Comparing cloud providers on VM cost

How do you compare two IaaS clouds? Is Amazon EC2’s small standard instance (1 ECU, 1.7GB RAM, 160GB storage) cheaper or is Rackspace cloud’s 256MB server (4 cores, 256MB RAM, 10GB storage) cheaper? It is obviously simpler to compare them if you focus only on one metric. For example, let us assume your application is CPU bound and it does not require much memory at all. Then you should focus solely on the CPU power a cloud VM gives you. We have translated GoGrid, Rackspace, and Terremark‘s VM configurations into their equivalent ECU, so you can simply take a ratio between the cost and the ECU rating and pick the lowest ratio. Unfortunately, real-life applications are never that simple. They demand CPU cycle, memory, as well as hard disk storage capacity. So, how do you compare apple-to-apple?

The methodology

Since no methodology exists yet, we will propose one. Since the comparison results depend highly on the methodology chosen, we first will spell out the methodology we use so that if you have a different one and you come up with a different result, you can trace the source of the difference. If you see areas where we can improve the methodology, please do leave a comment. The methodology works as follows:

1. We first break down the cost components in Amazon EC2. We assume Amazon has priced their instances using a linear model, i.e., the cost is equal to c * CPU + m * Mem + s * Storage, where c is the unit cost of CPU per ECU per hour, m is the unit cost of memory per GB per hour, and s is the unit cost of storage per GB per hour. Amazon provides several types of instances, each with a different combination of CPU, memory and storage, which is enough of a hint for us to use regression analysis to estimate c, m and s. The details are in our ECU cost breakdown analysis.
2. Once we have the unit cost in EC2, we can compare it with another cloud provider. We take one VM configuration from a cloud provider at a time, we then compute what Amazon EC2 would charge for an instance with the exact same specification if EC2 were to offer it. This can be easily done by multiplying the EC2 unit costs (c, m, and s) with the amount of CPU, RAM, and storage in the VM, and add them up. Of course, this is hypothetical, because EC2 does not offer an instance with an exact same spec. So even if the EC2 price is lower, you cannot just buy a substitute from Amazon. However, this gives us a good sense of the relative cost.

We have done the analysis with GoGrid, Rackspace, and Terremark.

We can compute a ratio between a cloud VM’s cost with its hypothetical equivalent in EC2. The following lists the top few VMs that have the lowest ratio. If you are curious about the ratio for other VM configurations, feel free to dig into the individual posts on each provider. The ratio listed is assuming that you will get the maximum CPU allowed under bursting, which is frequently the case in those cloud providers. Further, the ratio listed is comparing with EC2 N. Virginia data center. Other EC2 data centers have a higher cost.

Provider	RAM (GB)	CPU (cores)	storage (GB)	cost ratio with an equivalent in EC2
Rackspace	0.25	4	10	0.168
Terremark	0.5	8	charged separately at $0.25/month/GB	0.19
Rackspace	0.5	4	20	0.314
Terremark	0.5	4	charged separately at $0.25/month/GB	0.338
Terremark	1	8	charged separately at $0.25/month/GB	0.375
Terremark	1.5	8	charged separately at $0.25/month/GB	0.491

 

How to use this data?

Due to the limitations of this methodology (comparing with a hypothetical equivalent in EC2), it only makes sense if one of the cloud provider you are comparing is Amazon EC2. In other words, do not compare Rackspace with Terremark based on the ratio.

It also makes no sense to use our results if you know the exact specification for your server. In that case, you should find a minimum VM configuration that is just barely bigger than your requirement and compare price.

Our results are useful if your application is flexible. For example, instead of using one m1.small instance in EC2, you could use several Rackspace 256MB VMs to achieve a dramatic cost savings. Examples of a flexible application include a batch application, such as a MapReduce job, which could be chopped down to a finer granularity. Another example could be web servers in a web server farm, where the load balancer can divide up the work to take advantage of whatever computation capacity provisioned on the web server.

