Google Cloud Platform Certification, Associate Cloud engineer 공부 #day5

This section of the course showcases Google Cloud’s five core storage products: Cloud Storage, Cloud Bigtable, Cloud SQL, Cloud Spanner, and Firestore.

학습 목표

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• Identify the purpose of and use cases for Cloud Storage.
• Distinguish between Google Cloud's storage options.

 

Cloud Storage

These unique keys are in the form of URLs, 

which means object storage interacts well with Web technologies. 

Data commonly stored as objects include video, pictures and audio recordings.

 

 

Cloud storage files are organized into buckets. A bucket needs a globally unique identifier and a specific geographic location for where it should be stored and an ideal location for a bucket is where latency is minimized. 

 

Administrators have the option to either allow each new version to completely overwrite the older one or to keep track of each change made in a particular object by enabling versioning within a bucket.

 

two options to control user access to objects and buckets

The first is a scope which defines who can access and perform an action. 

This can be a specific user or group of users.

 

The second is a permission which defines what actions can be performed like read or write.

 

 

 

 

Cloud Storage: Storage classes and data transfer

 

 

Examples of Nearline Storage might include data backups, long-tail multimedia content, or data archiving.

Archive Storage - This is the lowest cost option used ideally for data archiving, online backup and disaster recovery.

 

Online transfer - many customers simply carry out their own online transfer using gsutil, which is the Cloud storage command from the Cloud SDK. Drag & drop in Chrome Web browser

Storage Transfer Service - for terabytes or even petabytes of data. 

 

Transfer Appliance - schedule and manage batch transfers to Cloud Storage from another Cloud provider, from a different Cloud Storage region or from an HTTPS endpoint.

 

Cloud SQL

 

Cloud SQL instances are accessible by other Google Cloud and external services.

Cloud SQL can be used with 

App Engine using standard drivers like 

connector J for java or MySQL DB for Python.

Compute Engine instances can be authorized to access Cloud SQL instances and configure 

the Cloud SQL instance to be in the same zone as your virtual machine.

 

 

Cloud SQL also supports other applications and tools that you might use like SQL Workbench, Toad, and other

 

external applications using standard MySQL drivers.

 

Cloud Spanner

 

Firestore

Firestore for mobile, web, and server development

 

the app can write, read, 

listen to, and query data even if the device is offline. 

When the device comes back online, 

Firestore synchronizes 

any local changes back to Firestore. 

 

bandwidth) 대역폭

 

 

 

Cloud Bigtable

 

- Handle massive workloads

- Consistent low latency

- High throughput

- operational applications

- Analytical applications(internet of things, user analytics, financial data analysis)

 

They're working with NoSQL data. 

This usually means transactions where strong relational semantics are not required.

asynchronous) 비동시성의

Using APIs data can be read from and written to Cloud Bigtable through a data service layer like Managed VMs, 

the HBase REST server, or a Java server using the HBase client. 

Typically this is used to serve data to applications, dashboards, and data services.

Data can also be streamed in through a variety of popular stream processing 

frameworks like data flow streaming, spark streaming, and storm.

 

 

 

Framework vs library) I call a library(jQuery), and Framework(Django) calls my code.

https://www.youtube.com/watch?v=t9ccIykXTCM 

And if streaming is not an option, data can also be read from and written to 

Cloud Bigtable through batch processes like Hadoop MapReduce, Dataflow, or Spark.

 

Often, summarized or newly calculated data is written back to Cloud Bigtable or to a downstream database.

 

Comparing storage options

Cloud SQL is best for web frameworks and existing applications like storing user credentials and customer orders. 

 

If cloud SQL doesn't fit your requirements because you need horizontal scalability, not just through read replicas, consider using Cloud Spanner.

For example, when planning for financial trading in e-commerce use cases. 

 

Firestore is best for storing, syncing, and querying data for mobile and web apps. 

 

 

BigQuery is not purely a data storage product. It's on the edge between data storage and data processing.

 

 

 

 

LAB: Getting Started with Cloud Storage and Cloud SQL

 

In this lab, you create a Cloud Storage bucket and place an image in it. You’ll also configure an application running in Compute Engine to use a database managed by Cloud SQL.