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7 Windows Azure = Managed for You Standalone Servers Applications Runtimes Database Operating System Virtualization Server Storage Networking Efficiency IaaS PaaS SaaS Control+Cost

8 Developer 1) Choose image, then create VM for DBMS and configure DBMS 2) Choose image, then create and configure VM(s) for application 3) Provision database, then create tables and add data 4) Install application 5) Configure load balancer 6) Manage VMs and DBMS (e.g., deploying new OS images in VMs) Library VM Images Data Application Load Balancer

9 Developer 1) Provision database, then create tables and add data 2) Deploy application Data Application Load Balancer

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11 Red Dog Front End (RDFE) Windows Azure Networking

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14 TOR Digi 40 Nodes APC TOR Digi 40 Nodes APC AGG TOR Digi 40 Nodes APC TOR Digi 40 Nodes APC AGG TOR Digi 40 Nodes APC TOR Digi 40 Nodes APC TOR Digi 40 Nodes APC AGG TOR Digi 40 Nodes APC TOR Digi 40 Nodes APC TOR Digi 40 Nodes APC AGG TOR Digi 40 Nodes APC TOR Digi 40 Nodes APC AGG TOR Digi 40 Nodes APC TOR Digi 40 Nodes APC AGG TOR Digi 40 Nodes APC DLA Architecture (Old) Quantum10 Architecture (New) DC Router DCR DCR DC Routers Access Routers LB LB LB LB Aggregation + LB Spine Spine Spine Spine L B L B L B L B L B L B L B L B L B L B L B L B 20Racks 20Racks 20Racks 20Racks TOR TOR TOR TOR

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16 Word SQL Server Exchange Online SQL Azure Server Datacenter

17 LB AGG LB TOR TOR TOR TOR TOR

18 Image Repository Maintenance OS Fabric Controller Windows Parent Azure Role Role Role Role OS Images Images Windows Deployment Server PXE Server FC Host Agent Windows Azure Node OS Windows Azure Hypervisor

19 Role B Worker Role Count: 2 Update Domains: 2 Size: Medium Load Balancer

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22 Physical Node Guest Partition Guest Partition Guest Partition Guest Partition Role Instance Role Instance Role Instance Role Instance Trust boundary Guest Agent Guest Agent Guest Agent Guest Agent Host Partition FC Host Agent Image Repository (OS VHDs, role ZIP files) Fabric Controller (Primary) Fabric Controller (Replica) Fabric Controller (Replica)

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25 Blobs Tables Queues

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27 Account Container Blob sally pictures movies IMG001.JPG IMG002.JPG MOV1.AVI

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29 Account Table Entity sally users photo index Name = = Name = = Photo ID = Date = Photo ID = Date =

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31 Account Queue Message sally thumbnail jobs photo processing jobs 128x128, 256x256,

32 Container Blobs Account Table Entities Queue Messages

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34 Front- End-1 Front- End-2 Middle Tier-1 Middle Tier-2 Middle Tier-3

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36 25 min Guest Agent Heartbeat 5s Guest Agent Heartbeat Timeout 10 min Guest Agent Guest Agent Connect Timeout Indefinite 15 min Role Instance Heartbeat 15s Role Instance Unresponsive Timeout 30s Load Balancer Heartbeat 15s Load Balancer Timeout 30s Role Instance Role Instance Launch Role Role Instance Instance Start Ready (for updates only)

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38 Load Balancer Front-End Front-End Middle- Tier Windows Azure Storage, SQL Azure

39 Using queues To scale, add more of either 1) Receive work Web Role ASP.NET, WCF, etc. Worker Role main() { } 4) Do work 2) Put work in queue 3) Get work from queue Queue

40 Queues are the application glue Queues decouple different parts of application, making it easier to scale app parts independently; Flexible resource allocation, different priority queues and separation of backend servers to process different queues. Queues mask faults in worker roles.

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42 BLAST (Basic Local Alignment Search Tool) Most important software in bioinformatics Identify similarity between bio-sequences Computationally intensive Large number of pairwise alignment operations A BLAST running can take 700 ~ 1000 CPU hours Sequence databases growing exponentially GenBank doubles in size every 15 months.