Our results are also useful if you want to get a high level overview. Consider an enterprise purchaser who wants to choose a cloud platform. There are many dimensions he has to consider, e.g., features, cost, SLA, contract terms….. Doing a deep analysis at the beginning is just going to be overwhelming. Since Amazon is a big player in cloud, it most likely will be part of the evaluation. Having a ratio would give a ten-thousand-feet view such that the decision maker would know whether an alternative cloud would save him money. Then, as the evaluation progresses, he can dig deeper into a finer comparison.

Caveats:

There are many caveats in using our results that we should spell out.

• This is only comparing a VM cost, including its CPU, memory and storage. But, it does not include other costs, such as bandwidth transfers. The bandwidth cost varies wildly, for example, GoGrid offers free inbound traffic, which can translate into a significant cost saving.

• When we compare CPUs, we are only comparing their processing power, not their IO capabilities (both disk and network IO). In Amazon, we sometimes observe degraded IO performance, possibly due to competing VMs on the same host. It is a sad side effect of using popular cloud offerings.

• As we mentioned, this only applies to fungible applications that can take full advantage of provisioned CPU, memory and storage resources. For example, if you cannot take advantage of the provisioned RAM, it does not matter if it is a good deal. You are wasting the memory, and you may be better off with a VM configuration from a different cloud provider with a smaller provisioned RAM.

• This is not a substitute for feature comparisons. For example, GoGrid offers free F5 hardware load balancer. If you need a hardware load balancer, you should consider that separately.

Terremark cost comparison with Amazon EC2

(Earlier posts in this series are: EC2 cost break down, GoGrid & EC2 cost comparison, Rackspace & EC2 cost comparison)

In this post, let us compare the VM cost between Terremark vCloud express and Amazon EC2. Terremark is one of the first cloud providers based on VMWare technology. Unlike EC2, Rackspace and GoGrid, which use Xen as the hypervisor, Terremark uses VMWare’s ESX hypervisor, which arguably is richer in functionality.

Following the methodology we have used so far, we need to first understand Terremark’s hardware infrastructure and its resource allocation policy. Using the same technique we used for EC2’s hardware analysis, we determine that Terremark runs on a platform with two sockets of Quad-core AMD Opteron 8389 processors. PassMark does not have a benchmark result for this processor, so we have to run the benchmark ourselves. We used the 16GB+8VPU configuration — its largest — to minimize interference from other VMs, and we run it multiple times late at night to ensure that we are indeed measuring the underlying hardware’s capacity. On average, the PassMark CPU mark result is 7100, which is roughly 18 ECU.

Terremark uses the ESX hypervisor’s default policy for scheduling CPU, i.e., a core shares the CPU equally with another core regardless of how much memory the VM has. This is different from GoGrid and Rackspace where the CPU is shared proportional to the amount of RAM a VM has. The scheduling policy can be verified by reading the GuestSDK API exposed by VMTools. By reading the API, we know that a VM not only has no minimum guaranteed CPU, but it also does not have a maximum burst limit. Each virtual core of a VM is assigned a CPU share of 1000, regardless of the memory it is allocated. Thus, the more cores a VM has, the more shares of the CPU it will get (e.g., 1VPU has 1000 shares, and 8VPU has 8000 shares).

It is difficult to determine how many VMs could be on a physical host, which determines the minimum guaranteed CPU. We are told in their forum that each physical host has 128GB of memory, which can accommodate at least 8 VMs, for example, each with 8 VPU+16GB RAM (its largest configuration). VMWare ESX hypervisor allows over-committing memory, so in theory, there could be many more VMs on a host. When we launched a vanilla 512MB VM, we learned from the Guest API that our VM only occupied 148MB RAM. Clearly, there is lots of room to over-commit, even though we see no evidence that they are doing so. Assuming there is no over-commitment, there still could be a lot of VMs competing for the CPU. In the worst case, all VMs on the host have 512MB RAM and 8VPU, which consume the least memory, but gain the maximum CPU weights. A physical host can host 256 such VMs, leaving a negligible CPU share for each VM. If a VM has only one core, it owns only 1/(8*256) share of the CPU, and an 8 VPU (8 virtual cores) VM owns only 1/256 share of the CPU.

