Google cloud cookbook: practical solutions for building and deploying cloud services
Gespeichert in:
Hauptverfasser: | , |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Sebastopol
O'Reilly
2021
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Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | xiii, 266 Seiten Illustrationen |
ISBN: | 9781492092896 |
Internformat
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Datensatz im Suchindex
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adam_text | Table of Contents Preface........................................................................................................ vii 1. Introduction............................................................................................ 1 2. Cloud Fondions............................ ......................................................... 25 2.1 Creating a Public HTTP Google Cloud Function 2.2 Authenticating an HTTP Google Cloud Function 2.3 Accessing Environment Variables at Runtime 2.4 Sending Emails from Cloud Functions withSendGrid 2.5 Deploying Cloud Functions with a GitLab CI/CD Pipeline 2.6 Responding to SMS Messages with Twilio and Cloud Functions 2.7 Unit Testing with GitLab and Cloud Functions 2.8 Building an API Gateway to Gather Telemetry Data 26 27 29 30 33 37 39 42 3. Google Cloud Run.................................................................................... 47 3.1 Deploying a Prebuilt Hello World Container 3.2 Building Your Own Hello World Container 3.3 Using Cloud Run with a Custom Domain 3.4 Triggering a Cloud Run from Cloud Pub/Sub 3.5 Deploying a Web Application to Cloud Run 3.6 Rolling Back a Cloud Run Service Deployment 3.7 Deploying Cloud Run Services in a Gradual Rollout 3.8 Cloud Run Configuration Parameters 48 51 54 56 61 63 64 65 4. Google App Engine.................................................................................. 69 4.1 Deploying a Hello World to App Engine (Standard) 4.2 Deploying a Hello World to App Engine (Flexible) 4.3 Securing Your Application with Identity-Aware Proxy 70 71 73 iii
4.4 Mapping Custom Domains with App Engine 4.5 Using the Google Cloud Translation Machine Learning APIs with App Engine 4.6 Building User Interfaces for Viewing Charts and Graphs 4.7 Debugging an Instance 4.8 Using CI/CD 5. Google Cloud Compute Engine............................................................. 5.1 Creating a Windows Virtual Machine 5.2 Creating a Linux Virtual Machine and Installing NGINX 5.3 Connecting to Your Windows Virtual Machines with Identity-Aware Proxy TCP Forwarding 5.4 Securing Your Virtual Machine Logins with Two-Step Verification 5.5 Running Startup Scripts 5.6 Creating a Group of NGINX Web Servers with a Managed Instance Group 5.7 Deploying Containers to Managed Instance Groups 5.8 Transferring Files to Your Virtual Machine 5.9 Using VM Manager for Patch Management 5.10 Backing Up Your Virtual Machine 76 78 80 88 89 91 91 93 96 100 102 105 107 109 111 113 6. Google Cloud Kübemetes Engine.......................................................... 115 6.1 Creating a Zonal Cluster 6.2 Creating a Regional Cluster 6.3 Resizing a Cluster 6.4 Automatically Routing Traffic to the Nearest Cluster with Multi-Cluster Ingress 6.5 Deploying a Spring Boot Java Application 6.6 Deploying a Java Application to Kübemetes, Using Skaffold 6.7 Using GKE Autopilot for Running an Application You Don’t Have to Manage 115 117 118 121 126 129 130 7. Working with Data........................................................................... 133 7.1 Speeding Up Cloud Storage Bulk Transfers by Multiprocessing 7.2 Speeding Up GCS Transfers for Large Files with Parallel
Composite Uploads 7.3 Mounting GCS as a Filesystem 7.4 Automatically Archiving and Deleting GCS Objects 7.5 Creating and Restoring from Persistent Disk Snapshots in GCE 7.6 Using Interleaved Tables in Your Cloud Spanner Database 7.7 Locking Down Firestore Database So a User Can Edit Only Their Data iv I Table of Contents 133 135 136 138 140 142 147
