Google Cloud API Essential Guide

What type of API does Google Cloud provide?

Based on the search results, Google Cloud primarily uses REST APIs, but also supports GraphQL in some cases. Here are the key points:

1. Google Cloud primarily uses REST APIs for most of its services.

2. REST is described as a software architectural style that allows developers to interact with services in a standard way.

3. While REST is the dominant API type for Google Cloud, the company also recognizes the growing popularity and usefulness of GraphQL.

Key considerations:

• REST APIs in Google Cloud often involve multiple endpoints, while GraphQL exchanges data at a single endpoint.
• REST APIs may sometimes over-fetch or under-fetch data compared to what an application needs, while GraphQL allows for more precise data retrieval.
• Google Cloud acknowledges that both REST and GraphQL can be used within the same teams or projects, depending on the specific requirements.

GraphQL support:

• Google Cloud has been exploring and supporting GraphQL alongside its REST APIs.
• The company provides guidance on how to apply REST-based best practices to GraphQL implementations.
• Some Google Cloud services may offer GraphQL APIs as an alternative or complement to their REST APIs, especially for use cases involving complex data relationships or when more efficient data fetching is required.

Best practices:

Google Cloud recommends several best practices when working with APIs, regardless of whether they are REST or GraphQL:

1. Treat APIs as digital products with consistent experiences for developers.
2. Optimize for re-usability and consistent behavior across different parts of the API.
3. Use data-driven hierarchies and plural nouns in API design.
4. Consider using a combination of REST and GraphQL when appropriate, rather than forcing one approach for all scenarios.

In summary, while Google Cloud primarily uses REST APIs, it also supports and provides guidance for GraphQL implementations, recognizing the strengths and use cases for both API types.

Does the Google Cloud API have webhooks?

Google Cloud API Webhooks

Yes, the official Google Cloud API does support webhooks, particularly through the Google Cloud Application Integration service. This service allows you to configure webhook triggers for various events.

Types of Events You Can Subscribe To

While the search results don't provide an exhaustive list of event types, they do mention some examples and configuration options:

1. Custom Events: You can configure webhook triggers to listen for custom events. For example, the search results mention a "user.created" event.

2. Integration Events: Webhooks can be triggered within invocation intents or scenes in Google Assistant Actions.

3. External Platform Events: The Hookdeck integration example suggests that you can receive webhooks from various external platforms and sources.

Key Points to Consider

1. Event Subscription Configuration: When setting up a webhook trigger, you need to configure:

   • Event Type Field Location (Header, Query Param, or Request Body)
   • Event Type Field Name

2. Authentication: The webhook listener supports various authentication types:

   • No Authentication
   • Google Authentication
   • API Key Authentication
   • Basic Authentication

3. Private Connectivity: You can enable private connectivity for secured communication between your backend application and the connection.

4. Dead-letter Configuration: You can configure a dead-letter Pub/Sub topic for unprocessed events.

5. Integration with Google Cloud Functions: Webhooks can be received and processed using Google Cloud Functions.

Best Practices

1. Security: Always use appropriate authentication for your webhook listeners to ensure secure communication.

2. Error Handling: Implement proper error handling and consider using dead-letter configurations for unprocessed events.

3. Monitoring: Utilize logging and monitoring features to track webhook events and troubleshoot issues.

4. Replay Capability: Consider using tools like Hookdeck that offer webhook replay functionality for failed events.

5. Testing: Use simulation tools to test your webhook setup before connecting to live external sources.

While the Google Cloud API does support webhooks, the specific events you can subscribe to may vary depending on the service you're using within Google Cloud. The Application Integration service provides a flexible way to configure and manage webhook triggers for various use cases.

Rate Limits and other limitations

Here are the key points about API rate limits for Google Cloud APIs:

1. The default rate limit for most Google Cloud APIs is 2,400 queries per minute per user per Google Cloud project [1].

2. For the Google Analytics Admin API, the default limits are [4]:

   • 1,200 requests per minute
   • 600 requests per minute per user
   • 600 writes per minute
   • 180 writes per minute per user

3. For API Gateway, there is a default limit of 10,000,000 quota units per 100 seconds per service producer project [2].

4. For the Service Usage API [3]:

   • 240 read-only API calls per minute
   • 60 write API calls per minute

5. There are also limits on things like payload size (32 MB for requests/responses) and number of APIs/configs that can be created [2].

6. Rate limits are typically enforced in 60-second intervals. If you exceed the limit, you'll receive a 403 error with "rateLimitExceeded" [4].

7. You can view and edit quotas for your project in the Google Cloud Console [2][4].

8. For many APIs, you can request an increase to the default quotas if needed [2].

9. It's recommended to implement exponential backoff when retrying failed API requests due to rate limiting [1].

10. The specific rate limits can vary between different Google Cloud APIs, so it's best to check the documentation for the particular API you're using.

In summary, Google Cloud implements various rate limits and quotas to protect their infrastructure and ensure fair usage. The exact limits depend on the specific API, but there are usually ways to increase limits if needed for your use case. Implementing proper error handling and backoff logic in your code is important when working with these APIs.