Following what we did to get EC2’s unit cost, we can run regression analysis to estimate Terremark’s unit cost. We assume the Cost = c * CPU + m * RAM (Terremark charges storage separately from the VM cost at $0.25/GB/month). The regression determines the unit cost to be

c = 2.06 cents/VPU/hour
m = 6.46 cents/GB/hour

The regression result does not fit the real cost very well. The following table shows both the original cost (color green) and the cost as determined by the estimated parameters (color red) for the various VM configurations.

memory (GB)\CPU	1 VPU	2 VPU	4 VPU	8 VPU
0.5	3.5 / 5.29	4 / 7.36	4.5 / 11.48	5 / 19.72
1	6 / 8.53	7 / 10.6	8 / 14.7	10 / 23
1.5	9 / 11.8	10.5 / 13.8	12 / 17.9	13.6 / 26.2
2	12 / 15	14.1 / 17	16.1 / 21.2	20.1 / 29.4
4	24.1 / 27.9	28.1 / 30	30.1 / 34.1	40.2 / 42.4
8	40.2 / 53.8	48.2 / 55.8	60.2 / 60	80.3 / 68.2
12	60.2 / 79.6	72.3 / 81.7	90.3 / 85.8	120.5 / 94.1
16	80.3 / 105.5	96.4 / 107.5	120.5 / 111.7	160.6 / 112

The reason that the regression analysis does not work well here is that Terremark heavily discounts both CPU and RAM as you move up in the configuration. Our linear model does not capture the economy of scale very well. However, we can think of the linear regression as a trend line, and the trend line indicates that Terremark is likely more expensive than EC2. For example, it costs 6.46 cents/GB/hour for its RAM, which is much higher than the 2.01 cents Amazon values its RAM at.

Another way to compare cost is to use EC2’s unit cost to figure out what an equivalent configuration will cost in EC2. The following table shows the cost comparison where we assume you can only get the minimum CPU at the worst case, where all other VMs are busy and a physical host is fully loaded with 8VPU+0.5GB VMs (without over-commitment). Each row shows the RAM and CPU configuration, Terremark’s price, what it would cost in EC2, and the ratio between Terremark and EC2 cost.

memory (GB)	VPU	Terremark price (cents/hour)	Equivalent EC2 cost (cents/hour)	Terremark cost/EC2 cost
0.5	1	3.5	1.02	3.44
0.5	2	4	1.03	3.89
0.5	4	4.5	1.05	4.27
0.5	8	5	1.10	4.54
1	1	6	2.02	2.97
1	2	7	2.03	3.44
1	4	8	2.06	3.89
1	8	10	2.11	4.75
1.5	1	9	3.03	2.97
1.5	2	10.5	3.04	3.45
1.5	4	12	3.06	3.92
1.5	8	13.6	3.11	4.37
2	1	12	4.03	2.98
2	2	14.1	4.05	3.49
2	4	16.1	4.07	3.96
2	8	20.1	4.12	4.88
4	1	24.1	8.06	2.99
4	2	28.1	8.07	3.48
4	4	30.1	8.09	3.72
4	8	40.2	8.14	4.94
8	1	40.2	16.1	2.5
8	2	48.2	16.11	2.99
8	4	60.2	16.13	3.73
8	8	80.3	16.18	4.96
12	1	60.2	24.14	2.49
12	2	72.3	24.15	2.99
12	4	90.3	24.18	3.73
12	8	120.5	24.23	4.97
16	1	80.3	32.18	2.49
16	2	96.4	32.2	2.99
16	4	120.5	32.22	3.74
16	8	160.6	32.27	4.98

The table shows that Terremark is 2.49 to 4.98 times more expensive than an equivalent in EC2. This is mainly due to the way Terremark shares CPUs. A 0.5GB VM in Terremark shares the CPU equally with a 16GB VM; thus, in the worst case, a VM may get very little CPU. Since Terremark does not set a minimum guarantee on the CPU share in the hypervisor, we have to assume the worst case.

