1. An OS for Multicore and Cloud + Microsoft Azure Platform
Cloud Computing, CS
An OS for Multicore and Cloud + Microsoft Azure Platform

2. Outline An OS for Multicore and Cloud Microsoft Azure Platform
Introduction
Architecture (University of Pittsburgh – Factored OS)
Case Studies
Implementation and Results
Microsoft Azure Platform
Windows Azure Platform: Compute, Storage, and Fabric
Azure Services: Application fabric, SQL Azure, Live Services
Azure Development Environment
Summary and Conclusions
I can pretty much read this one straight through and provide details in following slides.

3. An OS for Multicore and Cloud

4. An OS for Multicore and Cloud: Introduction
Motivation & Challenges:
Scalability
Variability of Demand
Faults
Programming Challenges
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

5. An OS for Multicore and Cloud: Introduction
Scalability:
Current OSes were designed for single processor or for small number of processor systems
Many core Computer systems highlight limitation of locks and reliance on shared memory
Data center with thousands of servers!
Variability of Demands:
Given the large number of cores; map processes to cores
Elasticity of the Cloud
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

6. An OS for Multicore and Cloud: Introduction
Faults:
Hardware faults: core failures and bit-flips
Performance interference: between Apps and VMs has an impact on QoS
Software faults: parallel programming debugging is hard
Programming Challenges:
Resource management must be done by the cloud app
Load balancing is hard in the cloud
No uniform programming model: Intra/Inter-machine communication
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

7. An OS for Multicore and Cloud: Architecture
New OS (University of Pittsburgh – Factored OS / FOS) should provide scalability, elasticity, fault tolerance, and simple programming model:
Single system image OS
Micro-kernel , OS services run in user space, and they communicate via messages, i.e., similar to Mach
Each service consists of group of servers, called fleet, that are distributed among the underlying cores and machines
Message passing is mapped transparently across cores and machines
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

8. An OS for Multicore and Cloud: Architecture
Single System Image (FOS):
Ease of administration Consistency
Transparent sharing Fault tolerance
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

9. An OS for Multicore and Cloud: Architecture
Microkernel:
Messaging, name cache, time multiplexing of cores, API
Messaging:
IPC & synchronization
Each process has number of mailboxes
Naming:
All servers within a fleet register under a given name
OS Services:
Fleet: spatially distributed, cooperating servers
FS fleet, Naming fleet, Scheduling fleet, Proxy network server fleet, etc
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

10. An OS for Multicore and Cloud: Architecture
Single System Image (FOS) - Microkernel:
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

11. An OS for Multicore and Cloud: Architecture
Messaging:
IPC over shared memory or over network
Transparent Intra- and Inter-machine communication
Force programmers to think carefully about the amount of shared data
Parallel Data Structure:
Managing state associated with a particular service among the members of the fleet
Common container interface: abstracts several implementations that provide different consistency, replication and performance properties
Existing solutions in the P2P community
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

12. An OS for Multicore and Cloud: Case Study – File System
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

13. An OS for Multicore and Cloud: Case Study – Spawning Server
Create new server process on – decided by spawn server:
Same VM
Another existing VM
Spawn1  proxy1  proxy2  spawn2
New VM
Create VM, send request to Cloud Manager
Add VM to group, exchange name information, notify all other machines
Forward spawn request to the new VM
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

14. An OS for Multicore and Cloud: Case Study – Elastic Fleet
Watchdog process monitoring the queue length
Add server to fleet
Spawn, handshaking
Make global decisions of elastic fleet
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

15. An OS for Multicore and Cloud: Implementation and Results
Xen PVM
Run on EC2 or Eucalyptus Cloud infrastructure
Configuration:
16 machine cluster, each has 8 cores running at 3.16 GHZ, 8 GB RAM, and 1 Gbps Ethernet
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

16. An OS for Multicore and Cloud: Implementation and Results
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

17. An OS for Multicore and Cloud: Implementation and Results
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

18. An OS for Multicore and Cloud: Implementation and Results
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

19. Microsoft Azure Platform

20. Microsoft Azure Platform: Windows Azure Platform
Azure platform is built as a distributed services in MS data centers
Platform is built over specialized OS called Windows Azure
Flexible Service Architecture:
Service is isolation boundary
Component roles: web role, worker role, and other role templates
# of identical instances of each role
Platform consists of: Compute, Storage, and Fabric
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

