Familiar with Amazon EKS, ECS, Lambda, faregate, and Serverless

Introduction

In the rapidly evolving world of cloud computing, organizations increasingly leverage containerization and serverless computing to build, deploy, and manage applications efficiently. Amazon Web Services (AWS) offers several powerful services to facilitate these needs: Amazon Elastic Kubernetes Service (EKS), Amazon Elastic Container Service (ECS), and AWS Lambda. Each service provides unique benefits tailored to specific application requirements and operational models. This guide provides a comprehensive overview of these services, highlighting their key features, architectures, use cases, and differences to help make informed decisions.

Amazon Elastic Kubernetes Service (EKS)

Amazon Elastic Kubernetes Service (EKS) is a fully managed Kubernetes service that simplifies the process of running Kubernetes on AWS. EKS eliminates the need to install, operate, and maintain your own Kubernetes control plane or nodes, allowing you to focus on building and scaling your applications. The key features of EKS are:

• Managed Control Plane: AWS handles the Kubernetes control plane operations, ensuring high availability and scalability across multiple Availability Zones.
• Integration with AWS Services: EKS integrates with various AWS services, such as IAM for authentication, VPC for network isolation, and CloudWatch for logging and monitoring.
• Flexible Scaling: EKS supports horizontal pod autoscaling and cluster autoscaling, enabling applications to scale based on demand.
• Security: It provides robust security features, including IAM roles for fine-grained access control, AWS PrivateLink for private connectivity, and secret encryption with AWS KMS.
• Multi-Region and Multi-AZ Support: Ensures high availability and fault tolerance by distributing control plane components across multiple regions and Availability Zones.

The architecture of EKS involves several key components that work together to provide a seamless, scalable, and secure environment for running containerized applications.

Kubernetes Control Plane

AWS manages the control plane components, ensuring high availability across multiple Availability Zones. This means you don’t have to worry about the control plane's uptime or scaling. The control plane components, such as the API server ETCD, are monitored and automatically replaced if they fail, ensuring resilience. some control plane components that are managed by AWS are:

• API Server: The API server is the front end of the Kubernetes control plane. It exposes the Kubernetes API and is responsible for handling all the administrative tasks of the Kubernetes cluster.
• ETCD: A consistent and highly available key-value store used as Kubernetes' backing store for all cluster data.
• Controller Manager: This role runs controller processes that regulate the state of the cluster, such as the Node, Replication, and Endpoints Controllers.
• Scheduler: This process assigns workloads (pods) to specific nodes in the cluster based on resource availability and other constraints.

Worker Nodes

You can manage worker nodes by EC2 or use AWS Fargate for a serverless experience. When using EC2 instances as worker nodes, you can choose instance types, attach additional storage, and configure auto-scaling groups. Also, EKS nodes are automatically registered with the cluster, and the kubelet (the Kubernetes node agent) runs on each node, managing the lifecycle of pods on that node.

• EC2 Instances: EKS worker nodes are EC2 instances that run containerized applications. These instances can be managed by EKS or by the user.
• AWS Fargate: A serverless compute engine for containers that lets run containers without managing the underlying EC2 instances.

Networking

• Amazon VPC: Each EKS cluster runs in a VPC, providing network isolation and security. The VPC is configured with subnets, route tables, and security groups.
• Elastic Load Balancing (ELB): Used to distribute incoming traffic across multiple nodes and ensure high availability.
• Kubernetes Networking: Includes CNI (Container Network Interface) plugins for network setup and management within the cluster.

Storage

• Amazon EBS: Provides persistent block storage for applications.
• Amazon EFS: Provides scalable file storage for EKS clusters.
• Amazon S3: Often used for object storage and can be integrated with Kubernetes for various storage needs.

Security

EKS integrates with AWS IAM to provide fine-grained access control. You can define IAM roles and policies to control access to the EKS API and resources. Network policies and security groups are used to control traffic between pods and services within the cluster. Secrets and configuration data can be stored securely using Kubernetes Secrets and AWS KMS (Key Management Service).

Observability

EKS integrates with Amazon CloudWatch for logging and monitoring. CloudWatch Container Insights allows you to collect and visualize metrics from your Kubernetes clusters. AWS X-Ray can be used to trace and debug applications running on EKS. Fluentd and other logging agents can be deployed within the cluster to aggregate and forward logs to various endpoints.

