7 AWS Lambda courses delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is intended for security engineers, security architects, and information security professionals. Overview Identify security benefits and responsibilities of using the AWS Cloud Build secure application infrastructures Protect applications and data from common security threats Perform and automate security checks Configure authentication and permissions for applications and resources Monitor AWS resources and respond to incidents Capture and process logs Create and configure automated and repeatable deployments with tools such as AMIs and AWS CloudFormation This course demonstrates how to efficiently use AWS security services to stay secure in the AWS Cloud. The course focuses on the security practices that AWS recommends for enhancing the security of your data and systems in the cloud. The course highlights the security features of AWS key services including compute, storage, networking, and database services. You will also learn how to leverage AWS services and tools for automation, continuous monitoring and logging, and responding to security incidents. Prerequisites We recommend that attendees of this course have: * Working knowledge of IT security practices and infrastructure concepts * Familiarity with cloud computing concepts * Completed AWS Security Essentials and Architecting on AWS courses 1 - SECURITY ON AWS * Security in the AWS cloud * AWS Shared Responsibility Model * Incident response overview * DevOps with Security Engineering 2 - IDENTIFYING ENTRY POINTS ON AWS * Identify the different ways to access the AWS platform * Understanding IAM policies * IAM Permissions Boundary * IAM Access Analyzer * Multi-factor authentication * AWS CloudTrail 3 - SECURITY CONSIDERATIONS: WEB APPLICATION ENVIRONMENTS * Threats in a three-tier architecture * Common threats: user access * Common threats: data access * AWS Trusted Advisor 4 - APPLICATION SECURITY * Amazon Machine Images * Amazon Inspector * AWS Systems Manager 5 - DATA SECURITY * Data protection strategies * Encryption on AWS * Protecting data at rest with Amazon S3, Amazon RDS, Amazon DynamoDB * Protecting archived data with Amazon S3 Glacier * Amazon S3 Access Analyzer * Amazon S3 Access Points 6 - SECURING NETWORK COMMUNICATIONS * Amazon VPC security considerations * Amazon VPC Traffic Mirroring * Responding to compromised instances * Elastic Load Balancing * AWS Certificate Manager 7 - MONITORING AND COLLECTING LOGS ON AWS * Amazon CloudWatch and CloudWatch Logs * AWS Config * Amazon Macie * Amazon VPC Flow Logs * Amazon S3 Server Access Logs * ELB Access Logs 8 - PROCESSING LOGS ON AWS * Amazon Kinesis * Amazon Athena 9 - SECURITY CONSIDERATIONS: HYBRID ENVIRONMENTS * AWS Site-to-Site and Client VPN connections * AWS Direct Connect * AWS Transit Gateway 10 - OUT-OF-REGION PROTECTION * Amazon Route 53 * AWS WAF * Amazon CloudFront * AWS Shield * AWS Firewall Manager * DDoS mitigation on AWS 11 - SECURITY CONSIDERATIONS: SERVERLESS ENVIRONMENTS * Amazon Cognito * Amazon API Gateway * AWS Lambda 12 - THREAT DETECTION AND INVESTIGATION * Amazon GuardDuty * AWS Security Hub * Amazon Detective 13 - SECRETS MANAGEMENT ON AWS * AWS KMS * AWS CloudHSM * AWS Secrets Manager 14 - AUTOMATION AND SECURITY BY DESIGN * AWS CloudFormation * AWS Service Catalog 15 - ACCOUNT MANAGEMENT AND PROVISIONING ON AWS * AWS Organizations * AWS Control Tower * AWS SSO * AWS Directory Service

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Intermediate software developers Overview In this course, you will learn to: Set up the AWS SDK and developer credentials for Java, C#/.NET, Python, and JavaScript Interact with AWS services and develop solutions by using the AWS SDK Use AWS Identity and Access Management (IAM) for service authentication Use Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB as data stores Integrate applications and data by using AWS Lambda, Amazon API Gateway, Amazon Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS), and AWS Step Functions Use Amazon Cognito for user authentication Use Amazon ElastiCache to improve application scalability Leverage