How to pick the best server based on Latency and Throughput

Choosing an optimal server location isn’t necessarily an easy task. Managing costs and selecting an appropriately sized hosting package is just one part of the deal. As much or more important than server capacity, is finding out how your services behave from your client’s perspective. Whether it is for choosing among different hosting providers or deciding in which location it is better to deploy your server, you need to measure latency and throughput. Having an insight into these two metrics can improve your service and result in cost-effective solutions.

In this article, we take a look into these two basic aspects of connectivity: latency and throughput. We discuss their behavior and show you how to use CloudPerf to compare and choose an optimal server for deploying a web page.

As we know, TCP performance is naturally limited by Latency. As for this, the first aspect we have to look into a server’s performance is Latency, then focus on throughput. No matter how big a link may be, if your users experience a high latency, it is not possible for them to achieve high performance. The next graph, shows the interdependency of Thoughput vs. Latency.


Here we can observe an inverse exponential curve, which in practical terms, it means that especially in the 1-30ms range, every millisecond of latency will have a heavy effect on the maximum achievable performance. With this in mind, we can picture very clearly the intuitive notion of choosing a server as close as possible to your clients, but still take into account even the smallest differences in latency.

Let’s say we have an account with a cloud provider and we want to deploy a service for European users. We can take Digital Ocean as an example, where we can deploy a VM in Amsterdam, London or Frankfurt, among others. We deploy the same test service on each of those locations. Then we set up a Static Object measurement for them in CloudPerf pointing to a 100KB test file and a Ping measurement to each server. We make sure to select the countries of our interest and start measuring. We choose to measure for one hour, one measurement per minute.

The following table shows the latencies obtained from each location to each of the three servers. The lowest latencies have been highlighted in yellow.


We can observe that depending on the countries we are serving to, we can expect a very different result for each server. But focusing on all countries altogether, we can say that Amsterdam and Frankfurt have the lowest latencies in general. Let’s confirm that with the graph:


This is one for latency, but what about throughput? Given similar enough latencies, like in this case, the effective TCP Throughput may be affected by other factors, so we take a look at the download speeds achieved for each server, now the highest Throughput has been highlighted in yellow.


Here we can clearly observe that clients from Austria and Germany, which showed ping values favorable to the Frankfurt server, actually show a higher throughput when serving from Amsterdam. Let’s take a look a the graph:


No we have confirmed that our Amsterdam server will show the best performance. Of course results will vary depending on which countries we focus on, but we can clearly see a general advantage of using Amsterdam as a single location for this selection of countries.

Are ISPs still throttling Netflix?

In the recent past we have seen a massive development of online streaming services, where Netflix is one of the leading brands in this new market. Netflix has built its own CDN (Netflix Open Connect) to support its worldwide expansion. This resulted in a rapid growth of bandwidth consumption from a considerable number of users, intensifying year after year together with Netflix’s popularity. Netflix has undergone a massive structural transformation in the way it delivers content. Parting from a monolithic application design with some external CDN support to building their own CDN around the world. Currently Netflix Open Connect has 233 server locations in all 6 continents. Their endpoints are primarily located among IXPs and within some ISPs as well. A model which reminds us of Google Global Cache, by installing cachés close to the last mile to deliver specific services.

ISPs have reacted differently across the globe, resulting in some heated discussions about traffic shaping, throttling and service differentiation from ISPs, which rose considerable criticism from defenders of net neutrality and consumers alike. Two years after our previous insight into this topic, we decided to find out what is happening today, if any ISPs are showing signs of throttling Netflix. We found that the situation has improved noticeably.

We setup an experiment which runs from thousands of Speedchecker probes around the world Netflix’s SpeedTest ( and right after that our own SpeedTest using Akamai endpoints. We compared the results of both tests using our SpeedTest with Akamai as reference and found out which ISPs show noticeable differences when connecting to Netflix. Due to Netflix’s high bandwith consumption and rapidly growing popularity, adapting to such changes might pose a challenge for some ISPs.

After running the experiment for 24 hours, we found that the performance differences between and our reference endpoints in Akamai are equivalent, which fortunately tells us that the general rule seems to be not to throttle Netflix.

peak vs offpeak_

We can also observe that the situation still changes notably between countries, with Italy showing the worst performance among the countries where our measurements ran.


In the following table, we can see the ISPs in which we measured the top 35 highest median speeds.

[embeddoc url=”” download=”no” viewer=”microsoft”]

After investigating ISPs in the USA only, we we able to rank their top 10 providers as follows comparing off-peak and peak traffic hours.

us-peak2 us-offpeak2

We couldn’t detect further major ISPs showing signs of Netflix throttling in the countries we studied. In the cases of CenturyLink, Charter Communications and possibly Time Warner Cable, we can observe a clear disadvantage of Netflix during peak hours.