In reality, you are unlikely to encounter the worst case, and you are very likely to get the full attention of a physical core. The reason is not only because the majority of VMs have more than 0.5GB (so that you can pack fewer of them on a host), but also because Terremark uses VMWare’s DRS (Distributed Resource Scheduler). We have noticed that, when we drive up the load on our VMs, our VMs are often moved (through VMotion) to a different host, presumably to avoid contention. Thus, unless the whole cluster gets really busy, it is unlikely that your VM would have a lot of other busy VMs to contend with on the same host. The following table shows the EC2 equivalent cost assuming a virtual core can get the full power of the physical core.

memory (GB)	VPU	Terremark price (cents/hour)	Equivalent EC2 cost (cents/hour)	Terremark cost/EC2 cost
0.5	1	3.5	4.09	0.86
0.5	2	4	7.17	0.56
0.5	4	4.5	13.33	0.34
0.5	8	5	25.65	0.19
1	1	6	5.09	1.18
1	2	7	8.17	0.86
1	4	8	14.33	0.56
1	8	10	26.66	0.38
1.5	1	9	6.1	1.48
1.5	2	10.5	9.18	1.14
1.5	4	12	15.34	0.78
1.5	8	13.6	27.66	0.49
2	1	12	7.1	1.69
2	2	14.1	10.18	1.38
2	4	16.1	16.35	0.98
2	8	20.1	28.67	0.7
4	1	24.1	11.12	2.17
4	2	28.1	14.21	1.98
4	4	30.1	20.37	1.48
4	8	40.2	32.69	1.23
8	1	40.2	19.17	2.1
8	2	48.2	22.25	2.17
8	4	60.2	28.41	2.12
8	8	80.3	40.73	1.97
12	1	60.2	27.21	2.21
12	2	72.3	30.29	2.39
12	4	90.3	36.45	2.48
12	8	120.5	48.78	2.47
16	1	80.3	35.25	2.28
16	2	96.4	38.33	2.51
16	4	120.5	44.5	2.71
16	8	160.6	56.82	2.83

There are several configurations where Terremark is much cheaper than EC2. The 8VPU+0.5GB configuration is the cheapest at 19% of the equivalent EC2 cost. This is due to two reasons. First, the 8 VPU has more scheduling weight, and it can compete for the full power of the physical host. Second, the RAM is the smallest. As we have seen, Terremark values RAM more than EC2 does (m=6.46 cents/GB/hour vs. EC2 m=2.01 cents/GB/hour), so the less RAM a configuration has, the lower the cost. The cost savings go away as you add more RAM and more CPU to the configuration.

Rackspace cost comparison with Amazon EC2

(Earlier posts in this series are: EC2 cost break down, GoGrid & EC2 cost comparison)

We looked at Amazon EC2 and GoGrid cost earlier. Let us examine another IaaS provider — Rackspace cloud. The first step again is to unify on the same unit of measurement on the CPU power. Using the same methodology as we used for EC2’s hardware analysis, we determine that Rackspace runs on a platform with two sockets of Quad-Core AMD Opteron 2374 HE processor. According to PassMark-CPU Mark results, this platform has a CPU mark score of 4642, which is roughly 12 ECU. Rackspace cloud’s FAQ states that “For Linux distributions, each Cloud Server is assigned four virtual cores and the amount of CPU cycles allocated to these cores is weighted based on the size of the Cloud Server.” From talking to Rackspace support, we know that each physical host has 32GB of RAM, and it can host at most 2 16GB (15.5GB to be precise) VMs. Therefore, a 16GB VM would own the complete 4 cores it is allocated, i.e., the 16GB VM has a guaranteed capacity of half of the platform, which is 6 ECU. Since Rackspace states that the CPU is proportionally shared based on the RAM, we can derive the minimum guaranteed CPU based on how many other VMs could fit on the same physical host. The following table lists the minimum CPU and the maximum CPU (assuming full bursting when all other VMs are idle). Again, we are only concerned about Linux VMs, as they do not include license costs, so they more accurately represent the true hardware cost.