Latest API Version

Based on the search results, there is no simple way to list all available versions of Google Cloud APIs. Here are the key points to consider:

1. Google does not publicly disclose all API versions. Some versions may require prior approval, be in alpha status, or require an NDA to access.

2. For APIs you need to use, it's recommended to subscribe to or follow the official blogs and release notes to stay updated on available versions.

3. Unless you have a specific requirement, it's best to use only the latest production (GA) version of an API. GA versions have published documentation detailing the interface, methods, and parameters.

4. There are several ways to potentially get access to newer API versions:

   • Joining Google's "Insiders" program, which is open to most customers and provides invitations for access to new services.

   • Joining Google Groups specific to certain Google Cloud services.

   • Building a relationship with the Product Manager (PM) for a particular API/service.

5. The discovery API endpoint (https://discovery.googleapis.com/discovery/v1/apis) remains one of the main ways to programmatically discover available APIs, though it may not include all versions.

6. There is no standard parameter like <api>.googleapis.com/$discovery/rest/versions to list all versions for individual APIs.

In summary, while there's no comprehensive method to list all API versions, staying informed through official channels and potentially engaging with Google's developer programs are the best ways to keep track of available API versions. For most use cases, using the latest GA version is recommended unless there's a specific need for a different version.

How to get a Google Cloud developer account and API Keys?

To get a developer account for Google Cloud and create an API integration, you need to follow these steps:

1. Create a Google account

If you don't already have one, you'll need to create a Google account. This will allow you to access Google developer products, including the Google Cloud Console.

2. Create a Google Cloud project

A Google Cloud project serves as a resource container for your Google Cloud resources. To create a project:

1. Go to the Google Cloud Console
2. Create a new project or select an existing one

3. Enable billing

Some Cloud APIs charge for usage, so you need to enable billing for your project:

1. Go to the Google Cloud Console billing page
2. Follow the instructions to create a billing account
3. Link your billing account to your project

4. Enable the necessary APIs

To use a specific Cloud API, you need to enable it for your project:

1. Go to the API Library in the Google Cloud Console
2. Search for and select the API you want to enable
3. Click the "Enable" button

5. Set up authentication

Depending on your use case, you'll need to set up authentication:

• For most applications, set up Application Default Credentials
• If the API supports it, you can use API keys
• For accessing resources owned by end users, create an OAuth 2.0 Client ID

6. Create credentials

To create credentials:

1. Go to the Credentials page in the Google Cloud Console
2. Click "Create credentials" and select the appropriate type (e.g., API key, OAuth client ID, or service account)

7. Grant necessary permissions

If using a service account:

1. Go to the Users & Permissions page in the Google Play Console
2. Add the service account email and grant the necessary permissions

What can you do with the Google Cloud API?

Based on the search results provided, here is a list of data models that can be interacted with using the Google Cloud API, along with what is possible for each:

Cloud Healthcare API Data Models

1. Digital Imaging and Communications in Medicine (DICOM) format:

   • Store and retrieve medical imaging data
   • Perform read, write, and search operations
   • Scale to handle large volumes of data

2. Health Level Seven Version 2.x (HL7v2) format:

   • Manage clinical event messages
   • Perform read, write, and search operations
   • Process and store healthcare-related data

3. Fast Healthcare Interoperability Resources (FHIR) format:

   • Handle clinical resources
   • Support DSTU2, STU3, and R4 standards
   • Perform read, write, and search operations

Cloud Firestore Data Model

4. Document-based NoSQL database:
   • Store and sync data for client- and server-side development
   • Organize data into collections and documents
   • Support complex, hierarchical data structures
   • Perform real-time updates and offline support

Cloud Spanner Data Model

5. Globally distributed relational database:
   • Store and manage structured data
   • Support SQL queries with some adjustments for Cloud Spanner's features
   • Perform high-performance, mission-critical operations
   • Utilize IAM for authentication and API-based interactions

Cloud SQL Data Model

6. Managed relational database service:
   • Support MySQL, PostgreSQL, and SQL Server databases
   • Connect using traditional methods (hostname, port, username/password)
   • Use familiar tools like psql and MySQL Workbench
   • Perform standard SQL operations

Other Google Cloud Database Services

7. Cloud Bigtable:

   • Manage large-scale, low-latency NoSQL data
   • Perform high-throughput reads and writes

8. Firestore:

   • Store and sync data for mobile and web applications
   • Support real-time updates and offline capabilities

9. Memorystore (for Redis and Memcached):

   • Manage in-memory data structures
   • Support caching and real-time data processing

Key Points to Consider

• Each data model has its own structural and processing characteristics
• Data location control is available for most services, allowing selection of storage regions
• Security is based on Google's Identity and Access Management (IAM) system
• Some services, like Cloud Spanner, primarily use API-based interactions, while others, like Cloud SQL, support traditional connection methods
• The choice of data model depends on specific organizational needs, application requirements, and compatibility considerations

Best Practices

• Evaluate requirements, compatibility, and security considerations when choosing a data model
• Consider hybrid approaches or workarounds if classical database connections are required
• Utilize the Google Cloud Console for additional management tasks and monitoring
• Take advantage of managed service benefits, such as automatic scaling and maintenance

By understanding these data models and their capabilities, developers can choose the most appropriate service for their specific use case within the Google Cloud ecosystem.