43 It is easy to parallelize BLAST Segment the input Segment processing (querying) is pleasingly parallel Segment the database Needs special result reduction processing Large volume data A normal Blast database can be as large as 10GB 100 nodes means the peak storage bandwidth could reach to 1TB The output of BLAST is usually x larger than the input

44 Parallel BLAST engine on Azure Query-segmentation data-parallel pattern split the input sequences query partitions in parallel merge results together when done Follows the general PaaS application model Web Role + Queue + Worker Wei Lu, Jared Jackson, and Roger Barga, AzureBlast: A Case Study of Developing Science Applications on the Cloud, in Proceedings of the 1st Workshop on Scientific Cloud Computing (Science Cloud 2010), Association for Computing Machinery, Inc., 21 June 2010

45 A simple Split/Join pattern Leverage multi-core of one instance argument a of NCBI-BLAST 1,2,4,8 for small, middle, large, and extra large instance size Task granularity Large partition load imbalance Small partition unnecessary overheads NCBI-BLAST overhead Data transferring overhead. Splitting task BLAST task BLAST task BLAST task BLAST task Best Practice: test runs to profiling and set size to mitigate the overhead Value of visibilitytimeout for each BLAST task, Essentially an estimate of the task run time. too small repeated computation; too large unnecessary long period of waiting time in case of the instance failure. Merging Task

46 Task size vs. Performance Benefit of the warm cache effect 100 sequences per partition is the best choice Instance size vs. Performance Super-linear speedup with larger size worker instances Primarily due to the memory capability. Task Size/Instance Size vs. Cost Extra-large instance generated the best and the most economical throughput Fully utilize the resource

47 BLAST task BLAST task Splitting task BLAST task Merging Task BLAST task Web Role Job Management Role Worker Web Portal Job registration Scaling Engine Worker Web Service Job Scheduler Global dispatch queue Worker NCBI databases Job Registry Azure Table Blast databases, temporary data, etc.) Database updating Role Azure Blob

48 Discovering Homologs Discover the interrelationships of known protein sequences All against All query The database is also the input query The protein database is large (4.2 GB size) Totally 9,865,668 sequences to be queried Theoretically, 100 billion sequence comparisons Performance estimation Based on the sampling-running on one extra-large Azure instance Would require 3,216,731 minutes (6.1 years) on one desktop One of largest BLAST jobs This scale of experiments usually are infeasible to most scientists

49 Allocated a total of ~4000 instances 475 extra-large VMs (8 cores per VM), four datacenters, US (2), Western and North Europe 8 deployments of AzureBLAST Each deployment has its own co-located storage service Divide 10 million sequences into multiple segments Each will be submitted to one deployment as one job for execution Each segment consists of smaller partitions When load imbalances, redistribute the load

50 3/31/2010 6:14 RD00155D3611B0 Executing the task /31/2010 6:25 RD00155D3611B0 Execution of task is done, it took 10.9mins 3/31/2010 6:25 RD00155D3611B0 Executing the task /31/2010 6:44 RD00155D3611B0 Execution of task is done, it took 19.3mins 3/31/2010 6:44 RD00155D3611B0 Executing the task /31/2010 7:02 RD00155D3611B0 Execution of task is done, it took mins 3/31/2010 8:22 RD00155D3611B0 Executing the task /31/2010 9:50 RD00155D3611B0 Executing the task /31/ :12 RD00155D3611B0 Execution of task is done, it took 82 mins

51 North Europe Data Center, totally 34,256 tasks processed All 62 compute nodes lost tasks and then came back in a group. This is an Update domain ~ 6 nodes in one group ~30 mins

52 West Europe Datacenter; 30,976 tasks are completed, and job was killed 35 Nodes experience blob writing failure at same time A reasonable guess: the Fault Domain is working

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55 Private IaaS Computing Public Storage IaaS PaaS Relational NoSQL Blobs Microsoft VMware Amazon OpenStack Key Cloud Platform Software Cloud Platform Service

56 Private IaaS Public Computing Storage IaaS PaaS Relational NoSQL Core cloud technologies implemented in System Center 2012 Blobs Microsoft Microsoft Private Cloud Microsoft Private Cloud (for hosters) VMware Amazon OpenStack Key Cloud Platform Software Cloud Platform Service

57 Private IaaS Public Computing Storage IaaS PaaS Relational NoSQL Core cloud technologies implemented in vsphere and vcloud Director Blobs Microsoft VMware Microsoft Private Cloud vcloud Microsoft Private Cloud (for hosters) vcloud DataCenter (for hosters) Amazon OpenStack Key Cloud Platform Software Cloud Platform Service

58 Private Public Computing Storage IaaS IaaS PaaS Relational NoSQL Blobs Microsoft Microsoft Private Cloud Microsoft Private Cloud Persistent VM Roles Web/Worker Roles SQL Azure Tables Blobs VMware vcloud vcloud DataCenter (for hosters) Amazon OpenStack Key Cloud Platform Software Cloud Platform Service

59 Private Public Computing Storage IaaS IaaS PaaS Relational NoSQL Blobs Microsoft Microsoft Private Cloud Microsoft Private Cloud Persistent VM Roles Web/Worker Roles SQL Azure Tables Blobs VMware vcloud vcloud DataCenter (for hosters) Cloud Foundry Cloud Foundry Cloud Foundry Amazon OpenStack Key Cloud Platform Software Cloud Platform Service