RAM (GB)	Storage (GB)	Min CPU (ECU)	Max CPU (ECU)	Cost (cents/hour)
0.256	10	0.09375	6	1.5
0.512	20	0.1875	6	3
1	40	0.375	6	6
2	80	0.75	6	12
4	160	1.5	6	24
8	320	3	6	48
16	620	6	6	96

Similar to GoGrid, Rackspace only charges based on the RAM, so it is not possible to determine how it values each component (i.e., CPU, RAM and storage) separately, as we have done for EC2. However, it is possible to project what a similar configuration would cost in EC2 using the unit cost we have derived from the EC2 cost breakdown. The results are shown in the following table where we assume a VM only gets its minimum guaranteed CPU. Each row corresponds to one VM configuration, which is denoted by its RAM size in the first column. We also show the ratio between the Rackspace cost and the projected equivalent EC2 cost.

RAM (GB)	Rackspace cost (cents/hour)	Equivalent EC2 cost (cents/hour)	Rackspace cost/EC2 cost
0.256	1.5	0.8	1.87
0.512	3	1.6	1.87
1	6	3.16	1.9
2	12	6.32	1.9
4	24	12.6	1.9
8	48	25.3	1.9
16	96	50.2	1.91

Since a Rackspace VM can burst if other VMs on the same host are idle, it could potentially grab a much larger share of the CPU. The following table shows the cost comparison assuming that the VM bursts to its fullest extent.

RAM (GB)	Rackspace cost (cents/hour)	Equivalent EC2 cost (cents/hour)	Rackspace cost/EC2 cost
0.256	1.5	8.89	0.17
0.512	3	9.56	0.31
1	6	10.86	0.55
2	12	13.5	0.89
4	24	18.8	1.28
8	48	29.4	1.63
16	96	50.2	1.91

If your VM is only getting the minimum guaranteed CPU, Rackspace is about 1.9 times more expensive than an equivalent in EC2. However, in our experience, we can frequently grab a much larger share of the CPU. Assuming you can grab the full 4 cores, the 256MB, 512MB, 1GB, and 2GB VMs are a great bargain, which are 17%, 31%, 55%, and 89% of the equivalent EC2 cost respectively.

GoGrid cost comparison with Amazon EC2

updated 1/30/2011 to include our own PassMark benchmark result and include GoGrid’s prepaid plan. Then updated 2/1/2011 to include cost/ECU comparison and clarifications.

(Other posts in the series are: EC2 cost break down, Rackspace & EC2 cost comparison, Terremark and EC2 cost comparison).

Continue on our series on cost comparison between IaaS cloud providers, we will look at GoGrid’s cost structure in this post. It is easier to compare RAM and storage apple-to-apple because all cloud providers standardize on the same unit, e.g., GB. To have a meaningful comparison on CPU, we must similarly standardize on a common unit of measurement. Unfortunately, the cloud providers do not make this easy, so we have to do the conversion ourselves.

Because Amazon is a popular cloud provider, we decide to standardize on its unit of measurement — the ECU (Elastic Compute Unit). In our EC2 hardware analysis, we concluded that an ECU is equivalent to a PassMark-CPU Mark score of roughly 400. We have run the benchmark in Amazon’s N. Virginia data center on several types of instances to verify experimentally that the CPU Mark score does scale linearly as the instance’s advertised ECU rating.

