Windows Azure What, how and why. Martin Maripuu Net Group OÜ

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1 Windows Azure What, how and why Martin Maripuu Net Group OÜ

2 Agenda 1. Why use cloud 2. IaaS, PaaS, SaaS 3. Windows Azure 4. Developing for Windows Azure

3 On-premise hosting

4 % of Capital Equipment Budget spent on IT in 2000? 45% Commerce Department Statistics

5 % of Utilized Server Capacity on Average? 6% Economist Survey on IT, 2008

Elasticity Provisioning for Peak Real World Server Utilization Is 5% to 20% Many Services Peak Exceeds Average by a Factor of 2 to 10 Most Provision

6 Elasticity Provisioning for Peak Real World Server Utilization Is 5% to 20% Many Services Peak Exceeds Average by a Factor of 2 to 10 Most Provision for Peak Painful to Under-Provision (Lost Customers) Provisioning for Peak Without Elasticity, We Waste Resources (Shaded Areas) During Non-Peak Times

7 Elasticity: Risks of Under-Provisioning Under-Provisioning #1 Potential Revenue (Shaded Area) Is Sacrificed Under-Provisioning #2 Some Users Respond to Under-Provisioning by Permanently Deserting the Site... Bad for Revenue!

8 Hosting

9 Hosting isn t sliced bread Complex contracts Years of legal battles for reimbruisement Do you trust your hosting provider? Same elasticity and scaling problems

10 If only there was a way I pay ONLY for what i use ONLY when i use it With the ability to SCALE capacity up and down on-demand Without large initial INVESTMENT Providing data SECURITY and service FAULT-TOLERANCE

11 We just defined the CLOUD MANIFESTO

12 Cloud is not a Grid/Cluster Cloud manifesto could be satisfied by a service provider running a medium sized grid/cluster

13 Cloud is not a Grid/Cluster Cloud Illusion of infinite computing resources avalibale Content is delivered from a cloud No upfront commitment needed Illusion of infinite failover available Location independence Agile scaling Grid/Cluster No illusion Content is delivered from a fixed point Upfront commitment usually needed Very specific failover limit Location dependence Not so agile scaling in most cases

14 Compute Compute Workload Patterns Optimal For Cloud On and Off Growing Fast Inactivity Period Average Usage Average Usage Time Time On & off workloads (e.g. batch job) Over provisioned capacity is wasted Time to market can be cumbersome Successful services needs to grow/scale Keeping up w/ growth is big IT challenge Complex lead time for deployment

Compute Compute Workload Patterns Optimal For Cloud Unpredictable Bursting Predictable Bursting Average Usage Average Usage Time Time Unexpected/unplanned peak in demand Sudden

15 Compute Compute Workload Patterns Optimal For Cloud Unpredictable Bursting Predictable Bursting Average Usage Average Usage Time Time Unexpected/unplanned peak in demand Sudden spike impacts performance Can t over provision for extreme cases Services with micro seasonality trends Peaks due to periodic increased demand IT complexity and wasted capacity

16 IaaS, PaaS, SaaS

IT as a service Private (On-Premise) Infrastructure (as a Service) Platform (as a Service)

Runtimes Runtimes Security & Integration Security & Integration Security & Integration Security

Virtualization Server HW Storage Managed by vendor Databases Servers Virtualization Server HW

17 IT as a service Private (On-Premise) Infrastructure (as a Service) Platform (as a Service) Software (as a Service) Applications Applications Applications Applications Runtimes Runtimes Runtimes Runtimes Security & Integration Security & Integration Security & Integration Security & Integration Databases Servers Virtualization Server HW Storage Databases Servers Virtualization Server HW Storage Managed by vendor Databases Servers Virtualization Server HW Storage Databases Servers Storage Managed by vendor Virtualization Server HW Networking Networking Networking Networking

18 IT as a service vs. hosting IT Private IaaS PaaS SaaS On-premise Hosted Cloud Hosting

19 Cost of ownership Small application, no significant change in usage patterns, no growth On-premesis Hosted (IaaS/PaaS/SaaS) Cloud (IaaS/PaaS/SaaS)

20 Cost of ownership Small application, medium change in usage patterns, medium growth On-premesis Hosted (IaaS/PaaS/SaaS) Cloud (IaaS/PaaS/SaaS)

21 Cost of ownership Small application, significant change in usage patterns, significant growth On-premesis Hosted (IaaS/PaaS/SaaS) Cloud (IaaS/PaaS/SaaS)

22 Volume Volume Why scaling is cheap in a cloud? $10,000 machine $1000 machine Cloud OS $500 machine $500 machine $500 machine $500 machine $500 machine Scale Up Scale Out # Machines

23 Windows Azure

24 Azure

25 Azure

26 Azure Applications and Data

27 Azure Applications and Data Web Role.NET (ASP, ASP.NET, MVC, WCF etc.) PHP Worker role.net Java Perl Etc. VM role Virtually no limit

28 Azure Roles

29 Azure Staging

30 Azure - Storage type>.core.windows.net/<storage specific>

31 Azure - Blobs

32 Azure - Queues

33 Azure - Tables

34 Azure - Fabric

35 Azure - Fabric

36 Azure - CDN

37 Azure - CDN

38 Azure - Connect

39 Azure - Connect

40 SQL Azure

41 SQL Azure Power of SQL server with cloud preformance and reliability

42 Developing for Azure

43 Developing for Azure SDK.NET Java PHP Ruby Python Tools Visual Studio Eclipse Development Fabric Applications Java MySql Tomcat Etc... Connectivity SOAP REST HTTP XML Etc...

44 Development life cycle

45 Development fabric

46 Emulator Compute UI

47 Emulator Storage UI

48 Configuration

49 Kas on tekkinud küsimusi?

50 Tänud kuulamast! Martin Maripuu

Dan Cohen Microsoft Consulting Services Microsoft Israel Team blog: My blog:

Art by Andrew Fryer Dan Cohen Microsoft Consulting Services Microsoft Israel email: danco@microsoft.com Team blog: http://blogs.microsoft.co.il/blogs/mcs My blog: http://dannycohen.info Agenda Recap: Why