Google Cloud Platform for Azure professionals

Updated Aug 16, 2019

This set of articles is designed to help professionals who are familiar with Microsoft Azure famliarize themselves with the key concepts required in order to get started with Google Cloud Platform (GCP). The guide compares GCP with Azure and highlights the similarities and differences between the two. In addition, the guide provides quick-reference mappings of Azure products, concepts, and terminology to the corresponding products, concepts, and terminology on GCP.

This document doesn't attempt to compare the syntax and semantics of the SDK, APIs, or command-line tools provided by Azure and GCP.

Why GCP?

For over 15 years, Google has been building one of the fastest, most powerful, and highest-quality cloud infrastructures on the planet. Internally, Google uses this infrastructure for several high-traffic and global-scale services, including Gmail, Maps, YouTube, and Search. Because of the size and scale of these services, Google has put a lot of work into optimizing its infrastructure and creating a suite of tools and services to manage it effectively. GCP puts this infrastructure and these management resources at your fingertips.

Regions and zones

As with Azure, GCP products are deployed within regions located around the world. Each region consists of one or more data centers that are in geographical proximity to each other. Both Azure and GCP further divide availability into zones, which are isolated locations within a region.

In addition, some GCP services, such as App Engine and Cloud Storage Multi-Regional Storage, replicate and serve data at a multi-regional level rather than at the more granular region or zone levels. GCP also provides a dual-region replication model for Cloud Storage and Compute Engine. As of April 2019, this feature is in beta.

For more details on zonal, regional, and multi-regional services, see Geography and regions.

Isolation and availability

By design, Azure pairs regions that are in the same continent and that are physically isolated from each other by at least 300 miles into availability sets. Azure encourages users to architect their systems and applications around these pairs, creating an active-active recovery setup for availability and isolation purposes. In addition, some Azure services, such as Blob Storage, have replication options that automatically replicate data across paired regions.

GCP employs a similar strategy for isolation and availability, isolating regions from each other for availability reasons. GCP does not prescribe specific regional pairings. However, as with Azure, you must architect your application across multiple regions if you want to achieve high availability. Also as with Azure, some GCP services such as Cloud Storage Multi-Regional Storage and Cloud Storage dual-regional storage classes have built-in multi-region synchronization.

Accounts and quotas

To use an Azure service, you must either sign up for an Azure account or add Azure to your existing Microsoft Account. After you set up your Azure account, you can create a subscription within the account, and then launch services within that subscription. Each Azure account can support multiple subscriptions, and each subscription can use its own billing account if needed.

The GCP model is similar to that of Azure. You get access to GCP services by setting up a Google Account, and you launch services within projects, which are functionally similar to subscriptions on Azure. You can group your projects by organization as well. Folders are an additional grouping mechanism on top of projects. You are required to have an Organization resource as a prerequisite to use folders. Folders and projects are all mapped under the Organization resource. For more information, see Cloud platform resource hierarchy.

Azure and GCP both have default soft limits on their services for new accounts. These soft limits are not tied to technical limitations for a given service. Instead, they help prevent fraudulent accounts from using excessive resources. These soft limits also help limit risk for new users, keeping them from spending more than intended as they explore the platform. If you find that your application has outgrown these limits, Azure and GCP provide ways to get in touch with the appropriate teams to raise the limits on their services.


Because pricing tends to change more often than core features or services, this set of articles avoids pricing specifics where possible. However, each article discusses the pricing model behind each service wherever that's helpful. For up-to-date price comparisons for your solution, use the Azure pricing calculator and GCP price calculator to see which configuration provides the best value in terms of flexibility, scalability, and cost.

Discount pricing

Both Azure and GCP provide discounts for a subset of their respective services, but through different mechanisms.

You can get discounts on some Azure services through your Microsoft Enterprise Agreement by committing to a base-wide installation of one or more Microsoft Server or Cloud components with full Software Assurance coverage. If you don't have a Microsoft Enterprise Agreement, you might also be able to get discounted rates through a reseller.

GCP provides sustained-use discounts on a per-service basis based on your monthly usage. For example, Google Compute Engine offers sustained-use discounts based on the cumulative number of hours that a given virtual machine runs in a given month. If your resource usage is steady and predictable, you can also get heavily discounted rates through committed-use discounts. Committed-use discounts allow you to purchase a specific number of virtual CPUs (vCPUs) and a specific amount of memory at a discount over full prices, depending on the duration you commit to.

Support plans

Azure and GCP approach their support plans in different ways. Azure bundles their support levels into five subscription tiers. For more information on the available Azure support plans, see Azure Support Plans. As with Azure, GCP provides basic account support and online help resources free of charge. Additionally, you can purchase GCP paid support services. For more information on available support plans, see GCP support plans.

