Practical Spring Cloud Function : Developing Cloud-Native Functions for Multi-Cloud and Hybrid-Cloud Environments

Unlike other resources that target only programming communities, this book targets both programming and business communities. With programming models shifting more towards no-code and low-code, citizen programmers from the business side will welcome this book as a guide for how to design and optimize their information pipeline while lowering costs for infrastructure. Programmers, on the other hand, will welcome this book's business-centric programming view, which will get them a step closer to fulfilling real business requirements. Practical Spring Cloud Function touches on the themes of portability, scalability, high performance and high availability. Each theme is explored via a real enterprise use case and code. The use cases target industries including energy (oil pipeline sensors), automotive (event-driven connected vehicles), and retail (conversational AI). After reading this book, you'll come away with the know-how to build and deploy cloud-native Java applications effectively and efficiently. What You Will Learn Write functions and deploy to Amazon Web Services, Microsoft Azure, Google Cloud, IBM Cloud, and on-prem clouds such as VMWare Tanzu and RedHat OpenShift Set up locally with KNative on Kubernetes, as well as on AWS, Azure, GCP, Tanzu, and others Build, test, and deploy a simple example with Spring Cloud Function Develop an event-driven data pipeline with Spring Cloud Function Integrate with AI and machine learning models Apply Spring Cloud Function to the Internet of Things (IoT) Get industry-specific examples of Spring Cloud Function in action Who This Book Is For Software and cloud-native application developers with prior programming experience in the cloud and/or Spring Framework. DevOps professionals may find this book beneficial as well. Table of Contents About the Author About the Technical Reviewer Acknowledgments Introduction Chapter 1: Why Use Spring Cloud Function 1.1. Functions as a Service (FaaS) 1.1.1. Implementation of an Enterprise Application 1.1.2. Migration ROI for a Portfolio of Application 1.1.3. The Serverless Functions Concept 1.1.4. Applying the Serverless Functions Concept to an Enterprise Application Serverless Function in the Cloud Why Is It Important for Serverless Functions to be Non-Proprietary? 1.2. Code Portability Issues 1.2.1. Serverless Container Portability Issue 1.3. Spring Cloud Function: Writing Once and Deploying to Any Cloud 1.4. Project Knative and Portable Serverless Containers 1.4.1. Containers, Serverless Platforms, and Knative 1.4.2. What Is Knative? 1.5. Sample Use Case: Payroll Application 1.6. Spring Cloud Function Support 1.6.1. Spring Cloud Function on AWS Lambda on AWS 1.6.2. Spring Cloud Function on Knative and EKS on AWS 1.6.3. Spring Cloud Function on Cloud Functions on GCP 1.6.4. Spring Cloud Function on Knative and GKE on GCP 1.6.5. Spring Cloud Function on Azure Functions on Azure 1.6.6. Spring Cloud Function on Knative and AKS on Azure 1.6.7. Spring Cloud Function on VMware Tanzu (TKG, PKS) 1.6.8. Spring Cloud Function on Red Hat OpenShift (OCP) 1.7. Summary Chapter 2: Getting Started with Spring Cloud Function 2.1. Setting Up the Spring Boot and Spring Cloud Function Locally 2.1.1. Step 1: Create the Spring Boot Scaffolding 2.1.2. Step 2: Create the Employee Model 2.1.3. Step 3: Write the Consumer 2.1.4. Step 4: Write the Supplier 2.1.5. Step 5: Write the Function 2.1.6. Step 6: Deploy and Run the Code Locally 2.1.7. Step 7: Test the Function 2.2. Setting Up Spring Cloud Function and AWS Lambda 2.3. Setting Up Spring Cloud Function and Google Cloud Functions 2.4. Setting Up Spring Cloud Function Azure Functions 2.5. Setting Up Locally with Kubernetes and Knative and Spring Cloud Function 2.6. Setting Up AWS with EKS and Knative with Spring Cloud Function 2.7. Setting Up GCP with Cloud Run/GKE and Knative with Spring Cloud Function 2.8. Setting Up Azure with AKS and Knative with Spring Cloud Function 2.9. Setting Up VMware Tanzu TKG and Knative 2.10. Summary Chapter 3: CI/CD with Spring Cloud Function 3.1. GitHub Actions 3.2. ArgoCD 3.3. Building a Simple Example with Spring Cloud Function 3.4. Setting Up a CI/CD Pipeline to Deploy to a Target Platform 3.5. Deploying to the Target Platform 3.5.1. Deploying to AWS Lambda 3.6. Deploying to GCP Cloud Functions 3.7. Deploying to Azure Functions 3.8. Deploying to Knative on Kubernetes 3.9. Summary Chapter 4: Building Event-Driven Data Pipelines with Spring Cloud Function 4.1. Data Event Pipelines 4.1.1. Acquire Data 4.1.2. Store/Ingest Data 4.1.3. Transform Data 4.1.4. Load Data 4.1.5. Analyze Data 4.2. Spring Cloud Function and Spring Cloud Data Flow and Spring Cloud Streams 4.2.1. Spring Cloud Function and SCDF 4.3. Spring Cloud Function and AWS Glue 4.3.1. Step 1: Set Up Kinesis 4.3.2. Step 2: Set Up AWS Glue 4.3.3. Step 3: Create a Function to Load Data into Kinesis 4.4. Spring Cloud Function and Google Cloud Dataflow 4.5. Summary Chapter 5: AI/ML Trained Serverless Endpoints with Spring Cloud Function 5.1. AI/ML in a Nutshell 5.1.1. Deciding Between Java and Python or Other Languages for AI/ML 5.2. Spring Framework and AI/ML 5.3. Model Serving with Spring Cloud Function with DJL 5.3.1. What Is DJL? 5.3.2. Spring Cloud Function with DJL 5.4. Model Serving with Spring Cloud Function with Google Cloud Functions and TensorFlow 5.4.1. TensorFlow 5.4.2. Example Model Training and Serving 5.5. Model Serving with Spring Cloud Function with AWS Lambda and TensorFlow 5.6. Spring Cloud Function with AWS SageMaker or AI/ML 5.7. Summary Chapter 6: Spring Cloud Function and IoT 6.1. The State of IoT 6.1.1. Example Spring Implementation 6.1.2. An Argument for Serverless Functions On-Premises 6.2. Spring Cloud Function on the Cloud with AWS IoT 6.3. Spring Cloud Function on the Cloud with Azure IoT 6.3.1. Azure IoT Edge Device 6.3.2. Azure IoT Hub 6.4. Spring Cloud Function on Azure IoT Edge 6.5. Spring Cloud Function On-Premises with IoT Gateway on a SaaS Provider (SmartSense) 6.6. Summary Chapter 7: Industry-Specific Examples with Spring Cloud Function 7.1. Oil/Natural Gas Pipeline Tracking with Spring Cloud Function and IOT 7.1.1. Sensors 7.1.2. IoT Gateway 7.1.3. IBM Cloud Functions 7.1.4. IBM Watson IoT Platform 7.1.5. IBM Watson IoT Platform: Message Gateway 7.1.6. IBM Event Streams 7.1.7. IBM Cloudant DB 7.2. Enabling Healthcare with Spring Cloud Function and Big Data Pipelines 7.3. Conversational AI in Retail Using Spring Cloud Function 7.3.1. Components of Conversational AI Solutions 7.3.2. Watson Assistant Webhooks and Spring Cloud Function 7.3.3. Implementing the Watson Assistant with Spring Cloud Function 7.4. Summary Index