the CI/CD pipeline to deploy applications on AWS In this course, you learn how to use the AWS SDK to develop secure and scalable cloud applications using multiple AWS services such as Amazon DynamoDB, Amazon Simple Storage Service, and AWS Lambda. You explore how to interact with AWS using code and learn about key concepts, best practices, and troubleshooting tips. MODULE 0: COURSE OVERVIEW * Agenda * Introductions * Student resources MODULE 1: INTRODUCTION TO AWS * Introduction to the AWS Cloud * Cloud scenarios * Infrastructure overview * Introduction to AWS foundation services MODULE 2: INTRODUCTION TO DEVELOPING ON AWS * Getting started with developing on AWS Introduction to developer tools Introduction to management tools MODULE 3: INTRODUCTION TO AWS IDENTITY AND ACCESS MANAGEMENT * Shared responsibility model * Introduction to IAM * Use authentication and authorization MODULE 4: INTRODUCTION TO THE LAB ENVIRONMENT * Introduction to the lab environment * Lab 1: Getting started and working with IAM MODULE 5: DEVELOPING STORAGE SOLUTIONS WITH AMAZON SIMPLE STORAGE SERVICE * Overview of AWS storage options * Amazon S3 key concepts * Best practices * Troubleshooting * Scenario: Building a complete application * Lab 2: Developing storage solutions with Amazon S3 MODULE 6: DEVELOPING FLEXIBLE NOSQL SOLUTIONS WITH AMAZON DYNAMODB * Introduction to AWS database options * Introduction to Amazon DynamoDB * Developing with DynamoDB * Best practices * Troubleshooting * Scenario: Building an end-to-end app * Lab 3: Developing flexible NoSQL solutions with Amazon DynamoDB MODULE 7: DEVELOPING EVENT-DRIVEN SOLUTIONS WITH AWS LAMBDA * What is serverless computing? * Introduction to AWS Lambda * Key concepts * How Lambda works * Use cases * Best practices * Scenario: Build an end-to-end app MODULE 8: DEVELOPING SOLUTIONS WITH AMAZON API GATEWAY * Introduction to Amazon API Gateway * Developing with API Gateway * Best practices * Introduction to AWS Serverless Application Model * Scenario: Building an end-to-end app * Lab 4: Developing event-driven solutions with AWS Lambda MODULE 9: DEVELOPING SOLUTIONS WITH AWS STEP FUNCTIONS * Understanding the need for Step Functions * Introduction to AWS Step Functions * Use cases MODULE 10: DEVELOPING SOLUTIONS WITH AMAZON SIMPLE QUEUE SERVICE AND AMAZON SIMPLE NOTIFICATION SERVICE * Why use a queueing service? * Developing with Amazon Simple Queue Service * Developing with Amazon Simple Notification Service * Developing with Amazon MQ * Lab 5: Developing messaging solutions with Amazon SQS and Amazon SNS MODULE 11: CACHING INFORMATION WITH AMAZON ELASTICACHE * Caching overview * Caching with Amazon ElastiCache * Caching strategies MODULE 12: DEVELOPING SECURE APPLICATIONS * Securing your applications * Authenticating your applications to AWS * Authenticating your customers * Scenario: Building an end-to-end app MODULE 13: DEPLOYING APPLICATIONS * Introduction to DevOps * Introduction to deployment and testing strategies * Deploying applications with AWS Elastic Beanstalk * Scenario: Building an end-to-end app * Lab 6: Building an end-to-end app MODULE 14: COURSE WRAP-UP * Course overview * AWS training courses * Certifications * Course feedback

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. MODULE 1: MACHINE LEARNING OVERVIEW * A brief history of AI, ML, and DL * The business importance of ML * Common challenges in ML * Different types of ML problems and tasks * AI on AWS MODULE 2: INTRODUCTION TO DEEP LEARNING * Introduction to DL * The DL concepts * A summary of how to train DL models on AWS * Introduction to Amazon SageMaker * Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model MODULE 3: INTRODUCTION TO APACHE MXNET * The motivation for and benefits of using MXNet and Gluon * Important terms and APIs used in MXNet * Convolutional neural networks (CNN) architecture * Hands-on lab: Training a CNN on a CIFAR-10 dataset MODULE 4: ML AND DL ARCHITECTURES ON AWS * AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) * Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) * Hands-on lab: Deploying a trained model for prediction on AWS Lambda ADDITIONAL