Scalr and Google Compute Engine

Today's guest post is from Sebastian Stadil, CEO of Scalr. The company providies a web-based control panel for cloud infrastructure that serves as an interface between end users and the multiple cloud platforms that they use. In this post, Sebastian discusses benchmarks they conducted to analyze Compute Engine performance.



At Scalr, we build a web-based control panel for cloud infrastructure, which serves as an interface between end users and the multiple cloud platforms that they use. Engineers use Scalr to achieve significant productivity gains, and IT departments use it to drive and control cloud adoption.



One of our customers — grandcentrix — used Scalr with Google Compute Engine a few months back. They were building the backend of the companion mobile application for the Eurovision song contest using both Compute Engine and Scalr. Our experience was documented on the Google Cloud Platform blog.



No random hiccups with Google. Only high and stable performance.

In a few words: this was the first time Eurovison had a companion app, so they had no idea how much traffic they’d have. Fortunately, our load tests had shown that Compute Engine was a predictable high performer with fast provisioning times, so all we had to do was ensure that the application architecture would scale horizontally.



Eurovision was a success, and we’re looking forward to taking on such a challenge again. Why? Because we feel very comfortable using Google Compute Engine. It just doesn’t surprise you, and delivers extremely consistent performance.



We’ve recently conducted performance benchmarks on persistent volumes across multiple cloud providers. For volumes, performance is only part of the story. Stability matters a lot, too. What good is a high performing volume if it fails to perform 1/10th of the time? Not much!



Using Google Compute Engine, every single volume performs the same, every hour of every day. If their throughput is sufficient when you run your tests, you can know for sure that Google volumes won’t let you down when you need them.



By the numbers: the benchmarks

Below, you’ll find graphs that compare the performance dispersion for IOPS, bandwidth, and latency for Google Compute Engine and EC2 volumes. This is basically a measurement of how consistent disk performance has been over hundreds of 10-minute disk-performance measurements.



What you’ll see is that Google volumes offer significantly more consistent performance than their AWS counterparts, including PIOPs volumes!



Here are the graphs. Lower dispersion means more consistent performance.

• Bandwidth Dispersion


• Latency Dispersion


• IOPS Dispersion

Note: we’re still in the process of adding benchmarks on sequential workloads for PIOPs volumes, but they have been benchmarked for random workloads.



Are you trying out Google Compute Engine?

Google Compute Engine, EC2, and Rackspace aren’t API-compatible, so if you intend to start using Google’s Cloud for your business today, you’ll probably need to rewrite quite a few integrations.



If that’s the case, you might want to look at the Scalr Cloud Management Platform. Using Scalr lets you design infrastructure and policies once, and use them with any cloud platform.



We actually used Scalr to run the benchmarks we presented here. If you’re interested, you could watch this talk from the OpenStack Summit, where we presented how we did it.



You can of course learn more about Scalr on our website, or request a POC.



-Contributed by Sebastian Stadil, CEO and Founder at Scalr