JUNE 7-10, 2010 | NEW ORLEANS, LA

Real-World Patterns for Cloud ComputingWade WegnerTechnical EvangelistMicrosoft Corporation

SESSION CODE: ARC304

Jerry SchulistSolutions ArchitectTribune Company

What is the Tribune Company?

Three Key Scenarios

1. Storage

2. Compute

3. Scale

Tools, Knowledge, Approach

Content(Blob Storage)

Image Processor (Queue)

Image Processor(Worker Role)

Content Ingestion Services 1

2

3

What will we look at?

4

So what?

Not just a case study

: YOU!

Three Key Scenarios

1. Storage

2. Compute

3. Scale

Uploading Content

Data management todayIs it really infinite?Code-near and code-far scenariosRelational data?

Things to consider

Challenges

1. Running out of disk space

2. Handling archived digital content

3. Data stored across multiple datacenters

Content(Blob Storage)

Image Processor (Queue)

Image Processor(Worker Role)

Content Ingestion Services 1

Blob storage

Leveraging Windows Azure StorageUploading massive amounts of content into Windows Azure blobs.

DEMO

Key Takeaways

1. Consolidate content in Windows Azure storage

2. Windows Azure Storage SDK best practices

3. Leverage the .NET Framework 4.0

Abstracting Work with Queues

Loosely coupled and scalable solutionsReliable storage and delivery of messagesIdempotency8KBs per message; up to 100TBs

Things to consider

Challenges

1. Need to process content

2. Independent of upload

3. Blobs aren’t the best for writing instructions

Content(Blob Storage)

Image Processor (Queue)

Image Processor(Worker Role)

Content Ingestion Services 1

2

Queues

Leveraging Windows Azure StorageUsing Queues to store instructions for content processing.

DEMO

Key Takeaways

1. Use Windows Azure queues to decouple

2. Include all data relevant to work in message

3. Idempotent

Three Key Scenarios

2. Compute

3. Scale

1. Storage

Content Processing with Worker Roles

Web Roles verses Worker RolesDecoupling with Windows Azure Queues

Things to consider

Challenges

1. Require multiple versions of content

2. JIT content processing is slow and expensive

3. Cost

Content(Blob Storage)

Image Processor (Queue)

Image Processor(Worker Role)

Content Ingestion Services 1

2

3

Worker Role

Leveraging Windows Azure ComputeProcessing content with Windows Azure Worker Roles

DEMO

Key Takeaways

1. Use worker roles for long running processes

2. Process ahead of time

3. Handle exceptions to prevent role recycling

Three Key Scenarios

2. Compute

3. Scale

1. Storage

Scaling Storage Accounts

Isn’t scale automatic?What does elastic scale actually mean?Multiple storage accounts?Multiple queues?

Things to consider

Challenges

1. Storage account limitation of 100 Terabytes

2. Handle this challenge in a supportable fashion

Content(Blob Storage)

Image Processor (Queue)

Image Processor(Worker Role)

Content Ingestion Services 1

2

3

Worker Role

4

Scaling in Windows AzureA round robin approach to elastic scale in Windows Azure storage

DEMO

Key Takeaways

1. Multiple storage accounts

2. Round robin through accounts

3. Only pay for what you use

Scaling Windows Azure roles

Isn’t scale automatic?What ways exist to scale?Cost

Things to consider

Challenges

1. Determine the number of roles required

2. Auto-scale

Scaling in Windows AzureAn approach to implementing auto-scale in Windows Azure

DEMO

Key Takeaways

1. Determine how to scale – queue or performance

2. Scaling service independent of application

3. Pay for what you use; scale wisely

1. Consider the impact that cloud computing will have on you, your company, and your customers

2. Explore the three scenarios we presented andhow they impact you

3. Take advantage of TechEd, product teams, andeach other

Next Steps

Resources

www.microsoft.com/teched

Sessions On-Demand & Community Microsoft Certification & Training Resources

Resources for IT Professionals Resources for Developers

www.microsoft.com/learning

http://microsoft.com/technet http://microsoft.com/msdn

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