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Aug 20, 2013

Is your cloud noisy and slow?

Ansley Kilgore

Is your cloud noisy and slowNow that most IT organizations have transitioned some of their infrastructure to the cloud, the game has changed yet again. While you may have already moved your email applications, disaster recovery, ERP or CRM systems to the cloud, now your CEO wants to incorporate big data, business intelligence and predictive analytics into the corporate strategy. But these large enterprise applications require more computing power than your current cloud architecture can support. How can you accommodate the CEO’s requests without sacrificing performance and inviting problems from noisy neighbors?

In an effort to not throw out the proverbial baby with the bath water, IT is faced with the challenge of using the current cloud infrastructure to meet the requirements of these new systems. A one-size-fits-all cloud solution doesn’t work for most enterprises, and few businesses can afford to sacrifice the automation and flexibility of the cloud and start manually provisioning physical servers again. Diversifying your infrastructure to include bare-metal cloud can help fill this gap. Bare metal provides the high performance processing capabilities of a dedicated environment, with the service delivery model of the cloud.

Establishing a mixed cloud environment
Understanding the requirements of your use case will help determine which mix of cloud is right for you. Workloads that require high disk I/O are usually better suited for physical, dedicated servers. Bare-metal cloud provides a new way to leverage cloud technology for high-performance, data-intensive workloads, such as big data applications and media encoding. Since bare-metal servers do not run a hypervisor, are not virtualized and are completely dedicated, including storage, you don’t have to worry about noisy neighbors or overhead delays.

Bare-metal cloud can be used in conjunction with virtualized cloud infrastructure to meet a wider range of business requirements. IT managers can balance the capabilities of various cloud models to create a cost-effective operating environment. This reduces capital costs, is operationally efficient and establishes a foundation for agility through adaptable hosting models. At the same time, businesses investigating virtualized clouds as their only hosting solution often prefer to host many of their high-performance, and most complex, applications internally. The bare-metal cloud offers an alternative to virtualized clouds and in-house environments, positioning IT managers to maximize the value of their application and service architectures.

The value of diversity
The ability to create a mixed cloud environment means cloud computing now offers more options than traditional virtualization, while still providing flexibility, scalability and utility-based pricing models. Using different types of cloud together provides organizations with exponentially more opportunities for cost-effective infrastructure.

As the cloud has evolved to include public, private, hybrid and now bare-metal options, IT now has more opportunities to create the right cloud mix to meet the needs of the enterprise. Taking a workload-centric approach can help establish a more strategic, cost-effective cloud solution. The bare-metal cloud is an integral part of an agile infrastructure that allows IT to efficiently meet the demands of business-critical applications.

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Ansley Kilgore

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Aug 13, 2013

Big data: Two critical definitions you need to know

INAP

Down in Cyberspace 01Big data is (clearly) a broadly defined and overused term. It’s been used to describe everything from general “information overload” to specific data mining and analytics to large-scale databases. In Internap’s hosting and cloud customer base, we see two main approaches to big data. In order to make better decisions about the infrastructure required to achieve your goals, you need to understand these different approaches and know where your needs fall.

There is a haystack, go find needles
One class of big data can be thought of as the “needle in a haystack” type. In this scenario, you have mountains of data already, and a very broad idea about the possibility of insights, analytics, and interrelationships within the data. Therefore, your goal is to crunch the data and find the relationships that allow you to understand and gain insight about the data over time. This type of static “big” data requires big backend processing power from technologies such as Hadoop. These applications tend to be mostly batch jobs with sporadic and often unpredictable infrastructure needs.

Massive real-time “big” database
The term “big data” is also used to describe the more mainstream, real-time database applications that have a scale problem to solve well beyond the means of traditional SQL databases. Real-time big data applications, such as Mongo DB, Cassandra and others deliver needed scale and performance for modern scale-out applications. Relational databases are often too limiting for large amounts of unstructured data. NoSQL and key value databases are better suited for the task, but they require high performance storage, high IOPs and the ability to rapidly scale in place. These requirements are vastly different from those of the data-crunching needle in a haystack type of big data, yet the same term is often used to describe both.

The performance question
Performance isn’t unimportant in the first type of big data, but it has a different meaning versus the real-time database scenario. For large data-mining applications, real-time data insertion isn’t as important, because you already have the data. The importance of performance in this case is the ability to extract the data fast enough and process it quickly, and this depends on the type of data you are mining and the business application of it. With that said, the type of infrastructure has a big impact on how long it takes to process your “big data” job. If you can reduce the processing time from three days to two days thanks to a more powerful cloud infrastructure, that can change how you define your business model.

For real-time big database applications, I/O becomes critical. For example, mobile advertising technology companies require real-time data insertion and performance in order to capture the right data at the right time and subsequently deliver timely, relevant ads. What really happens when millions of users simultaneously “check in” at their favorite restaurants and then at the movies via a social media mobile app? Extracting and capturing this information relies on real-time data insertion, but quickly processing and learning from that data relies on compute performance. The ads you see are formulated and delivered based on your real-time location information, behavior patterns and preferences. Dynamic, real-time data requires high I/O storage and superior compute performance in order to provide such targeted ads.