60 Private Public Computing Storage IaaS IaaS PaaS Relational NoSQL Blobs Microsoft Microsoft Private Cloud Microsoft Private Cloud Persistent VM Roles Web/Worker Roles SQL Azure Tables Blobs VMware vcloud vcloud DataCenter Cloud Foundry Cloud Foundry (for hosters) Cloud Foundry Amazon Elastic Compute Cloud (EC2) Elastic Beanstalk Relational Database Service (RDS) SimpleDB DynamoDB Simple Storage Service (S3) Key Cloud Platform Software OpenStack Cloud Platform Service

61 Private Public Computing Storage IaaS IaaS PaaS Relational NoSQL Blobs Microsoft Microsoft Private Cloud Microsoft Private Cloud Persistent VM Roles Web/Worker Roles SQL Azure Tables Blobs VMware vcloud vcloud DataCenter Cloud Foundry Cloud Foundry (for hosters) Cloud Foundry Amazon Eucalyptus Elastic Compute Cloud (EC2) Elastic Beanstalk Relational Database Service (RDS) SimpleDB DynamoDB Simple Storage Service (S3) Key Cloud Platform Software OpenStack Cloud Platform Service

62 Private Public Computing Storage IaaS IaaS PaaS Relational NoSQL Blobs Microsoft Microsoft Private Cloud Microsoft Private Cloud Persistent VM Roles Web/Worker Roles SQL Azure Tables Blobs VMware vcloud vcloud DataCenter Cloud Foundry Cloud Foundry (for hosters) Cloud Foundry Amazon OpenStack Eucalyptus OpenStack Compute Elastic Compute Cloud (EC2) OpenStack Compute (for hosters) Elastic Beanstalk Relational Database Service (RDS) SimpleDB DynamoDB Simple Storage Service (S3) OpenStack Object Storage (for hosters) Key Cloud Platform Software Cloud Platform Service

63 IaaS PaaS Interesting to people building applications: Developers Running New Cloud-Native Apps High Performance Computing and Big Data Running a Standard DBMS VMs for a Dev/Test Lab Running Existing Web Apps/Sites Running Standard Packaged Apps Interesting to people running applications: Operations Virtual Data Center (VMs for On-Demand Use) Disaster Recovery

64 Developer Operations A much bigger market today Examples Reliability Provided By Best Suited For Typical Management Tools Main Benefits Typical Buyer

65 Microsoft Offering Windows Azure Persistent VM Role Hypervisor Hyper-V IaaS Type Developer Elastic Compute Cloud Amazon Xen Developer (EC2) CSC CloudCompute VMware Operations Leaders in Gartner Magic Quadrant for Public Cloud IaaS Terremark Enterprise Cloud, vcloud Express VMware Operations, Developer Savvis Symphony VPDC VMware Operations Bluelock Virtual Bluelock VMware Operations Datacenters Rackspace Cloud Servers Xen Developer SmartCloud IBM KVM Developer Enterprise HP Cloud Compute KVM Developer GoGrid Cloud Servers Xen Developer

66 Offering Languages/ Frameworks Storage Comments Microsoft Windows Azure Web/Worker Roles C# and VB/.NET, PHP, JavaScript/Node.js, Relational (SQL Azure), NoSQL (Tables), Blobs Designed to be a fully PaaS platform Amazon Elastic Beanstalk Java/Servlets Relational (RDS), NoSQL (SimpleDB, DynamoDB), Beanstalk is a simple extension to EC2 Google App Engine Java, Python, Go Relational (CloudSQL), NoSQL (Datastore), Blobs App Engine has undergone many recent changes Salesforce AppForce Apex/AppForce Framework NoSQL (Database.com) Pricing is per user, not based on resources used Heroku Heroku Ruby/Rails, JavaScript/ Node.js, Java, Relational (MySQL, Postgres, ), NoSQL (Redis, ) Heroku runs on EC2 and is owned by Salesforce Engine Yard EngineYard Cloud, Orchestra PHP Ruby/Rails, PHP Relational (MySQL), NoSQL (Redis) Runs on EC2; enterprise version runs on Terremark Oracle Java/Java EE (WebLogic) Relational (Oracle DBMS) Oracle Public Cloud Announced October 2011 IBM IBM SmartCloud Application Services None; focused on tools for deploying/managing apps Relational (DB2) Announced October 2011; not really a PaaS platform LongJump LongJump Cloud Applications Platform Java and JavaScript/ LongJump Framework NoSQL (Proprietary) Runs on Rackspace; also sells PaaS software separately

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