This flexibility allows developers to choose the language they are most comfortable with. 5. Automatic Scaling: Lambda automatically scales to handle incoming requests. It provides the required infrastructure to execute your code in response to the incoming events. You don't need to worry about scaling or capacity planning. 6. Integrated Security: Lambda integrates with AWS Identity and Access Management (IAM) for access control and AWS Key Management Service (KMS) for encryption of function code and environment variables. You can define fine-grained permissions to control who can invoke your functions and what resources they can access. 7. Stateless Execution Environment: Lambda functions run in a stateless environment, meaning each function execution is isolated from previous executions. However, you can use external storage services like Amazon S3 or Amazon DynamoDB to maintain state across function invocations if needed. 8. Monitoring and Logging: Lambda provides built-in monitoring and logging through Amazon CloudWatch. You can monitor function invocations, errors, and performance metrics in real-time. You can also use CloudWatch Logs to capture and analyze log data generated by your Lambda functions. 9. Versioning and Aliases: Lambda supports versioning and aliases, allowing you to publish multiple versions of your functions and control which version is invoked by your applications. This feature is useful for A/B testing, blue-green deployments, and rolling updates. Overall, AWS Lambda simplifies the process of building scalable and cost-effective serverless applications by abstracting away the underlying infrastructure management, enabling developers to focus on writing code and delivering business value. #aws #cloudcomputing #devops #awsdevops #awslambda #awscommunity #cloudcommunity #DevOpscloud #cloud