In conclusion, we have seen the situation of Netflix evolve in positive terms for the consumer. We can see from our test results that the global tendency is to respect net neutrality. There are still ISPs worldwide which haven’t joined Netflix OpenConnect CDN yet and therefore they cannot profit from its traffic delivery benefits. Others simply slow down altogether during peak hours which reveals difficulties at coping with high traffic demand. So far this year, Netflix global launch seems to have gone peacefully and without any major incidents. The market has made its share of pressure to the industry, pushing them to develop high performance infrastructure for the end consumer, while clearing the path for other applications high in bandwidth consumption to enter the market with lower technical and legal barriers.

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Speedchecker @ IETF 96

This year the IETF meeting in its 96th edition took place in the vibrating city of Berlin. We didn’t want to miss out on this important gathering and decided to contribute to one of their workshops on network measurement: nmrg.

We presented a study that was made in cooperation with LACNIC Labs, where the Latin America and Caribbean region was measured using Speedchecker ProbeAPI during one year, making possible to map the region in terms of connectivity. This allowed us to identify clusters of countries that were better connected between them than to the rest of the region. A definition for connectivity had to be defined in such a way that permitted to draw interesting and useful conclusions about the situation in the LAC region.

Screen Shot 2016-07-21 at 12.10.13

The video of our presentation at IETF96 can be found here, our presentation starts at minute 43:00. The original blog post by Agustín Formoso from LACNIC Labs can be found here.

The study was received with high interest by both the chairs and audience at the workshop, spawning interesting discussions during and after the session. We are happy to be able to participate and discuss our measurement experiences with the IETF/IRTF community. We collected valuable suggestions and comments which will surely help us point not only our measurement techniques in the right direction, but also develop our products and regional presence in a way that favors coverage and scientific precision.

The IETF 96 meeting has been a very nice experience, allowing us to get in touch and meet personally important actors of this worldwide community as well as keeping ourselves up to date with relevant decisions, norms and standards that are currently being discussed.

Announcing new Feature: Page-Load Waterfall Analysis

Here at Speedchecker, we are aware of our customer’s requirements and we strive hard to build our products not only robustly and precisely, but also expand on features which will help everybody to diagnose their sites performance in greater detail, while at the same time , retaining that ease of use and clarity our customers love. Today we proudly announce the introduction of a new feature in CloudPerf: a detailed view of all your measurements. This feature is especially useful for frontend developers, who need to examine if the webpage loading time is not impacted too much by including slow external resources such as 3rd party tracking scripts or assets.


Inside your Benchmark’s results page, just move the mouse pointer along the graph  and click once in the position you would like to take a deeper look. The pop-up windows will stay after your click and you can go inside the detailed view by clicking “Show Detail”.

Screen Shot 2016-06-22 at 16.57.44

In this view you can see a panel on the left side, where you can choose the benchmark where you would like to take a closer look, the country of the measurements, destination website and the time range for which the results will be shown.

Screen Shot 2016-06-22 at 17.26.12
On the top you can see a timeline where after selecting the time-range you can choose with precision the time of the day you want to take a look into. Directly underneath the list of measurements made at that time will appear, showing the details of every single one of them.
Screen Shot 2016-06-22 at 17.26.22


If you are running a Page-Load Test, be sure to check the box “Collect resource timing data” in its configuration before running it. If you did so, using this new feature will be enable you to take a look using a very cool and useful Waterfall Chart, which will show you the loading times of every resource of the site you are measuring, for every single measurement in the time-range you selected. This way you can follow the behaviour of your services in detail over time.
I hope you enjoy this new addition to CloudPerf and overall we expect it helps you to gain a greater insight into monitoring your resources.

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Cloud vs CDN… Are CDNs always an improvement?

During the last years we have witnessed an explosive evolution in how the Internet is structured. Although traditional hosting and content delivery is still the norm in most cases, its basic function has been enhanced by CDNs and the advantages of cloud computing when we need to optimize our service’s presence.

On one hand, CDNs have built themselves a reputation of speed, power, “freedom”, space, air…which reflects on their market names as well: Fastly, Highwinds, CloudFlare, Skypark, Cachefly, etc. You get the idea. In many cases the technical results do reflect their marketing images, in most situations adding a CDN will probably benefit your site… but is it always like that?

On the other hand we have Cloud Computing services have improved and matured a great deal, while at the same time can offer either their own CDN connectivity or simply it’s easy to hook one up. We have found that, even without CDNs some cloud services work at CDN-like speeds and it seems that adding one won’t bring noticeable speed boosts.

We take the case of DigitalOcean as cloud provider. Famed by their approach as a simple and clean environment and low costs, we could observe remarkable speeds in the UK using our tool CloudPerf.

In this graph we can observe how DigitalOcean compares to Google and Amazon (without CDN) in a single 1MB object download.

DOvsGoogvsAma-httpget UK

We set-up a simple web-page for comparing the time it takes to load a whole page.

DOvsGoogvsAmaz pageload
We can already observe a clear difference to both giants Google and Amazon. Both offer their own CDNs which will speed up their service, even locally. But why not get a cheaper and already fast solution?

