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Summary:

Benchmarking results from Zencoder show that Amazon Web Services beats out Google’s Compute Engine in a test of a specific CPU-intensive workload. Compute Engine’s performance was hindered by a lack of HPC instances, which Google could one day add. But it’s nice to see real-world comparisons.

GCE-vs-EC2 copy

According benchmark tests by video-transcoding startup Zencoder, Google’s new Compute Engine infrastructure-as-a-service offering has some work to do if it wants to catch up with Amazon Web Services on the performance front. But the offering, still in “limited preview” mode and far from fully baked, should be able to make the necessary adjustments rather easily.

The results, detailed in a blog post on Tuesday, suggest that Google Compute Engine’s real problem right now might just be a lack of high-performance instances. Its current workhorse — an 8-core Intel Sandy Bridge instance with 30GB of memory and 22 compute units — can’t hang with the Amazon Cluster Compute Instances that Zencoder uses for its transcoding workloads. The largest of those is a 16-core dual-CPU Intel Xeon instance providing 60.5GB of memory and 88 compute units running atop a 10 Gigabit Ethernet platform.

As Zencoder ramped up the workloads, the performance differences became clear:

Compute Engine didn’t fare any better when Zencoder tested transfer speeds between the cloud storage platform and the cloud computing platform. Whereas rates between Amazon S3 and Amazon EC2 topped out at 1,458.32 Mbps, the rate between Google Cloud Storage and Google Compute Engine peaked at 202.6 Mbps. In fact, the post’s author writes, “it appears that GCS is slower than S3, and GCE transfer is slower than EC2, such that even if you’re using Google for compute, you may be better off using S3 for storage.”

While the results are interesting because they’re the first real apple-to-apples comparison I’ve seen between Compute Engine and EC2 (BuildFax cloud architect Joe Emison’s pre-release benchmarks were pulled from his Compute Engine review on InformationWeek), they need to taken as what they are. They are, as Zencoder points out, tests of a specific CPU-bound workload — the performance of which Google could improve by adding higher-powered instances — and don’t take into account the difficulties of running at massive scale — a capability Google touted when it launched Compute Engine in June.

And, the author notes, Compute Engine is generally a quality platform, “especially [with regard to] disk I/O, boot times, and consistency, which historically haven’t been EC2′s strong suit.”

This might actually be the more-important measure for most potential Compute Engine users. As GigaOM contributor James Urquhart wrote recently, “If Google can deliver a service that eliminates most of the I/O and network performance inconsistencies that AWS customers currently experience, I can guarantee you there are many major compute customers of AWS that will want to give Compute Engine a test run.”

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  1. I think calling this an apples-to-apples comparison is a bit of a stretch. The fact of the matter is that they are comparing AWS’s cluster compute instances which are designed specifically for this type of workload to GCE’s largest standard instance which is designed to fit a variety of workloads. It is a good comparison of the best possible performance you can achieve from each cloud for this type of workload, but in my opinion this is different than an apples-to-apples comparison.

    1. That’s a fair point, although I’d argue that you can’t get much more apples-to-apples than just comparing the highest-powered instances on both clouds. Right now, Amazon just has the HPC market cornered with CCI.

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