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Azure Resource Manager vs Google Cloud Deployment Manager: What are the differences?
Azure Resource Manager (ARM) and Google Cloud Deployment Manager (CDM) are both infrastructure-as-code (IaC) tools that allow users to define and manage cloud resources in a declarative way. While they have similar functionalities, there are several key differences between ARM and CDM.
Multicloud Support: Azure Resource Manager is specific to the Azure cloud, while Google Cloud Deployment Manager is designed for the Google Cloud Platform. This means that ARM can only be used to manage resources in Azure, while CDM supports multiple cloud providers. CDM can be used to manage resources across Google Cloud, AWS, and even on-premises systems.
Language and Syntax: Azure Resource Manager uses JSON (JavaScript Object Notation) for defining resource templates, which can be complex and challenging for beginners to understand. On the other hand, Google Cloud Deployment Manager uses YAML (YAML Ain't Markup Language), which is considered more human-readable and easier to work with.
Deployment and Updates: In Azure Resource Manager, resources can be deployed and updated as a single unit known as a resource group. This can be advantageous when managing related resources together. In Google Cloud Deployment Manager, resources are deployed and updated individually, which provides more flexibility but requires extra management overhead.
Resource Types: Azure Resource Manager supports a wide range of resource types specific to the Azure platform, including virtual machines, storage accounts, and virtual networks. Google Cloud Deployment Manager has its own set of resource types, such as compute instances, storage buckets, and networking resources. The resource types and their capabilities may vary between the two tools.
Integration with Other Services: Azure Resource Manager integrates tightly with other Azure services, such as Azure Active Directory for authentication and authorization. Google Cloud Deployment Manager similarly integrates with Google Cloud Identity and Access Management (IAM) for managing access controls. The specific integrations and capabilities may differ between the two tools.
Community and Ecosystem: Azure Resource Manager has a large and mature community of users and a well-established ecosystem of third-party tools and libraries. Google Cloud Deployment Manager, while gaining popularity, may have a smaller community and less extensive ecosystem. This can impact the availability of resources, tutorials, and support.
In Summary, Azure Resource Manager is focused on Azure cloud and supports JSON for defining resource templates, while Google Cloud Deployment Manager is more versatile, supporting multiple cloud providers and using YAML for configurations. The two tools also differ in deployment and update methods, supported resource types, integrations, and community support.
I personally am not a huge fan of vendor lock in for multiple reasons:
- I've seen cost saving moves to the cloud end up costing a fortune and trapping companies due to over utilization of cloud specific features.
- I've seen S3 failures nearly take down half the internet.
- I've seen companies get stuck in the cloud because they aren't built cloud agnostic.
I choose to use terraform for my cloud provisioning for these reasons:
- It's cloud agnostic so I can use it no matter where I am.
- It isn't difficult to use and uses a relatively easy to read language.
- It tests infrastructure before running it, and enables me to see and keep changes up to date.
- It runs from the same CLI I do most of my CM work from.
Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.
Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!
Check Out My Architecture: CLICK ME
Check out the GitHub repo attached
Pros of Azure Resource Manager
- Bicep - Simple Declarative Language3
- Infrastructure-as-Code1
- Over 1K samples the QuickStart repo1
- Deep integration with Azure services like Azure Policy1
- Day 1 resource support1
- RBAC and Policies in templates1
- Versioned deployment via Blueprints1
Pros of Google Cloud Deployment Manager
- Automates infrastructure deployments2
- Fast deploy and update1
- Infrastracture as a code1
- Easy to deploy for GCP1
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Cons of Azure Resource Manager
Cons of Google Cloud Deployment Manager
- Only using in GCP1