Especially for local audiences, like this case in the UK, there could lie a very cost-effective solution for delivering low-latency content. So why isn’t this the case? One factor could be the simple, developer-oriented approach of DigitalOcean, which can be beneficial for somebody who knows how to do everything by hand, but the benefits of using a big multi-service Cloud-Provider like Google or Amazon are something you also pay for: being able to interconnect services, easy application-level management, auto-respawning of faulty machines and overall an easier management among many other interoperable options need to be taken into account… especially if you have a relatively complex machinery to operate.

You could mount a very complex network in DigitalOcean as well, but you would need to configure everything by yourself and management ends up being more tedious. In that sense, depending on your budget, sometimes paying less on one side can result in higher operational costs. Please take into account that we are actually comparing a VPS solution against complete Cloud service providers.

On the other side, DigitalOcean is an example of how the Cloud is becoming more and more affordable, to the point where it competes against traditional web-hosting prices and still delivers high performance. You can literally have a new server up and running in less than a minute and maybe 5 minutes if you’re new to it. Since there isn’t much to fiddle around, this very straightforward and simple approach will spawn you one or more new servers instantly, with public ip-addresses and pre-installed keys to log in remotely by ssh. Starting from $5 a month for a basic VM running on the Cloud.

Even if you already use another Cloud provider to run your machines, trying this out won’t hurt at all. Hooking up a CDN to it is very simple and even IF you need it. Since the high performance of the service itself is already on-par with CDNs, you can think it twice if it’s truly beneficial to use one.

This is a point we would like to stress: a CDN by itself may or may not accelerate a service. The decision of which CDN to use and whether it fits your own user distribution is a complex question which requires a well researched individual answer for each case. Having stated that CDN isn’t synonyms with “higher speed”, we woud like to ask again: why isn’t this option more popular? Maybe is it the already established usage of a Cloud platform, which makes it convenient to just spawn a machine and control everything from the same place. Maybe adopting another provider is too much extra papework, or maybe the public simply isn’t aware of this.

Let’s take a look at the following comparisons, where CloudPerf measured DigitalOcean against multiple CDNs in the UK:

DOvsCDN-httpget UK

If we compare DigitalOcean’s (here labeled as “Origin”) performance in the UK directly against CDNs we will find that it is at least on-par with most of them.

DOvsCDN pageload all

And if we filter out most of them and take a look to the CDNs performing the closest:

DOvsCDN less

We find that it performs even better than Highwinds and Skypark. With CloudFlare and CloudFront performing with better averages.

DOvsCDN pageload less

So, looking at the example we showed here, if you have your audience near any DigitalOcean location, then you’re probably not going to need a CDN to speed up you service. Nevertheless, depending on what solution you adopt, you could benefit from other features of CDNs, like added SSL security and easy escalability without having to resize machines in many cases.

When we compare prices, the picture gets even more interesting. Let’s take DigitalOcean’s $20/month package: you get 3TB of data transfer included and a generous VM. That’s $0.03 per hour and $0.0067 per GB together in one price. A similar configuration in GCP will cost approx. $28.08 only for having the VM and ~$460.8 for 3 TB of traffic, that makes ~$488,88 a month. In AWS a similar config would cost ca. ~$40.32 for the VM and ~$476.16 for 3 TB of traffic, that’s ~$516.48. So DigitalOcean with $20 a month will give you an equivalent of ~$500 investment in other platforms.

What about the bigger VMs? The biggest plan DigitalOcean offers is $640 a month for a very capable machine and 9TB data transfer included. An similar setup in GCP will cost ~$449.28 ($0.624/hr) plus $1024 for 9TB of traffic giving a total of $1473.28. In AWS you can either choose a $0.528/hr which is a less capable machine but similar in price or $1.056/hr for a more similar one to the ones used in the competition. 9TB of data transfer will cost $1428.48 and running the VMs will cost either $380.16/month or $760.32/month, giving a total of ~$1808.64 for the smaller machine or ~$2188.8 for the bigger one. In any case expect to pay around $2000 a month. All that without CDN. To make things simpler, if we assume an approximate price of $0.1 per GB in a CDN, we find that you have to put $300 or $900 on top of your already existing hosting costs for accelerating those 3TB or 9TB of data respectively.

Please take into account that these figures are an approximate calculation since, as you may very well know, pricing in Cloud services and CDNs is extremely dependant on what resources, how and when were they used. In that sense, this also favours DigitalOcean in giving you a clear and straightforward fixed pricing structure.

Summing up, we have seen that a simple Cloud VPS provider like DigitalOcean can achieve very low latencies locally in the UK. We compared its performance and pricing against Google Cloud and Amazon S3. We saw that DigitalOcean generally performs better than both. Then, comparing DigitalOcean’s performance against CDNs serving the same content, CloudPerf reported that the VPS by itself is fast enough in the UK to compete head to head against CDNs. In this perspective, we can only recommend to analyse and think twice what kind of solution you need to adopt. For that matter, making an informed decision without measurements sounds indeed contradictory. Using our tool CloudPerf, we discovered particular circumstances where a large very important location like the UK can be covered simply using a modern high-performance Cloud VPS service.

Do you want to discover your best options yourself using CloudPerf? Sign up now!