COURSE DETAILS: Nexus Humans Deep Learning on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Deep Learning on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for Experienced software developers who are already familiar with AWS services Overview In this course, you will learn how to: Analyze a monolithic application architecture to determine logical or programmatic break points where the application can be broken up across different AWS services Apply Twelve-Factor Application manifesto concepts and steps while migrating from a monolithic architecture Recommend the appropriate AWS services to develop a microservices based cloud-native application Use the AWS API, CLI, and SDKs to monitor and manage AWS services Migrate a monolithic application to a microservices application using the 6 Rs of migration Explain the SysOps and DevOps interdependencies necessary to deploy a microservices application in AWS The Advanced Developing on AWS course uses the real-world scenario of taking a legacy, on-premises monolithic application and refactoring it into a serverless microservices architecture. This three-day advanced course covers advanced development topics such as architecting for a cloud-native environment; deconstructing on-premises, legacy applications and repackaging them into cloud-based, cloud-native architectures; and applying the tenets of the Twelve-Factor Application methodology. MODULE 1: THE CLOUD JOURNEY * Common off-cloud architecture * Introduction to Cloud Air * Monolithic architecture * Migration to the cloud * Guardrails * The six R?s of migration * The Twelve-Factor Application Methodology * Architectural styles and patterns * Overview of AWS Services * Interfacing with AWS Services * Authentication * Infrastructure as code and Elastic Beanstalk * Demonstration: Walk through creating base infrastructure with AWS CloudFormation in the AWS console * Hands-on lab 1: Deploy your monolith application using AWS Elastic Beanstalk MODULE 2: GAINING AGILITY * DevOps * CI/CD * Application configuration * Secrets management * CI/CD Services in AWS * Demonstration: Demo AWS Secrets Manager MODULE 3: MONOLITH TO MICROSERVICES * Microservices * Serverless * A look at Cloud Air * Microservices using Lambda and API Gateway * SAM * Strangling the Monolith * Hands-on lab: Using AWS Lambda to develop microservices MODULE 4: POLYGLOT PERSISTENCE & DISTRIBUTED COMPLEXITY * Polyglot persistence * DynamoDB best practices * Distributed complexity * Steps functions MODULE 5: RESILIENCE AND SCALE * Decentralized data stores * Amazon SQS * Amazon SNS * Amazon Kinesis Streams * AWS IoT Message Broker * Serverless event bus * Event sourcing and CQRS * Designing for resilience in the cloud * Hands-on lab: Exploring the AWS messaging options MODULE 6: SECURITY AND OBSERVABILITY * Serverless Compute with AWS Lambda * Authentication with Amazon Cognito * Debugging and traceability * Hands-on lab: Developing microservices on AWS ADDITIONAL COURSE DETAILS: Nexus Humans Advanced Developing on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Advanced Developing on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: DevOps engineers DevOps architects Operations engineers System administrators Developers Overview In this course, you will learn to: Use DevOps best practices to develop, deliver, and maintain applications and services at high velocity on AWS List the advantages, roles and responsibilities of small autonomous DevOps teams Design and implement an infrastructure on AWS that supports DevOps development projects Leverage AWS Cloud9 to write, run and debug your code Deploy various environments with AWS CloudFormation Host secure, highly scalable, and private Git repositories with AWS CodeCommit Integrate Git repositories into CI/CD pipelines Automate build, test, and packaging code with AWS CodeBuild Securely store and leverage Docker images and integrate them into your CI/CD pipelines Build CI/CD pipelines to deploy applications on Amazon EC2, serverless applications, and container-based applications Implement common deployment strategies such as 'all at once,' 'rolling,' and 'blue/green' Integrate