1 / 11

Business Objective Oriented Problem Determination and Mitigation

Business Objective Oriented Problem Determination and Mitigation. Presented by: Opher Etzion – HRL The Team members: Dagan Gilat, Segev Wasserkrug, Natalia Razinkov, Sarel Aiber, Aviad Sela, Ariel landau. Business Objective Oriented Problem Prediction and Mitigation.

chet
Download Presentation

Business Objective Oriented Problem Determination and Mitigation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Business Objective Oriented Problem Determination and Mitigation Presented by: Opher Etzion – HRL The Team members: Dagan Gilat, Segev Wasserkrug, Natalia Razinkov, Sarel Aiber, Aviad Sela, Ariel landau

  2. Business Objective Oriented Problem Prediction and Mitigation • Current goals for managing an IT infrastructure site typically focus on IT measuressuch as ensuring that the site availability is 99.9% • However, what the enterprise really cares about are the business objectives, such as total profit • Therefore, the following is required: • The ability to predict when a problem will significantly impact the business objectives • The ability to mitigate the problem so as to minimize its adverse effect on the business objective

  3. What does a solution require? • An economic model of business transactions (gains, explicit penalties, hidden penalties – customer deserting, reputation) • A model of the IT infrastructure • A model of impact analysis – how do problems impact the business objectives…

  4. Requirements – drilling down one more level… • We need the ability to optimize business goals based on dynamic knowledge • We need the ability to model the relationships among IT and business model • We need the ability to identify problems that impact the business objectives in order to re-optimize the IT in order to mitigate these problems

  5. ARAD architecture

  6. AMOBO problem detection and mitigation process

  7. Proactive Significant Problem Detection • A significant problem is defined as a problem which will have a significant impact on the business objectives • In order to decide whether a problem is significant, the following is carried out: • Whenever the monitoring tools detect a problem, i.e. server failure, a copy of the simulation model is created to reflect this problem • The business objective results as predicted by the updated model are compared with the business objective results as predicted by the previous model using statistical tests – e.g. the Chi-squared test • If according to the statistical tests the difference between the two is significant – the problem is deemed significant

  8. Proactive Significant Problem Mitigation • The mitigation of the problem takes place as follows: • The previous simulation model is replaced with the updated model • Re-optimization is carried out • Alternatively, a list of problems deemed significant may be defined, that would always result in re-optimization

  9. Significant Problem Detection and Mitigation – Case Study • Scenario: • eTrading Web site • Customers have two important attributes: • Average spending amount – High, Medium, Low • Average response time SLA – Platinum, Gold, Regular (WSLA) • Business Objective – optimize income generated from customers according to the following rules: • There is a 2% commission on each stock trade • Penalties are paid for each SLA violation • A flat fee is paid by each customer with a SLA

  10. Significant Problem Detection and Mitigation – Case Study Results • System was optimized for two servers • Two IT failures occur: • Failure of a CPU, which is not deemed significant • Failure of a disk, which causes one of the servers to fail – significant problem • This failure is recognized and the system is re-optimized (Initiating re-optimization process as a result of significant problem detection) • The business objectives results both before and after the failure were : • Conclusion: Recognizing this problem as significant and re-optimizing the IT policy, results in significantly higher profit than the profit generated by remaining with the original policy

  11. Summary • The need for business objective based problem determination and mitigation was introduced • The requirements enabling such problem determination were defined • An architecture, process and algorithms enabling the both problem determination and mitigation were introduced • A case study and demo were shown

More Related