Google cloud platform for architects design and manage powerful cloud solutions
Get acquainted with GCP and manage robust, highly available, and dynamic solutions to drive business objective About This Book Identify the strengths, weaknesses and ideal use-cases for individual services offered on the Google Cloud Platform Make intelligent choices about which cloud technology wor...
| Otros Autores: | , , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham ; Mumbai :
Packt
2018.
|
| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630650706719 |
Tabla de Contenidos:
- Cover
- Title Page
- Copyright and Credits
- Packt Upsell
- Contributors
- Table of Contents
- Preface
- Chapter 1: The Case for Cloud Computing
- Genesis
- Why Google Cloud Platform (GCP)?
- Autoscaling and autohealing
- Capital expenditure (CAPEX) versus operating expenses (OPEX)
- Career implications
- Summary
- Chapter 2: 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
- Chapter 3: 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
- Chapter 4: 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
- Chapter 5: 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
- Chapter 6: 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
- Chapter 7: 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
- Chapter 8: 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
- Chapter 9: 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
- Chapter 10: Managing Hadoop with Dataproc
- Hadoop and Spark
- Hadoop on the cloud
- Google Cloud Dataproc
- Compute options for Dataproc
- Working with Dataproc
- Summary
- Chapter 11: 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
- Chapter 12: 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
- Chapter 13: Logging and Monitoring
- Logging
- Working with logs
- More Stackdriver - creating log-based metrics
- Monitoring
- Summary
- Chapter 14: Infrastructure Automation
- Managed Instance Groups
- Cloud deployment manager
- Summary
- Chapter 15: 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.
- Chapter 16: 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
- Chapter 17: 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
- Index.