EKS seamlessly integrates with several AWS services to enhance its capabilities:

IAM (Identity and Access Management)

EKS uses IAM to manage permissions and authentication. This allows the creation of fine-grained access control policies for users and applications. IAM roles can be assigned to Kubernetes service accounts, providing secure and granular access control within your cluster.

VPC (Virtual Private Cloud)

Every EKS cluster is deployed in a VPC for Kubernetes workload security and isolation. Customize VPC settings like subnets, security groups, and route tables to align with networking needs. Also, AWS PrivateLink can be utilized for private EKS connectivity without public Internet exposure.

Elastic Load Balancing (ELB)

EKS supports integration with Classic Load Balancers, Application Load Balancers (ALB), and Network Load Balancers (NLB) to distribute incoming traffic. Ingress controllers like the AWS ALB Ingress Controller can manage HTTP and HTTPS application traffic.

Amazon RDS (Relational Database Service).

Amazon RDS-hosted databases can be securely accessed from the EKS cluster using VPC endpoints and security groups. EKS can handle the lifecycle of database connections, offering high availability and failover features.

AWS Fargate

Fargate enables running Kubernetes pods without the need to handle the underlying infrastructure. This serverless choice simplifies cluster management, lessening operational burden. Fargate automatically scales in response to the running pod count, guaranteeing adequate resources for your applications.

Amazon CloudWatch

CloudWatch Container Insights offers comprehensive metrics and logs for EKS clusters. Generate dashboards to visualize cluster performance and establish alarms to monitor key metrics. Logs can also be sent to CloudWatch Logs for centralized log management and analysis.

AWS X-Ray

X-Ray assists in tracking requests flowing through the EKS cluster, offering visibility into application performance and dependencies. It enables pinpointing bottlenecks, resolving issues, and enhancing the efficiency of your distributed applications.

Amazon S3 (Simple Storage Service)

Amazon S3 provides scalable object storage that can be used by applications running in EKS. You can store and retrieve large amounts of data, such as logs, backups, and media files. Kubernetes applications can interact with S3 using tools like the S3 API, Kubernetes secrets for storing credentials, and S3-backed storage classes for persistent storage.

AWS Secrets Manager and AWS Systems Manager Parameter Store

AWS Secrets Manager and Systems Manager Parameter Store can be used to securely store and manage sensitive information such as database credentials, API keys, and configuration parameters. Kubernetes secrets can be used to pull data from these AWS services, ensuring that your applications have secure access to necessary credentials.

Amazon EFS (Elastic File System)

Amazon EFS provides scalable file storage that can be mounted to the EKS worker nodes, allowing multiple pods to share the same file system. EFS can be used to provide persistent storage for stateful applications, ensuring data is retained across pod restarts and scaling events.

Amazon Elastic Kubernetes Service (EKS) offers a robust and scalable solution for running Kubernetes workloads on AWS. By leveraging EKS, you can focus on developing and deploying your applications while AWS manages the underlying infrastructure. The seamless integration with other AWS services further enhances EKS's capabilities, providing a comprehensive platform for building modern, containerized applications.

Amazon Elastic Container Service (ECS)

Amazon Elastic Container Service (ECS) is a fully managed container orchestration service that makes it easy to run, stop, and manage containers on a cluster. With ECS, you can deploy your applications in Docker containers on a fully managed cluster of Amazon EC2 instances or use the serverless AWS Fargate to run containers without managing the underlying infrastructure. ECS is designed to integrate deeply with the rest of the AWS ecosystem, offering a scalable, secure, and flexible solution for containerized applications. The key features of ECS are:

• AWS Integration: ECS integrates with other AWS services, such as IAM for access control, CloudWatch for monitoring and logging, and ELB for load balancing, providing a seamless experience.
• Ease of Use: Simplifies container management with task definitions, service definitions, and automatic scaling.
• Flexible Compute Options: Supports both Amazon EC2 instances and AWS Fargate for running containers.
• Security: Provides robust security features, including IAM task roles, network isolation with VPC, and ECS Service Discovery for service-to-service communication.
• Scalability: ECS can automatically scale your applications up or down based on defined metrics.

ECS architecture involves several components that work together to manage and orchestrate containerized applications.

Clusters

An ECS cluster is a logical grouping of tasks or services. You can run multiple clusters within a single account, and clusters can span multiple Availability Zones within a region.

