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• Leave a review - let other readers know what you think
• Other Books You May Enjoy
• Summary
• Don't be Milton!
• Understand the differences between snapshots and images
• Understand the main choices for ML applications

• Leave a review - let other readers know what you think 更新時間：2021-06-25 20:49:13
• Other Books You May Enjoy
• Summary
• Don't be Milton!
• Understand the differences between snapshots and images
• Understand the main choices for ML applications
• Understand the unified architecture for batch and stream
• Keep your Dataproc clusters stateless
• Use pre-emptible instances in your Dataproc clusters
• Use BigQuery unless you have a specific reason not to
• Read the fine print on GCS pricing
• Understand how sustained use discounts work
• Try to find reasons to use network peering
• Make friends with the gsuite admins
• Pay for what you allocate not what you use
• Careful that you don't get nickel-and-dimed
• Eat the Kubernetes frog
• Effective Use of the GCP
• Summary
• Vision API
• Key Management Service – KMS
• Video Intelligence API
• Stackdriver
• Cloud ML Engine
• Pub/Sub
• Google Kubernetes Engine
• Cloud SQL
• Datastore
• BigQuery
• BigTable
• Compute Engine
• Pricing Considerations
• Summary
• BeyondCorp – Identity-Aware Proxy
• Some security best practices
• Google-provided tools and options for security
• Security features at Google and on the GCP
• Security on the GCP
• Summary
• Cloud deployment manager
• Managed Instance Groups
• Infrastructure Automation
• Summary
• Monitoring
• More Stackdriver – creating log-based metrics
• Working with logs
• Logging
• Logging and Monitoring
• Summary
• Working with firewall rules
• Working with custom subnets
• Working with VPCs
• VPN and cloud router
• Internal and external IP addresses
• The default VPC
• VPC networks and subnets
• Why GCP's networking model is unique
• Networking in GCP
• Summary
• Other load balancing
• Configuring Internal Load Balancing
• Configuring HTTP(S) load balancing
• HTTP(S) load balancing
• Taxonomy of GCP load balancers
• Why load balancers matter now
• Load Balancing
• Summary
• Working with Dataproc
• Compute options for Dataproc
• Google Cloud Dataproc
• Hadoop on the cloud
• Hadoop and Spark
• Managing Hadoop with Dataproc
• Summary
• Working with IAM – creating a custom role
• Working with cloud IAM – grant a role
• Creating a Service Account
• Units of identity in GCP
• Permissions and roles
• Resource hierarchy of GCP
• Identity and Access Management
• Summary
• Analyzing financial time series with BigQuery
• BigQuery pricing
• Working with BigQuery using CLI
• Deleting datasets
• Loading data into a table using BigQuery
• Working with the BigQuery console
• Legacy versus standard SQL
• BigQuery public datasets
• Underlying data representation of BigQuery
• BigQuery
• Summary
• Using Datastore
• Full indexing and perfect index
• When to use Datastore
• Working with Datastore
• Comparison with traditional databases
• The Google Cloud Datastore
• Scaling GCP Cloud BigTable
• Exporting/Importing a table from Cloud Bigtable
• Creating and operating an HBase table using Cloud Bigtable
• Performing operations on Bigtable
• Ideal row key choices
• Solving performance issues
• Choosing storage for Bigtable
• Solving hot-spotting
• When to use Bigtable
• Working with Bigtable
• Support for ACID properties
• Denormalization
• Columnar datastore
• Fundamental properties of Bigtable
• Cloud Bigtable
• NoSQL databases
• NoSQL Databases
• Summary
• Interleaving tables in Cloud Spanner
• Querying a database in a Cloud Spanner instance
• Creating a database in Cloud Spanner instances
• Creating a Cloud Spanner instance
• Cloud Spanner
• Automatic backup and restore
• Use case – operating Cloud SQL through VM instances
• Use case – managing certificates
• Use case – managing replicas
• Testing Cloud SQL instances
• Importing a database
• Creating a database in a Cloud SQL instance
• Creating a Cloud SQL instance
• GCP Cloud SQL
• Scaling up versus scaling out
• OLTP and the ACID properties
• Relational databases SQL and schemas
• Relational Databases
• Summary
• Use case – offline ingestion options
• Mounting GCS buckets
• Use case – mounting GCS using gcsfuse
• Use case – auto-syncing folders
• Use case – using customer supplied encryption keys
• Setting up object change notifications with the gsutil notification watchbucket
• Use case – reacting to object changes
• Setting up signed URLs for cloud storage
• Use case – signed and timed URLs
• Managing permissions in bucket using the GCP console
• Use case – restricting access with both ACLs and IAM
• Deleting objects permanently using gsutil
• Deleting objects permanently using the web console
• Manipulating object life-cycle via JSON file
• Managing bucket life cycle using the web console
• Use case – object life cycle policies
• Object versioning in the Cloud Storage bucket
• Use case – Object Versioning
• Transfer Service or gsutil?