Measure and compare CDNs with CloudPerf

In this tutorial we show you a practical application of CloudPerf, which is measuring and comparing CDNs. Since nowadays the CDN market is bigger than ever and equally diverse, we think it is very important to be able to compare and analyse CDN performance using an independent measurement platform before making any decision. This way you can see and compare by yourself using the same measurements across all providers of your interest.

It is important to take into account, that CloudPerf makes last-mile measurements, that is, right there where your users are. That is especially useful to contrast what CDNs or other providers say about their services and what your users are actually experiencing in real time.

Preparing your setup

    •  Make sure you have an account with CloudPerf, if not, you can get a free trial account on this link.
    • Make a list of all the URLs you would like to measure directly from your site. In this example we will use only one url to compare with four CDNs.
    • Make sure to compare a copy of the same file across all destinations.
    • Make sure all your URLs use the same protocol (http or https).
    • Set up your test domains for measuring your service with your desired CDN. You can get trial accounts on most CDNs. You can also setup a series of subdomains for testing many different CDNs with your content. So is linked to CDN-1, is for CDN-2 and so on.
    • Confirm that all your testing sites are using similar DNS configurations. CNAME cascading can affect measurements greatly and lead to unrealistic results.

In general, keep in mind that for testing purposes, it is best to configure all links as similarly as possible. Depending on the options each CDN gives, most of them can also provide test files for comparing their services. Some of these test files can also be found in the web. Nevertheless, we think that measurements are more meaningful if you test directly with your content. Especially if your site mixes cached and uncached content or if your site updates frequently, caching times become more relevant in the equation.

Screen Shot 2016-04-20 at 17.31.48

* NEW * – CloudPerf now offers pre-configured links to popular CDNs for your convenience. Just click the drop-down menu on the “Create New Benchmark” button in the Dashboard and select “CDN Benchmark”. The benchmark editor will now include a list of checkboxes with popular CDNs so you can compare your own destinations with our current selection of CDN providers. We will be adding more and more CDNs with time!


Configuring CloudPerf

In this example, we will set up a comparison between one static object against 4 CDNs. Once you have everything prepared, log in to CloudPerf and you will be taken to the Dashboard. Click on “Create new Benchmark”. You will be taken to the benchmark editor.

Screen Shot 2016-03-23 at 01.00.41
We name this benchmark “CDN Test”. We chose to measure a Static Object, but this example is also valid for using Page Load. Since we want to run the test for some hours, a 5 minute frequency is OK. For longer or permanent tests, you may want to measure less often. We select a number of countries in which we are interested to run the measurements.

CloudPerf uses a technique we call “Connection pre-warming”, in which two subsequent requests are made with every measurement: the first request will need DNS resolving and therefore will report longer measured times, while the second request has already a resolved DNS and will only report the connection time to the server. You have the option of including the DNS lookup time in your results.
This time we choose not to include DNS lookup times in our measurements, so we can observe in our results the “pure” connection time to our destinations.

For the first destination, we input the direct link to our origin server against which we will compare the CDNs’ performance. We chose to name it “Origin” and under URL we input naturally the direct link to the file we will test. Click on “Add new destination” and another line will appear. We name this and the subsequent lines with the CDN’s respective names, in this case, we simply numbered them. In the URL box we put either the address of the subdomain you previously configured to work with your site or any other link to a static object or web page to measure. For this post we compared one of our homepages with four real CDNs serving the same file.

Screen Shot 2016-03-23 at 01.15.06
Click on “Save & Update” and voilà! We have configured our benchmark to measure our site and some CDNs simultaneously from thousands of different locations. We only have to wait now and take a look at the results after enough samples are taken.

Viewing Results

If enough time has passed, our first results will be ready. We simply log back into CloudPerf and once in the Dashboard view, we click our measurement’s name, which will take us to the results page.

By default we see first the latency measurement graph. The first thing we can notice from these results is that using any of those CDNs will make our website more responsive.

Screen Shot 2016-03-23 at 11.16.36

If we remove the origin from the graph using the destinations buttons, since it is the slowest URL in this experiment, the graph will automatically zoom in and you will be able to observe and compare all four CDNs much more clearly. Please note the color change of the graph lines after modifying the destinations.

Screen Shot 2016-04-20 at 19.00.43

You can use the results table below for having a first look at the measured latencies by country.
Screen Shot 2016-04-20 at 19.03.24
If you wish to see the measurements over time in the countries of your interest only, you can select them using the Tests Running From field. You can also switch the graph between destinations and location using the Group By option.

It may be very intresting to compare results using different statistics. For example, if we select the 25th Percentile (faster connections) we can observe that CDN4 clearly outperforms the other three CDNs:
Screen Shot 2016-04-21 at 00.49.02
while selecting the 95th Percentile (slower connections) our results show us longer latencies, but less clear differences between CDNs, although maintaining the general tendencies among them.
Screen Shot 2016-04-21 at 00.54.49

Remember that CloudPerf is a very flexible tool and can be used for much more than measuring CDNs. Please take a look at our Quick User’s Guide and explore all the powerful options that CloudPerf has to offer!

