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any45 says...

Pricing

Pay only for what you use. There is no minimum fee. Estimate your monthly bill using AWS Simple Monthly Calculator. The prices listed are based on the Region in which your instance is running.

On-Demand Instances

On-Demand Instances let you pay for compute capacity by the hour with no long-term commitments. This frees you from the costs and complexities of planning, purchasing, and maintaining hardware and transforms what are commonly large fixed costs into much smaller variable costs.

The pricing below includes the cost to run private and public AMIs on the specified operating system. Amazon also provides you with additional instances with other option for Amazon EC2 running Microsoft and Amazon EC2 running IBM that are priced differently.

United States
 
Europe
 
Standard On-Demand Instances Linux/UNIX Usage Windows Usage
Small (Default) $0.085 per hour $0.12 per hour
Large $0.34 per hour $0.48 per hour
Extra Large $0.68 per hour $0.96 per hour
High-Memory On-Demand Instances Linux/UNIX Usage Windows Usage
Double Extra Large $1.20 per hour $1.44 per hour
Quadruple Extra Large $2.40 per hour $2.88 per hour
High-CPU On-Demand Instances Linux/UNIX Usage Windows Usage
Medium $0.17 per hour $0.29 per hour
Extra Large $0.68 per hour $1.16 per hour
United States
 
Europe
 
Standard On-Demand Instances Linux/UNIX Usage Windows Usage
Small (Default) $0.095 per hour $0.13 per hour
Large $0.38 per hour $0.52 per hour
Extra Large $0.76 per hour $1.04 per hour
High-Memory On-Demand Instances Linux/UNIX Usage Windows Usage
Double Extra Large $1.34 per hour $1.58 per hour
Quadruple Extra Large $2.68 per hour $3.16 per hour
High-CPU On-Demand Instances Linux/UNIX Usage Windows Usage
Medium $0.19 per hour $0.31 per hour
Extra Large $0.76 per hour $1.24 per hour

Pricing is per instance-hour consumed for each instance type, from the time an instance is launched until it is terminated. Each partial instance-hour consumed will be billed as a full hour.

Reserved Instances

Reserved Instances give you the option to make a low, one-time payment for each instance you want to reserve and in turn receive a significant discount on the hourly usage charge for that instance. After the one-time payment for an instance, that instance is reserved for you, and you have no further obligation; you may choose to run that instance for the discounted usage rate for the duration of your term, or when you do not use the instance, you will not pay usage charges on it.

United States
 
Europe
 
Linux/UNIX One-time Fee  
Standard Reserved Instances 1 yr Term 3 yr Term Usage
Small (Default) $227.50 $350 $0.03 per hour
Large $910 $1400 $0.12 per hour
Extra Large $1820 $2800 $0.24 per hour
High-Memory Reserved Instances 1 yr Term 3 yr Term Usage
Double Extra Large $3185 $4900 $0.42 per hour
Quadruple Extra Large $6370 $9800 $0.84 per hour
High-CPU Reserved Instances 1 yr Term 3 yr Term Usage
Medium $455 $700 $0.06 per hour
Extra Large $1820 $2800 $0.24 per hour
United States
 
Europe
 
Linux/UNIX One-time Fee  
Standard Reserved Instances 1 yr Term 3 yr Term Usage
Small (Default) $227.50 $350 $0.04 per hour
Large $910 $1400 $0.16 per hour
Extra Large $1820 $2800 $0.32 per hour
High-Memory Reserved Instances 1 yr Term 3 yr Term Usage
Double Extra Large $3185 $4900 $0.56 per hour
Quadruple Extra Large $6370 $9800 $1.12 per hour
High-CPU Reserved Instances 1 yr Term 3 yr Term Usage
Medium $455 $700 $0.08 per hour
Extra Large $1820 $2800 $0.32 per hour

Reserved Instances can be purchased for 1 or 3 year terms, and the one-time fee per instance is non-refundable. Usage pricing is per instance-hour consumed. Instance-hours are billed for the time that instances are in a running state; if you do not run the instance in an hour, there is zero usage charge. Partial instance-hours consumed are billed as full hours.

Reserved Instances are currently available for Linux/UNIX operating systems. Click here to learn more about Reserved Instances.