• Using the Transfer Service (instead of gsutil or the web console)
• Copying data between buckets using the gsutil command line
• Copying data between buckets using the web console
• Uploading data to buckets using gsutil
• Uploading data to buckets using the web console
• Transferring data in and out of buckets
• Changing the storage class of bucket and objects
• Creating buckets using gsutil
• Creating buckets using the web console
• Creating buckets
• Working with GCS buckets
• Storage classes–Regional multi-regional nearline and coldline
• Serving Static Content with GCS Buckets
• Knowing when (and when not) to use GCS
• Google Cloud Storage – Fishing in a Bucket
• Summary
• Cloud functions triggered by GCS object notifications
• Cloud Functions triggered by Pub/Sub
• Cloud Functions triggered by HTTP
• Serverless compute with cloud functions
• Traffic splitting
• Deploying and running on App Engine Standard
• Typical App Engine architecture
• Hosted web apps with App Engine Standard
• Google App Engine – standard
• Advantages of GKE over Docker on VMs or App Engine Flex
• Cron Jobs with App Engine Flex
• Running a simple Python application with App Engine Flex
• Hosted Docker containers with App Engine Flex
• Google App Engine – flexible
• Federated clusters
• The container registry
• Rolling updates
• Cloud VPN integration
• Multi-zone clusters
• Scaling pods with the horizontal pod autoscaler
• Scaling nodes with the cluster autoscaler
• Auto scaling
• Load balancing
• Storage and persistent disks
• Using the features of GKE
• Creating a Kubernetes cluster and deploying a WordPress container
• GKE
• Docker containers and Kubernetes – complements not substitutes
• What is a container?
• Contrasting containers and VMs
• GKE
• GKE App Engine and Cloud Functions
• Summary
• Modifying GCE VMs
• Deploying LAMP stack using GCE
• Cloud launcher
• How to create an image of a disk
• How to snapshot a disk
• Snapshots and images
• Startup scripts
• Labels and tags
• Billing
• Autoscaling and managed instance groups
• Load balancing
• Preemptibillity
• Auto-restart
• Availability policies
• Rightsizing recommendations
• More on working with GCE VMs
• Resizing a persistent disk
• Sharing a persistent disk between multiple instances
• Linux procedure for formatting and mounting a persistent disk
• Creating and attaching a persistent disk
• Understanding persistent disks and local SSDs
• Persistent disks and local SSDs – block storage for GCE
• Storage options
• Networks – aka VPCs
• Machine type
• Compute zone
• Operating system
• VM customization options
• Creating a VM instance using the command line
• Creating a VM instance using the web console
• Creating VMs
• Google Compute Engine – GCE
• Compute Choices – VMs and the Google Compute Engine
• Summary
• Using the Cloud Shell
• Setting up a GCP account
• Projects and billing
• Accessing the Google Cloud Platform
• Global regional and zonal resources
• Introduction to Google Cloud Platform
• Summary
• Career implications
• Capital expenditure (CAPEX) versus operating expenses (OPEX)
• Autoscaling and autohealing
• Why Google Cloud Platform (GCP)?
• Genesis
• The Case for Cloud Computing
• Reviews
• Get in touch
• Conventions used
• To get the most out of this book
• What this book covers
• Who this book is for
• Preface
• Packt is searching for authors like you
• About the reviewer
• About the authors
• Contributors
• PacktPub.com
• Why subscribe?