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Google CDN Beta is here… and it’s already one of the fastest CDNs out there!

Some months ago, Google launched their Alpha program for their upcoming CDN service. We kept a close eye to their development and in the meanwhile, in NEXT 2016 Google has already announced the Beta phase of their CDN. We already discussed how this new product will fit in the broad palette of content distribution solutions Google has implemented. We have seen Google Global Cache, which is primarily aimed at speeding up their own services at ISP level, with more than 800 caches installed globally. CDN Interconnect is their partner program with third party providers like Cloudflare, Level3, Akamai, Highwinds, Fastly and Verizon, allowing them to use Google’s backbone network to transport content faster than ever from the source to practically anywhere where it is required, powering up CDNs not only with faster caching, but also enabling them to deliver rapidly changing content at top speeds.

Cloud CDN is Google’s own CDN solution for sites running in VMs inside Compute Engine. It is designed and implemented a bit differently from other CDNs, since it is meant to cache not only static content, but practically a whole site in more than 50 edge caches globally. It is a whole new take in the concept of CDNs, going way further than simply caching files, since it is directly integrated into their Load Balancing system and it literally means that a copy of your site will be running and serving from the closest location to your customers, with a single public IP address thanks to Anycast. In addition to HTTP/1.0 and 1.1 it also supports the new HTTP/2 protocol as well as free HTTPS, putting your site at the edge of current Web technology.


Using our tool CloudPerf, we were able to try out and see how well it performs compared to other CDN providers, including some of their Interconnect partners. We have four exact copies of our test VM in Google Compute Engine running in different locations worldwide. Since Cloud CDN is designed to run in front of a whole site, instead of only caching static objects, we designed a simple 100kB page to test this system at its best capabilities. CloudPerf uses a real instance of Chrome to load the whole page and measure the time it takes to visualize the content in a real web browser, measuring as always from the last mile, where real users are.

Please consider that CloudPerf‘s Page Load test, by using a real instance of Chrome requires a cold start of the browser instance and includes DNS resolution times. That means that at this moment the measurements using this method will have an overhead of +/-600ms added to the real measurement time. The relative measured times between all destinations are correct since all of them are made with the same probe, but the absolute measured times include the above mentioned overhead.

Now let’s see what happens with the 100kB Page Load test in a selection* of worldwide countries.

World Pageload graph
The average measured times by country and CDN can be seen in the following table:
World Pageload table
We can clearly see that Google Cloud CDN outperforms all other CDNs in loading a whole page in most countries. We can have a look at the special case of Japan, which shows the lowest measured times, by simply filtering results in CloudPerf.
Screen Shot 2016-04-15 at 16.13.36

Going further, if we take a look at a selection of european countries**, we observe a similar situation only with Cloudfront, Level3 and Akamai coming a lot closer to Google’s performance.
PageLoad Europe

Now, in the USA the battle is fierce, although higher than Japan, the overall loading times of most CDNs are very close to each other and the general performance is really good, except for MaxCDN, which in our measurements got a little behind the rest, but still performing reasonably well in comparison to other regions. Nevertheless, it is evident that CDNs strive for top performance especially in the US market.
USA Pageload graph

How does Google achieve such top loading times practically everywhere? We think that this is precisely due to the fact that Google CDN is embedded in the Load Balancing system of Compute Engine and that means that you can configure your site to automatically replicate your VMs whenever it is necessary to a location closest to your users, meaning an overall higher response time and effectively shortening loading times.There is a very noticeable difference when we include into the equation the time it takes to load and resolve all objects of a page from a single location close to the user, as opposed to other CDNs where only traditionally cacheable content gets copied and the rest has to be retrieved from the origin.

PS: You can make your own comparisons and performance tests using CloudPerf.Sign up now!

* Australia, Brazil, France, Germany, India, Japan, Russia, Singapore, South Africa, Turkey, United Kingdom and United States

** France, Germany, Italy, Netherlands, Norway, Poland, Romania, Spain, Sweden and United Kingdom.

Surprise! Google CDN Alpha already outperforming competitors in Europe


During the last couple of years, Google has been undergoing massive structural transformations: first they shut down their PageSpeed Service which was their own take into the CDN world until August this year. In exchange of that, they launched CDN Interconnect, a program where Google joined forces with other CDN providers like Cloudflare, Fastly, Level3, Highwinds and lastly Akamai, opening the doors to those partner CDNs to serve content originated from Google Cloud Platform and profiting from using the giant’s Backbone Network. On top of that, Google has been quite successful in building their impressive Global Cache for speeding up their own services by directly installing caches on ISPs. In a previous post we found out more than 800 cache locations worldwide.

The Alpha Release of Google Cloud CDN was interpreted by the press as competition with their own partners from CDN Interconnect. We looked closer and discussed our first impressions in our previous post. Now it’s time to look inside this new service and see what it has to offer. We looked at our results with skepticism at first, but after looking closer at them, we could recognize the gestation of what could be the new wunderkind among CDNs.

Since the current release state of Cloud CDN is Alpha, you can only use it by invitation. In our case, we requested access and it was granted only 2 days later.