• Amazon EC2 Instances: EC2 instances can be used as worker nodes in your ECS clusters. You have full control over instance types, storage, and network configurations.
• AWS Fargate: With Fargate, you can run containers without managing the underlying EC2 instances. Fargate handles all the infrastructure management for you.

Task Definitions

A task definition is a blueprint that describes how Docker containers should be run. It includes parameters such as the Docker image to use, CPU and memory requirements, and networking settings.

• Containers: Defines the image, port mappings, environment variables, and other container-specific configurations.
• Volumes: Specifies data volumes that can be mounted by containers.

Tasks and Services

Tasks and services are the units of work in ECS.

• Tasks: Running instances of a task definition. ECS can start tasks manually or automatically.
• Services: These services ensure that a specified number of tasks are constantly running and can optionally be load-balanced by ELB. They are used for long-running applications.

Networking

ECS uses Amazon VPC for network isolation and security. Each task or service can be configured with its own networking settings.

• Subnets: Tasks can run in private or public subnets within VPC.
• Security Groups: Control the inbound and outbound traffic to tasks.

Load Balancing

ECS integrates with Elastic Load Balancing (ELB) to distribute traffic across your tasks.

• Application Load Balancer (ALB): Best suited for HTTP and HTTPS traffic, providing advanced routing and load balancing features.
• Network Load Balancer (NLB): Handles TCP traffic and is optimized for high throughput and low latency.

Comprehending the fundamental mechanisms of ECS can assist in efficiently optimizing and overseeing containerized workloads.

• Managed Cluster and Task Scheduling: ECS manages the scheduling of tasks within a cluster, ensuring optimal placement based on resource requirements, constraints, and availability. The ECS scheduler monitors the cluster's state and reschedules tasks if needed, maintaining the desired state of your services.

• Serverless Compute with AWS Fargate: Fargate allows you to run containers without managing servers. You define your task definitions, and Fargate takes care of the rest, including provisioning, scaling, and maintaining the infrastructure. With Fargate, you only pay for the computing resources you use, making it a cost-effective option for running containers.

• Security and Compliance: ECS integrates with AWS IAM to provide fine-grained access control. You can assign IAM roles to ECS tasks, enabling secure and granular permissions. ECS supports VPC networking, allowing you to isolate tasks within your VPC and control traffic using security groups and network ACLs. ECS tasks can store sensitive information securely using AWS Secrets Manager and AWS Systems Manager Parameter Store.

• Monitoring and Logging: ECS integrates with Amazon CloudWatch to provide detailed metrics and logs for your tasks and services. You can create CloudWatch dashboards to monitor the performance of your cluster. Logs can be forwarded to CloudWatch Logs or other logging services using Fluentd or other log forwarding agents.

ECS integrates with a wide range of AWS services, enhancing its capabilities and providing a comprehensive platform for managing containerized applications:

IAM (Identity and Access Management)

ECS uses IAM to manage permissions and authentication. IAM roles can be assigned to ECS tasks, providing secure and granular access control. IAM can be used to authenticate users and applications accessing the ECS API.

VPC (Virtual Private Cloud)

ECS tasks run within a VPC, providing network isolation and security. You can configure subnets, route tables, and security groups. AWS PrivateLink can provide private connectivity to ECS without exposing traffic to the public Internet.

Elastic Load Balancing (ELB)

ECS supports integrating ALB and NLB to distribute incoming traffic across multiple tasks. Ingress controllers can manage HTTP and HTTPS traffic.

Amazon RDS (Relational Database Service)

ECS tasks can securely access databases hosted on Amazon RDS using VPC endpoints and security groups. ECS can manage the lifecycle of database connections.

Amazon CloudWatch

CloudWatch Container Insights provides detailed metrics and logs for ECS tasks. You can create dashboards to visualize cluster performance and set up alarms to monitor critical metrics.

AWS X-Ray

X-Ray helps you trace requests as they travel through your ECS tasks, providing insights into application performance and dependencies.

Amazon S3 (Simple Storage Service)

Amazon S3 provides scalable object storage that can be used by ECS tasks. You can store and retrieve large amounts of data, such as logs, backups, and media files.

AWS Secrets Manager and AWS Systems Manager Parameter Store

These services can be used to securely store and manage sensitive information such as database credentials, API keys, and configuration parameters. ECS tasks can access these secrets securely.

