دانلود کتاب Google Cloud Certified Professional Cloud Developer Exam Guide: Modernize your applications using cloud-native services and best practices

فهرست مطالب :

Cover\nTitle Page\nCopyright and Credits\nContributors\nPreface\nSection 1: Welcome to the Google Cloud Developers Guide\nChapter 1: Google Cloud Platform Developer Fundamentals\n Technical requirements\n The basics that every developer should know about Google Cloud infrastructure\n Regions and zones\n What is X as a Service?\n How to reduce latency to your end users\n Graceful shutdowns\n Top tips for developing and implementing resilient and scalable applications\n Microservice ecosystems\n Handling user sessions and the importance of stateless applications in the autoscaling world\n Application logging, your best friend in error troubleshooting\n Why should your microservices handle retries?\n How to handle high traffic with autoscaling\n Avoiding overload caching your data\n Loosely coupled microservices with topics\n Don\'t waste your time – use cloud management services and securely run your applications\n Don\'t reinvent the wheel\n Accessing services in a secure way\n Summary\nChapter 2: Security Fundamentals and Best Practices\n Technical requirements\n Reducing the attack surface with POLP\n POLP\n How to authenticate client-to-service and service-to-service solutions\n IAM\n IAM hierarchy\n Service accounts\n Authenticating with Google services\n OAuth 2.0\n Identity-Aware Proxy\n Managing secrets with Google Secret Manager\n How to store your sensitive data in a secure way\n Google Secret Manager\n Cloud Key Management Service\n Google Cloud best practices\n POLP and roles\n Create one service account per microservice\n Avoid using Owner, Editor, and Viewer roles\n allUsers versus allAuthenticatedUsers\n Understand how the IAM hierarchy works\n Use Google management keys whenever possible\n Use OAuth 2.0 instead of sharing credentials between applications\n Use IAP when possible to authenticate and authorize users inside your organization\n Always use a key vault for the storage of secrets\n Summary\nSection 2: Developing and Modernizing Applications on Google Cloud Platform\nChapter 3: Application Modernization Using Google Cloud\n Technical requirements\n Preparing your environment for developing applications on Google Cloud\n Emulating Google Cloud services for local application development\n Creating Google Cloud projects\n Using the command-line interface withCloud SDK\n Using developer tooling\n Be sure that your application will work fine on the cloud with testing\n Unit testing\n Integration testing\n End-to-end testing\n Load testing\n Improving your delivery speed with continuous integration and delivery pipelines\n Source control management\n Creating secure container images from code\n Application modernization best practices\n Modern application design\n Refactoring a monolith to microservices\n Summary\nChapter 4: Using Cloud Functions and Google App Engine\n Technical requirements\n Welcome to serverless applications\n What is serverless?\n Advantages and disadvantages of serverless applications\n Event-based applications\n What is Google App Engine?\n Introducing Google Cloud Functions\n Different flavors for different situations\n HTTP functions\n Background functions\n Triggering cloud functions from Cloud Storage\n Triggering cloud functions from Pub/Sub\n Triggering cloud functions from Firestore\n Terminating HTTP functions\n Terminating background cloud functions\n App Engine standard environment\n App Engine flexible environment\n Exposing your services to the internet\n Google App Engine invoked via HTTP\n Cloud functions invoked via HTTP\n Deployment and security considerations\n Location considerations\n Securing cloud functions\n Securing App Engine\n How to make a canary release strategy with A/B testing\n Static versus dynamic data considerations\n Using traffic splitting in App Engine\n Summary\nChapter 5: Virtual Machines and Container Applications on Google Cloud Platform\n Technical requirements\n Introduction to Docker and Kubernetes\n What is Docker?\n What are containers and Docker container images?\n What is Kubernetes?