• Packt Upsell
• 版權信息
• 封面

• 封面
• 版權信息
• Packt Upsell
• Why subscribe?
• PacktPub.com
• Contributors
• About the authors
• About the reviewer
• Packt is searching for authors like you
• Preface
• Who this book is for
• What this book covers
• To get the most out of this book
• Conventions used
• Get in touch
• Reviews
• The Case for Cloud Computing
• Genesis
• Why Google Cloud Platform (GCP)?
• Autoscaling and autohealing
• Capital expenditure (CAPEX) versus operating expenses (OPEX)
• Career implications
• Summary
• Introduction to Google Cloud Platform
• Global regional and zonal resources
• Accessing the Google Cloud Platform
• Projects and billing
• Setting up a GCP account
• Using the Cloud Shell
• Summary
• Compute Choices – VMs and the Google Compute Engine
• Google Compute Engine – GCE
• Creating VMs
• Creating a VM instance using the web console
• Creating a VM instance using the command line
• VM customization options
• Operating system
• Compute zone
• Machine type
• Networks – aka VPCs
• Storage options
• Persistent disks and local SSDs – block storage for GCE
• Understanding persistent disks and local SSDs
• Creating and attaching a persistent disk
• Linux procedure for formatting and mounting a persistent disk
• Sharing a persistent disk between multiple instances
• Resizing a persistent disk
• More on working with GCE VMs
• Rightsizing recommendations
• Availability policies
• Auto-restart
• Preemptibillity
• Load balancing
• Autoscaling and managed instance groups
• Billing
• Labels and tags
• Startup scripts
• Snapshots and images
• How to snapshot a disk
• How to create an image of a disk
• Cloud launcher
• Deploying LAMP stack using GCE
• Modifying GCE VMs
• Summary
• GKE App Engine and Cloud Functions
• GKE
• Contrasting containers and VMs
• What is a container?
• Docker containers and Kubernetes – complements not substitutes
• GKE
• Creating a Kubernetes cluster and deploying a WordPress container
• Using the features of GKE
• Storage and persistent disks
• Load balancing
• Auto scaling
• Scaling nodes with the cluster autoscaler
• Scaling pods with the horizontal pod autoscaler
• Multi-zone clusters
• Cloud VPN integration
• Rolling updates
• The container registry
• Federated clusters
• Google App Engine – flexible
• Hosted Docker containers with App Engine Flex
• Running a simple Python application with App Engine Flex
• Cron Jobs with App Engine Flex
• Advantages of GKE over Docker on VMs or App Engine Flex
• Google App Engine – standard
• Hosted web apps with App Engine Standard
• Typical App Engine architecture
• Deploying and running on App Engine Standard
• Traffic splitting
• Serverless compute with cloud functions
• Cloud Functions triggered by HTTP
• Cloud Functions triggered by Pub/Sub
• Cloud functions triggered by GCS object notifications
• Summary
• Google Cloud Storage – Fishing in a Bucket
• Knowing when (and when not) to use GCS
• Serving Static Content with GCS Buckets
• Storage classes–Regional multi-regional nearline and coldline
• Working with GCS buckets
• Creating buckets
• Creating buckets using the web console
• Creating buckets using gsutil
• Changing the storage class of bucket and objects
• Transferring data in and out of buckets
• Uploading data to buckets using the web console
• Uploading data to buckets using gsutil
• Copying data between buckets using the web console
• Copying data between buckets using the gsutil command line
• Using the Transfer Service (instead of gsutil or the web console)
• Transfer Service or gsutil?
