Welcome!

@CloudExpo Authors: Elizabeth White, Yeshim Deniz, Liz McMillan, Pat Romanski, William Schmarzo

Related Topics: @CloudExpo, Microsoft Cloud, Containers Expo Blog, Cloud Security, Government Cloud

@CloudExpo: Article

Cloud Economics – Amazon, Microsoft, Google Compared

A Platform Comparison

Any new technology adoption happens because of one of the three reasons:
  1. Capability: It allows us to do something which was not feasible earlier
  2. Convenience: It simplifies
  3. Cost: It significantly reduces cost of doing something

What is our expectation from cloud computing? As I had stated earlier, it is all about cost saving … (1) through elastic capacity and (2) through economy of scale. So, for any CIO who is interested in moving to cloud, it is very important to understand what the cost elements are for different cloud solutions. I am going to look at 3 platforms: Amazon EC2, Google App Engine and Microsoft Azure. They are sufficiently different from each other and each of these companies is following a different cloud strategy – so we need to understand their pricing model.

(A word of caution: this analysis is as per the published data on 20th January, 2010 and texts in green italics are my interpretation)

[Update on Amazon offering as on June, 2011]

Quick Read: Market forces seem to have ensured that all the prices are similar – for quick rule of thumb calculation to look at viability, use the following numbers irrespective of the provider. You will not go too much off the mark.

  • Base machine = $0.1 per hour (for 1.5 GHz Intel Processor)
  • Storage = $0.15 per GB per month
  • I/O = $0.01 for 1,000 write and $0.001 for 1,000 read
  • Bandwidth = $0.1 per GB for incoming traffic and $0.15 per GB for outgoing traffic

However, if you have time, you can go through the detail analysis given below.

Amazon:
  • Overview: You can create one or more instances of a virtual machine for processing and for storage
    • You pay based on time the instances are running and not on how much they are used – if an instance is idle, you still pay for it
    • There are three physically different locations where the facility is available (called availability zones) – US(N. Virginia, N. California) and EU(Ireland)
    • When you either shutdown the machine instance or it crashes for whatever reason you lose all your data
    • It is possible to have a reserve instance (for 1 year or 3 years) for an initial payment and discounted rate of usage – however, I do not think it provides any guarantee against data loss because of machine crash
    • Data storage can be both relational and non-relational
  • Machine Instance: Virtual machine can be of different capacity – Standard(Small, Large, Extra Large), High-Memory(Double Extra Large, Quadruple Extra Large), High-CPU(Medium, Extra Large)
    • Charge for Machine Usage: You are charged for the time you keep the instance of the machine running – the time is calculated in hours, any fraction of hour is taken as full hour
      • Hourly charge vary from $0.085 (Small – Linux – N. Virginia) to $3.16 (Quadruple Extra Large – Windows – N. California)
      • Both Linux and Windows machine instances are supported – Windows machines are about 40% more expensive – other software charges are extra
    • There are separate charges for mapping IP addresses, for monitoring & auto scaling ($0.015 per instance per hour) and load balancing
    • A message queue is available (Simple Queue Service – SQS) but again it has a separate charge – $0.1 to $0.17 per GB depending on the total monthly volume
  • Data Persistence: To persistent data storage you can one of the 3 alternatives – Simple DB, Simple Storage Service (S3) or Relational Database Service (RDS)
    • Simple DB and S3 storage mechanism is not RDBMS – that is you do not have tables therefore you cannot retrieve records through using JOIN
    • RDS is an instance of MySQL – so you can use it like a normal RDBMS
    • Charges for Simple DB: you pay separately for CPU, disk space and data transfer – though up to a limit they are free (25 CPU hours, 1GB data transfer, 1GB of storage)
      • CPU usage calculation is normalized to 1.7 GHz Xeon (2007) processor and works out to $0.14 to $0.154 per hour depending on location
      • Data transfer In is free till June 2010 and charge for transfer Out is between $0.1 to $0.17
        per GB depending on the total monthly volume
      • Actual storage is charger at $0.25 to $0.275 per GB per month – it includes 45 bytes of overhead for each item uploaded
    • Charges for S3: You are charged for disk space, data transfer and number of request made instead of CPU usage – data transfer charges are the same
      • Storage charge varies from $.055 to $0.165 per GB per month making it slightly cheaper than Simple DB but at a higher level of usage (more than 1000 TB)
      • I/O requests are charged separately – you pay between $0.01 to $0.011 per 1,000 write requests and $0.01 to $0.011 per 10,000 read requests – deletes are free
    • Charge for RDS: You pay for storage, I/O request, data transfer and machine instance (Small, Large, Extra Large, Double Extra Large, Quadruple Extra Large) based on usage
      • You pay for RDS instance – charges vary from $0.11 to $3.10 per hour depending on the instance size
      • The storage charge is not pay as you use – you have to decide in advance (5 GB to 1 TB) and the charges are $0.10 per GB per month
      • The is no charge for backup up to the amount of storage you have chosen but you have to pay $0.15 per GB per month for extra backup
      • You pay separately for I/O at $0.10 per 1 million I/O requests