Data Transfer

Internet Data Transfer

The pricing below is based on data transferred "in" and "out" of Amazon EC2.

Data Transfer In  
All Data Transfer $0.10 per GB

Data Transfer Out  
First 10 TB per Month $0.17 per GB
Next 40 TB per Month $0.13 per GB
Next 100TB per Month $0.11 per GB
Over 150 TB per Month $0.10 per GB

Data transferred between two Amazon Web Services within the same region (i.e. between Amazon EC2 US and another AWS service in the US, or between Amazon EC2 Europe and another AWS service in Europe) is free of charge (i.e., $0.00 per GB). Data transferred between AWS services in different regions will be charged as Internet Data Transfer on both sides of the transfer.

Usage for other Amazon Web Services is billed separately from Amazon EC2.

Availability Zone Data Transfer

  • $0.00 per GB – all data transferred between instances in the same Availability Zone using private IP addresses.

Regional Data Transfer

  • $0.01 per GB in/out – all data transferred between instances in different Availability Zones in the same region.

Public and Elastic IP and Elastic Load Balancing Data Transfer

  • $0.01 per GB in/out – If you choose to communicate using your Public or Elastic IP address or Elastic Load Balancer inside of the Amazon EC2 network, you’ll pay Regional Data Transfer rates even if the instances are in the same Availability Zone. For data transfer within the same Availability Zone, you can easily avoid this charge (and get better network performance) by using your private IP whenever possible.

See Availability Zones for tools to describe instance location.

Amazon Elastic Block Store

United States
 
Europe
 
Amazon EBS Volumes
  • $0.10 per GB-month of provisioned storage
  • $0.10 per 1 million I/O requests
Amazon EBS Snapshots to Amazon S3 (priced the same as Amazon S3)
  • $0.15 per GB-month of data stored
  • $0.01 per 1,000 PUT requests (when saving a snapshot)
  • $0.01 per 10,000 GET requests (when loading a snapshot)
United States
 
Europe
 
Amazon EBS Volumes
  • $0.11 per GB-month of provisioned storage
  • $0.11 per 1 million I/O requests
Amazon EBS Snapshots to Amazon S3 (priced the same as Amazon S3)
  • $0.18 per GB-month of data stored
  • $0.012 per 1,000 PUT requests (when saving a snapshot)
  • $0.012 per 10,000 GET requests (when loading a snapshot)

Elastic IP Addresses

No cost for Elastic IP addresses while in use

  • $0.01 per non-attached Elastic IP address per complete hour
  • $0.00 per Elastic IP address remap – first 100 remaps / month
  • $0.10 per Elastic IP address remap – additional remap / month over 100

Amazon CloudWatch

United States
 
Europe
 
Amazon EC2 Monitoring
  • $0.015 per instance-hour (or partial hour)
United States
 
Europe
 
Amazon EC2 Monitoring
  • $0.015 per instance-hour (or partial hour)

Auto Scaling

Auto Scaling is enabled by Amazon CloudWatch and carries no additional fees. Each instance launched by Auto Scaling is automatically enabled for monitoring and the Amazon CloudWatch monitoring charge will be applied.

Elastic Load Balancing

United States
 
Europe
 
  • $0.025 per Elastic Load Balancer-hour (or partial hour)
  • $0.008 per GB of data processed by an Elastic Load Balancer
United States
 
Europe
 
  • $0.028 per Elastic Load Balancer-hour (or partial hour)
  • $0.008 per GB of data processed by an Elastic Load Balancer

(Amazon EC2 is sold by Amazon Web Services LLC.)

Filed under: cloud

any45 says...

Windows Azure

  • Compute = $0.12 / hour
  • Storage = $0.15 / GB stored / month
  • Storage transactions = $0.01 / 10K
  • Data transfers = $0.10 in / $0.15 out / GB - ($0.30 in / $0.45 out / GB in Asia)

Windows Azure Service Level Agreement
For compute, we guarantee that when you deploy two or more role instances in different fault and upgrade domains, your internet facing roles will have external connectivity at least 99.95% of the time. For storage, we guarantee that at least 99.9% of the time we will successfully process correctly formatted requests that we receive to add, update, read and delete data. More information on Service Level Agreements.


