26 AWS Lambda courses

Get hands-on with Kafka monitoring setup with Prometheus and Grafana, Kafka operations and Kafka cluster upgrades Setup in AWS.

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

This extensive course for beginners provides the basics of chatbots with machine learning, deep learning, AWS, and its applications, building it from scratch with hands-on practice for chatbot development. This course will help you learn basic to advanced mechanisms of developing chatbots using machine learning, deep learning, and AWS with Python.

This course not only comprises core theoretical concepts but also several interesting hands-on demonstrations that will help you build practical experience on the Amazon Web Services (AWS) platform; you will gain confidence in architecting, designing, and implementing solutions on AWS.

With this course, you will master all CloudFormation concepts, and become confident in writing CloudFormation templates using YAML. Throughout the course, you will encounter various interesting examples and activities that will help you to consolidate your learning.

This course covers the important topics needed to pass the AWS Certified Data Analytics-Specialty exam (AWS DAS-C01). You will learn about Kinesis, EMR, DynamoDB, and Redshift, and get ready for the exam by working through quizzes, exercises, and practice exams, along with exploring essential tips and techniques.

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

The course helps you learn Snowflake from scratch and explore a few of its important features. You will build automated pipelines with Snowflake and use the AWS cloud with Snowflake as a data warehouse. You will also explore Snowpark to be worked on the data pipelines.

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.

Better than REST APIs! Build a fast and scalable HTTP/2 API for a Go microservice with gRPC and protocol buffers (protobufs)