    Google:
    • Overview: Application written in Python or Java can directly be deployed – the implementation is a subset
      • No need to instantiate any virtual machine
      • You are charged on the actual normalized CPU cycles used
      • Storage is only non-relational
      • Charge is calculated on these parameters – bandwidth, CPU, storage, emails send
      • You have free quota for each of these parameters – it is enough for development, testing and small deployment
      • There are limits imposed for peak usage on many different parameters – with daily limits & limits on usage in a burst
      • You will need to rewrite your application to work on Google App Engine – see this
      • Charge for CPU usage: It is calculated in CPU seconds equivalent to 1.2 GHz Intel x86 processor
        • You pay $0.10 per hour of CPU usage for processing requests
        • 6.5 hours of CPU time is free
        • You do not pay for CPU idle time
      • Charge for storage: Only non-relational storage is available
        • You pay $0.15 per GB per month – the size includes overhead, metadata and storage required for indexes
        • It includes data stored in the datastore, memcache, blobstore
        • You pay for CPU usages for data I/O at $0.10 per hour
        • 60 hours of CPU time for data I/O is free
        • Up to 1 GB of storage is freeFAQ page says that it is 500 MB
        • You are charged every day at $0.005 GB per day after subtracting your free quota
      • Charge for bandwidth usage: Inward and outward bandwidth usage is charged at different rate
        • You pay $0.10 per GB for incoming traffic
        • You pay $0.12 per GB for outgoing traffic
        • 1 GB of incoming traffic and 1 GB of outgoing traffic is free
    Microsoft:
    • Overview: Offering has 3 main parts – Windows Azure, SQL Azure and App Fabric
      • Details available on the Microsoft site is more about the vision of the product than about what is implemented here and now.
      • However this document “Introducing Windows Azure” is good
      • It uses Hyper-V for virtualization – it works more like Amazon than like Google
      • There is an introductory offer where the service can be avail for free
      • The development environment is Visual Studio through an SDK
      • The emphasis of creating applications which partly runs in premise
        and partly on cloud
      • Microsoft wants to keep the programming model as much unaltered as possible – see this
      • Charge for CPU usage: It is calculated in CPU seconds equivalent to 1.2 GHz Intel x86 processor
        • You pay $0.12 per hour of CPU usage for processing requests
      • Charge for storage: Only non-relational storage is available
        • You pay $0.15 per GB per month
        • Storage transactions are charged separately at $0.01 per 10,000 transactions
      • Charge for bandwidth usage: Inward and outward bandwidth usage is charged at different rate
        • You pay $0.10 per GB for incoming traffic – rates for Asia are different $0.30 per GB
        • You pay $0.15 per GB for outgoing traffic – rates for Asia are different $0.45 per GB

Looking at the complexity of pricing I see great prospect for anybody who specializes in optimizing application for cloud – unlike traditional applications – any improvement in cloud application and directly be measured in $$$ saved.

More Stories By Udayan Banerjee

Udayan Banerjee is CTO at NIIT Technologies Ltd, an IT industry veteran with more than 30 years' experience. He blogs at http://setandbma.wordpress.com.
The blog focuses on emerging technologies like cloud computing, mobile computing, social media aka web 2.0 etc. It also contains stuff about agile methodology and trends in architecture. It is a world view seen through the lens of a software service provider based out of Bangalore and serving clients across the world. The focus is mostly on...

  • Keep the hype out and project a realistic picture
  • Uncover trends not very apparent
  • Draw conclusion from real life experience
  • Point out fallacy & discrepancy when I see them
  • Talk about trends which I find interesting
Google

Comments (1)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


CloudEXPO Stories
With the proliferation of both SQL and NoSQL databases, organizations can now target specific fit-for-purpose database tools for their different application needs regarding scalability, ease of use, ACID support, etc. Platform as a Service offerings make this even easier now, enabling developers to roll out their own database infrastructure in minutes with minimal management overhead. However, this same amount of flexibility also comes with the challenges of picking the right tool, on the right provider and with the proper expectations. In his session at 18th Cloud Expo, Christo Kutrovsky, a Principal Consultant at Pythian, compared the NoSQL and SQL offerings from AWS, Microsoft Azure and Google Cloud, their similarities, differences and use cases for each one based on client projects.
In his session at 21st Cloud Expo, Raju Shreewastava, founder of Big Data Trunk, provided a fun and simple way to introduce Machine Leaning to anyone and everyone. He solved a machine learning problem and demonstrated an easy way to be able to do machine learning without even coding. Raju Shreewastava is the founder of Big Data Trunk (www.BigDataTrunk.com), a Big Data Training and consulting firm with offices in the United States. He previously led the data warehouse/business intelligence and Big Data teams at Autodesk. He is a contributing author of book on Azure and Big Data published by SAMS.
Nicolas Fierro is CEO of MIMIR Blockchain Solutions. He is a programmer, technologist, and operations dev who has worked with Ethereum and blockchain since 2014. His knowledge in blockchain dates to when he performed dev ops services to the Ethereum Foundation as one the privileged few developers to work with the original core team in Switzerland.
Cloud-enabled transformation has evolved from cost saving measure to business innovation strategy -- one that combines the cloud with cognitive capabilities to drive market disruption. Learn how you can achieve the insight and agility you need to gain a competitive advantage. Industry-acclaimed CTO and cloud expert, Shankar Kalyana presents. Only the most exceptional IBMers are appointed with the rare distinction of IBM Fellow, the highest technical honor in the company. Shankar has also received the prestigious Outstanding Technical Achievement Award three times - an accomplishment befitting only the most innovative thinkers. Shankar Kalyana is among the most respected strategists in the global technology industry. As CTO, with over 32 years of IT experience, Mr. Kalyana has architected, designed, developed, and implemented custom and packaged software solutions across a vast spectrum o...
Digital Transformation and Disruption, Amazon Style - What You Can Learn. Chris Kocher is a co-founder of Grey Heron, a management and strategic marketing consulting firm. He has 25+ years in both strategic and hands-on operating experience helping executives and investors build revenues and shareholder value. He has consulted with over 130 companies on innovating with new business models, product strategies and monetization. Chris has held management positions at HP and Symantec in addition to advisory roles at startups. He has worked extensively on monetization, SAAS, IoT, ecosystems, partnerships and accelerating growth in new business initiatives.