Cloud CDN is built within Compute Engine, which is their Cloud Service for creating and running Virtual Machines (VMs). This service features elasticity options for responding to changing traffic conditions, such as replicated instances and Load Balancing. This is where Cloud CDN comes into play: as part of a load-balancing configuration.

According to its own documentation:

” Google Cloud CDN (Content Delivery Network) uses Google’s globally distributed edge caches to cache HTTP(S) Load Balanced content close to your users. Caching content at the edges of Google’s network provides faster delivery of content to your users while reducing the load on your servers.”

The charges for using this service are based on the pricing for Load Balancing and Protocol Forwarding. On top of the hourly charges for using the first 5 Forwarding Rules of $0.025/hour, the cost per processed GB is $0.008/GB. On top of these costs, consider the standard Internet Egress rates you have to pay for delivering your content, which ranges from $0.08/GB to $0.23/GB depending on the region and monthly usage. Heavier users profit from cheaper rates. Neverhteless, this is not a particularly cheap solution, as we can find more affordable CDNs, you can take a look at this comparison.

If you already have a backend service running in a VM in Compute Engine, activating Cloud CDN after registration requires only one command. In case you don’t have a load-balanced backend service running you can take a look at our quick tutorial for setting it up. This will spare you some time of reading through many different pages of documentation.

We ran 48 hours of continuous performance monitoring using our tool Cloudperf, with a total of 33600 single last-mile measurements for each test. We can see that in terms of throughput, Google CDN doesn’t perform especially well in comparison with other CDNs.

Throughput Table
But if we look at our measurements in Europe… Surprise! Amazingly low latencies!

Latency EU - GraphLatency EU - Table
Our Thoughput measurments confirm that the young Cloud CDN is already giving top performance in Europe! This is a very clear sign on where Cloud CDN shows competitive advantages, should you decide to use it on its current state. If you’re interested in speeding up your services in Europe, this CDN is already a viable solution.

On the other hand, in the US we could observe a notoriously high latency and not very fast download speeds.

Latency US by ISP - Graph
These results may surprise us at first, but we have to remember that this CDN service is still in Alpha stage, which means that it can still be radically altered during its development. According to the current documentation (December 2015), content is cached only in a small subset of POPs during this stage; the full POP usage will be available later on. Also the cacheable file size is currently limited to 4MB. Caching larger files will have to wait for a further release.

In the next table we can compare the latencies achieved in the US on different ISPs.

Latency US by ISP - Table
In other countries the latency tests didn’t show much better results except for european countries, where it performed notably well.

Latency G20 - GraphLatency G20 - Table

From the current state of development, we have observed that Google Cloud CDN isn’t going full speed yet. It is evident that it’s in fact an Alpha release. Nevertheless, looking at their performance in Europe, we can definitely see its immediate utility in multi-CDN scenarios, where customers demanding fine tuned performance can use Google CDN in Europe while using different CDNs in other regions.

How does this fit between CDN Interconnect and Global Cache? Technically speaking, we can see that Cloud CDN is built upon the Load Balancing system for their Cloud Backend Services. With that in mind, we can consider this a hand-cut CDN solution designed especially for Google’s own cloud services. On the other hand, Global Cache accelerates mainstream Google services at an ISP level, while CDN Interconnect allows partner third party CDNs to cache and serve content stored in Google Servers much faster.

All this helps us visualize an impressive caching infrastructure Google is extending to keep his place in today’s and tomorrow’s very competitive Internet. Even in an Alpha release which reasonably showed mediocre results for the most part, we know this is to be expected and should radically change after its final release. Of course Google knows this…after all, being and staying an Internet giant isn’t easy!

PS: You can make your own comparisons and performance tests using CloudPerf. Sign up now!

Is Google taking on Akamai? …not really.

The past 9th of December Venturebeat published a rather controversial article stating that Google is quietly launching its own CDN to compete against Akamai. News spread fast, and now Google’s move is in everybody’s lips. Is this an unexpected low punch from Google’s side? If we take a closer look, we may find that appearances can be deceiving.

The internet keeps growing and reaching more people every year. With an estimated number of 3.4 Billion users, the network has covered 46.1% of the worlds population (source). Big players in today’s Net are rearranging their lines to confront this fierce battle that comes with delivering content to such a massive number of users. We already talked about Google’s Interconnect program, where strategic partnerships with CDN providers like Highwinds, Level 3, CloudFlare and Fastly were made to allow them to serve content stored in Google’s datacenters using the giant’s backbone network. We also talked about the very extended Google Global Cache in our last post, with more than 800 cache instances putting their popular contents and services closest to consumers.

Now Google has announced another take of their own in the world of CDNs with the Alpha Release of Google Cloud CDN. Adding to their network 70 globally distributed Edge Points of Presence, which will cache Google’s content for partnered network operators.

