Overview of Azure

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Notes from Chris Auld's presentation at TechEd 09. Again, as with the other TechEd blogs, these are just notes that I can use to find out further information when more time is available. :)

Azure:
  • High scale application architecture
  • Consolidate traditional IT to the cloud
  • Move servers and apps out-house
  • Reliable hardware in the cloud
  • Virtualize to the cloud
  • Manage explosive growth (scale out cloud)
  • Scale out clouds are built around disposable hardware
  • Reliability is built using software
  • Scale out cloud is load balanced by default
  • Greeness - PUE (power usage effectiveness) = Total Facility Power / IT Equipment Power. Google and Microsoft are getting around 1.10 to 1.25 PUE. Intergen server room is running at about 1.6 PUE.
  • MS cloud offering = Windows Azure, .NET Services, SQL Azure
  • Azure sits you above the abstraction layer (IMAGE TO GO IN HERE)
  • Compute source (IMAGE TO GO IN HERE)
  • Load balancer is key part of Windows Azure
  • RoleEntryPointStart() has no return value. Always while True.
  • VMs are cloud optimised
  • VMs are running 64 bit Windows Server 2008
  • Each VM has one to one relationship with processor core
  • Developers have a desktop environment available that simulates the cloud locally
Storage in the cloud
  • HTTP(S) via REST services into cloud storage
  • Scales out across server farms consistently
  • Blobs are addressable as URLs
  • Tables are persistent dictionary, not relational
  • Queues link worker role and web app role
  • Can access Azure storage from any app that can get through using HTTPS via port 443
  • Only port 443 at the moment
  • Horizontal data partitioning
  • Have to nominate a partition key
  • Items with same partition key stored on same partition
  • Items with different partition keys MAY be stored on different partitions
  • MUST access via REST, can't use ADO.NET
  • SDK provides some useful tools
  • No SQL - no real joins/aggregates; limited indexes; no schemas; no referential integrity
  • Can't easily move relational database to the cloud
  • Will scale out MASSIVELY
  • Don't need prior knowledge of how many partitions will be required
  • Queue - receive work in to the web role, it then writes message to the queue, worker role processes the message and then deletes it. If message not done, it is re-added to the queue and processed again. Need to watch out for messages being duplicated.
  • May only need 10 instances for 24/7/365, but it's easy to switch to 1000 instances for the 5 days a year that you may need that many.
  • Great for start up businesses as there are no requirements to buy server hardware anymore, you can get up and running very quickly in the cloud
SQL Azure
  • True relational database management source
  • Pared back, so missing some things, i.e. SSAS, SSRS
  • "Huron'' data hub
  • Accessed via port 1433 using tabular data stream
  • Sticky, stateful load balancer
  • Database spread across a minimum of 3 servers
  • 10GB is currently the largest database size in the cloud
  • If you put too much load you'll get errors - so if you have a large DB, partition it.
  • Need to deal with partition code inside your application
.NET Services
  • Inter application message broker
  • Provides access control service / claim mapping
  • Provides service bus
  • Cloud based intermediary between clients and internal applications
  • Provides service registry that finds services
  • Quickly establish bi-directional communication
  • Direct connectivity libraries with NAT probing
  • Access control service implements security token service (STS) in the cloud. Accepts new token and issues another as claims outgoing may be different to incoming claims.
  • Admin can define rules for claim transformations.
What others are doing
  • Amazon/Mosso - pay as you go - you have to set up and maintain your own servers in the cloud.
  • Microsoft/Google/SalesForce - pay as you go - vertically integrated, no server setup/maintenance required
  • VMWare/Appistry - Buy up front - set up and maintain your own servers
  • Amazon are currently the market leaders
  • Amazon use the Elastic Compute Cloud (EC2)
  • Amazon - VMs that let you run Linux or Windows, have to patch/maintain your own servers in the cloud
  • Amazon's cloud offering is highly flexible
  • Google app engine supports Java/Python only
  • Google you can only execute code for 30 seconds at a time
  • Google uses non-relational, scale out storage
  • Salesforce (SFDC) uses the SFDC defined language
  • SFDC is used for data driven apps
  • SFDC uses non-relational, scale out storage
  • SFDC has no dedicated processor instance
  • Windows Azure + SQL Azure = cheapest HA offering available at the moment
Before moving to the cloud:
  • Think about how you'd partition your data
  • Follow high scale application architecture guidelines


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