testing and security into CI/CD pipelines Monitor applications and environments using AWS tools and technologies DevOps Engineering on AWS teaches you how to use the combination of DevOps cultural philosophies, practices, and tools to increase your organization?s ability to develop, deliver, and maintain applications and services at high velocity on AWS. This course covers Continuous Integration (CI), Continuous Delivery (CD), infrastructure as code, microservices, monitoring and logging, and communication and collaboration. Hands-on labs give you experience building and deploying AWS CloudFormation templates and CI/CD pipelines that build and deploy applications on Amazon Elastic Compute Cloud (Amazon EC2), serverless applications, and container-based applications. Labs for multi-pipeline workflows and pipelines that deploy to multiple environments are also included. MODULE 0: COURSE OVERVIEW * Course objective * Suggested prerequisites * Course overview breakdown MODULE 1: INTRODUCTION TO DEVOPS * What is DevOps? The Amazon journey to DevOps Foundations for DevOps MODULE 2: INFRASTRUCTURE AUTOMATION * Introduction to Infrastructure Automation * Diving into the AWS CloudFormation template * Modifying an AWS CloudFormation template * Demonstration: AWS CloudFormation template structure, parameters, stacks, updates, importing resources, and drift detection MODULE 3: AWS TOOLKITS * Configuring the AWS CLI * AWS Software Development Kits (AWS SDKs) * AWS SAM CLI * AWS Cloud Development Kit (AWS CDK) * AWS Cloud9 * Demonstration: AWS CLI and AWS CDK * Hands-on lab: Using AWS CloudFormation to provision and manage a basic infrastructure MODULE 4: CONTINUOUS INTEGRATION AND CONTINUOUS DELIVERY (CI/CD) WITH DEVELOPMENT TOOLS * CI/CD Pipeline and Dev Tools * Demonstration: CI/CD pipeline displaying some actions from AWS CodeCommit, AWS CodeBuild, AWS CodeDeploy and AWS CodePipeline * Hands-on lab: Deploying an application to an EC2 fleet using AWS CodeDeploy * AWS CodePipeline * Demonstration: AWS integration with Jenkins * Hands-on lab: Automating code deployments using AWS CodePipeline MODULE 5: INTRODUCTION TO MICROSERVICES * Introduction to Microservices MODULE 6: DEVOPS AND CONTAINERS * Deploying applications with Docker Amazon Elastic Container Service and AWS Fargate Amazon Elastic Container Registry and Amazon Elastic Kubernetes service Demonstration: CI/CD pipeline deployment in a containerized application MODULE 7: DEVOPS AND SERVERLESS COMPUTING * AWS Lambda and AWS Fargate AWS Serverless Application Repository and AWS SAM AWS Step Functions Demonstration: AWS Lambda and characteristics Demonstration: AWS SAM quick start in AWS Cloud9 Hands-on lab: Deploying a serverless application using AWS Serverless Application Model (AWS SAM) and a CI/CD Pipeline MODULE 8: DEPLOYMENT STRATEGIES * Continuous Deployment Deployments with AWS Services MODULE 9: AUTOMATED TESTING * Introduction to testing * Tests: Unit, integration, fault tolerance, load, and synthetic * Product and service integrations MODULE 10: SECURITY AUTOMATION * Introduction to DevSecOps * Security of the Pipeline * Security in the Pipeline * Threat Detection Tools * Demonstration: AWS Security Hub, Amazon GuardDuty, AWS Config, and Amazon Inspector MODULE 11: CONFIGURATION MANAGEMENT * Introduction to the configuration management process AWS services and tooling for configuration management Hands-on lab: Performing blue/green deployments with CI/CD pipelines and Amazon Elastic Container Service (Amazon ECS) MODULE 12: OBSERVABILITY * Introduction to observability * AWS tools to assist with observability * Hands-on lab: Using AWS DevOps tools for CI/CD pipeline automations MODULE 13: REFERENCE ARCHITECTURE (OPTIONAL MODULE) * Reference architectures MODULE 14: COURSE SUMMARY * Components of DevOps practice * CI/CD pipeline review * AWS Certification