Amazon EFS (Elastic File System)

Amazon EFS provides scalable file storage that can be mounted to ECS tasks, allowing multiple containers to share the same file system.

Amazon Elastic Container Service (ECS) offers a robust and scalable solution for running containerized applications on AWS. Whether you prefer managing your own EC2 instances or opting for a serverless experience with AWS Fargate, ECS provides the flexibility and integration needed to build and deploy modern applications. By leveraging ECS and its seamless integration with other AWS services, you can focus on developing your applications while AWS handles the underlying infrastructure.

Serverless Computing with AWS

Serverless computing is a cloud computing execution model where the cloud provider dynamically manages the allocation and provisioning of servers. In a serverless architecture, developers can build and run applications and services without having to manage the underlying infrastructure. AWS provides several services that enable serverless computing, including AWS Lambda, AWS Fargate, Amazon API Gateway, and AWS Step Functions. The key features of serverless are:

• No Server Management: Developers do not need to provision, scale, or manage any servers. The cloud provider handles all infrastructure management tasks.
• Automatic Scaling: Serverless applications automatically scale up and down based on the number of incoming requests, ensuring optimal resource utilization.
• Cost-Efficiency: With serverless computing, you only pay for the computing time you consume. There are no charges for idle resources.
• Event-Driven Execution: Serverless functions are triggered by events such as HTTP requests, changes in data, or messages from other services.
• Rapid Deployment: Serverless architectures enable faster development cycles by focusing on small units of functionality, known as functions.

The AWS Serverless Services

AWS serverless services are the essential cloud computing services that are used to build and operate serverless applications. These services eliminate the need to manage servers and infrastructure, allowing developers to focus solely on writing and deploying code.

1. AWS Lambda

AWS Lambda is a serverless compute service that runs code in response to events and automatically manages the underlying compute resources. The features are:

• Event-Driven: Executes code in response to various events, such as HTTP requests, changes in data in S3 buckets or DynamoDB tables, and messages from SNS and SQS.
• Fully Managed: AWS handles the provisioning, scaling, patching, and management of the servers required to run your code.
• Short Execution Time: Designed for short-lived tasks with a maximum execution time of 15 minutes per invocation.

2. AWS Fargate

AWS Fargate is a serverless compute engine for containers that works with Amazon ECS and Amazon EKS. The key features are:

• Serverless Containers: Allows to run containers without managing the underlying EC2 instances.
• Seamless Integration: Works with ECS and EKS, providing flexibility in container orchestration.
• Automatic Scaling: Automatically scales your applications based on demand.

3. Amazon API Gateway

Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs. The key features are:

• RESTful APIs: Create RESTful APIs that act as a "front door" for applications to access data, business logic, or functionality from backend services.
• WebSocket APIs: Build WebSocket APIs that enable two-way communication between clients and servers.
• Integration: Seamlessly integrates with AWS Lambda, enabling serverless API backends.

4. AWS Step Functions

AWS Step Functions is a serverless orchestration service that lets coordinate multiple AWS services into serverless workflows.

• State Machines: Define workflows as state machines, where each step is a state that performs a task.
• Error Handling and Retries: Built-in error handling and retries for each step in the workflow.
• Integration: Integrates with AWS Lambda, ECS, Fargate, and other AWS services.

Serverless computing with AWS offers a powerful and flexible solution for running applications without managing the underlying infrastructure. You can build highly scalable and cost-efficient applications that automatically scale based on demand by leveraging services like AWS Lambda, AWS Fargate, Amazon API Gateway, and AWS Step Functions. The seamless integration with various AWS services further enhances the capabilities of serverless computing, providing a comprehensive platform for building modern, event-driven applications.

AWS Fargate

AWS Fargate is a serverless compute engine for containers that work with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). Fargate allows containers to run without having to manage the underlying server infrastructure, providing a simplified and scalable way to deploy containerized applications.

Key Features of AWS Fargate

• Serverless: Fargate eliminates the need to provision and manage servers. You define your container specifications, and Fargate handles the rest.
• Seamless Integration: Works with both ECS and EKS, allowing you to choose your preferred container orchestration service.
• Automatic Scaling: Fargate automatically scales your applications based on demand, ensuring you have the right amount of computing resources.
• Cost-Efficiency: You pay only for the compute resources that your containers use, with no upfront costs or long-term commitments.
• Security: Provides isolation at the infrastructure level, with each task or pod running in its own dedicated environment.