• Use case – Object Versioning
• Object versioning in the Cloud Storage bucket
• Use case – object life cycle policies
• Managing bucket life cycle using the web console
• Manipulating object life-cycle via JSON file
• Deleting objects permanently using the web console
• Deleting objects permanently using gsutil
• Use case – restricting access with both ACLs and IAM
• Managing permissions in bucket using the GCP console
• Use case – signed and timed URLs
• Setting up signed URLs for cloud storage
• Use case – reacting to object changes
• Setting up object change notifications with the gsutil notification watchbucket
• Use case – using customer supplied encryption keys
• Use case – auto-syncing folders
• Use case – mounting GCS using gcsfuse
• Mounting GCS buckets
• Use case – offline ingestion options
• Summary
• Relational Databases
• Relational databases SQL and schemas
• OLTP and the ACID properties
• Scaling up versus scaling out
• GCP Cloud SQL
• Creating a Cloud SQL instance
• Creating a database in a Cloud SQL instance
• Importing a database
• Testing Cloud SQL instances
• Use case – managing replicas
• Use case – managing certificates
• Use case – operating Cloud SQL through VM instances
• Automatic backup and restore
• Cloud Spanner
• Creating a Cloud Spanner instance
• Creating a database in Cloud Spanner instances
• Querying a database in a Cloud Spanner instance
• Interleaving tables in Cloud Spanner
• Summary
• NoSQL Databases
• NoSQL databases
• Cloud Bigtable
• Fundamental properties of Bigtable
• Columnar datastore
• Denormalization
• Support for ACID properties
• Working with Bigtable
• When to use Bigtable
• Solving hot-spotting
• Choosing storage for Bigtable
• Solving performance issues
• Ideal row key choices
• Performing operations on Bigtable
• Creating and operating an HBase table using Cloud Bigtable
• Exporting/Importing a table from Cloud Bigtable
• Scaling GCP Cloud BigTable
• The Google Cloud Datastore
• Comparison with traditional databases
• Working with Datastore
• When to use Datastore
• Full indexing and perfect index
• Using Datastore
• Summary
• BigQuery
• Underlying data representation of BigQuery
• BigQuery public datasets
• Legacy versus standard SQL
• Working with the BigQuery console
• Loading data into a table using BigQuery
• Deleting datasets
• Working with BigQuery using CLI
• BigQuery pricing
• Analyzing financial time series with BigQuery
• Summary
• Identity and Access Management
• Resource hierarchy of GCP
• Permissions and roles
• Units of identity in GCP
• Creating a Service Account
• Working with cloud IAM – grant a role
• Working with IAM – creating a custom role
• Summary
• Managing Hadoop with Dataproc
• Hadoop and Spark
• Hadoop on the cloud
• Google Cloud Dataproc
• Compute options for Dataproc
• Working with Dataproc
• Summary
• Load Balancing
• Why load balancers matter now
• Taxonomy of GCP load balancers
• HTTP(S) load balancing
• Configuring HTTP(S) load balancing
• Configuring Internal Load Balancing
• Other load balancing
• Summary
• Networking in GCP
• Why GCP's networking model is unique
• VPC networks and subnets
• The default VPC
• Internal and external IP addresses
• VPN and cloud router
• Working with VPCs
• Working with custom subnets
• Working with firewall rules
• Summary
• Logging and Monitoring
• Logging
• Working with logs
• More Stackdriver – creating log-based metrics
• Monitoring
• Summary
• Infrastructure Automation
• Managed Instance Groups
• Cloud deployment manager
• Summary
• Security on the GCP
• Security features at Google and on the GCP
• Google-provided tools and options for security
• Some security best practices
• BeyondCorp – Identity-Aware Proxy
• Summary
• Pricing Considerations
• Compute Engine
• BigTable
• BigQuery
• Datastore
• Cloud SQL
• Google Kubernetes Engine
• Pub/Sub
• Cloud ML Engine
• Stackdriver
• Video Intelligence API
• Key Management Service – KMS
• Vision API
• Summary
• Effective Use of the GCP
• Eat the Kubernetes frog
• Careful that you don't get nickel-and-dimed
• Pay for what you allocate not what you use
• Make friends with the gsuite admins
• Try to find reasons to use network peering
• Understand how sustained use discounts work
• Read the fine print on GCS pricing
• Use BigQuery unless you have a specific reason not to
• Use pre-emptible instances in your Dataproc clusters
• Keep your Dataproc clusters stateless
• Understand the unified architecture for batch and stream
• Understand the main choices for ML applications
• Understand the differences between snapshots and images
• Don't be Milton!
• Summary
• Other Books You May Enjoy
• Leave a review - let other readers know what you think 更新時間：2021-06-25 20:49:13