Does The Cloud Mean A Loss Of Infrastructure Control?

The cloud’s convenience, speed, flexibility, scalability, programmability, and automation capabilities brought about a sea-change in the way organizations think about infrastructure deployment. Things changed because there are obvious and significant benefits to the public cloud when compared to collocation and other physical infrastructure modes. There are some cases where physical infrastructure is preferable — mostly for legacy applications — but for the most part, the cloud is where it’s at.

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Bimodal IT is an industry buzzword for the segmentation of a company’s IT infrastructure into two buckets – Type 1 and Type 2. Type 1 infrastructure emphasizes stability and safety. Type 2 infrastructure emphasizes agility, speed, and flexibility. In reality, that means Type 1 infrastructure is legacy infrastructure, and Type 2 infrastructure is cloud infrastructure.

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This article was written by guest blogger, Daan Pepijn

In information technology, high availability refers to the continuous operation of a system or component. It is colloquially referred to as the “5 nines,” which means being available 99.999% of the time. This availability can refer to the availability of the local network, the web server, or any or all of the IT resources of an organization. For small businesses, this high availability is an important requirement especially when it comes to meeting customer expectations, and particularly in growing and expanding.

Scale and traction are among the main goals of any small business or startup. Opportunities for growth will always exist especially for companies that are well-managed and consistent in providing great products and services. In this regard, high availability yields a myriad of benefits. In terms of business growth, these advantages translate to improvements in the following four vital aspects of doing business that contribute to growth.

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Distributed Cloud Computing will be Essential to the Internet Of Things

The Internet Of Things will be depend on fast, local compute and storage built on highly distributed cloud platforms.

Traditional Cloud Models Won’t Cut It

Traditionally, the cloud has been construed in much the same way as on-premise infrastructure: a centralized source of compute and storage. The cloud is more flexible, more agile, and often less expensive than traditional infrastructure, impacting how businesses think about IT management and utilization. But for the most part, cloud infrastructure has been centralized infrastructure.

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Bellevue, WA – July 27, 2015ComputeNext, a cloud marketplace platform provider, will be exhibiting at CompTIA ChannelCon 2015, in Chicago from August 3-5. ComputeNext will be demonstrating in booth number 418 at the Hilton Chicago.

At ChannelCon, ComputeNext will showcase its Cloud Marketplace platform, which enables cloud service providers, IT resellers and distributors to broker cloud services and infrastructure for their customer base in order to drive revenue, extend service offerings and enhance customer relationships and loyalty. The platform allows the customers of channel and white label partners to browse, select, buy and deploy cloud services, infrastructure and apps, all transactionally and instantaneously. ComputeNext provides end-to-end design, creation, management, billing and operation of its white label cloud marketplaces, and also collaborates with channel and white label partners on co-marketing and go-to-market activities.

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Announcing the ComputeNext CloudED Channel Training & Education Program:

One of the biggest challenges facing IT channel sales organizations today is maintaining their sales revenue through transitioning their clientele from on-premise infrastructure and software to off-premise cloud-based services.  This fundamental business shift needs to handled very carefully such that the channel partner can maintain their role as the “trusted advisor” for their clients, providing adequate guidance and knowledge through that transition.

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The choice of data storage method can have a significant impact on factors ranging from performance and reliability to management complexity and cost. There’s no right choice for all scenarios. Storage strategies should be chosen based on the specific requirements of the application in question: the optimal choice for a geographically redundant data store would be a poor choice for a high-performance database application.

We’re to discuss three potential data storage options and their specific advantages, before focusing on the best option for the very large datasets often required by Big Data applications.


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Protect Your Virtual Machines: Six Best Practices For Securing Cloud Data

In spite of the persistent questioning of cloud security by physical infrastructure partisans, in truth, the cloud is as secure as any other infrastructure platform — which is to say, it’s as secure as cloud vendors and cloud users make it.

If managed properly, the cloud and the virtual machines that run on it, and by extension the data they hold, are secure.

In this article, we’re going to take a look at six security practices that contribute to a secure cloud environment.

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The Correlation Between Application Performance and Cloud Location

If you’ve ever been left twiddling your thumbs as you wait for your webmail service to present a usable interface or your SaaS spreadsheet to become responsive, it’s likely that the networks that lie between you and your application provider are responsible. Data surges from its home network at high speed before being bogged down somewhere on its way to you. The further away from the source you are, the longer you’ll be waiting.

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Using Federated Clouds For Accurate, Real World Load Testing

The nightmare scenario for system administrators working on web services and applications: they push a new iteration of their code into production, everything seems to be going well, then, as demand peaks, their cloud servers slow to a crawl, users start complaining, databases can’t keep up with the demand.

The code push introduced a regression that wasn’t caught in testing and under real world use, the service goes down. Perhaps it was a caching flaw, an error with the way files were pushed out to content distribution networks, or a coding mistake that caused the application to use far more resources that it should.

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