21. Microsoft Azure Platform: Windows Azure Platform – Compute
Compute instance is exposed to the client as role types reflecting tailored configurations for typical purposes
Web role instance generally interact with the end user
Worker role instance cater to background tasks ~ Google App Engine, cron jobs
Azure provides additional role templates
For each role, user can specify static configuration settings such as URL, # of instances. Load balancer will automatically distribute incoming traffic to the running instances
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

22. Microsoft Azure Platform: Windows Azure Platform – Storage
Azure Storage provides services that host 3 kinds of data:
Blobs: stream of unstructured data (files)
Tables: structured (not Relational), it is rows/entities and columns (properties). Tables do not enforce a schema nor use SQL
Queues: mechanism for Apps to communicate and coordinate asynchronously
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

23. Microsoft Azure Platform: Windows Azure Platform – Fabric
Azure Fabric refers to a set of machines running the Azure OS that are collectively managed and generally co-located in the same region
Fabric controller is the layer of code that provisions all the user instances (web and worker roles) and perform any necessary upgrades
Monitor the applications, re-provisioning and reallocating resources as needed to ensure all services remain healthy
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

24. Microsoft Azure Platform: Azure Services
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

25. Microsoft Azure Platform: Azure Services – Application Fabric
Service Bus
It is Microsoft .NET Service Bus
Provides connectivity between systems when not sharing LAN
In Cloud, physical adjacency is not guaranteed
Service bus provides proxy connections when direct connectivity is difficult
Service Bus
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

26. Microsoft Azure Platform: Azure Services – Application Fabric
Access Control Service
It is Microsoft .NET ACS
Authenticate and authorize users relying on Windows Live ID or Corporate Active Directory or some federated identity management
Administration portal allows service owner to define access control rules and rights ad
Username:
Password: OK
Cancel
Aadfs2
acs
Google
Yahoo
Live ID
Facebook
ACS
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

27. Microsoft Azure Platform: Azure Services – Application Fabric
AppFabric Cache
Delivers distributed, in-memory, cache service for Windows Azure and SQL Azure applications
Similar to Memcached; it improves performance and scalability
Possible to enable HA through replication to multiple servers
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

28. Microsoft Azure Platform: Azure Services – SQL Azure
SQL Azure is RDBMS which is different from Azure storage described earlier
It is SQL server offered in the Cloud
It is limited to 10 GB/database!
Reporting: extends SQL server reporting to SQL Azure while simplifying integration with legacy SQL code
Data Sync: synchronizing replicated data
Database: SQL Server in the cloud
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

29. Microsoft Azure Platform: Azure Services – SQL Azure
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?
TDS: Table Data Storage

30. Microsoft Azure Platform: Azure Services – SQL Azure
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

31. Microsoft Azure Platform: Azure Services – Live Services
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

32. Microsoft Azure Platform: Azure Services – Live Services
Live Services provide a set of building blocks that can be used to handle user data and application resources including identity, contacts, Windows Live Messenger, Live Search and Maps
Live Framework (Live Mesh) offers data synchronization across multiple devices using FeedSync (RSS extensions)
Extending the reach of client devices accessible from the cloud and creating an integrated and consistent view of user data
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

33. Microsoft Azure Platform: Azure Development Environment
Typically use Visual Studio to access the Azure platform, which relies on .NET framework
In addition, Microsoft provides an SDK for Java and Ruby
Ultimately, there is expected to have support to Java, Python, Ruby, PHP, OpenID, and Eclipse
Of course, more community support available if you are using native Microsoft implementation. This requires:
The Windows Azure Software Development Kit
Windows Azure Tools for Microsoft Visual Studio
Once the application has been tested locally, it can be uploaded to Azure using Visual Studio, and then managed using the Azure Services Developer Portal; allows you to stage the application before deployment. User can suspend an instance and resume later
Since economies of scale are in play, larger DC is in favor. So the HW blocks can be enumerated.
How do you design for best performance?

34. Summary and Conclusion
Current OSes were designed for single processor or for small number of processor systems
There is a need for new OS that can support the following:
Scalability
Variability of Demand
Faults
Programming Challenges
Azure is Microsoft Platform for the Cloud
Azure Platform is built over specialized OS called Windows Azure; consists of Compute, Storage, Fabric
Azure platform provides 3 services: AppFabric, SQL Azure, and Live Services

35. END