\n Clusters, nodes, and pods in Kubernetes\n How to use virtual machines on GCP\n Google Compute Engine fundamentals\n Managing service accounts for VMs\n Bootstrapping applications\n Managing Compute Engine VM images\n Reading instance metadata to obtain application configuration\n Forgetting the complexity of managing a Kubernetes cluster with GKE and Cloud Run\n GKE fundamentals\n Cloud Run fundamentals\n Configuring Kubernetes namespaces\n Pod life cycle and resource configuration\n Managing Kubernetes RBAC and Google Cloud IAM relationships\n The full deployment life cycle of an application on Google Compute Engine\n Installing an application in a virtual machine\n Creating an instance template\n Creating a managed instance group\n Configuring a load balancer\n Hands-on tutorials in Google Compute Engine\n The full deployment life cycle of an application on Google Kubernetes Engine and Cloud Run\n Building a container image using Cloud Build\n Defining workload specifications\n Deploying a containerized application to GKE\n Deploying a containerized application to Cloud Run\n Hands-on tutorials in Cloud Run\n Summary\nChapter 6: Managing APIs on Google Cloud Platform\n Technical requirements\n The basics before implementing an API management solution in Google Cloud\n APIs\n API management\n The most common authentication methods\n OpenAPI Specification\n Swagger UI\n Swagger Editor\n How to protect your APIs using Cloud Endpoints on your deployments\n ESP implementation for Cloud Endpoints\n OpenAPI configuration for Cloud Endpoints\n Discovering the enterprise API management world with Apigee\n Deploying a serverless API using Cloud Functions\n Implementing an API management solution with Apigee\n Adding policies\n Creating an API product\n Creating a developer app\n Securing and managing your serverless workloads with the new Cloud API Gateway\n Deploying a serverless API using Cloud Functions\n Creating an API in API Gateway\n Exposing our service\n Protecting our services\n API development best practices\n An overview of DDD\n REST\n Summary\nSection 3: Storage Foundations\nChapter 7: Handling Unstructured Data\n Technical requirements\n Different real-world use cases for cloud storage\n Worldwide delivery\n Analytics\n Backup\n Disaster recovery\n Audit\n Optimizing costs regarding storage use cases\n How to reduce costs using different tiers\n Standard\n Nearline\n Coldline\n Archive\n Explaining storage pricing\n Cloud storage summary diagrams\n Backing up and deleting files automatically\n Managing life cycles\n Rule conditions\n Implementing object life cycles\n Object versioning\n Bucket retention policy\n Object hold protection\n Protecting my data with security best practices\n Access control\n Data encryption\n Signed URLs\n Integrating cloud storage with my application\n Storing and retrieving objects from cloud storage\n How to avoid CORS problems\n Summary\nChapter 8: Databases and Event Messages in Google Cloud\n Technical requirements\n First steps in the Cloud SQL and NoSQL world with Firestore\n What is Cloud SQL?\n Firestore\n Differences in designing and integrating a SQL database versus a NoSQL database in your application\n SQL versus NoSQL databases\n Which database is better for my workload?\n Traditional schema versus semi-structured database in Firestore\n Understanding how to connect to a Cloud SQL instance and the Firestore dashboard\n Creating and connecting to a Cloud SQL instance\n Configuring a Firestore instance and viewing the Firestore dashboard\n Decoupling applications using Pub/Sub\n Pub/Sub types\n Pub/Sub\n Pub/Sub Lite\n Relationship options\n Publishing a message\n Consuming a message using pull and push subscriptions\n Creating, updating, and showing data in your frontend application\n Firestore dependencies\n Creating a document\n Updating a document\n Transactions\n Batch writes\n Getting a document from a collection\n Getting a list of documents from a collection\n Query cursors\n Compound queries\n Sub-collection queries\n Deleting a document\n Some points to remember when using Firestore\n Summary\nChapter 9: Data Management and Database Strategies\n Technical requirements\n How to decide which database fits your needs\n Cloud SQL\n Cloud Spanner\n Bigtable\n Firestore\n Choosing the right database\n Data management strategies for your databases in Google Cloud\n What is database sharding?\n What is hot-spotting, and why should you avoid it?