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Cloud Service Models and Performance

Cloud Service Models and Performance. Ang Li 09/13/2010. Roadmap. Re-cap on cloud computing Classes of cloud providers Common services offered by cloud providers Cloud performance comparison. Re-cap on cloud computing. What is cloud computing? Cloud application: software-as-a-service

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Cloud Service Models and Performance

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  1. Cloud Service Modelsand Performance Ang Li 09/13/2010

  2. Roadmap • Re-cap on cloud computing • Classes of cloud providers • Common services offered by cloud providers • Cloud performance comparison

  3. Re-cap on cloud computing • What is cloud computing? • Cloud application: software-as-a-service • Cloud provider: hardware and software infrastructure that supports the cloud applications • Benefits of cloud computing • Pay-as-you-go • On-demand scaling

  4. Classes of cloud providers Platform as a Service (PaaS) Infrastructure as a Service (IaaS)

  5. Infrastructure-as-a-Service providers • Offer near bare-metal virtual machines • You can ssh, get root privilege, install new software, do whatever you want • Can use the APIs provided by the OS • Highly flexible and customizable • Charge by machine-hour • (How many machines you use) X (how long you use them) • You can afford it!

  6. Demo time! • Amazon AWS

  7. Platform-as-a-Service providers • Offer a sandbox environment • Upload a program, they run it for you • Can only use the APIs provided by the environment • Charged by CPU utilization • Pay only how much resource you use • A few free hours per day!

  8. Demo time! • AppEngine

  9. Windows Azure: a combination of both • Offer a sand-box environment of C# (PaaS) • Charge by machine-hour (IaaS) • Demo time!

  10. Discussion • What are the pros and cons of IaaS and PaaS? • Which one do you prefer? • Your homepage • E-business application • Video processing

  11. Services offered by a cloud • Elastic compute cluster • Persistent storage • Intra-cloud and wide-area network • and others… • MapReduce service • CDN service

  12. Elastic compute cluster • Where your application is running • VM or sandbox environment • Why cluster? • Multiple “instances” can be running your application simultaneously • Why elastic? • You can add new instances or remove existing ones with very short latency

  13. Scaling the compute cluster • Opaque scaling • User can manually increase/decrease the number of instances • Alternatively, she can set up a scaling policy • IaaS providers (including Azure) • Transparent scaling • Scaling happens automatically (magically) • PaaSproviders

  14. Persistent storage • Where to store your application’s data • Why persistent? • Local storage (VM disk) is not reliable • Different types of storage service • Table, blob, queue, etc. • Highly scalable and available

  15. Access the storage services • Storage APIs • HTTP-based GET https://sdb.amazonaws.com/ ?Action=PutAttributes &Attribute.1.Name=data &Attribute.1.Value=haha &AWSAccessKeyId=[valid access key id] &DomainName=table &ItemName=k… • Library call DatastoreServicedatastore = DatastoreServiceFactory.getDatastoreService(); Key k = KeyFactory.createKey(table, key); Entity e = new Entity(k); e.setProperty("data", “haha"); datastore.put(e);

  16. Networking service • Intra-cloud network: between two instances or between an instance and the storage service • Wide-area network: between a cloud instance and the end user

  17. Intra-cloud network • Within a data center • High bandwidth, low latency

  18. Wide-area network • Every provider has multiple locations to host cloud applications • Application content can be served from the closest location • Why is this a good thing?

  19. Re-cap: cloud services Wide-area network Web application Intra-cloud network Computation service Storage service

  20. CloudCmp: comparing cloud providers • Motivation • Provide shopping advice • Analogy: should I buy an IBM or a Dell or a Mac? • Identify performance problems • Challenges • What to compare? • Each provider is unique in some way… • How do we measure?

  21. Methodology • Identify the common services • We just did this • Pick a few metrics for each service relevant to application performance • Develop benchmarking task for each metric • Run the tasks on different providers and compare

  22. Choose the providers to compare • AWS, Rackspace, Azure, and AppEngine

  23. Metrics: elastic compute cluster • Benchmark finishing time • Java-based benchmark tasks • Cost per benchmark • From per-hour price and billing API • Scaling latency • Periodically allocate new instances

  24. Metrics: persistent storage • Operation latency • Client matters • Cost per operation • Time to consistency • Read-after-write test

  25. Metrics: networking service • Intra-cloud network • Bandwidth (iperf) • Latency (ping) • Wide-area network • Use PlanetLab nodes to simulate a diverse user base • Let each node ping each data center of a cloud provider • Optimal wide-area latency

  26. Result: computation performance • What can we learn from the figure? • How do the performance differ across different clouds? • Within a provider, how do performance differ across different instance types? • Is this enough information to choose provider/instance? • How about cost?

  27. Result: computation cost • What can we learn from this figure? • Is some provider particularly cost-effective? • Which instance type should I choose within a provider?

  28. Result: scaling efficiency • How is the scaling latency (high/low)? • Linux vs Windows?

  29. Result: storage (table) • The storage services show high variation • Median – 30ms, 90 percentile – 60ms • Is it good or bad? Why?

  30. Result: intra-cloud network • Intra-cloud bandwidth varies across different providers • From 200Mbps to 800Mbps • What might be the cause?

  31. Result: wide-area network • Wide-area network latency also varies a lot • C3 is much better than the others • What might be the reason?

  32. Result summary • No provider stands out • C1 has the highest network bandwidth, while its instance is not the most cost-effective • C2 has the most powerful instances, while its network bandwidth is low • C3 has the lowest wide-area network latency, while its storage is slower than others • It is not trivial to shop for a cloud provider! • Many research challenges in developing a sound mechanism to select the best provider for an application

  33. Summary • Two main classes of cloud providers • IaaS: bare-metal virtual machines • PaaS: sand-box environment • Four common services • Elastic compute cluster • Persistent storage • Intra-cloud network • Wide-area network • No provider has the best performance over all services

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