All we need to do now is to figure out GoGrid’s PassMark-CPU Mark number. This is easy to do if we know the underlying hardware. Following the same methodology we used for the EC2 hardware analysis, we find that the GoGrid infrastructure consists of two types of hardware platform: one with dual-socket Intel E5520 processors, another with dual-socket Intel X5650 processors. According to PassMark-CPU mark results, we know the dual-socket E5520 has a score of 9,174 and the dual-socket X5650 has a score of 15,071. GoGrid enables hyperthreading, so the dual-socket E5520 platform has 16 cores, and the dual-socket X5650 platform has 24 cores. Hyperthreading does not really double the performance because there is still only one physical core which is hardware-threaded by two virtual cores.

Instead of relying on PassMark’s reported result, we also run the benchmark ourselves to get a true measure of performance. We run the benchmark late at night for several times to make sure that the result is stable and that we are getting the maximum CPU allowed by bursting. PassMark benchmark only runs on Windows OS, and in Windows, we can only see up to 8 cores. As a result, the 8GB(8cores) and 16GB(8cores) VMs both return a CPU mark result of roughly 7850, which is 19.5 ECU. The 4GB(4cores) VM returns a CPU mark result of roughly 3,800, which is 9.6 ECU. And, the 2GB(2cores) VM returns a CPU mark of roughly 1,900, which is 4.8 ECU. Since there are no 1GB(1core) or 0.5GB(1core) Windows VM, we project their maximum CPU power to be half of a 2-core VM at 2.4 ECU. Lastly, since we cannot measure the 16 cores performance, we use the reported E5520 benchmark result of 9174 from PassMark instead as its maximum, which is 23 ECU. These numbers determine the maximum CPU when bursting full. Based on GoGrid’s VM configuration, we can then determine the minimum guaranteed CPU from maximum CPU.

The translation from GoGrid’s CPU allocation to an equivalent ECU is shown in the following table. Each row of the table corresponds to one GoGrid’s VM configuration, where we list the amount of CPU, RAM and storage in each configuration. We also list GoGrid’s current pay-as-you-go VM price as the last column for reference.

Min CPU (cores)	Min CPU (ECU)	Max CPU (cores)	Max CPU (ECU)	RAM (GB)	Storage (GB)	pay-as-you-go Cost (cents/hour)
0.5	1.2	1	2.4	0.5	25	9.5
1	2.4	1	2.4	1	50	19
1	2.4	2	4.8	2	100	38
3	7.2	4	9.6	4	200	76
6	14.4	8	19.2	8	400	152
8	19.2	16	23	16	800	304

One way to compare GoGrid and EC2 is to purely look at the cost per ECU. The following table shows the cost/ECU for GoGrid VMs assuming all of them get the maximum possible CPU. We list two cost/ECU results, one based on their pay-as-you-go price of $0.19/RAM-hour, another based on their Enterprise cloud prepaid plan of $0.05/RAM-hour.

RAM (GB)	Max CPU (ECU)	pay-as-you-go cost/ECU (cents/ECU/hour)	prepaid cost/ECU (cents/ECU/hour)
0.5	2.4	3.96	1.04
1	2.4	7.91	2.08
2	4.8	7.91	2.08
4	9.6	7.91	2.08
8	19.2	7.91	2.08
16	23	13.2	3.48

In comparison, the following table shows EC2 cost/ECU for the nine different types of instances in the N. Virginia data center.

instance	CPU (ECU)	RAM (GB)	cost/ECU (cents/ECU/hour)
m1.small	1	1.7	8.5
m1.large	4	7.5	8.5
m1.xlarge	8	15	8.5
t1.micro	0.35	0.613	5.71
m2.xlarge	6.5	17.1	7.69
m2.2xlarge	13	34.2	7.69
m2.4xlarge	26	68.4	7.69
c1.medium	5	1.7	3.4
c1.xlarge	20	7	3.4

Comparing on cost/ECU only makes sense when your application is CPU bound, i.e., your memory requirement is always less than what the instance gives you.