\n Defining a key structure for high-write applications in Bigtable\n Key design in Cloud Spanner\n Defining keys for Firestore to avoid hot-spotting\n Database and application management best practices\n Keep your Cloud SQL small\n Be prepared to fail\n Improve the speed of your database to import data\n Have a recovery plan\n Optimize query execution in Cloud Spanner\n Optimize bulk loading in Cloud Spanner\n Optimize update operations in Cloud Spanner\n Bigtable test best practices\n Firestore location cases\n Avoid hot-spotting due to read and write operations in collections\n Reading and writing documents from Firestore\n Reduce costs and remove limits with indexing exemption\n Summary\nChapter 10: Optimizing Applications with Caching Strategies on Google Cloud Platform\n Technical requirements\n How, when, and why you should use a caching strategy in your applications\n Why is having a cache strategy important?\n When can we implement a cache strategy?\n How can we implement a caching strategy?\n Handling high traffic volumes with Memorystore for Memcached\n Creating a Memcached instance\n Connecting to a Memcached instance\n Optimizing your application with Memorystore for Redis\n Creating a Redis instance\n Connecting to a Redis instance\n Summary\nSection 4: SRE for Developers\nChapter 11: Logging on Google Cloud Platform\n Technical requirements\n Introduction to Cloud Logging, the logging solution of GCP\n Learning logging best practices in the cloud\n Use libraries in your application to record logs\n Don\'t create all logs on a single level\n Categorize your logs correctly\n Add meaningful descriptions\n Make your logs understandable to both humans and machines\n Add unique event IDs\n Review your logging ingestion metrics\n Exclude logs for cost optimization\n How to enable an application to create custom logs\n Enabling an app to create custom logs\n Using Cloud Storage for cost optimization\n Using Pub/Sub to trigger events\n Using BigQuery for logs analysis\n How to watch logs and make advanced logging queries on Cloud Logging\n Our first search query\n Advanced queries\n Real-case logging examples using Cloud Logging and Cloud Monitoring\n Centralization of multiple logs in a GCP project\n Automatic error alerts\n Summary\nChapter 12: Cloud Monitoring, Tracing, and Debugging\n Technical requirements\n Your first operational dashboard and metrics\n Creating your first workspace\n Creating your first dashboard\n Monitoring your application uptime 24/7\n Creating an uptime check\n Finding bugs in your application with cloud debugging\n Creating our base application\n Using Cloud Debugger\n Creating a snapshot\n Creating a logpoint\n Optimizing your application with cloud tracing and profiling\n Cloud Trace\n Cloud Profiler\n Using Cloud Trace in our application\n Using Cloud Profiler in our application\n Real case examples using cloud monitoring, debugging, and tracing for applications on GCP\n Cloud monitoring SLOs\n Cloud Debugger in the cloud\n Cloud Trace cases\n Official documentation resources\n Summary\nSection 5: Analyzing a Sample Case Study\nChapter 13: HipLocal Sample Case Study Preparation\n Technical requirements\n Pro tips to ace the sample case study\n Sample case structure\n How to order the case information\n Map services and technologies with Google Cloud\n Reviewing the executive statement, existing solution, and requirements\n Executive statement\n Existing technical environment\n Reviewing the technical requirements\n Reviewing the business requirements\n Architecting the solution\n Summary\nChapter 14: Questions and Answers\n Technical requirements\n Questions\n Google Cloud Platform (GCP) developer fundamentals\n Security fundamentals and best practices\n Application modernization using Google Cloud\n Using Cloud Functions and GAE\n Virtual machines (VMs) and container applications on GCP\n Managing APIs on GCP\n Handling unstructured data\n Databases and event messages in Google Cloud\n Data management and database strategy\n Optimizing applications with caching strategies on GCP\n Logging on GCP\n Cloud monitoring, tracing, and debugging\n Answers\n GCP developer fundamentals\n Security fundamentals and best practices\n Application modernization using Google Cloud\n Using Cloud Functions and GAE\n VMs and container applications on GCP\n Managing APIs on GCP\n Handling unstructured data\n Databases and event messages in Google Cloud\n Data management and database strategy\n Optimizing applications with caching strategies on GCP\n Logging on GCP\n Cloud monitoring, tracing, and debugging\n Summary\nOther Books You May Enjoy\nIndex