Fargate Architecture

The architecture of AWS Fargate involves several components that work together to provide a seamless, scalable, and secure environment for running containerized applications.

1. Task Definitions (ECS) and Pod Specifications (EKS)

Task definitions in ECS and pod specifications in EKS describe how your containers should be run. These include details such as the Docker image, CPU and memory requirements, networking settings, and environment variables.

• Containers: Defines the image, port mappings, environment variables, and other container-specific configurations.
• Volumes: Specifies data volumes that can be mounted by containers.

2. Tasks (ECS) and Pods (EKS)

Tasks in ECS and pods in EKS are the units of work in Fargate. Each task or pod runs one or more containers as defined in the task definition or pod specification.

• Tasks (ECS): Running instances of a task definition. ECS can start tasks manually or automatically.
• Pods (EKS): Groups of one or more containers that are scheduled and managed by Kubernetes.

3. Clusters

Clusters are logical groupings of tasks or pods. Fargate manages the infrastructure for these clusters, ensuring they have the necessary resources.

• ECS Clusters: Logical groupings of tasks that can span multiple Availability Zones.
• EKS Clusters: Logical groupings of pods managed by Kubernetes.

4. Networking

Fargate tasks and pods run within your Amazon VPC, providing network isolation and security. You can configure subnets, route tables, and security groups to control network traffic.

• Subnets: Tasks and pods can run in private or public subnets within your VPC.
• Security Groups: Control the inbound and outbound traffic to your tasks and pods.

5. Storage

Fargate integrates with various AWS storage services to provide persistent storage for your containers.

• Amazon EBS: Provides persistent block storage for your applications.
• Amazon EFS: Provides scalable file storage for your containers.
• Amazon S3: Often used for object storage and can be integrated with containers for various storage needs.

AWS Fargate offers a powerful and flexible solution for running containerized applications without managing the underlying infrastructure. By leveraging Fargate with ECS or EKS, you can focus on building and deploying your applications while AWS handles the heavy lifting of infrastructure management. The seamless integration with various AWS services further enhances Fargate's capabilities, providing a comprehensive platform for building modern, scalable, and cost-efficient containerized applications.

AWS Lambda

AWS Lambda is a serverless compute service that runs your code in response to events and automatically manages the underlying compute resources. With Lambda, you can run code without provisioning or managing servers, making it a cost-effective solution for running applications and backend services. Lambda allows you to focus on writing and deploying code while AWS handles the infrastructure, scaling, and availability. The key features of Lambda are:

• Event-Driven Execution: AWS Lambda executes your code in response to various events such as HTTP requests, changes in data in S3 buckets or DynamoDB tables, and messages from Amazon SNS and SQS.
• Fully Managed: AWS handles the infrastructure, including provisioning, scaling, patching, and managing the servers required to run your code.
• Automatic Scaling: Lambda automatically scales applications by running code in response to each event, scaling precisely with the size of the workload.
• Short Execution Time: Lambda is designed for short-lived tasks, with a maximum execution time of 15 minutes per invocation.
• Cost-Efficiency: You only pay for the computing time you consume, with no charges when your code is not running. This includes both the number of requests and the duration of the code execution.

The architecture of AWS Lambda involves several key components that work together to provide a scalable, reliable, and efficient execution environment for your code.

Lambda Functions

Lambda functions are the core building blocks of AWS Lambda. Each function contains your code along with associated configuration information such as the function name, resource requirements, and runtime environment.

• Code: Can be written in various programming languages such as Node.js, Python, Java, Go, .NET Core, and Ruby.
• Handler: The entry point for Lambda to begin executing your code. The handler receives the event data and context object.
• Runtime: The runtime provides the language-specific environment for your code. AWS Lambda supports multiple runtimes, and you can also bring your own custom runtime.

Event Sources

Event sources are services or systems that generate events to trigger Lambda functions.

• Amazon S3: Events such as object creation or deletion in S3 buckets.
• Amazon DynamoDB: Stream records when items are added, updated, or deleted.
• Amazon SNS: Messages published to an SNS topic.
• Amazon SQS: Messages in an SQS queue.
• Amazon Kinesis: Stream records from Kinesis data streams.
• Amazon CloudWatch Events and Logs: Scheduled events or log events.
• API Gateway: HTTP requests to RESTful APIs.

Execution Environment

The execution environment is the runtime environment that AWS Lambda provides for executing your functions.