Resource management interfaces

Azure and GCP each provide command-line interfaces (CLIs) for interacting with services and resources. Azure provides both the Azure CLI, which is a cross-platform tool, and a set of Azure PowerShell cmdlets that you can install and use through Windows PowerShell. GCP provides a set of command-line tools and PowerShell cmdlets through the Cloud SDK, a cross-platform toolkit.

Azure and GCP also provide web-based consoles. Each console allows users to create, manage, and monitor their resources. The console for GCP is located at You can also use the Cloud SDK in your web browser by using Google Cloud Shell.

Core services

Cloud platforms provide a set of core services: compute, storage, networking, and database services. Azure's core services include the following:

  • Compute: Azure virtual machines, Azure App Service, Azure Kubernetes Service
  • Storage: Azure Blob Storage, Azure Managed Disks
  • Networking: Azure Virtual Network (VNet)
  • Databases: Azure Cloud SQL Database, Azure SQL Data Warehouse, Azure Table Storage, CosmosDB

GCP's core services include the following:

  • Compute: Compute Engine, App Engine, Google Kubernetes Engine
  • Storage: Cloud Storage, Compute Engine persistent disks
  • Networking: Virtual Private Cloud (VPC)
  • Databases: Cloud SQL, Cloud Firestore, Cloud Bigtable, Cloud Spanner

Each platform then builds other offerings on top of these services. Typically, the higher-level services can be categorized as one of the following types:

  • Application services: Services designed to help optimize applications in the cloud. Examples include Azure Service Bus and Google Cloud Pub/Sub.
  • Big data and analytics, AI, and IoT services: Services designed to help process, interpret, and derive insights from large amounts of data, such as Azure HDInsight and Google Cloud Dataflow.
  • Management services: Services designed to help you manage your application and track its performance. Examples include Azure Application Insights and Google Stackdriver Monitoring.

Service comparisons

The following tables provide a side-by-side comparison of the services available on Azure and GCP.

For a detailed listing of GCP products, visit Products and services.


Category Azure GCP
IaaS Virtual Machines Compute Engine
PaaS App Service, Cloud Services App Engine
Containers Azure Kubernetes Service, Azure Service Fabric Google Kubernetes Engine
Serverless functions Azure Functions Cloud Functions


Category Azure GCP
Virtual networks Azure VNets VPC
Load balancer Azure Load Balancer, Application Gateway Cloud Load Balancing
Dedicated interconnect ExpressRoute Cloud Interconnect
DNS Azure DNS Cloud DNS
CDN Azure CDN Cloud CDN


Category Azure GCP
Object storage Azure Blob Storage Cloud Storage
Block storage Disk Storage Persistent Disk
File storage Azure File Storage Cloud Filestore
Reduced-availability storage Azure Cool Blob Storage Cloud Storage Nearline
Archival storage Azure Archive Blob Storage Cloud Storage Coldline


Category Azure GCP
RDBMS SQL Database Cloud SQL, Cloud Spanner
NoSQL: key-value Table Storage Cloud Firestore, Cloud Bigtable
NoSQL: indexed Cosmos DB Cloud Firestore

Big data and analytics

Category Azure GCP
Batch data processing HDInsight, Batch Cloud Dataproc, Cloud Dataflow
Stream data processing Stream Analytics Cloud Dataflow
Stream data ingestion Event Hubs, Service Bus Cloud Pub/Sub
Analytics Data Lake Analytics, Data Lake Store BigQuery

Application services

Category Azure GCP
Messaging Service Bus, Storage Queues Cloud Pub/Sub
API management API Management Apigee, Cloud Endpoints
Web firewall Azure WAF Google Cloud Armor
DDoS protection Azure DDoS Protection Google Cloud Armor
Caching Azure Cache for Redis Cloud Memorystore

Management services

Category Azure GCP
Monitoring Application Insights Monitoring
Logging Log Analytics Stackdriver Logging
Deployment Azure Resource Manager Cloud Deployment Manager

Artificial intelligence

Category Azure GCP
Auto-generated models Automated Machine Learning Cloud AutoML
Speech Cognitive Services - Speech Cloud Speech-to-Text
Vision Cognitive Services - Computer Vision AutoML Vision
Natural language processing Cognitive Services - Language Cloud Natural Language
Video intelligence Video Indexer Cloud Video Intelligence
Fully managed ML Cognitive Services, Automated Machine Learning AI Platform Prediction


Category Azure GCP
Managed IoT Azure IoT Hub Cloud IoT Core
IoT on Edge Azure IoT Edge Cloud IoT Edge TPU (Beta)

What's next?

Check out the GCP for Azure Professionals articles for each service type:

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Google Cloud Platform for Azure Professionals