Measuring Windows Azure Consumption

  • Compute time, measured in service hours: Windows Azure compute hours are charged only for when your application is deployed. When developing and testing your application, developers will want to remove the compute instances that are not being used to minimize compute hour billing.
  • Storage, measured in GB: Storage is metered in units of average daily amount of data stored (in GB) over a monthly period. For example, if a user uploaded 30GB of data and stored it on Windows Azure for a day, her monthly billed storage would be 1 GB. If the same user uploaded 30GB of data and stored it on Windows Azure for an entire billing period, her monthly billed storage would be 30GB. Storage is also metered in terms of storage transactions used to add, update, read and delete storage data. These are billed at a rate of $0.01 for 10,000 (10k) transaction requests
  • Data transfers measured in GB (transmissions to and from the Windows Azure datacenter): Data transfers are charged based on the total amount of data going in and out of the Azure services via the internet in a given 30-day period. Data transfers within a datacenter are free.
  • Transactions, measured as application requests.

SQL Azure

  • Web Edition:  Up to 1 GB relational database = $9.99 / month
  • Business Edition:  Up to 10 GB relational database = $99.99 / month
  • Data transfers = $0.10 in / $0.15 out / GB - ($0.30 in / $0.45 out / GB in Asia)

SQL Azure Service Level Agreement
SQL Azure customers will have connectivity between the database and our internet gateway. SQL Azure will maintain a “Monthly Availability” of 99.9% during a calendar month. More information on Service Level Agreements.


Measuring SQL Azure Consumption

Web Edition Relational Database includes:

  • Up to 1 GB of T-SQL based relational database
  • Self-managed DB, auto high availability
  • Best suited for Web application, Departmental custom apps.

Business Edition DB includes:

  • Up to 10 GB of T-SQL based relational database
  • Self-managed DB, auto high availability
  • Additional features in the future like auto-partition, CLR, fanouts etc.
  • Best suited for ISVs packaged LOB apps, Department custom apps

We charge a monthly fee for each SQL Azure database, but we amortize that database fee over the month and charge you on a daily basis. You pay for the databases you have, on the days you have them.

Windows Azure Platform AppFabric

  • Messages = $0.15/100K message operations, including Service Bus messages, Access Control transactions and service management operations
  • Data transfers = $0.10 in / $0.15 out / GB - ($0.30 in / $0.45 out / GB in Asia)

AppFabric Service Level Agreement
Uptime percentage commitments and SLA credits for AppFabric are similar to those specified in the Windows Azure SLA. More information on Service Level Agreements


Measuring AppFabric Consumption

Messages (Includes Access Control, Orchestration, and Reliable Queuing for messages): AppFabric allows developers to easily connect their cloud applications and databases with existing software assets and users through the exchange of messages. Customers will pay only for the number of message operations that their applications use. The definition of a “message operation” includes Service Bus messages, Access Control transactions and service management operations. Messages are charged to the customer in discrete blocks of 100,000 (“100k”) for each monthly billing period. For example:

  • A customer who consumed 95,000 messages would be billed for 1x100k messages (plus data transfers to send messages in or out).
  • A customer who uses 150,000 messages in a billing period would be charged for 2x100k messages (plus data transfers to send messages in or out).
  • A customer who uses 20 million messages in a billing period would be charged for 200x100k messages (plus data transfers to send messages in or out).

 

Filed under: cloud

matrax says...

Czy ktoś zna jakąś firmę działającą jedynie na chmurce? Nie chodzi mi nawet o rozwiązanie netowe ale taki lokalny firmowy cloud firma

Filed under: cloud

spruiked says...

I've been invited to participate in the Office 2010 beta test. This is exciting stuff for me. I never get to do this stuff -- well, except Google Wave, I suppose. But this is much more exciting. Microsoft in the Cloud. Sounds like a Mills and Boon novel...

Filed under: cloud

Daniel says...

Legal Implications of Cloud Computing -- Part Three (Relationships in the Cloud)

While there is much debate on the IT side as to whether Cloud computing is revolutionary, evolutionary or “more of the same” with a snazzy marketing label, in the legal context, Cloud computing does have a potential significant impact on legal risk. Part three of our ongoing Cloud legal series explores the relationships in the Cloud, and the potential legal implications and impacts suggested by them (if you would like, for context, you can read Part One [the Basics and Framing the Issues] and Part Two[Privacy and the Cloud] of the series.

