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Presentation Presentation Presentation Transcript

  • IBM SmartCloud Camp 2011 Presentation
    Team 3:
    Terry Chang
    Deepak
    Wai Phyo Kyaw
    Charlotte Ng
    Desmond See
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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)
  • 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
  • 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
  • Scenario 2: Intended Design
    New User Registration/Login
    APIs
    - our own Business Logic (authentication, creating new account in DB)
  • Scenario 2: Intended Design
    Dashboard for Customer
    ** First, Create DeveloperCloudClient to execute requests against the Cloud | DeveloperCloudClientgetClient()
  • Scenario 2: Intended Design
    Billing information
  • 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)
  • 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
  • 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
  • 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)
  • Scenario 2: Design Considerations
    Customers information security
    Standardization and automation
    User friendly interfaces
    Cost saving
  • 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
  • Scenario 3: Dummy Data
    Extracted, transformed and selected data from OLTP (ETL Process)
  • 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
  • Scenario 3: Generated Reports
    Expense and Revenue across Shifts
    Product Sales over Five Years
  • Scenario 3: Generated Reports
    Geospatial analysis of performance of Rainbow Food outlets
    for products, for staffing
  • 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)
  • 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
  • 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)
  • Thank you :)