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Intro to Cloud Computing

Intro to Cloud Computing. Source: http://www.free-pictures-photos.com/. Cloud Computing. No longer the next big thing – the current big thing Began in 2007 – IBM and Google “Blue Cloud” Name cloud inspired by cloud symbol representing internet in diagrams. What is Cloud Computing?.

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Intro to Cloud Computing

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  1. Intro to Cloud Computing

  2. Source: http://www.free-pictures-photos.com/

  3. Cloud Computing • No longer the next big thing – the current big thing • Began in 2007 – IBM and Google “Blue Cloud” • Name cloud inspired by cloud symbol representing internet in diagrams

  4. What is Cloud Computing? • But what is it? • Everyone has a different opinion on what it is • Is it trendy? • “The computer industry is the only industry that is more fashion-driven than women’s fashion” • Larry Ellison

  5. Questions to answer • What clouds have you used today (yesterday)? • What is a cloud?

  6. Applications • What does cloud computing actually do? • Consider applications you may currently be running on laptop, desktop, phone, server • Cloud has them also, or can potentially bring them to you • Brings applications, views, manipulates, shares data

  7. Cloud Computing • Everyone has an opinion on what to use a cloud for • Applications on the internet – email, tax prep • Storage for business, personal data • Web services for photos, maps, GPS • Rent a virtual server, load software on it, turn it on /off, clone it if sudden workload demand • Store, secure data for authorized access (really?) • Use a platform including OS, Apache, MySQL, Python, PHP

  8. Cloud Computing Characteristics • So what are its characteristics? • AKA On-demand computing, pay as you go, software as a service, utility computing • Typically access through the internet • Distributed and highly parallel approach • Usually costs $$$, but cost-effective • Virtualization • Elastic • Replication, replication, replication …

  9. Cloud Components • 3 components • Clients • Mobile, thin, thick • Datacenter • Distributed servers

  10. Data Center • Data Center • Collection of servers • In large room in your building, across world • Distributed Servers • Distributed data centers • geographically disparate • Robust if failure • Dynamic datacenter so can increase as needed

  11. Clouds • Allow access to applications other than on local computer or internet connected device • Instead, company hosts your application - Advantages? • No more licenses, service packs, etc. • Less hardware, etc. • Can access anywhere but • Works only as long as have internet connection • Lose control – can’t optimize

  12. Cloud Computing Characteristics • Cost-effective • start-up company to use a cloud instead of buy computers, hire IT people, etc. • Elastic Computing • company has a temporary surge in business, use cloud instead of invest in new computing equipment

  13. Virtualization • What is virtualization? • Software implementation of a computer that executes programs like a physical machine • Installation of one machine runs on another • All software in the cloud runs on a server within virtual machine • AMD-Virtualization and Intel Virtualization Technologies (IVT) extensions made it doable

  14. Virtualization • Virtual Machine VM • isolated guest OS installation within a normal host OS • Object of deployment • Virtual Machine Image – • Static data containing software (OS, apps, data files) the VM will run once started • Used to create VM instance • Typically stored on disk • Virtual Machine Instance – • Running virtual machine • Started from image, runs OS and processes, computes, etc. • Dynamic object you can interact with

  15. Virtualization • Hypervisor – Virtual Machine Manager VMM • One level higher than supervisory program • Installed on server hardware • Easily create copies of existing environments • Can exist on same servers or different machines • Single server multiple OS instances, minimize CPU idle time App App App App App App OS OS OS Operating System Hypervisor Hardware Hardware Traditional Stack Virtualized Stack

  16. Elastic - Cloud Computing Characteristics • Use what you need • Hardware, platform (OS), software • Cloud infrastructure used depends on application • Massive number of servers needed OR • Only need one server to run small job • Company has a temporary surge in business, use cloud instead of invest in new computing equipment • Company has a decline in business, don’t have to maintain unused equipment

  17. Cloud Computing Characteristics • Redundancy • Redundancy is the key to the success of clouds • Google approach – cheap components that fail, so replicate all processing and storage

  18. What Motivated Cloud Computing Initial motivation: • Web-scale problems – data intensive Solutions: • Large data centers How to access: • Highly-interactive Web applications (thin client) Next Step: • Different models of computing

  19. Data Intensive - How much data? • CERN’s LHC will generate 15 PB a year • Facebook – 2.5 Pb, growing at 15TB per day in 2012? • 25 TB 1000 times volume of mail delivered by USPS • Sloan Digital Sky Survey – 0.5 PB /month in 2015 • “all words ever spoken by human beings” • ~ 5 EB – 1018

  20. Solution: Large Data Centers • Although Google famous for innovating web searching, Google’s architecture as much a revolution • Instead of few expensive servers, use many cheap servers ($5000 instead of $100,000) • 1/2M servers in ~ 12 locations) • With thin, wide network • Cloud – robust and self-healing • Uses a lot of power • Need cheaper power solutions

  21. The Result:Different Computing Model “Why do it yourself if you can pay someone to do it for you?”

  22. IaaS • Infrastructure as a Service (IaaS) – aka Hardware as a Service (HaaS) and Utility computing • Why buy machines when you can rent cycles? • Utility computing billing – based on what used • Provides basic storage and compute capabilities as server • Servers, storage systems, CPU cycles, switches, routers, etc. • Ex: Amazon’s EC2

  23. IaaS • Does not provide applications to customers (SaaS and PaaS do) • Saves cost of purchasing • Infrastructure can be scaled up or down • Multiple tenants can use equipment at the same time • Device independence – access systems on different hardware • Low barriers to entry, example? • e.g. Samba