In the legal world, some take the position that Cloud is no different than “outsourcing”.    Unfortunately, making that comparison reveals a misunderstanding of the Cloud and its implications.  It is sort of like saying that running is no different than running shoes. Like “running,” outsourcing is a general term describing an activity. In this case the activity involves organizations offloading certain business processes to third parties. Cloud computing (like “running shoes”) is a “new” method for leveraging existing technologies (and technological improvements that have occurred in the past 20 years) that can be used by outsourcers to provide their services more effectively and cheaply (as running shoes represents a technology that can be used to achieve the activity of running more efficiently).  In other words, one can outsource utilizing a Cloud architecture provided by a third party, or by using a more traditional dedicated third party hosted technology solution. Both are different technologies or methods for achieving the same activity: outsourcing of business processes.

For lawyers analyzing outsourcing to the Cloud the question is whether the technology, operational aspects and various relationships of a given Cloud transaction create new legal issues or exacerbate known legal problems. To illuminate this question, this post explores the relationships that exist between organizations outsourcing in the Cloud (“Cloud Users”) and those providing services in the Cloud. Coincidentally (or maybe not so much) understanding these relationships is crucial for attorneys that need to address legal compliance risk and draft contracts to protect clients entering into the Cloud.

Dark Opaque Storm Clouds or White Fluffy Transparent Clouds?

When it comes to relationships is the Cloud more like a dark storm cloud that one cannot peer into, or is it more like a fluffy, light and transparent cloud that allows one to see what is happening within? Unfortunately, the current forecast in some areas is for dark Clouds that make it difficult for Cloud Users to understand exactly with whom they are dealing and who is storing and processing their data.   Transparency may be elusive and the very nature of the Cloud computing architecture may be the cause of this. In other words, even if an attorney wants to discover who is actually processing their data, the nature of the Cloud may make it very difficult for Cloud providers to provide definitive information on that point. This is in stark contrast to most traditional outsourcing relationships involving a single vendor and dedicated computing resources or software.

Moreover, even if all the Cloud players are known, it may be difficult for Cloud Users to manage and shift responsibility to a party that it has no direct relationship with, and no direct contractual legal rights or remedies. 

In a traditional dedicated outsourcing model (e.g. web or data hosting, ASP model, etc.) organizations often deal with a single service provider that provides computing resources. That service provider typically would own or control the computing resources that support the outsourcing transaction. Oftentimes those computing resources would be dedicated solely to a particular client. To clarify and solidify this one-to-one relationship the outsourcing contract might have a clause prohibiting the use of sub-contractors to provide the services. In terms of legal risk, the organization utilizing the service provider would be able to conduct its due diligence (e.g. privacy compliance, “reasonable security,” etc.) on a single entity. Moreover, the organization would be able to negotiate a contract shifting risk between it and the service provider knowing that the service provider in essence directly “controlled” the risk by virtue of its control of the computing environment. Even in cases where a service provider uses a sub-contractor, in the typical case, the organization could fairly easily discover the identity of that party and perform its due diligence. More rare are instances of generic unidentified sub-contractors, or sub-contractors utilizing sub-sub-contractors.

Relationships in the Cloud: Who is processing my data?

It can be very different in the Cloud (click here to view one version of the Cloud landscape). This is not to say that Cloud relationships are not/cannot involve one-to-one relationships like traditional outsourcing. They can. At the base of the Cloud stack, it would not be unusual for IaSS providers to have direct relationships with some of their end-clients. For example, if an organization contracts directly with Amazon Web Services, a Cloud Platform (Infrastructure as a service – IaaS), to allow the organization to build its computing resources in Amazon’s Cloud, it would have a degree of confidence that it was dealing with the party that directly controlled and was responsible for maintaining the Cloud Platform. However, there are service-oriented organizations (integrators) that will actually help to build computing resources on a particular Cloud Platform. In that case a client would not necessarily have a direct relationship with the Cloud Platform, and yet would be subject to the limitations and problems of the Cloud Platform.