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Database architects Database administrators Database developers Data analysts and scientists Overview This course is designed to teach you how to: Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution Architect the data warehouse Identify performance issues, optimize queries, and tune the database for better performance Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data MODULE 1: INTRODUCTION TO DATA WAREHOUSING * Relational databases * Data warehousing concepts * The intersection of data warehousing and big data * Overview of data management in AWS * Hands-on lab 1: Introduction to Amazon Redshift MODULE 2: INTRODUCTION TO AMAZON REDSHIFT * Conceptual overview * Real-world use cases * Hands-on lab 2: Launching an Amazon Redshift cluster MODULE 3: LAUNCHING CLUSTERS * Building the cluster * Connecting to the cluster * Controlling access * Database security * Load data * Hands-on lab 3: Optimizing database schemas MODULE 4: DESIGNING THE DATABASE SCHEMA * Schemas and data types * Columnar compression * Data distribution styles * Data sorting methods MODULE 5: IDENTIFYING DATA SOURCES * Data sources overview * Amazon S3 * Amazon DynamoDB * Amazon EMR * Amazon Kinesis Data Firehose * AWS Lambda Database Loader for Amazon Redshift * Hands-on lab 4: Loading real-time data into an Amazon Redshift database MODULE 6: LOADING DATA * Preparing Data * Loading data using COPY * Data Warehousing on AWS * AWS Classroom Training * Concurrent write operations * Troubleshooting load issues * Hands-on lab 5: Loading data with the COPY command MODULE 7: WRITING QUERIES AND TUNING FOR PERFORMANCE * Amazon Redshift SQL * User-Defined Functions (UDFs) * Factors that affect query performance * The EXPLAIN command and query plans * Workload Management (WLM) * Hands-on lab 6: Configuring workload management MODULE 8: AMAZON REDSHIFT SPECTRUM * Amazon Redshift Spectrum * Configuring data for Amazon Redshift Spectrum * Amazon Redshift Spectrum Queries * Hands-on lab 7: Using Amazon Redshift Spectrum MODULE 9: MAINTAINING CLUSTERS * Audit logging * Performance monitoring * Events and notifications * Lab 8: Auditing and monitoring clusters * Resizing clusters * Backing up and restoring clusters * Resource tagging and limits and constraints * Hands-on lab 9: Backing up, restoring and resizing clusters MODULE 10: ANALYZING AND VISUALIZING DATA * Power of visualizations * Building dashboards * Amazon QuickSight editions and feature

Duration 3 Days 18 CPD hours This course is intended for Developers who have some familiarity with serverless and experience with development in the AWS Cloud Overview In this course, you will learn to: Apply event-driven best practices to a serverless application design using appropriate AWS services Identify the challenges and trade-offs of transitioning to serverless development, and make recommendations that suit your development organization and environment Build serverless applications using patterns that connect AWS managed services together, and account for service characteristics, including service quotas, available integrations, invocation model, error handling, and event source payload Compare and contrast available options for writing infrastructure as code, including AWS CloudFormation, AWS Amplify, AWS Serverless Application Model (AWS SAM), and AWS Cloud Development Kit (AWS CDK) Apply best practices to writing Lambda functions inclusive of error handling, logging, environment re-use, using layers, statelessness, idempotency, and configuring concurrency and memory Apply best practices for building observability and monitoring into your serverless application Apply security best practices to serverless applications Identify key scaling considerations in a serverless application, and match each consideration to the methods, tools, or best practices to manage it Use AWS SAM, AWS CDK, and AWS developer tools to configure a CI/CD workflow, and automate deployment of a serverless application Create and actively maintain a list of serverless resources that will assist in your ongoing serverless development and engagement with the serverless community This course gives developers exposure to and practice with best practices for building serverless applications using AWS Lambda and other services in the AWS serverless platform. You will use AWS frameworks to deploy a serverless application in hands-on labs