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      • Getting started with AWS EC2 instances

        An organization can find many good reasons to take advantage of AWS offerings, but just how do you get started? This handbook provides detailed guidance on creating a first AWS EC2 instance, including on how to secure and configure it.

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      • For AWS cloud computing, it's not all sunshine and rainbows

        At first glance, Amazon Web Services may seem as user-friendly as a point-and-click consumer app. But as many customers can attest -- and as the history of software proves -- the reality can be much more complex. With organizations far and wide flocking to the cloud computing platform, it's growing ever more important to look beyond the hype.

        Don't be scared: In this handbook, our editors have compiled answers to some of the most common and pressing questions regarding the managing, monitoring and addressing of potential problems in the AWS cloud. Readers will get an introduction to how the AWS Management Console -- the central point for managing all your AWS resources -- really works. Next, industry analysts highlight some of the most common traps users fall into -- the AWS “gotchas.” We close with a study on how to properly, and effectively, select third-party management and monitoring tools.

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      • The ins, outs and in-betweens of AWS big data analytics

        Big data and Amazon Web Services may go well together, but what are the steps to getting started? How much of an investment -- time, people, power and money -- are big data projects? With data this big, fast-changing and varied, most traditional approaches to data management won’t hack it. And even the biggest multinationals couldn’t shoulder the on-premises costs.

        In this handbook, readers will learn about the technologies needed for big data analytics -- such as Kinesis, Hadoop and Elastic MapReduce -- and how it works in AWS. Cloud expert David Linthicum takes a look at the cost-effective approaches to big data AWS is offering -- and how they can benefit your organization. Next, Matt Wood, general manager of data science at AWS, answers questions about the changes AWS has made to its cloud in recent years. The changes -- 42 price cuts among them -- have raised this question: Just how low can pricing go? Wood also discusses a host of market trends in data science and analytics. Finally, consultant Tom Nolle looks at the future of the cloud -- specifically the addition of hosted services, such as AppStream and Kinesis, as enterprise and developer problem solvers.

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      • The AWS role in disaster recovery

        No matter how well prepared you might be, disaster can strike. Most mature IT organizations have disaster recovery plans, but Amazon Web Services offers a unique set of services that can keep your business running if the worst happens. This handbook discusses the strategies and options available to companies looking to AWS for disaster preparedness and business continuity, including understanding EC2 availability zones, using S3 for backup and storage, testing your DR strategy in AWS and preparing for AWS outages.

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      • Dollars and sense: The economics of AWS

        Competitive pricing is driving much of the growth in the adoption of Amazon Web Services. But how cheap is AWS, really? Users need to understand exactly what they are paying for and how to control cost overruns.

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      • Who's who? Identity management a key to AWS security

        Understanding security is essential for trusting any cloud service, and AWS is no exception. How is data secured in AWS? What are its rules, methods and models? What are the best practices? And which elements are the responsibility of the customer and which are handled by Amazon Web Services? This handbook examines those questions, and proposes strategies for making the most of roles, groups and specific AWS identity management tools.

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      • When AWS automation takes the wheel

        One of the greatest advantages of Amazon Web Services is the ability to automate services and functions of cloud applications. Still, before organizations can reap the benefits they must have a firm understanding of what actually makes up AWS' automation -- Auto Scaling and CloudFront, specifically.

        In this three-part guide, SearchAWS editors will delve into the information necessary to understand the ins, outs and in-betweens of AWS automation. To begin, software engineer Brian Tarbox takes a hard look at reactive programming, which enables a program to automatically react to load changes in its environment. It's not new, but AWS's Auto Scaling services is putting a fresh spin on the concept. Tarbox details Auto Scaling further, highlighting for readers two important components: hysteresis and EC2 pricing. Next, journalist George Lawton drills down on the primary use case for AWS CloudFront: delivery of static content to users. Lawton serves up examples from a host of different organizations to show what CloudFront can do to improve content and content delivery, though he warns, "It is not a silver bullet for every source of delay in Web performance." Tarbox finishes the handbook with final look at Auto Scaling, and the different methods to scale workloads. Organizations have just three options to choose from, but it's no easy decision.

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  • Business Information

    Cloud computing, mobile devices and massive amounts of data flowing into organizations are combining to put heavy pressure on business systems. To adapt, organizations have been forced to transform the way in which corporate information is managed.

  • Modern Infrastructure

    Modern Infrastructure covers the convergence of technologies -- from cloud computing to virtualization to mobile devices -- and the impact on data centers.

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  • Enterprise Hadoop: Ready for prime time?

    Many vendors are pitching Hadoop as the foundation for enterprise data management environments that delivers information and insights to business users and serves as a hub for other data systems and applications. In the era of big data, the case for Hadoop is strong: Hadoop provides a cost-effective way to ingest, store and process large volumes of multi-structured data. With Hadoop, organizations can store all data in its original format and provide a system of record for the enterprise. Even more, they can bring the applications to Hadoop and process the data in place.

    But does reality square with the promise today? Are companies willing to trust their enterprise data to Hadoop? The big question is whether Hadoop is ready to support enterprise-scale, production environments where data can't be corrupted or inconsistent. Does Hadoop have adequate management, monitoring, backup, recovery and security features? What are the major gaps today and what are vendors doing to plug the holes? At what point can companies trust production computing environments to Hadoop? This report, based on a comprehensive survey of business intelligence professionals and interviews with experts in the field, addresses these questions.

  • Overcome today's disaster recovery challenges

    The use of devices not connected to a local network is a challenge for IT staffs tasked with protecting data on those devices. Completing backups within a reasonable timeframe has become an issue for organizations. Some organizations are opting for alternatives to traditional backup to address these challenges. The cloud has been pushed as an alternative to tape for offsite storage for disaster recovery. However, there are challenges with this approach and with protecting applications running in the cloud.

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