The problem is more prevalent as one moves up the Cloud stack. Companies that offer software as a service (SaaS) may have built their application within a particular Cloud Platform (examples can be found herehereherehere and here). The Cloud User again would typically be dealing solely with the SaaS provider despite the fact that the Cloud User’s data is actually being stored and processed (in part or whole) by the Cloud Platform (at the PaaS or IaaS layer). In fact, it is possible that a particular Saas may actually serve its application on multiple Cloud Platforms. Those Cloud Platforms again are one step removed from the Cloud User and each may pose different legal risks. For example one Cloud Platform may have servers across the globe thereby potentially exposing a Cloud User to multiple privacy laws in various jurisdictions, while another may be purely domestic (thereby limiting the jurisdictions to which it the Cloud User may be exposed). In fact, there may be significant economic incentives for SaaS providers to switch between Cloud Platforms that are more efficient or less expensive (thereby improving the SaaS profit margin).

To make the situation more complex, it is also possible for a particular SaaS to use more than one Cloud Platform for an individual Cloud User client. In these cases, data processing might alternate between multiple Cloud Platforms (either because it provides for better efficiencies or perhaps a particular Cloud Platform provides the SaaS with a better price/profit margin). Again, in the legal context this can be problematic. If a SaaS decides to move processing to a Cloud Platform with weak security for example, it could significantly increase the liability risk of a Cloud User if the platform suffers a security breach. It would be very difficult to perform adequate “due diligence” where data is constantly shifting between multiple Cloud Platforms.

Cloud Service Aggregators

Unfortunately, this may be just the tip of the iceberg. In the foregoing example the Cloud User was at least dealing with a single Cloud SaaS provider on the front end. This would not be the case when dealing with Cloud service aggregators. Aggregators essentially bundle (and possibly integrate) multiple SaaS services into a “single” service (examples of aggregation models are here and here). For example, one could envision an aggregator bundling multiple Cloud SaaS offerings for use by travel agents (you can search for examples of SaaS providers serving industry verticals here). The bundle might include a customer relationship management application, a booking and reservations application, a credit card processing application, a billing platform, an international time zone translator application and an electronic signature/e-commerce application. To the Cloud User this bundle would appear to be a single seamless consolidated application. 

The reality is that each of the applications may be operated or created by separate SaaS providers. It is also possible that each of these SaaS providers might serve their application on a different Cloud Platform. There may be variations in each application in terms of reliability and security. Moreover, as discussed above each SaaS provider might be using multiple Cloud Platform’s and that use may not remain static (e.g. it’s a moving target). While aggregation models appear to be just gaining traction they could become more prominent going forward, and legal and security/privacy impacts of these models need to be carefully scrutinized.

The Legal Conundrum

The scenario described above poses significant legal challenges for Cloud Users’ transactional and compliance counsel (as well as security and privacy professionals). Due diligence and contracting are potentially much more difficult when the Cloud is involved.

In some cases the Cloud User may be two or three levels removed from the organizations actually processing and storing the Cloud User’s data.   For example, without a direct relationship with the lowest level Cloud Providers, organizations will not be able to directly analyze compliance issues around privacy and security compliance and reasonableness. As such Cloud Users will have to somehow confirm that the direct party they are dealing with engaged in proper due diligence. It almost becomes a meta analysis: due diligence might involve a Cloud User analyzing whether a Cloud Provider’s due diligence process itself was adequate. This would likely include receiving any reports or other types of analysis performed by the higher and lower level Cloud Providers.  As discussed below it should also include a review of the contracts the higher layer Cloud Provider has with the level below it. 

Of course it more than two levels are involved or there are multiple service providers or Cloud Platforms involved on a particular level, one must have confidence that each of the players also performed adequate due diligence on the providers it utilizes, and so on. So in essence, the Cloud User would be seeking to somehow validate that the Cloud Provider performed adequate due diligence of the due diligence process of the Cloud providers in the level immediately below it. In essence, the Cloud User would want to see a “Chain of Due Diligence.”   This requires that the providers on each level of the chain think ahead and anticipate the needs of the Cloud provider or Cloud User in the layer immediately above it.

Another example to illustrate the point involves incident response contract terms. What happens when the Cloud transaction involves multiple layers and the lower layer suffers a data security breach exposing the PII of the Cloud User’s data? What happens when the Cloud User needs to implement a litigation hold to preserve data where the data resides in the lowest layer of the Cloud?

