1. IBM SmartCloud Camp 2011 Presentation Team 3: Terry Chang Deepak Wai Phyo Kyaw Charlotte Ng Desmond See

2. Scenario 1: Problem Definition To design 3-tier Application with features: load balancing failover redundancy scalability secure Solve single point of failure in our systems

3. Scenario 1: Architectural Design IBM HTTP SERVER with WAS Plugin IBM HTTP SERVER with WAS Plugin LOADBALANCER LOADBALANCER INTERNET Websphere Application Server Cluster App: Clone 1 App: Clone 2 Node 1 FIREWALL App: Clone 3 App: Clone 4 IBM DB2 Server Cluster IBM SAN (Redundant Disks: RAID 10) Instance 1 Node 2 stores data Instance 2 Deployment Manager *instances will be created in different data centres around the world

4. Scenario 1: Configuration in Instances Assign Virtual IP Install Pacemaker Configure Heartbeat communication layer Provision at least 2 number of VMs instances and get ready In time of failure: Reconfigure Virtual IP for the alive instance Automatic direct traffic to the alive nodes Fault-tolerance, fast recovery times, session replication

5. Scenario 1: Advantages of IBM Cloud Systems What and how did we leverage IBM Technologies? IBM HTTP Server Workload Management + Loadbalancer IBM Websphere Application Server Clustering, Automatic failover IBM DB2 (with HADR/v9.5+) Database Client Nodes Clustering with HADR SQL Replication, Shared Disks/SAN Support DB2 HA: DB2 High Availability Instance Configuration Utility (db2haicu) IBM Storage Area Network SAN: RAID 1 or RAID 10 (not RAID 5) Shared Disk redundancy

6. Scenario 1: Design Considerations Different Physical Locations of Instances Automatic Trigger, Notification and Configuration Data integrity after recovery/during failover/in SAN Security in configuring/writing scripts

7. Scenario 1: Project Management Scope & Deliverables: Complete implementation of high availability data recovery three-tier application on SCE : from architecture to scripting configurations Configure WAS, DB2 instances and SAN nodes? Configure automated scripts, Provision monitoring instances Proposed Timeline: 100 man hours 5 persons team Resource Estimation: 2 x firewall+loadbalancer, 2x IBM HTTP Server, 2x WAS Nodes, 2x DB2 Instances, 2x SAN Sites Test Plan Test instances failure (kill the services), Test recovery process (automation, time, data integrity)

8. Scenario 1: Project Risks Technical Configured incorrectly during failover and recovery Data integrity issues, session not replicated, data not copied properly SCE issues? Recovery time exceeds minimum as stated in SLA Team Inadequate skills, inexperience Manpower shortage

9. Scenario 2: Problem Definition To build a scalable and multi-tenancy web portal as a platform Customer self-management portal system To provide SaaS to customer as an Independent Software Vendor Simplified and standardized technical setup of the software for the customers

10. Scenario 2: Intended Design New User Registration/Login APIs - our own Business Logic (authentication, creating new account in DB)

11. Scenario 2: Intended Design Dashboard for Customer ** First, Create DeveloperCloudClient to execute requests against the Cloud | DeveloperCloudClientgetClient()

13. Scenario 2: Intended Design Billing information

14. Scenario 2: Project Management Scope Web portal DB2 – (customer authentication and data storage) Proxy server Business logic Deliverables Create portal system with fully functioning interface Create database integrated system + a relational database Add security features to protect customers’ data Modularized and loosely coupled system(Use of RESTful Services)

15. Scenario 2: Test Process Create multiple same Customer IDs Create > 5 instances of VM which is over the limitation Create Failover at either the SCE side or Proxy server. Give wrong user credentials Accuracy of the billings

16. Scenario 2: Project Risks Technical Security – authentication between users and proxy server or proxy server and SCE Failover and workload balance at SCE, proxy server Connection timeout between client, proxy and SCE Configuration error in creating the instances of the vm or application. SCE unable to create instances or access Team Skill and knowledge inadequate Illness, MC Underestimation of projected timeline Service level agreement

17. Scenario 2: Advantages of Cloud Systems Low total cost of ownership of the equipment Flexible usage of the services : Pay Per Use, Utility Billing High availability Handle Variable Demand (Dynamic Load) Pervasiveness (Anytime, anywhere)

18. Scenario 2: Design Considerations Customers information security Standardization and automation User friendly interfaces Cost saving

19. Scenario 3: Problem Definition Aim: Provide information to managers and identifying poor/well-performing branches (acc to branch, then country, then continent) Business problem: Unable to make adequate decisions because data is confusing and not presented in a readable format for further analysis

20. Scenario 3: Dummy Data Extracted, transformed and selected data from OLTP (ETL Process)

21. Scenario 3: How Cognos can help Rainbow Food Shopping experience: Identify, report on and analyze trends Use predictive models and association rules Gain insight into customer perceptions of service, store, products and merchandising Promotion and merchandise planning: Optimize merchandise levels and inventory Conduct market basket analysis Develop plans for key financial indicators Smarter operations: Set, measure and monitor key performance metrics based on standard financial statements. Use predictive models to improve recruitment and optimize staffing decisions. Gain visibility into key metrics across the chain: sales, labor, inventory and promotions Monitor turnover and employee productivity

22. Scenario 3: Generated Reports Expense and Revenue across Shifts Product Sales over Five Years

23. Scenario 3: Generated Reports Geospatial analysis of performance of Rainbow Food outlets for products, for staffing

24. Scenario 3: Intelligence Staff underutilization: understand which area is understaffed during particular shifts with maps and other outlets’ realtime data, we can relocate staff instead of retrenching or letting them idle Non-selling products: different regions have different tastes varies from time to time as well remove unpopular food items from menu analyze new food trends Mashup (interconnected) intelligence: import external datasets (eating habits, demographics, research agencies)

25. Scenario 3: Leveraging Cloud Systems Why Cognos, instead of Excel? can handle large datasets can draw data from different sources real-time multiple parties can gain insights at the same time, share data all stakeholders can access anytime anywhere use LotusLive for collaboration (sharing of reports) more transparency

26. Scenario 3: Project Management Scope: Create intelligent reports based on fusion of diverse data Deliverables: User-friendly, collaborative, interactive reports Timeline: 1 week (training) + 2 weeks (collection) + 1 weeks (report design) + 2 weeks (validation of reports) Resources: Reliable datasets, BI Training and Tools, Commitment of analysts Risks: Unfamiliar with Cognos, Garbage data, Context of data (food poisoning)

27. Thank you :)