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George Crump

One Way To Avoid Cloud Outages

Don't take chances with data availability. An onramping solution can help keep your customers--and your IT staff--happy.

Moving to the cloud? Don't take chances with data availability. An onramping solution can help keep your customers--and your IT staff--happy.

Every time there is an outage at one of the major cloud providers, it raises new concerns about the cloud and cloud storage. If you're planning to move some or all of your data to the cloud, how can you avoid losing access to that data when an outage occurs?

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Understand Your Provider. There are hundreds of different cloud providers to choose from today. Each one has different skills and abilities. Some provide only the very basics of infrastructure and expect you to navigate their service and create your own redundancy to protect your data if part of their cloud suffers an outage. While these providers may be less expensive, they put the burden of managing data availability on you.

For organizations with the time and skillset to learn those ins and outs, the cost savings may be worth the additional work. But as I discussed in a recent webinar, many organizations' IT staffs are stretched too thin to learn yet another availability strategy. These organizations need to select a full-service cloud provider that offers complete cloud redundancy as a standard feature, ideally in a way that doesn't require IT workers to do anything programmatically to take advantage of it.

[ Salesforce suffers a service outage after an electrical equipment upgrade knocks out its servers. Read more at Salesforce Outage Follows Data Center Power Glitch. ]

Understand Your Cloud OnRamp.

There are two basic options for getting data to the cloud: You can integrate access into your applications; or you can use a cloud gateway, which we refer to as an onramp. Today most enterprises get data to the cloud via an onramp. These solutions can come in a variety of forms: as software, appliances, or virtual appliances. They typically translate between the more standard data center storage interfaces (fibre, iSCSI, NFS, CIFS) and a cloud storage access method like REST.

Onramps can play another role, too. As we've seen in recent cloud storage onramp testing, they can also provide cloud mirroring. Essentially, this means that data can be written to two different cloud providers at the same time. This is the ultimate in protection from an outage since chances are slim that two providers would suffer an outage at the same time.

This strategy also protects your data from another type of outage--a permanent one caused by a cloud provider going out of business. If that happened, you wouldn't have to worry about data migration; you would simply turn off one side of the mirror. If the onramp also encrypted data, all you'd need to do is destroy the keys for the volume hosted by the out-of-business cloud provider, and your data would be unreadable by anyone else.

Having two providers would not double the cost, either. If you handle data availability on your own, you could purchase the lower-availability options from the two cloud providers.

If your users can't access their data, they're going to come after you--even if you've outsourced storage of that data to someone else. So it makes sense to ensure that data is always available. This requires that you pay extra due diligence when you select a cloud supplier, or that you manage the data redundancy yourself. Choose the option that best matches your IT staff's capabilities to make sure you meet your users' expectations.

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By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



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