In a typical direct outsourcing relationship, the outsourcer and its client would build processes in to address these issues and the contract would provide for particular rights and remedies. While similar contractual rights and obligations may be built into a Cloud transaction, it is not clear how useful they would be when multiple layers are involved. For example, if a SaaS built on a Cloud Platform has itself failed to obtain certain rights and abilities to forensically analyze and preserve data processed in the Cloud Platform, the Cloud User may not be able to adequately build defenses in a security breach context or implement an effective litigation hold (regardless of what the contract between the SaaS and Cloud User provides).

A final example: data retention and destruction policies. What if the SaaS provider is working on a Cloud Platform that creates residual copies of data that the Cloud User has a legal obligation to delete? What if the SaaS provider works with a Cloud Platform that does not have the technology or capability to properly wipe data? Even if the Cloud Platform has these capabilities, what if the SaaS provider has not negotiated for the right to obtain these services? Again, to make this work it is incumbent on the SaaS provider to anticipate the end Cloud User’s needs and to only work with Cloud Platforms (or other Cloud providers) that have the capability (and willingness) to meet those needs.

Conclusion

We are very much at the start of the Cloud computing phenomenon, and luckily we have an opportunity to proactive identify and attack these issues now. However, it appears that Cloud is gaining significant momentum and time is running short to address these matters.  While the ultimate “solutions” will take time to develop, legal counsel (and the legal community as a whole) should begin developing strategies and approaches for handling Cloud transactions.

A key factor (and crucial first step) in addressing Cloud legal risk for a particular transaction is understanding the relationships of the Cloud. Legal counsel (with a huge assist from IT and security) should consider taking steps to achieve this understanding and limit risk, including without limitation: 

  • Insist on and acheive transparency. Don’t allow the Cloud to be a black-box storm cloud. Identify the Cloud players involved in a transaction, identify where they process the Cloud User’s data, map the data flow between Cloud players and determine whether the Cloud players are static or dynamic (e.g. can/will the Cloud players change in the middle of the contract). Do this early so the organization does not need to play catch-up.
  • Develop due diligence strategies and procedures, and follow and document them. Primary Cloud relationships should be directly scrutinized. Moreover, the due diligence processes of Cloud providers relying on lower layer Cloud providers should be analyzed to determine if they are adequate. Any validations (e.g compliance with standards such as ISO 270001 or SAS 70s II) or relevant reports from the various players should be obtained. The capabilities, limitations and processes of lower layer Cloud providers should be explored to ensure that they can satisfy the Cloud User’s legal obligations and do not pose additional, unanticipated legal risk or obligations.
  • Confirm that Cloud providers have contractual rights to do what you need them to do. Contractually requiring an Cloud aggregator or SaaS provider to retain data, or obtaining the right to audit the security protecting the Cloud User’s data, is meaningless if the aggregator or SaaS itself does not have such rights with respect to lower layer Cloud providers. Cloud Users do not want to find this out when they have a need to exercise their contract rights (e.g. when a regulatory action, privacy breach of lawsuit happens). As such, it is important to analyze the contracts a higher level Cloud provider has with the Cloud providers it relies on to make sure the necessary rights flow through the contract chain.
  • Think Way Ahead – Contractual Requirements Should be Part of the Request for Proposal Phase. Obviously performing a proper due diligence can be very time consuming, especially when multiple layers of Cloud providers are involved. It is much more difficult to achieve due diligence when the Cloud transaction has moved forward significantly (e.g. the competitors have been told they are no longer being considered and negotiations on key terms, like price, have occurred). The time to address these issues is in the RFP process. Organizations should plan ahead and identify the criteria necessary for the company and have Cloud providers confirm that they meet the criteria in their response to a RFP. At this point in time, I recommend that RFPs actually identify legal contract terms (e.g. indemnification, exceptions to limits of liability and consequential damage disclaimers) that Cloud vendors must agree to in order to get the business. Not only does this save time, but it also creates a competitive incentive for Cloud providers to take on more risk (so that they can win the business). 

Filed under: Cloud

arya says...


Chrome OS is being positioned as a solution for users' secondary machines, offering a speedy, browser-based operating system consisting of Web apps and cloud-based data storage. The focus on speed begins at the top, with boot times currently clocking in at approximately 7 seconds
Excerpt from MacRumors. Image is from MacRumors.

