Paperless Timesheet Management Project Anant Pednekar Anuradha Shringarpure Vidya Venkataraman CS 562 – Advanced Java Class Submitted To: Robert Zhu Date: July 13 th 2010

System Objective Paperless Timesheet Management System is a web-based time, effort and resource management solution. Simplifies time tracking and time keeping of employees. Enables the enterprise to manage people and projects better

Audience End Users : – Student employees – University employees

End Goal The end-goal would be to move the existing offline time tracking system at Herguan University to a user-friendly time tracking web application. Eventually incorporate the Google App Engine (GAE) model into utilizing the powerful cloud computing concept

What’s In It For Us? As a student project, our objective would be to make use of this opportunity to learn the cutting-edge technology like JSP, Servlets, Struts, JDO and GAE Cloud computing is the big thing right now. Using Google’s web application hosting services, we intend to get a deeper picture about the cloud computing infrastructure.

Architecture Diagram Client Browser (Renders the page) Web server (Google App Engine) Presentation Layer (Written in JSP, Servlets using Struts framework) Business Layer (Written in JDO) App Engine’s Datastore (Data tier provided by Google App Engine)

Technology Stack Front- end : JSP, Struts 2 framework, HTML/CSS ORM : JDO Web Server : Google App Engine Database : Google App Engine’s Data store

Development Tools Source code dev : Eclipse IDE with GAE plug-in Version Control : Subversion plug-in in Eclipse IDE Bug Tracking/Defect logging : JIRA

A Walk In The Clouds… New IT Buzzword!!! “… a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet” - Wikipedia “… a pay-per-use model for enabling available, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, services) that can be rapidly provisioned and released with minimal management effort or service provider interaction”- National Institute of Standards and Technology (NIST)

Cloud Computing Models Defined

Cloud Computing Delivery Models SaaS : "Software as a Service " deliver software as a service over the Internet, eliminating the need to install and run the application on the customer's own computers and simplifying maintenance and supportSoftware as a ServicesoftwareInternet PaaS : "Platform as a Service " deliver a computing platform and/or solution stack as a service, often consuming cloud infrastructure and sustaining cloud applications. It facilitates deployment of applications without the cost and complexity of buying and managing the underlying hardware and software layerscomputing platformsolution stack IaaS : "Infrastructure as a Service " delivers computer infrastructure, typically a platform virtualization environment as a service. Rather than purchasing servers, software, data center space or network equipment, clients instead buy those resources as a fully outsourced service.computerinfrastructure platform virtualization

Google App Engine Easy to build Easy to maintain Easy to scale

Google App Engine

Do-It-Yourself Hosting Maintenance Software patches/upgrades License fees Traffic and Utilization

Google App Engine To The Rescue SDK & “The Cloud” PAAS Hardware Networking Operating system Application runtime Java, Python Static file serving Services Fault tolerance Automatic Scaling Load balancing

Runtimes

Services

Portable

Admin Console

Development & Deployment Tools

Limitations Of Google App Engine Programming Model – Application runs in sandbox and cannot: Write to file system Make arbitrary network connections Use multiple threads/processes Perform long-lasting processing Permissions Know about other instances/applications Quotas (Request, In/Out bandwidth, CPU time, API calls) – Billable quotas Set by application owner to keep in budget – Fixed quotas Set by GAE to ensure integrity of the system

System Demo Task items achieved so far – Development Environment Setup – Knowledge Transfer Sessions – Database Design – Screen Shots

Future Course Of Action Data Model Mapping in JDO UI Development Testing Deployment