Join Joseph Lowery for an in-depth discussion in this video Understanding Google Cloud Storage and data, part of Google Cloud Storage and Data Essential Training.
- No matter how extensive the network or how powerful its computing engine, and the Google Cloud Platform integrates one of the most vast and powerful, you'll need a way to store and manage the data that makes up its content. In this lesson, I'll provide an overview of the storage and data components of the Google Cloud Platform that do just that. The Google Cloud Platform is currently comprised of six major components and a number of services. The components are App Engine, Compute Engine, Cloud Storage, Cloud Datastore, Cloud SQL, or Cloud SQL, if you prefer, and BigQuery.
Google has recently introduced a number of services, including Cloud Endpoints, among others, as well. In this course, we're gonna be focusing on four of the core components, Cloud Storage, Cloud Datastore, Cloud SQL, and BigQuery. Let's dive into Cloud Storage first. Google Cloud Storage is great for storing your website or application assets and data from around the globe. Google's network provides edge caching, where data is served from the closest data center, which means a reduced latency and fast data access.
Reliability is guaranteed at a 99.95% up-time. Now, Google also provides the ability to back up and restore your data. What's more, there's no cap on storage limits. Other Cloud Storage features include a enhanced security, OAuth 2.0 authentication protocols, and group-based access controls, including Access Control Lists, or ACLs. As with the other Google Cloud Platform services, you pay only for what you use, and the prices start at 12 cents per gigabyte for the first terabyte per month.
We'll explore Cloud Storage fully in Chapter 2. Cloud Storage is great for files, but what about data not contained in a discrete file? Google Cloud Platform offers two separate data-oriented solutions, the first of which is Cloud SQL. Cloud SQL is intended for relational data, and based on the MySQL relational database. With Cloud SQL, you have the choice of a hosting region, US, Europe or Asia, with 100 gigabytes of storage up to 16 gigabytes RAM per database instance.
Also with Cloud SQL, you get all the power of MySQL, with automatic replication of your data across multiple data centers. Additional peace of mind comes from the point-in-time backup and recovery services. Importing and exporting of your existing data is supported by commonly-used tools, like mysqldump, MySQL Wire Protocol, and JDBC. Much of the power of Cloud SQL stems from the fact that an application can spin up database instances on an as-needed basis.
These instances can be accessed in a number of ways. One technique, which we'll demonstrate later in the course, is through the Google Cloud Console. We'll also explore the readily-available SQL prompt. Additionally, you're free to use the MySQL Client through the command line or the JSON API. Chapter 3 covers Cloud SQL in depth. The other approach to managing data with the Google Cloud Platform is Cloud Datastore. Unlike Cloud SQL, Cloud Datastore is intended for non-relational data.
and is addressed in the SQL-like variant, NoSQL. Cloud Datastore features built-in redundancy with automatic replication across data centers. Small operations are available at no charge, and up to 100,000 read/write instructions are six cents per months. Through NoSQL, Cloud Datastore supports ACID transactions for reliable processing. ACID is short for Atomicity, Consistency, Isolation and Durability.
Access to Cloud Datastore and NoSQL is available through the Google Cloud Console interface, a command line tool called gcd, and a full-featured JSON API, as well. You can learn more about Cloud Datastore upcoming in Chapter 4. Well, now that you've got all this data available to you in the Cloud, how are you going to understand it? For that, let's look at BigQuery. With BigQuery, you can analyze massive amounts of data. We're talking millions of records within seconds.
We'll give BigQuery a run-through in Chapter 5. Google Cloud Platform is continually evolving. There are other services in development, including Container Engine, a container-based distribution platform, Cloud DNS, for nameserver management, and Pub/Sub, for handling asynchronous publication subscription messaging between applications. That concludes our overview of the components we'll be covering in depth in this course. But before we begin that exploration in earnest, we'll take a look at how the storage and data aspects mesh with the other Google Cloud Platform components, coming up next.
- Installing the Google Cloud SDK
- Working with buckets and objects
- Building a website with Cloud Storage
- Using Cloud SQL to manage data
- Setting up Cloud Datastore
- Exploring data with BigQuery
- Managing storage and data with Python