Decoding Google Cloud Storage with CTO.ai

Google Cloud Storage is an online service for storing and accessing your data on Google's infrastructure. The service combines the performance and scalability of Google's cloud with advanced security and sharing capabilities. This blog post will serve as an introductory guide to understanding Google Cloud Storage.

What is Google Cloud Storage?

Google Cloud Storage is a RESTful online file storage web service for storing and accessing data on Google Cloud Platform infrastructure. This scalable service is designed for high durability, storing data across multiple geographical locations. It supports both frequently accessed data like websites and mobile app content, and infrequently accessed data like backups and archives.

We have our GCP stack; you can explore and configure your managed databases for your application and workflow. This stack includes the Memory Store and Cloud SQL.

Cloud SQL

Cloud SQL is a fully-managed service that makes it easy to set up, manage, and administer relational databases on Google Cloud Platform. It offers support for MySQL, PostgreSQL, and SQL Server databases. Here are some key features:

Automated backups, failover, and replication processes ensure reliability and data safety.
It integrates well with other Google Cloud services, providing a consistent method of access across applications.
Allows easy scaling of performance to handle increased traffic and database complexity.

import pulumi_gcp as gcp
import pulumi_random as random


class CloudSql:
    outputs = dict()

    def __init__(
        self,
        id: str,
        name: str,
        database_version: str,
        region: str,
        tier: str,
        admin_user: str,
        database_name: str,
    ):
        self.id = id
        self.name = name
        self.database_version = database_version
        self.region = region
        self.tier = tier
        self.admin_user = admin_user
        self.database_name = database_name

Memorystore

Memory store is a fully-managed service for in-memory data storage, currently offering support for two popular open-source in-memory databases, Redis and Memcached. It is used for applications that require a high throughput and low latency data access. Here are some key features:

Automatic failover, updates, and patching, along with monitoring and alerting capabilities.
It provides a secure and highly available network for your applications with built-in redundancy and security features.
Seamless integration with GCP's Cloud Monitoring and Cloud Logging for in-depth performance visibility.

import pulumi_gcp as gcp


class MemoryStore:
    outputs = dict()

    def __init__(
        self,
        id: str,
        network: str,
        memory_size_gb: int, 
        name: str,
        location: str,
    ):
        self.id = id
        self.network = network
        self.memory_size_gb = memory_size_gb
        self.name = name
        self.location = location

        memory_store = gcp.redis.Instance(
            f"{self.id}-cache-instance", 
            name = self.name, 
            display_name = self.name,
            memory_size_gb=self.memory_size_gb,
            location_id=self.location,
            authorized_network=network
        )

Types of Storage Classes

There are four storage classes in Google Cloud Storage: Standard, Nearline, Coldline, and Archive. Each class differs by availability, minimum storage duration, pricing for storage, and access.

Standard Storage: This class is designed for frequently accessed data, such as serving website content, interactive workloads, or gaming applications.
Nearline Storage: Nearline Storage is a low-cost, highly durable storage service for storing infrequently accessed data. It is ideal for data you plan to read or modify on average once per month or less.
Coldline Storage: This class provides a very low cost, highly durable storage service that's ideal for data archiving, online backup, and disaster recovery. Data is available within milliseconds, not hours or days.
Archive Storage: Archive Storage provides the lowest cost, highly durable storage for data archiving, online backup, and disaster recovery. Unlike the Coldline Storage, data retrieval may take hours.

Creating a Bucket

The first step in working with Google Cloud Storage is creating a bucket. A bucket is a container for objects (files). To create a bucket:

Open the Cloud Storage browser in the Google Cloud Console.
Click on Create bucket.
Enter your bucket information (Name, storage class, and location) and click Create.

Access Control

Google Cloud Storage offers different ways to control who has access to your data, including Identity and Access Management (IAM), Access Control Lists (ACLs), and signed URLs.

IAM: IAM lets you create policies and give roles to users or Google Cloud services, giving different permissions to different entities.
ACLs: ACLs provide a more granular access control over your data. You can define who has access to the entire bucket or to individual objects.
Signed URLs: A signed URL gives time-limited read or write access to an object to anyone in possession of the URL.