On the other side of the coin, we have Akamai claiming to be the world’s biggest CDN. Their own philosophy and network design is radically different from Google’s: Akamai’s backbone is the Internet itself. Akamai’s strategy is to distribute and operate isolated cache instances everywhere they can. Caches aren’t even connected between themselves in any particular way, in other words, no special “backbone”…achieving impressive results and an excellent reputation, this giant has reached a virtually ubiquitous worldwide coverage: 130000+ servers, 2200 POPs covering 1200 Networks in more than 800 locations in 81 countries.

POPs Locations Countries
Akamai 2200+ 800+ 81+
Google Global Cache ? 800+ 100+
Google CDN 70 51 33

Looking at this picture, imagining Akamai and Google clashing against each other in the battle of the clouds may seem like a likely scenario for many, but this is far from becoming reality. It is true that both are immersed in the same business, but their focus is completely different. While anyone can go directly to Akamai and get their CDN services, Google doesn’t offer the Global Cache infrastructure directly to third parties, in fact, until now Google’s focus has been facilitating the delivery of their own content, whether from their own platforms like Youtube or any other content hosted in their datacenters. Since their content is so massively popular, ISPs are naturally interested in serving them as fast as possible, so Google was able to construct a massive network of caches directly installing them within the ISPs probably at no cost, profiting from a win-win situation.

Seen under this light, we think it is unlikely that ISPs would allow Google to use their Global Cache without taking a proper share of that pie.

So all this confusion about Google and Akamai battling in the clouds seems to be a bit exaggerated. In fact, Akamai is also recently participating on the Google Interconnect Platform, which will also allow customers to save up to 66 percent on Google Cloud Platform egress costs.

“As more and more enterprises come to rely on cloud-based computing and storage resources to drive their businesses, it’s critically important that performance is maximized and cost effectiveness is maintained,”
explained Bill Wheaton, executive vice president and general manager, Media Products Division, Akamai. “As the operator of the world’s largest distributed CDN platform, we’re collaborating with Google Cloud Platform to ensure that our joint customers can pass traffic directly from Google Cloud Platform to the Akamai CDN, empowering them to take full advantage of their cloud investments.”
(source: PR Newswire)

The real battle of the clouds is being fought against Amazon and Microsoft, where Google is actually lining up with key players in the world of CDNs and not getting in their way. Trying to own everything is not necessarily the best strategy.

Demystifying Google Global Cache

The amount of data Google serves through the Internet is undoubtedly enormous and their network is correspondingly efficient in doing so. One key component of Google’s information superhighway is their CDN-Like Cache infrastructure: the Google Global Cache. We ran some tests with ProbeAPI and had a closer look at this vast network, which enables us to enjoy Youtube at the best quality our ISP’s capacities allow.

Our experiment showed us the extent of the deployed network in its worldwide coverage. We were able to observe the impressive number of 2383 Cache Instances across 800 locations all around the globe. It is important to take into account, that there may be more locations where a particular ISP wasn’t available through any probe when we ran the experiment or, for example, we have no probes in an ISP which runs through a particular Cache Server, especially in remote locations where the presence of ProbeAPI Probes is still scarce.

We used all the available probes at the moment we ran the experiment, delivering a total of 240184 individual results, which were grouped and cross-linked to obtain relevant data.

The cache locations are codenamed with three letter airport-codes. Cross-linking the Airport codes from the IATA with the codes obtained from the Cache-Servers’ names, we were able to obtain their approximate geographical location.


Detected Cache Instances





North America


South America






Central America



The top 20 Countries with the highest number of detected Cache Locations are:



Detected Cache Instances

North America United States 296
Asia Russia 263
South America Brazil 220
Asia India 83
North America Canada 76
North America Mexico 70
Europe United Kingdom 67
Asia Japan 63
Europe Ukraine 59
Asia Thailand 51
Oceania Australia 48
Europe Poland 45
Asia Indonesia 38
Europe Germany 36
South America Argentina 31
Oceania New Zealand 27
Europe Spain 27
Europe Italy 27
Europe France 26
Asia Bangladesh 24


Top 25 Cities with the most Cache Locations detected:

City Country Detected Cache Instances Detected Networks Ratio Networks/Caches
Moscow Russia 42 918 21,9
Sao Paulo Brazil 31 740 23,9
Tokyo Japan 31 116 3,7
Rio De Janeiro Brazil 28 322 11,5
Kiev Ukraine 28 277 9,9
London United Kingdom 24 347 14,5
Dhaka Bangladesh 22 51 2,3
Bangkok Thailand 21 28 1,3
St. Petersburg Russia 18 102 5,7
Sofia Bulgaria 17 104 6,1
Yekaterinburg Russia 17 84 4,9
Buenos Aires Argentina 17 79 4,6
Jakarta Indonesia 17 28 1,6
Bucharest Romania 15 92 6,1
Belgrade Serbia 15 42 2,8
Budapest Hungary 14 123 8,8
Sydney Australia 14 54 3,9
Mumbai India 14 46 3,3
Montreal Canada 14 43 3,1
Auckland New Zealand 14 39 2,8
Warsaw Poland 13 318 24,5
New York United States 13 276 21,2
Novosibirsk Russia 13 76 5,8
Toronto Canada 13 71 5,5
Kuala Lumpur Malaysia 13 28 2,2

To give ourselves an idea of the number of users covered by our detected servers, we have ranked the 25 top countries in terms of the estimated number of users.