8. BigQuery and Data Warehousing............................................................... 149 8.1 Using Cloud Console to Run a BigQuery Query 8.2 Loading Data to BigQuery from CSV 8.3 Building a Pivot Table in BigQuery 8.4 Adding Partitioned and Clustered Columns to an Existing Table 8.5 Adding Clustering to a Table That Can’t or Shouldn’t Be Partitioned 8.6 Selecting the Top-1 Result 8.7 Merging Tables in BigQuery Without Duplicates 8.8 Deduplicating Rows in BigQuery with Timestamps 8.9 Undeleting a Table in BigQuery 8.10 Streaming JSON or Avrò Data into BigQuery with a Dataflow Template 149 152 156 158 162 163 165 167 169 170 9. Data Processing Tools.............................................................................. 175 9.1 Cleaning Data Using the Data Fusion GUI 9.2 Running a Simple Python Dataflow Pipeline 9.3 Building a Streaming Pipeline in Dataflow SQL 9.4 Querying BigQuery from a Dataproc Job 9.5 Adding Event Timestamps to Pub/Sub 9.6 Inferring and Using Schemas in Dataflow 9.7 Mini-batching and Streaming Dataflow Data to BigQuery Using Filters 9.8 Triggering a Dataflow Job Automatically from a GCS Upload 175 180 184 188 191 192 195 197 10. AI/ML.................................................................................................... 201 10.1 Creating a Vertex AI Notebook 10.2 Training a Python ML Model Serverlessly 10.3 Making Serverless Predictions with a Python Model 10.4 Creating a Custom Notebook Environment 10.5 Extracting Data from BigQuery to Pandas for Model Training 10.6 Training a Model in SQL with BQML 201 204 206 208 210 213
11. Google Cloud Security and Access............................................................... 217 11.1 Creating a Service Account 11.2 Creating Custom Roles to Access a Cloud Storage Bucket 11.3 Authenticating an Application Running on Kübemetes Engine 11.4 Retrieving the Authenticated User’s Identity 11.5 Authenticating a Java Application Using a Service Account 11.6 Building Reports Using the Cloud Asset API 11.7 Allowing a List of IP Addresses to Access Your Application 217 219 221 227 228 230 234 12. Google Cloud Networking........................................................................ 237 12.1 Creating a Custom Mode VPC Network 12.2 Creating a Static External IP Address 237 239 Table of Contents | v
12.3 Create a Firewall Rule 12.4 Serving Content for Users in a Specific Region 12.5 Configuring VPC Network Peering 12.6 Creating VPN Gateways with Cloud Routers 12.7 Deployments of Networks Using Terraform 12.8 Limiting Access to Only Authorized Networks with VPC Service Controls 239 241 244 247 252 253 Index....................................................................................................... 257 vi Į Table of Contents
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adam_txt |
Table of Contents Preface. vii 1. Introduction. 1 2. Cloud Fondions. . 25 2.1 Creating a Public HTTP Google Cloud Function 2.2 Authenticating an HTTP Google Cloud Function 2.3 Accessing Environment Variables at Runtime 2.4 Sending Emails from Cloud Functions withSendGrid 2.5 Deploying Cloud Functions with a GitLab CI/CD Pipeline 2.6 Responding to SMS Messages with Twilio and Cloud Functions 2.7 Unit Testing with GitLab and Cloud Functions 2.8 Building an API Gateway to Gather Telemetry Data 26 27 29 30 33 37 39 42 3. Google Cloud Run. 47 3.1 Deploying a Prebuilt Hello World Container 3.2 Building Your Own Hello World Container 3.3 Using Cloud Run with a Custom Domain 3.4 Triggering a Cloud Run from Cloud Pub/Sub 3.5 Deploying a Web Application to Cloud Run 3.6 Rolling Back a Cloud Run Service Deployment 3.7 Deploying Cloud Run Services in a Gradual Rollout 3.8 Cloud Run Configuration Parameters 48 51 54 56 61 63 64 65 4. Google App Engine. 69 4.1 Deploying a Hello World to App Engine (Standard) 4.2 Deploying a Hello World to App Engine (Flexible) 4.3 Securing Your Application with Identity-Aware Proxy 70 71 73 iii
4.4 Mapping Custom Domains with App Engine 4.5 Using the Google Cloud Translation Machine Learning APIs with App Engine 4.6 Building User Interfaces for Viewing Charts and Graphs 4.7 Debugging an Instance 4.8 Using CI/CD 5. Google Cloud Compute Engine. 5.1 Creating a Windows Virtual Machine 5.2 Creating a Linux Virtual Machine and Installing NGINX 5.3 Connecting to Your Windows Virtual Machines with Identity-Aware Proxy TCP Forwarding 5.4 Securing Your Virtual Machine Logins with Two-Step Verification 5.5 Running Startup Scripts 5.6 Creating a Group of NGINX Web Servers with a Managed Instance Group 5.7 Deploying Containers to Managed Instance Groups 5.8 Transferring Files to Your Virtual Machine 5.9 Using VM Manager for Patch Management 5.10 Backing Up Your Virtual Machine 76 78 80 88 89 91 91 93 96 100 102 105 107 109 111 113 6. Google Cloud Kübemetes Engine. 115 6.1 Creating a Zonal Cluster 6.2 Creating a Regional Cluster 6.3 Resizing a Cluster 6.4 Automatically Routing Traffic to the Nearest Cluster with Multi-Cluster Ingress 6.5 Deploying a Spring Boot Java Application 6.6 Deploying a Java Application to Kübemetes, Using Skaffold 6.7 Using GKE Autopilot for Running an Application You Don’t Have to Manage 115 117 118 121 126 129 130 7. Working with Data. 133 7.1 Speeding Up Cloud Storage Bulk Transfers by Multiprocessing 7.2 Speeding Up GCS Transfers for Large Files with Parallel
