1. GIS & Cloud Computing GAA-SC Fall Summit Florence, SC October 14th – 15th, 2010 Jim Tochterman, VP - Research & Development www.bcs-gis.com www.facebook.com/bcsgis www.twitter.com/bcsgis
2. What is Cloud Computing? Many different variations and meanings depending on who you ask, but the principle tenets are always: Rented physical infrastructure and/or applications Shared architecture Maintained off premises Delivered on demand as a service Technology pioneered by Amazon Cloud offerings can range from data storage and end-user web applications to other computing services.
3. Traditional vs. Cloud? Critical difference is the scalability and elastic nature that cloud services provide. In simpler terms cloud computing allows to: Dynamically scale up and quickly scale down for high reliability, quick response times Flexibility to handle traffic fluctuations and demand.
4. Cloud Components Software as a Service (SaaS) End-user applications delivered as a service rather than on premise software Salesforce.com -> CRM Software Office.com -> Productivity Software Apps.Google.com -> Document Creation Services ArcGIS.com -> ArcGIS Explorer, Business Analyst Online Platform as a Service (PaaS) Application platform or middleware as a service that developers can build and deploy custom applications SQL Azure -> RDBMS ArcGIS.com -> Online API’s
5. Cloud Computing Components Infrastructure as a Service (IaaS) Encompasses the hardware and technology for computing power, storage, operating systems, or other infrastructure (shared data centers) Amazon Elastic Compute Cloud (EC2) Amazon Simple Storage Service (S3) Amazon Elastic Block Volumes (EBS) Amazon Relational Data Service (RDS) Delivered as off-premises, on demand services rather then dedicated, on-site resources.
7. Things To Understand Cloud Applications: Accessed by end-users Cloud Platforms: Used by developers Public Cloud: Code & data that live in Internet accessible data centers (Amazon, Microsoft, Google, etc.) The technology itself has no value. The value comes from how it is used!
8. What is Amazon AWS & EC2? Amazon Web Services provide Virtual Machines & Services for storing unstructured data, relational data and more. Amazon EC2 is a web service that enables you to launch and manage server instances in Amazon’s data centers. Instances are available in different sizes and configurations.
9. What is an Instance? It’s a Virtual Machine! Similar to what you might be working with now. Created from an Amazon Machine Image (AMI) Use an image that is already installed and setup Use one available from a different software vendor Microsoft, Oracle, IBM, Esri AMIs of ArcGIS Server and Geodatabase are available through the product: ArcGIS Server for AWS Pricing based on EC2 Compute Units EC2 Compute Unit (ECU) – One EC2 Compute Unit (ECU) provides the equivalent CPU capacity of a 1.0-1.2 GHz 2007 Opteron or 2007 Xeon processor.
10. Amazon EC2 – Standard Instances Small Instance: (Default) 1.7 GB of memory, 1 EC2 Compute Unit (1 virtual core with 1 EC2 Compute Unit), 160 GB of local instance storage, 32-bit platform Large Instance: 7.5 GB of memory, 4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each), 850 GB of local instance storage, 64-bit platform Extra Large Instance: 15 GB of memory, 8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each), 1690 GB of local instance storage, 64-bit platform * Instances of this family are well suited for most applications.
11. Amazon EC2 – High Memory Instances Extra Large Instance: 17.1 GB memory, 6.5 ECU (2 virtual cores with 3.25 EC2 Compute Units each), 420 GB of local instance storage, 64-bit platform Double Extra Large Instance: 34.2 GB of memory, 13 EC2 Compute Units (4 virtual cores with 3.25 EC2 Compute Units each), 850 GB of local instance storage, 64-bit platform Quadruple Extra Large Instance: 68.4 GB of memory, 26 EC2 Compute Units (8 virtual cores with 3.25 EC2 Compute Units each), 1690 GB of local instance storage, 64-bit platform * Instances of this family offer large memory sizes for high throughput applications, including database and memory caching applications.
12. Amazon EC2 – High CPU Instances Medium Instance: 1.7 GB of memory, 5 EC2 Compute Units (2 virtual cores with 2.5 EC2 Compute Units each), 350 GB of local instance storage, 32-bit platform Extra Large Instance: 7 GB of memory, 20 EC2 Compute Units (8 virtual cores with 2.5 EC2 Compute Units each), 1690 GB of local instance storage, 64-bit platform * Instances of this family have proportionally more CPU resources than memory (RAM) and are well suited for compute-intensive applications.
13. Amazon EC2 – Sample Pricing *An online calculator is available for more accurate pricing. http://calculator.s3.amazonaws.com/calc5.html
14. Demo… Where do I get started? Creating an AWS Account Using the AWS Management Console https://console.aws.amazon.com/ec2/home
15. Why Use Cloud Computing? While not everything will move into the cloud, nearly every organization will use, or is using, this approach in some way. For GIS users, the cloud opens a number of new possibilities. What are they? Why might they be better than what I am doing now? Why should I care?
17. Emerging Usage Patterns On-Premise System for daily use and editing Cloud is used for publishing
18. Emerging Usage Patterns Cache Cooking For 1 instance, a single mask was used to confine cache creation to a rectangular area. For 3 and 5 instances, the same mask was divided into 3 and 5 equal parts, one for each server * Cache throughput varies depending on factors related to working on Amazon Cloud.
19. Emerging Usage Patterns Amazon S3 Deployment – Disconnected Cache Local ArcGIS Server is used to create the map cache. Files are uploaded to S3 ArcGIS Server API’s (Flex, Silverlight, Javascript) are used to point to the cache files. Pros: Cheaper Cons: No query on this cache, setup another location for queries Cache completely cooked. No periodic update.
20. How Is Esri Using The Cloud? Providing users the ability to deploy ArcGIS Server on AWS. Built ArcGIS.com for offering tools and shared data for GIS applications. Building Cloud versions of applications: ArcGIS Explorer, ArcLogistics, and Business Analyst Online. ArcGIS Server is the platform for delivering GIS Services to software on other systems. Exposed as RESTful web services, SOAP web services. Consumed by clients written in various technologies (JavaScript, Adobe Flex, Microsoft Silverlight).
21. Why Deploy AGS In The Cloud? Easier Deployment: Esri provides a preconfigured AMI so you can create an EC2 VM from this AMI. Faster Deployment: In most organizations making a VM is a multi-step process that can take weeks. With AWS, this process can take minutes. Broad Availability: Accessible by anyone with an Internet connection. Better Performance: Through the scalability and bandwidth available to AWS
23. Benefits and Risks Depending on the industry, compliance and Governmental requirements must be met and secured Continuity of operations and disaster recovery Security standards (ISO 27001) Logs and audit trails Sarbanes-Oxley HIPPA
24. Benefits and Risks There are specific legal concerns when providing cloud services and consuming them Liability and recourse Intellectual property issues Terms on vendor transparency regarding location of recovery data centers When consuming cloud services it’s important to recognize the potential hazards and risks ahead of time.
26. Conclusion Cloud computing is here and it’s effects will be widespread. Esri is providing clear examples of how these technologies can be used: using cloud platform to provide new deployment options (ArcGIS Server on AWS). using cloud platform to support web sites & applications that provide broadly usable GIS data & tools (ArcGIS.com). offering cloud applications as alternatives to existing on-premises versions (ArcGIS Explorer, ArcLogistics, and Business Analyst Online). This shift will have some impact on your organization (if not already) in both GIS and/or IT. The time to understand this shift is now.
