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Google Cloud Storage for backups

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Article from ADMIN 53/2019
We compare Google Cloud Storage for Internet-based backups with Amazon S3.

Amazon Simple Storage Service (Amazon S3) is considered the mother of all object memories and, thanks to its great durability, availability, and built-in scaling, has been virtually unrivalled thus far. However, other providers now also offer S3 alternatives with interesting features. Like Amazon S3, Google Cloud Storage (GCS) is an object storage service for storing and retrieving data from anywhere on the Internet with a REST-flavored API (AWS S3 historically also supports SOAP and BitTorrent) or with a program based on one of the supported SDKs. In fact, GCS buckets and objects are conceptually similar to those in Amazon Web Services (AWS). As with AWS, anything you want to store in GCS must be dropped into buckets, which both organize data and control access.

Deployment Scenarios

Google Cloud Storage supports a wide range of use cases. With GCS, users can store content such as text files, images, videos, and more over the Internet. GCS also supports hosting of static website content, while also offering all the benefits of a highly scalable architecture. For example, if you experience web request load peaks (e.g., because many users are trying to read a popular post or download a coupon code), the system can automatically process the increasing load volume without manual intervention.

Google Cloud Storage also helps IT managers develop and operate serverless applications – for example, by executing tasks in response to events in GCS. Each time a file is uploaded, a format checker or conversion tool could launch, triggered by Google Functions. Finally, GCS can be used for cloud-based backups and for archiving data that is rarely accessed. Unlike Amazon S3, however, GCS lets you recover the archived data within milliseconds, instead of minutes – or hours in the case of AWS Glacier.

Memory Classes and Access Times

As in AWS, buckets are containers that store objects. They cannot be nested and must have a unique name across the entire Google Storage namespace. GCS also supports object versioning. The objects themselves always comprise the object data (e.g., the files to be stored in GCS) and object metadata components (e.g., a collection of key-value pairs that describe an object's attributes). General metadata attributes include content type, content encoding, and cache control, but users can also store user-defined values.

Amazon S3 supports the Standard, Infrequent Access (S3 Standard-IA), and One Zone-Infrequent Access (S3 One Zone-IA) storage classes, and you can also regard S3 Reduced Redundancy (with only 99.99 percent reliability) as a storage class. In addition to archiving, Amazon Glacier is a storage class, because Glacier can be addressed directly by the Glacier API or the S3 API and exists as a "transition" within the framework of S3 life-cycle management. Whereas the access time for S3 is in the range of seconds to milliseconds, Glacier access times range up to five hours for the standard retrieval procedure.

With GCS, on the other hand, the access time is consistently in the millisecond range across all memory classes:

  • Data in Google Multi-Regional Storage is geo-redundant. The data is redundantly stored at two or more data centers at least 100 miles apart within the selected multi-regional location.
  • Regional storage data, on the other hand, is stored in a bucket created in a regional location. This data does not leave the data centers in the specified region.
  • Nearline Storage, the Google counterpart to AWS S3 IA, is a cost-effective, extremely long-lasting storage service for rarely accessed data. The data is redundant within a single region. Nearline Storage is ideal for data that needs to be read or changed once a month or less frequently on average.
  • Coldline Storage data, unlike other "cold" storage services like AWS Glacier, is available within milliseconds, not hours or days. Google users can also set up life-cycle management policies to transfer objects between Nearline or Coldline storage classes on a multi-regional or regional basis.

Access Control

Securing access to data in GCS is accomplished in three ways. In addition to the use of Access Control Lists (ACLs), access can also be routed by Identity and Access Management (IAM) authorizations and roles and with the aid of presigned URLs.

With Google Cloud IAM, administrators of the Google Cloud Platform (GCP) can control user and group access to buckets and objects at the project level, allowing a user to perform all tasks on all objects in that project but not create, modify, or delete buckets in the same project. The GCS projects feature adds an additional organizational level to classic G Suite or Google Drive accounts.

Optionally, or additionally, the IT manager in GCS can control access by applying an access control list to individual objects or buckets. Finally, signed URLs make it possible to grant time-limited read or write access for all persons who are in possession of a URL to be generated beforehand.

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