Composite Uploads 7.3 Mounting GCS as a Filesystem 7.4 Automatically Archiving and Deleting GCS Objects 7.5 Creating and Restoring from Persistent Disk Snapshots in GCE 7.6 Using Interleaved Tables in Your Cloud Spanner Database 7.7 Locking Down Firestore Database So a User Can Edit Only Their Data iv I Table of Contents 133 135 136 138 140 142 147
8. BigQuery and Data Warehousing. 149 8.1 Using Cloud Console to Run a BigQuery Query 8.2 Loading Data to BigQuery from CSV 8.3 Building a Pivot Table in BigQuery 8.4 Adding Partitioned and Clustered Columns to an Existing Table 8.5 Adding Clustering to a Table That Can’t or Shouldn’t Be Partitioned 8.6 Selecting the Top-1 Result 8.7 Merging Tables in BigQuery Without Duplicates 8.8 Deduplicating Rows in BigQuery with Timestamps 8.9 Undeleting a Table in BigQuery 8.10 Streaming JSON or Avrò Data into BigQuery with a Dataflow Template 149 152 156 158 162 163 165 167 169 170 9. Data Processing Tools. 175 9.1 Cleaning Data Using the Data Fusion GUI 9.2 Running a Simple Python Dataflow Pipeline 9.3 Building a Streaming Pipeline in Dataflow SQL 9.4 Querying BigQuery from a Dataproc Job 9.5 Adding Event Timestamps to Pub/Sub 9.6 Inferring and Using Schemas in Dataflow 9.7 Mini-batching and Streaming Dataflow Data to BigQuery Using Filters 9.8 Triggering a Dataflow Job Automatically from a GCS Upload 175 180 184 188 191 192 195 197 10. AI/ML. 201 10.1 Creating a Vertex AI Notebook 10.2 Training a Python ML Model Serverlessly 10.3 Making Serverless Predictions with a Python Model 10.4 Creating a Custom Notebook Environment 10.5 Extracting Data from BigQuery to Pandas for Model Training 10.6 Training a Model in SQL with BQML 201 204 206 208 210 213
11. Google Cloud Security and Access. 217 11.1 Creating a Service Account 11.2 Creating Custom Roles to Access a Cloud Storage Bucket 11.3 Authenticating an Application Running on Kübemetes Engine 11.4 Retrieving the Authenticated User’s Identity 11.5 Authenticating a Java Application Using a Service Account 11.6 Building Reports Using the Cloud Asset API 11.7 Allowing a List of IP Addresses to Access Your Application 217 219 221 227 228 230 234 12. Google Cloud Networking. 237 12.1 Creating a Custom Mode VPC Network 12.2 Creating a Static External IP Address 237 239 Table of Contents | v
12.3 Create a Firewall Rule 12.4 Serving Content for Users in a Specific Region 12.5 Configuring VPC Network Peering 12.6 Creating VPN Gateways with Cloud Routers 12.7 Deployments of Networks Using Terraform 12.8 Limiting Access to Only Authorized Networks with VPC Service Controls 239 241 244 247 252 253 Index. 257 vi Į Table of Contents |
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spellingShingle | Costa, Rui Hodun, Drew Google cloud cookbook practical solutions for building and deploying cloud services Google Cloud Platform (DE-588)1163407496 gnd Cloud Computing (DE-588)7623494-0 gnd |
subject_GND | (DE-588)1163407496 (DE-588)7623494-0 |
title | Google cloud cookbook practical solutions for building and deploying cloud services |
title_auth | Google cloud cookbook practical solutions for building and deploying cloud services |
title_exact_search | Google cloud cookbook practical solutions for building and deploying cloud services |
title_exact_search_txtP | Google cloud cookbook practical solutions for building and deploying cloud services |
title_full | Google cloud cookbook practical solutions for building and deploying cloud services Rui Costa and Drew Hodun |
title_fullStr | Google cloud cookbook practical solutions for building and deploying cloud services Rui Costa and Drew Hodun |
title_full_unstemmed | Google cloud cookbook practical solutions for building and deploying cloud services Rui Costa and Drew Hodun |
title_short | Google cloud cookbook |
title_sort | google cloud cookbook practical solutions for building and deploying cloud services |
title_sub | practical solutions for building and deploying cloud services |
topic | Google Cloud Platform (DE-588)1163407496 gnd Cloud Computing (DE-588)7623494-0 gnd |
topic_facet | Google Cloud Platform Cloud Computing |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=033036944&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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