  24. PaaS • Platform as a Service (PaaS) aka cloudware • Supplies all resources needed to build apps and services without having to download or install software • Provides a computing platform and solution stack • Customer interacts with platform through API • Layer of software encapsulated provided as service to build higher level services • Ex: Google Apps Engine

  25. PaaS provides • Development teams across world to work together • Merge web services from multiple sources • Cost savings from using built-in security, scalability and failover • Cost-savings from using higher-level programming abstractions

  26. SaaS • Software as a Service (SaaS) – web based applications • Software available on cloud for use • Application hosted as a service to customers who access via the internet • Single instance runs and services multiple end users • Ex: salesforce.com, Gmail

  27. SaaS • Pros/Cons • Customer doesn’t have to maintain or support SW • Out of customer’s hands when hosting service changes it • Use software out of box • Instead of just paying for its once, billed • Don’t have to pay as much up front, cheaper more reliable • Security (SSL used), don’t need VPNs (Virtual private networks on back-end)

  28. Benefits to SaaS • Everyone knows WWW, little training needed • Smaller IT staff needed • Easier to customize • Better marketing by providers, accommodate more • Security (SSL used), don’t need VPNs (Virtual private networks on back-end) • But: • Specific computational need not addressed – may have to buy own • Lock-in – can’t move to new vendor without penalty

  29. Future of SaaS • Move all processing power to the cloud and carry ultralight input device • Already happening? • E-mail • Google Docs • Implications for Microsoft, software as purchasable local application • Windows Live (Microsoft’s cloud) • Adobe web based photoshop

  30. IaaS, PaaS, SaaS

  31. When not to use a Cloud • Legislative Issues • Laws and policy allow freer access to data on a cloud than private server • FBI can access data without warrant or owner’s consent • Geopolitical concerns • If in Canada, cannot store data on U.S. cloud – Why? • (because of patriot act…) • What about storing your data on clouds outside of USA?

  32. Types of Clouds • Public, Private, Hybrid Clouds • Names do not necessarily dictate location • Type may depend on whether temporary or permanent

  33. Data Bases in Cloud Environments Based on: Md. Ashfakul Islam Department of Computer Science The University of Alabama

  34. Issues to Consider • Distributed or Centralized application? • How can ACID guarantees be maintained? • CAPS theorem • Consistency, Availability, Partition • Data availability (even if network partition) is achieved by compromising consistency • Traditional consistency techniques become obsolete • Consistency becomes bottleneck of data management deployment in cloud • Costly to maintain

  35. Analytical DBs - Data Warehousing • Data Warehousing DW - Popular application of Hadoop • Typically DW is relational (OLAP) • but also semi-structured, unstructured data • Can also be parallel DBs (teradata) • column oriented • Can be expensive, e.g. TBs of data • Hadoop for DW • Facebook abandoned Oracle for Hadoop (Hive) • Also Pig – for semi-structured

  36. Evaluation of Analytical DB • Analytical DB handles historical data with little or no updates - no ACID properties. • Elasticity • Since no ACID – easier • E.g. no updates, so locking not needed • A number of commercial products support elasticity. • Security • requirement of sensitive and detailed data • third party vendor store data • potential risk of data leakage and privacy violation • Replication • Recent snapshot of DB serves purpose. • Strong consistency isn’t required.

  37. Transactional Data Management Needed because: • Transactional Data Management • heart of database industry • almost all financial transaction conducted through it • rely on ACID guarantees • ACID properties are main challenge in transactional DM deployment in Cloud.

  38. Relational Joins • Hadoop is not a DB • Debate between parallel DBs and MR for OLAPS • Dewitt/Stonebreaker call MR “step backwards” • Parallel faster because can create indexes

  39. Consistency in Clouds • Consistent database must remain consistent after execution of successful operations. • Inconsistency may cause to problems • Consistency is always sacrificed to achieve availability and scalability. • Strong consistency maintenance in cloud is very costly.

  40. DBs in the Cloud • Slow start for DBs – why?? • Considered Scalable Transactions for Web Applications in the Cloud • Two important properties of Web applications • all transactions are short-lived • data request can be responded to with a small set of well-identified data items • Eventual consistency acceptable

  41. Cloud Provider DB Options

  42. Windows Azure

  43. Data Management • Can run SQL Server or another DBMS in a VM created with Azure Virtual Machines • Free to run NoSQL technologies such as MongoDB and Cassandra • Running your own database system is straightforward- also requires handling the administration of that DBMS

  44. Data Management Options • Figure 3: For data management, Windows Azure provides relational storage, scalable NoSQL tables, and unstructured binary storage.

  45. Data Management Options • Each of the three options addresses a different need: • relational storage • fast access to potentially large amounts of simple typed data • unstructured binary storage. • In all cases, data is automatically replicated across three different computers in an Azure datacenter • All three options can be accessed either by Windows Azure applications or by applications running elsewhere, such as an on-premises datacenter, a laptop, or phone.

  46. Relational Storage – SQL Database • Provides all of the key features of a relational database management system, including • atomic transactions, concurrent data access by multiple users with data integrity, ANSI SQL queries, and a familiar programming model. • If know SQL Server, using SQL Database is straightforward. • can be accessed using Entity Framework, ADO.NET, JDBC

  47. SQL Database • But SQL Database isn't just a DBMS in the cloud-it's a PaaS service. • You control your data and who can access it and SQL Database takes care of the administrative grunt work • such as managing the hardware infrastructure and automatically keeping the database and operating system software up to date. • SQL Database provides a federation option that distributes data across multiple servers. • Spread data access requests across multiple servers for better performance.

  48. Tables • For application that needs fast access to lots of typed data, it, but doesn't need to perform complex SQL queries • For storing data, and retrieving it in simple ways • NOT relational • very scalable, with a single table can hold as much as a terabyte of data

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