• Isolation: Each function runs in its own isolated environment.
• Ephemeral Storage: A temporary file system available during the execution.
• Memory Allocation: Configurable from 128 MB to 10,240 MB, affecting the CPU and network resources allocated.

Understanding the underlying mechanisms of AWS Lambda can help optimize and manage serverless applications effectively:

Execution Model

Lambda functions are triggered by events from AWS services or custom event sources. When an event occurs, Lambda launches an execution environment to run the function code. The execution environment is initialized, which includes setting up the runtime, loading the function code, and running any initialization code.

Scaling and Performance

AWS Lambda scales automatically by running additional instances of your function in response to incoming events. Each instance of your function can process a single event at a time. Lambda functions can scale from a few requests per day to thousands per second, depending on the volume of events.

Cold Starts and Warm Starts

Cold Start Occurs when a new execution environment is created. It includes the time taken to set up the runtime and initialize the function. Warm Start Reuses an existing execution environment for subsequent invocations, resulting in lower latency.

Security and Compliance

Lambda integrates with AWS IAM to provide fine-grained access control. You can assign IAM roles to Lambda functions, enabling secure and granular permissions. Environment variables can be used to securely pass configuration settings and sensitive information.

Monitoring and Logging

AWS Lambda integrates with Amazon CloudWatch to provide detailed metrics and logs for your functions. You can create CloudWatch dashboards to monitor the performance of your functions. Logs can be viewed and analyzed in CloudWatch Logs, and you can set up alarms to monitor function execution.

Integration with AWS Services

AWS Lambda integrates seamlessly with various AWS services, enhancing its capabilities and providing a comprehensive platform for building serverless applications:

IAM (Identity and Access Management)

• Access Control: Lambda uses IAM to manage permissions and authentication. IAM roles can be assigned to Lambda functions, providing secure and granular access control.
• Authentication: IAM can be used to authenticate users and applications accessing the Lambda API.

VPC (Virtual Private Cloud)

• Network Isolation: Lambda functions can run within a VPC, providing network isolation and security. You can configure subnets, route tables, and security groups.
• Private Connectivity: AWS PrivateLink can provide private connectivity to Lambda functions without exposing traffic to the public Internet.

Amazon S3

• Event Triggers: Lambda functions can be triggered by events in Amazon S3, such as object creation or deletion.
• Storage Integration: Lambda functions can read from and write to S3 buckets, enabling data processing and storage operations.

Amazon DynamoDB

• Event Triggers: Lambda functions can be triggered by changes in DynamoDB tables, such as item insertions, updates, or deletions.
• Database Integration: Lambda functions can interact with DynamoDB to read and write data, enabling serverless database operations.

Amazon SNS and SQS

• Event Triggers: Lambda functions can be triggered by messages published to SNS topics or messages in SQS queues.
• Message Processing: Lambda functions can process messages, enabling asynchronous workflows and event-driven architectures.

Amazon Kinesis

• Stream Processing: Records in Kinesis data streams can trigger Lambda functions, enabling real-time data processing and analytics.

Amazon CloudWatch

• Monitoring and Logging: CloudWatch provides detailed metrics and logs for Lambda functions. You can create dashboards to monitor function performance and set up alarms to detect issues.
• Scheduled Events: Lambda functions can be triggered by scheduled events in CloudWatch, enabling periodic tasks and cron jobs.

Amazon RDS (Relational Database Service)

• Database Integration: Lambda functions can securely access databases hosted on Amazon RDS using VPC endpoints and security groups. Lambda can handle the lifecycle of database connections, offering high availability and failover features.

AWS Secrets Manager and AWS Systems Manager Parameter Store

• Secure Storage of Secrets: These services can be used to securely store and manage sensitive information such as database credentials, API keys, and configuration parameters. Lambda functions can access these secrets securely.

AWS Step Functions

• Orchestration: AWS Step Functions can be used to coordinate multiple Lambda functions into workflows, providing state management, error handling, and retries.

AWS Lambda offers a powerful and flexible solution for running serverless applications on AWS. With its event-driven execution model, automatic scaling, and seamless integration with various AWS services, Lambda enables you to build highly scalable and cost-efficient applications without managing the underlying infrastructure. By leveraging AWS Lambda and its integrations, you can focus on writing and deploying code while AWS handles the heavy lifting of infrastructure management.