Here, we propose a different way, comparing them by taking into account the CPU, the RAM and storage allocation altogether. Ideally, if we can derive the unit cost of each, we can straightforwardly compare. Unfortunately, GoGrid charges purely based on RAM hours, it is not possible to figure out how it values CPU, RAM and storage separately, like we have done for Amazon EC2. If we do a regression analysis, the result will show that CPU and storage cost nothing, and RAM bears all the cost.

Since we cannot compare the unit cost, we propose a different approach. Basically, we take one VM configuration from GoGrid, and try to figure out what a hypothetical instance with the exact same specification would cost in EC2 if Amazon were to offer it. We can project what EC2 would charge for such a hypothetical instance because we know EC2’s unit cost from our EC2 cost break down.

The following table shows what a VM will cost in EC2 if the same configuration is offered there, assuming we only get the minimum guaranteed CPU. Each row of the table corresponds to one GoGrid VM configuration, where we only list the RAM size for that configuration (see the previous table for a configuration’s CPU and storage size). We also show the ratio between the GoGrid pay-as-you-go price and the projected EC2 cost.

RAM (GB)	GoGrid pay-as-you-go cost (cents/hour)	Equivalent EC2 cost (cents/hour)	GoGrid cost/hypothetical EC2 cost
0.5	9.5	3.05	3.12
1	19	6.09	3.12
2	38	8.9	4.27
4	76	21.1	3.6
8	152	42.2	3.6
16	304	71.2	4.27

Unlike EC2, other cloud providers, including GoGrid, all allow a VM to burst beyond their minimum guaranteed capacity if there are free cycles available. The following table compares the cost under the optimistic scenario where you get the maximum CPU possible.

RAM (GB)	GoGrid pay-as-you-go cost (cents/hour)	Equivalent EC2 cost (cents/hour)	GoGrid cost/EC2 cost
0.5	9.5	4.69	2.03
1	19	6.1	3.12
2	38	12.2	3.12
4	76	24.4	3.12
8	152	48.7	3.12
16	304	76.4	3.98

As Paul from GoGrid pointed out, GoGrid also offers a prepaid plan that is significantly cheaper than the pay-as-you-go plan. This is different from Amazon’s reserved instance where you get a discount if you pay an up-front fee. Although cheaper, Amazon’s reserved instance pricing only applies to that one instance you reserved, and when you need to dynamically scale, you cannot benefit from the lower price. GoGrid’s prepaid plan allows you to use the discount on any instances. To see the benefits of buying bulk, we also compare EC2 cost with GoGrid’s Enterprise Cloud prepaid plan, which costs $9,999 a month, but entitles you to 200,000 RAM hours at $0.05/hour. For brevity, we do not compare with other prepaid plans, which you can easily do yourself following our methodology.

The following table shows what a VM will cost in EC2 if the same configuration is offered there, assuming we only get the minimum guaranteed CPU.

RAM (GB)	GoGrid Enterprise cloud pre-paid cost (cents/hour)	Equivalent EC2 cost (cents/hour)	GoGrid cost/EC2 cost
0.5	2.5	3.05	0.82
1	5	6.09	0.82
2	10	8.9	1.12
4	20	21.1	0.95
8	40	42.2	0.95
16	80	71.2	1.12

The following table compares the cost under the optimistic scenario where you get the maximum CPU possible.

RAM (GB)	GoGrid enterprise cloud pre-paid cost (cents/hour)	Equivalent EC2 cost (cents/hour)	GoGrid cost/EC2 cost
0.5	2.5	4.69	0.53
1	5	6.1	0.82
2	10	12.2	0.82
4	20	24.4	0.82
8	40	48.7	0.82
16	80	76.4	1.05

Under GoGrid’s pay-as-you-go plan, we can see that GoGrid is 2 to 4 times more expensive than a hypothetical instance in EC2 with an exact same specification. However, if you can buy bulk, the cost is significantly lower. The smaller 0.5GB server could be as cheap as 53% of the cost of an equivalent EC2 instance.