From the proverbial needle-in-a-haystack backend processing to modern, real-time database applications, the term “big data” is used for both. Once you understand the distinct qualities of each type, you can make better decisions regarding the infrastructure and IaaS (Infrastructure-as-a-Service) models that fit one versus the other. Your organization likely has both types of “big data” challenges. Talk to Internap to find out how we can help you meet the needs of both.

Next: How to make IaaS work for your big data needs

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Jul 3, 2013

Choose your own cloud adventure: the SaaS alternate ending

Ansley Kilgore

In our previous post, we described IaaS (Infrastructure as a Service) and PaaS (Platform as a Service). Today we’ll discuss how Software as a Service (SaaS) fits into the stack and explore which type of infrastructure makes sense in different scenarios. Various combinations of these services can help meet your needs for flexibility and resource control so you can manage and create applications as desired.

SaaS
Most SaaS providers deliver end-user applications on-demand, as a service, over the Internet. Salesforce.com and Google Apps are two common examples of this. However, many SaaS applications can provide services to other applications, usually via a SOAP or RESTful API over the Internet. A good example of this is how Yelp integrates Google Maps into its mobile application – Google is the SaaS provider, and the Yelp application becomes the consumer of the software service.

A SaaS provider may use a PaaS provider or an IaaS provider, depending on the level of development and operational efforts they need to balance out.

Here’s an illustration of how an application may interact with another SaaS provider:
SaaS alternate ending

As you can see, the application now interacts with other applications for complete functionality. Just as a developer can increase speed-to-launch by using a PaaS provider (at the expense of flexibility and customization), this developer can use existing third-party SaaS applications without having to recreate each piece of functionality desired.

Ultimately, the more you move your application “up the stack”, the fewer resources you are required to manage. Integrating an application with SaaS providers allows a developer to consume SaaS services as components and building blocks without having to reinvent the wheel (e.g., using Google Maps for location services, using RSS aggregators for content/news services, etc.).

Using a PaaS provider will provide a framework for you to develop your own application without having to manage an infrastructure. And if the PaaS is too limiting – say, you want to use certain web server features not provided by the platform, or you want to use a preferred development framework – then IaaS may make more sense.

As indicated in the final illustration below, the further down the stack, the more lower-level components a developer will need to recreate and maintain.
SaaS alternate ending

There is plenty of opportunity for “mix and match”. No one service is correct for all use cases, and I can certainly see distributed applications consuming one or more portions of the stack on multiple cloud service providers.

The decision to go with one or another ultimately comes down to a few considerations:

  • The resources the team wants to manage.
  • The capabilities of the development (and operations) teams building and supporting the application.
  • How quickly the team needs to deploy production software with the resources available.

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Jun 26, 2013

Choose your own cloud adventure: PaaS or IaaS?

Ansley Kilgore

While many IT decision makers are familiar with how Software as a Service (SaaS) can benefit their organization, PaaS (Platform as a Service) has become equally as popular. Add IaaS (Infrastructure as a Service) to the mix, and it often raises questions – how do you know which one is best for your needs, and how do these cloud services work together? When building an application, you can choose any combination of services that allow you the greatest combination of flexibility and resource control to meet your requirements.

IaaS
Think of IaaS, PaaS and SaaS as “stacks” that can either reduce the level of effort required to build your application, or provide more flexibility.

For example, IaaS provides raw infrastructure-like compute and storage resources, providing the most flexibility while requiring the most hands-on management. Developers interact with the operating systems directly, build/use their own frameworks and consume infrastructure resources directly.

The image below shows the relationship of your application to the services provided by the IaaS provider.
PaaS or IaaS?

PaaS
PaaS, on the other hand, will provide a development platform (as a service) to create new applications. Think of it as a cloud-based middleware: it provides services beyond the raw operating system and abstracts the underlying resources from you. The developer doesn’t have to manage compute resources; instead she gets to build on frameworks specifically provided for her application. For small dev teams without infrastructure management capabilities, this is a great way to reduce the “time-to-usefulness” of their project, but it restricts the flexibility since they must work within the frameworks provided.

PaaS services typically use an underlying IaaS service; e.g., Acquia (Drupal platform as a service) and Heroku (Ruby on Rails platform as a service) both use Amazon AWS as a foundation to their platforms. As an IaaS provider, Internap has similar customers that provide a Platform-as-a-Service for developers who want to develop code against a managed framework rather than manage the frameworks themselves.

The following example illustrates what a PaaS provider might offer to your application.
PaaS or IaaS?

Tune in next time as we discuss how SaaS fits into the cloud infrastructure landscape, and how using a combination of these services can provide you with the desired level of control and flexibility for your applications.

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Ansley Kilgore

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