As a developer, you understand just how complex your application stack can be. Depending on its environment, there can be hundreds of critical components that together make up your app, and each piece is vital to its performance and reliability. To monitor each component, you might use multiple, non-integrated tools to gain visibility into your stack. And that makes troubleshooting app performance issues a challenging endeavor.

**Using New Relic?  Activate Newvem’s free AWS Cost & Usage Plugin toady and follow these two easy steps.

 **Not Using New Relic?  Get NewRelic’s Standard package for FREE when you activate Newvem’s free AWS Cost & Usage Plugin for NewRelic!  A $49/month server value!

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Newvem periodically analyzes the AWS cloud usage of our users to identify, benchmark and recommend areas where AWS users can improve their awareness and approach to cost savings, security vulnerabilities, availability issues, and utilization efficiency. In comparison to previous 2012 Cloud Radar reports, we’ve identified huge improvements in AWS resource usage by users specifically across security, Reserved Instance utilization, and data recovery practices.

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While investing in building new data centers all over the world and creating the management overlay in order to be able to sell their hardware, IaaS operators are also relying on their ecosystem to support the evolving enterprises that go to the cloud (e.g. the “Enterprise Grade Cloud”).

API First

The move to the cloud pushes the data center to re-invent itself within the new environment. It is a fact that, although the cloud is a pure revolution (at least in MHO), terms such as SLA, TCO and ROI are still valid in this new IT era. Thanks to industry leaders such as Salesforce.com that realize the notion of “API first”, vendors such Amazon cloud present new capabilities first through their APIs. In this way, the cloud operator platform enables development of its ecosystem.

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A while back, I was starting up an EC2 instance on the AWS cloud when it entered an endless restart loop. All the application deployment efforts we’d made (installation and service configuration) over two weeks just went down the drain. So we called support. The support rep redirected us to his team leader who simply told us that, as indicated in the SLA, we had to abide by the shared responsibility model and they were not liable for our loss.

The Shared Responsibility Model - Shared Responsibility refers to the responsibility of the cloud vendor, as well as the cloud consumer, to make sure that everything is backed up and appropriately configured to avoid situations like the one we were in. In short, it was our fault for not having better programmed our architecture.

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Pic 1:Newvem’s Spot Instances Filter

AWS Spot Instances can be a great way to save money on projects that are not time-sensitive or to boost your on-demand compute power. Spot Instances are based on supply and demand giving you the unique opportunity to name your price, with the understanding, of course, that once the price exceeds your bid, you will lose that instance.

The problem is that users struggle to track and understand their Spot Instance consumption because the price is constantly fluctuating. That’s where the Newvem Spot Instance Filter comes in to play.

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Do you Auto-Scale your Cloud? Do you automatically shut down, resize or schedule your cloud compute resources?

Auto-scaling is one of the most important features for cloud computing. In order to really benefit from the cloud and ensure your capacity meets demand, you need to be able to scale your cloud’s allocated capacity automatically (up or down)  at any given time.

In comparison to the limited capacity of the traditional data center, the cloud has (at least in principle) infinite resources; auto-scaling being the basic feature of this perception. Auto-scaling configuration should react to a variety of monitored thresholds such as CPU load or even RPS (requests per second).

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The benefits of migrating workloads between different cloud providers or between private and public clouds can only truly be redeemed with an understanding of the cloud business model and cloud workload management. To discuss these benefits, we brought together Joe Weinman, author of Cloudonomics, and Patrick Pushor, founder of CloudChronicle.com.

In a conversation that was aired live on May 16, 2013, Joe and Patrick discussed the basics of managing workloads across the cloud, the benefits of migrating cloud workloads between private, public, and hybrid clouds, and the business value of cloud computing.

Check out their conversation here!

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This video presents an overview of the new features and capabilities of Newvem Analytics for Windows Azure.Newvem Analytics for Windows Azure allows you to:

1. Plan your cloud strategy
2. Measure your usage
3. Analyze your cloud’s cost, assets, and utilization
4. Improve your overall cloud performance

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We are thrilled to announce the launch of Newvem Cloud Operations Optimization for Windows Azure. This latest offering empowers Windows Azure users with straight forward visibility into their cloud inventory and usage, enabling better decision making, minimalizing operational exposures, and aligning cloud operations with business objectives.

Built for the Enterprise

Azure offers a natural extension to enterprise IT operations by allowing them to relieve IT resources and prevent bottlenecks.  With this powerful solution, enterprises can respond quickly to market needs with Microsoft’s enterprise-grade reliability. Public Cloud adoption in the enterprise centers on the developers need to provision servers to address the enterprises IT needs as well as meet new demands.

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The benefits of migrating workloads between different cloud providers or between private and public clouds can only truly be redeemed with an understanding of the cloud business model and cloud workload management. It seems that cloud adoption has reached the phase where advanced cloud users are creating their own hybrid solutions or migrating between clouds while striving to achieve interoperability values within their systems. This article aims to answer some of the questions that arise when managing cloud workloads.

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