So, everyone is moving to the cloud.

Filed under: cloud

pnealey says...

Hiker near Jackson Hole Wyoming.
License from Getty Images: http://www.gettyimages.com/detail/200460900-001/Digital-Vision

Filed under: Cloud

x0x04pat says...

Filed under: cloud

Michael says...

Photo by Photographer Paolo De Faveri

Filed under: cloud

morphar says...

Yesterday, one of my clients, needed me to advice them on which servers to pick, for a project that needs scaling cabilities.
In that connection, I wanted a better overview of some of the providers out there.
I haven't included expensive managed solutions like Rackspace's dedicated servers, as these don't fit in this category (they are managed).
The reason for this comparison, was to get a less know factor into the equation, when deciding whether to choose a dedicated server or a cloud server.

The question that I wanted answered was: "What is the comparable price, for self-managed servers?".

Some of the cloud companies are professionally vaque in describing, what they are giving you.
To make things even more difficult to compare, in reality they aren't even giving you the same product.
Amazon allocates CPU for you, while Rackspace Cloud limits you if necessary.
This can make a Rackspace Cloud machine VERY much faster, as it will have acces to something like dual quad core 2GHz CPUs.
What makes this an uninteresting fact for me - actually close to a negative point, is that you can run a test a 100 times at one point, but the result is completely useless, as you can not tell, if this will hold at a later point of time.

Amazon allocates a certain amount of EC2 Compute Units (ECU), which they describe as:
One EC2 Compute Unit (ECU) provides the equivalent CPU capacity of a 1.0-1.2 GHz 2007 Opteron or 2007 Xeon processor.

If this isn't vaque enough for you, then try out this description from Rackspace:
Each cloud server has 2 quad core processors that are at least 2Ghz+. The 256MB plan will get 1/64 of the CPU allocation, the 512MB plan will get 1/32 of the CPU allocation, and the 1GB plan will get 1/16 of the CPU allocation. The 2GB plan will get 1/ 8 CPU, the 4GB plan will get 1/4, the 8GB plan will get 1/2, and the 15.5GB plan will get all CPU allocation in the server.
Which fortunately is comparably vaque to Amazons description, as the calculation gives you 1+GHz pr. 1GB RAM :-P

The worst of them all, I am sad to say, is definitely Media Temple.
I have had servers hosted at Media Temple several times.
The service is good, customer support fine and pricing reasonable - but... They are the vaquest "cloud" hosting service of them all.
The only way, I could do some comparison, was by checking out their "nitro" product, finding out, what that server was physically, then assume the "dedicated virtual" servers was running on the same hardware. Finally I calculated the CPU like Rackspace Cloud does - by dividing.

There is a lot of different factors, not calculated into this little experiment, like:
  1. Which hard drives, how many and how much capcity
  2. Backed up or not
  3. How many CPU cores
  4. Connection to the internet - but: clouds generally has massive connection, while dedicated are more diverse
  5. General hardware: server-grade or not? I.e. consumer CPUs or server-grade? etc.

Also, traffic is an important factor - especially for the cloud services, as these are "pay-as-you-go".
I chose to calculate 200GB of traffic into the price.
The traffic is spread as: 25% traffic from client to server, 75% from server to client.

Anyways... Here it is! The pretty little chart, that roughly gives an idea, of the cost for 1GHz CPU + 1GB RAM + 200GB data pr. month.
There are a different amount of point pr. provider - these are different configurations.
Amazon and Rackspace Cloud has an amazingly consistent price!

Just a couple of final reminders:

Most of us already knew, that clouds were more expensive, than dedicated servers.
But this gives an idea of how much.

Cloud servers are not directly comparable to dedicated servers, as dedicated servers has ALL resources allocated for you.
Cloud servers is influenced by being managed by virtualization softwaree, sharing resources with a lot of other servers, sometimes not having real disks, etc.

The upside of cloud servers is, that you can start / stop them at any time, dedicated servers is usually paid pr. month or more + it can take days before it's up.
It's always a good thing, to have your servers physically close - with clouds you can start i.e. 100 servers for 2 days and then shut them down again, while maintaining all of the goodness of physical closeness, if your other servers are in the cloud.

Hope this helps a couple of decission makers! :-)

Filed under: Cloud