Cloud Storage: Key Storage Specifications

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Company online storage is more flexible and offers more features and performance than ever before.

Even among the three main cloud services – Google Cloud Platform, Amazon Web Services and Microsoft Azure – there is now a full range of capacity, availability, performance and security options.

However, this choice does not facilitate the task of the IT department. Buyers must balance cost, performance, application compatibility, and flexibility, while comparing offerings from all three vendors.

But getting this right is key to getting the most out of the cloud. Here we present some of the key specifications when provisioning cloud storage.

Storage assumptions

The choice of storage architecture usually depends on application support or use case, and cloud providers are now offering block or file storage formats as well as “pure” object storage.

Alternatively, for applications such as archiving or low-end personal storage, the cloud service provider will choose an efficient underlying storage architecture, most often object. Dropbox, for example, recently moved to object storage architecture.

Cost also remains a key factor. For some applications, this is the most important factor when it comes to cloud storage, and cost and performance are closely related.

Decipher the cost structures for cloud services is a task in itself, with the need to consider bandwidth, storage capacity, egress charges, location, and even application programming interface (APIs) calls. And with major cloud service providers now offering performance tiers, it’s necessary to trade off price and performance for any cloud storage purchasing decision.

Key Storage Criteria:

Companies that store data in the cloud should be aware of the availablity service provider offerings, so they can compare with on-premises systems and business needs. Not all applications need “telco-grade” or five-nine availability, however, and it can reduce costs.

Amazon’s S3 Standard storage offers 99.99% service level agreements (SLAs), but some S3 services offer 99.9% and the S3 One Zone-IA storage class aims for 99.5%. Azure offers 99.99% for its Azure NetApp files via locally redundant storage.

Google Cloud ranges from 99.9% for its Coldline and Archive products to 99.99% for standard storage, or better for multi-regional and dual-regional setups.

However, the actual metrics are rather more complicated than the SLAs suggest and require in-depth study. AWS claims 11 nines for some configurations, eg.

Bandwidth, IOPS and latency all impact the performance of applications using cloud storage.

Bandwidth is governed by the cloud service provider’s offerings and the capacity of customer links to its data centers and other systems.

GCP advertises a capacity of 5,000 object reads per second for its storage buckets, with a per-region limit of 50 Gbps per project, per region when accessing data from a given multi-region. But GCP scales up to 1 Tbit/s if needed. Amazon claims 50 Gbps between EC2 and S3 in the same region. On Azure, a single Blob supports 500 requests per second, with Block Blob storage accounts capable of more.

For IOPS, AWS offers options ranging from 16,000 to 64,000 per volume through EBS. Azure Managed Disk achieves up to 160,000 IOPS and Azure Files up to 100,000 IOPS.

GCP’s persistent disk performs at up to 100,000 read IOPS and its local SSD at up to 2,400,000 read IOPS. On all platforms, writing is generally slower.

As these data points suggest, and despite the importance of bandwidth and IOPS, comparing cloud providers is difficult. Businesses should examine their application’s detailed requirements to find the best solution.

On paper, cloud storage capacity is endless. In practice, there are technical, practical and financial limitations. Additionally, service providers offer storage tiers that help match capacity, performance, and cost.

AWS can store data in an S3 bucket with objects in no less than seven tiers, from standard storage to deep archive storage. Smart tiering can do some of the heavy lifting, moving data between tiers, depending on usage.

Azure provides hot, cold, and archive tiers for blob data. Its warm tier has the highest storage but lowest access costs, with the cold and archive tiers charging less for storage and more for access. Google offers four storage classes: standard, nearline, coldline, and archive.

It should be noted that in addition to cost and latency differences, there are (minimum) storage time limits for tiers. Microsoft’s archive is 180 days minimum, Google’s is 365 days, and S3 ranges from 90 to 180 days.

When it comes to capacity, again, it’s worth looking at the details. S3 has no maximum bucket size or limit to the number of objects in a bucket, but the maximum bucket size is 5 TB. Google has a 5 TiB limit for an object. Azure specifies a maximum storage account limit of 5 PiB by default.

Note, however, that CSPs may also have limits on Availability Zones and different limits for single-region and multi-region configurations.

  • Recovery and other (hidden) costs

Often the biggest complaints from companies running cloud computing infrastructure are unexpected or hidden costs.

Calculating the true cost of a service based on consumption is difficult because it involves estimating anticipated demand and then trying to match product performance to that demand. In some cases, the benefits of cloud will create more demand as it is easy to use and efficient. Archiving is a good example.

Then there’s the question of whether savings on on-premises systems really materialize with a move to the cloud.

However, cloud services have not always succeeded in making their pricing transparent. A common source of complaint is exit or recovery fees. Cloud storage can be very cheap, and sometimes even free. But service providers charge fees instead for moving data out of their systems. These costs can be difficult to predict and may surprise customers.

Cloud service providers are now much more transparent about recovery fees and provide detailed guidance to users on how to structure their storage.

Certainly, some past cost issues stemmed from organizations choosing the wrong architecture for the wrong workload, such as frequently accessing data in long-term storage or placing less-used data on high-performance systems and at low latency and therefore paying more than they should.

Service providers further mitigate this issue with automated prioritization. CIOs need to adopt the logic used for this prioritization over trust, but unless a company has a large and highly skilled storage management team, it’s likely to be more efficient and less expensive than any process. manual.

Organizations will always have their own data security and compliance requirements, especially in areas such as government, healthcare, finance, and defense.

For cloud service buyers, this means matching a cloud service provider’s offering to the organization’s baseline security requirements. Again, this is an area where cloud providers have made real progress over the past few years.

Microsoft, for example, recently released the Azure Security Reference for Storagewhich in turn is part of the company’s cloud security benchmark.

AWS has similar standards and best practices, while Google has also full safety instructions. It is also possible to support the processing of specialized data, such as PCI-DSS payment information, personal health data or even classified files in the cloud.

The good news for buyers of cloud services is that the security levels of the big three providers match and often exceed those of on-premises data storage.

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