that progress from simpler to more complex topics. You will use AWS documentation throughout the course to develop authentic methods for learning and problem-solving beyond the classroom. INTRODUCTION * Introduction to the application you will build * Access to course resources (Student Guide, Lab Guide, and Online Course Supplement) THINKING SERVERLESS * Best practices for building modern serverless applications * Event-driven design * AWS services that support event-driven serverless applications API-DRIVEN DEVELOPMENT AND SYNCHRONOUS EVENT SOURCES * Characteristics of standard request/response API-based web applications * How Amazon API Gateway fits into serverless applications * Try-it-out exercise: Set up an HTTP API endpoint integrated with a Lambda function * High-level comparison of API types (REST/HTTP, WebSocket, GraphQL) INTRODUCTION TO AUTHENTICATION, AUTHORIZATION, AND ACCESS CONTROL * Authentication vs. Authorization * Options for authenticating to APIs using API Gateway * Amazon Cognito in serverless applications * Amazon Cognito user pools vs. federated identities SERVERLESS DEPLOYMENT FRAMEWORKS * Overview of imperative vs. declarative programming for infrastructure as code * Comparison of CloudFormation, AWS CDK, Amplify, and AWS SAM frameworks * Features of AWS SAM and the AWS SAM CLI for local emulation and testing USING AMAZON EVENTBRIDGE AND AMAZON SNS TO DECOUPLE COMPONENTS * Development considerations when using asynchronous event sources * Features and use cases of Amazon EventBridge * Try-it-out exercise: Build a custom EventBridge bus and rule * Comparison of use cases for Amazon Simple Notification Service (Amazon SNS) vs. EventBridge * Try-it-out exercise: Configure an Amazon SNS topic with filtering EVENT-DRIVEN DEVELOPMENT USING QUEUES AND STREAMS * Development considerations when using polling event sources to trigger Lambda functions * Distinctions between queues and streams as event sources for Lambda * Selecting appropriate configurations when using Amazon Simple Queue Service (Amazon SQS) or Amazon Kinesis Data Streams as an event source for Lambda * Try-it-out exercise: Configure an Amazon SQS queue with a dead-letter queue as a Lambda event source WRITING GOOD LAMBDA FUNCTIONS * How the Lambda lifecycle influences your function code * Best practices for your Lambda functions * Configuring a function * Function code, versions and aliases * Try-it-out exercise: Configure and test a Lambda function * Lambda error handling * Handling partial failures with queues and streams STEP FUNCTIONS FOR ORCHESTRATION * AWS Step Functions in serverless architectures * Try-it-out exercise: Step Functions states * The callback pattern * Standard vs. Express Workflows * Step Functions direct integrations * Try-it-out exercise: Troubleshooting a Standard Step Functions workflow OBSERVABILITY AND MONITORING * The three pillars of observability * Amazon CloudWatch Logs and Logs Insights * Writing effective log files * Try-it-out exercise: Interpreting logs * Using AWS X-Ray for observability * Try-it-out exercise: Enable X-Ray and interpret X-Ray traces * CloudWatch metrics and embedded metrics format * Try-it-out exercise: Metrics and alarms * Try-it-out exercise: ServiceLens SERVERLESS APPLICATION SECURITY * Security best practices for serverless applications * Applying security at all layers * API Gateway and application security * Lambda and application security * Protecting data in your serverless data stores * Auditing and traceability HANDLING SCALE IN SERVERLESS APPLICATIONS * Scaling considerations for serverless applications * Using API Gateway to manage scale * Lambda concurrency scaling * How different event sources scale with Lambda AUTOMATING THE DEPLOYMENT PIPELINE * The importance of CI/CD in serverless applications * Tools in a serverless pipeline * AWS SAM features for serverless deployments * Best practices for automation * Course wrap-up ADDITIONAL COURSE DETAILS: Nexus Humans AWS Developing Serverless Solutions on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the AWS Developing Serverless Solutions on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.