Country Detected Cache Instances est. Number of Users Users/Cache
India 83 236.000.000 2.845.000
United States 296 219.000.000 741.000
Brazil 220 105.000.000 478.000
Japan 63 93.000.000 1.478.000
Russian Federation 263 78.000.000 298.000
Indonesia 38 66.000.000 1.733.000
Germany 36 66.000.000 1.826.000
Nigeria 8 61.000.000 7.666.000
Mexico 70 61.000.000 870.000
France 26 52.000.000 2.000.000
United Kingdom 67 51.000.000 764.000
Egypt 13 45.000.000 3.455.000
Philippines 11 41.000.000 3.715.000
Vietnam 16 40.000.000 2.496.000
Turkey 1 35.000.000 35.212.000
Spain 27 34.000.000 1.271.000
Italy 27 34.000.000 1.268.000
Bangladesh 24 32.000.000 1.321.000
Colombia 22 30.000.000 1.375.000
Argentina 31 30.000.000 976.000
Pakistan 3 27.000.000 9.147.000
South Africa 14 23.000.000 1.642.000
Poland 45 22.000.000 500.000
Kenya 6 21.000.000 3.517.000

* Thanks to APNIC for helping us estimate the number of users in each network.

The following map pinpoints all the instances of Google Global Cache we could observe. Please remember that the pins are pointing to the cities’ airports and not their precise location within the city, which is close enough for describing their location for these purposes.

From the huge number of Probes we applied for the experiment, we got an impressive array of the variety of networks connected to each Cache Location.

When clicking on the pins, we can see a list of cache instances and below the corresponding list of connected networks to each cache.

Top 25 Cities with the most networks detected:

City Country Cache Instances Detected Networks Ratio Networks/Caches
Moscow Russia 42 918 21,9
Sao Paulo Brazil 31 740 23,9
Chicago United States 11 511 46,5
Frankfurt Germany 7 475 67,9
Washington United States 10 470 47,0
Paris France 12 405 33,8
Amsterdam Netherlands 8 383 47,9
Dallas-Fort Worth United States 9 356 39,6
London United Kingdom 24 347 14,5
Rio De Janeiro Brazil 28 322 11,5
Warsaw Poland 13 318 24,5
Prague Czech Republic 10 288 28,8
Kiev Ukraine 28 277 9,9
New York United States 13 276 21,2
Los Angeles United States 11 262 23,8
Miami United States 6 236 39,3
Atlanta United States 7 177 25,3
San Jose United States 3 159 53,0
Milan Italy 4 158 39,5
Katowice Poland 4 145 36,3
Belo Horizonte Brazil 12 131 10,9
Madrid Spain 9 125 13,9
Budapest Hungary 14 123 8,8
Tokyo Japan 31 116 3,7
Mountain View United States 2 109 54,5

We can observe, that there are locations with a high number of access points and also a high number of networks, but like in the case of Moscow or São Paulo, the relationship between the number of networks vs. number of access points is very high. A notable case is Tokyo, where 116 ISPs for 31 Cache Access Points were observed, giving a ratio of only 3,7.

It has to be taken into account that many access points are dedicated to different segments, for example, if we look at Berlin, Germany we will see that Vodafone and Telefonica Germany have their own dedicated access points (vodafone-ber1 and hansenet-ber2). On the other side, ber01s12 is probably owned by Deutsche Telekom AG, the biggest Telecom in Germany, which is giving access to other companies through their infrastructure, so we can see Verizon, Kabel Deutschland and also some other Telefonica users go through this other Access Point. Finally, if we observe ecix-ber1 we can see that that point seems to be reserved for Private Business ISPs, like e.discom, WEMACOM, the multimedia specialist MyWire or the private IT Infrastructure provider Macnetix.

Another important fact that has influence on the number of detected networks is our own coverage with ProbeAPI. In cases like Moscow, ProbeAPI has a high number of active probes in Russia, with Moscow having the highest concentration of them. That’s why this data has to be considered a snapshot of Google’s CDN taken with all our available probes at one particular time.

Following the same line, an interesting case is Turkey, where we could detect only one Cache Location, despite of having typically a high concentration of active Probes there. Turkey has been blocking access to Youtube and other Google services intermittently during the last years following political controversies, which could explain the low number of results obtained from a well covered region.


There is much mystery surrounding Google Global Cache which is one of Google’s most important pieces of infrastructure. We were able to gather an impressive number of information with one single measurement of ProbeAPI, which helped us to understand the extent and distribution of Google’s Cache Locations.

Taking into account that this information was made snapshot-like with one sole measurement, we gathered 2383 Cache Instances across 800 locations worldwide (at least) that Google is actively using throughout their partner network operators.

There are still some issues to be covered by more measurements over time which will surely reveal more networks and cache locations. This is one case where continuous monitoring will offer a good opportunity to get thorough measurements, not only in terms of traffic variability, but also in terms of coverage, as probes connect to ProbeAPI through different locations during any period of time.

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