Joe Masters Emison


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Where the Cloud Touches Down: Simplifying Data Center Infrastructure Management

Thursday, July 25, 2013
10:00 AM PT/1:00 PM ET

In most data centers, DCIM rests on a shaky foundation of manual record keeping and scattered documentation. OpManager replaces data center documentation with a single repository for data, QRCodes for asset tracking, accurate 3D mapping of asset locations, and a configuration management database (CMDB). In this webcast, sponsored by ManageEngine, you will see how a real-world datacenter mapping stored in racktables gets imported into OpManager, which then provides a 3D visualization of where assets actually are. You'll also see how the QR Code generator helps you make the link between real assets and the monitoring world, and how the layered CMDB provides a single point of view for all your configuration data.

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A Network Computing Webinar:
SDN First Steps

Thursday, August 8, 2013
11:00 AM PT / 2:00 PM ET

This webinar will help attendees understand the overall concept of SDN and its benefits, describe the different conceptual approaches to SDN, and examine the various technologies, both proprietary and open source, that are emerging. It will also help users decide whether SDN makes sense in their environment, and outline the first steps IT can take for testing SDN technologies.

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IaaS Performance Benchmarks Part 4: Google Compute Engine

This is the fourth part in a series of articles about creating my own IaaS performance benchmarking project. In the first part, I explained the methodology I'm using to test instance types across major IaaS providers. In the second and third parts, I ran benchmarks across every instance type in every US region run by Amazon Web Services (AWS), the most widely used IaaS provider. In this part, I look at Google Compute Engine (GCE), which just came out of beta and is widely seen as one of the biggest potential competitors to AWS. I compared instance types across GCE as well as against AWS.

As of today, there is only one US region with two zones available for GCE in RightScale. In that region, in each of its zones, I kicked off one of each GCE instance type that comes with local disk storage, for a total of 24 VMs. As with AWS, I ran on RightScale’s CentOS 6.4 images. One note: GCE makes life simpler than AWS in terms of pricing, as you don’t have to deal with choosing and allocating reserved instances, and GCE bills in minute increments, not hour increments. That said, because AWS is the industry leader, when I compare GCE to AWS, I will calculate both the most expensive and cheapest pricing that AWS can provide.

GCE Instance Comparisons

Here are the main takeaways that I have from comparing instance types across GCE:

• Performance is consistent across both GCE zones, regardless of instance type (except that you should expect the performance of the f1-micro to fluctuate). This is good, although with only two US zones, it’s hard to really compare GCE to AWS.

• The best price-per-performance comes with the f1-micro (which is subject to more serious fluctuations in performance; your mileage will vary at any given moment), although both the g1-small and n1-standard-1 are fairly close.

• GCE also has consistent performance across VMs as far as the single-threaded UnixBench results go. If you’re just going to hit a single CPU (and don’t have particularly high memory requirements), you should probably look at either the g1-small or the n1-standard-1, both of which get the best price-per-performance in this particular comparison.

• Keeping with the consistency theme, when GCE gives you two, four, or eight cores, you get pretty similar performance across each of the types with that number of cores (“standard,” “high memory,” or “high cpu”), with “high cpu” doing a little bit better (2-8% better in my tests), but priced significantly less than the “standard” instances with that same number of cores. So n1-highcpu-8 only outperforms n1-standard-8 by 8%, but it’s around 60% of the price.


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(Note: The prices here are based on the “-d” instance types, which are no longer available post-beta, but are decent approximations of what it would cost to buy both the instance type and persistent storage volumes that you’ll need with GCE).


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Next: GCE-AWS Comparison


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