First review presentation

1,013 views
937 views

Published on

My first review report, created using Latex

Published in: Education, Technology
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
1,013
On SlideShare
0
From Embeds
0
Number of Embeds
6
Actions
Shares
0
Downloads
21
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

First review presentation

  1. 1. Design and Implementation of a ServiceMonitoring Console within a Service Oriented Architecture Framework Arvind Krishnaa .J 31508104017 Guided By Dr. Chitra Babu HOD/CSE SSN College of Engineering First Review - 23rd February, 2012
  2. 2. OLAP2Db Interface Data from each data center CAL log accumulated in PHX colo. Data in PHX colo stored in centralized data cube. Data from cube pushed onto relational DB, by OLAP2Db scripts. Figure: OLAP2Db Interface with Data loss occurs here. cube delay
  3. 3. Minimizing the data loss Run CAL cube data availability scripts. CALDb records were found to be consistent with static CAL data. Data loss was isolated to partioned relational database. 2/3 cron jobs pushing data to the database were idle. Once the cron jobs were restarted, the relational database synced the data accurately.
  4. 4. Minimizing the data loss Figure: Before cron jobs were Figure: After cron jobs were activated activated
  5. 5. SMC Vs TMC : Feature Comparison
  6. 6. Turmeric Monitoring Console Figure: Java Class Hierarchy
  7. 7. Data Collection Possibilities A real-time Cassandra cluster where metrics are stored. Metrics reader class reads data from each cluster. Offline aggregator accumulates the data. Metrics writer pushes back the data to each node. Previously stored data in Figure: Using Cassandra Storage each node is deleted No single point of failure
  8. 8. Data Collection Possibilities Implement a message queue on each server. This message queue will push the metric data onto a central database. This database acts as an aggregated storage provider. Single point of failure, at the centralized database. Figure: Using Message Queue
  9. 9. Minimizing the data loss Using OpenTSDB Distributed, scalable high performance time series database, implemented over HBase. Allows simple storage and retrieval of metrics. Easy to graph the trends. Difficult to set up hardware components. Complicated installation procedure.
  10. 10. Data Collection Workflow Figure: Activity diagram representing the data collection workflow
  11. 11. Implementation Schedule
  12. 12. References [1]Jeffrey Dean, Sanjay Ghemawat, Google Inc., MapReduce: Simplified Data Processing on Large Clusters, In Sixth Symposium on Operating System Design and Implementation(OSDI’04), San Francisco, CA, December, 2004 [2] Eben Hewitt, Cassandra: The Definitive Guide, OReilly Publications, November 2010. [3] eBay Open Source Project, Turmeric SOA platform, http: //www.ebayopensource.org/index.php/Turmeric/HomePage
  13. 13. References [4] eBay Open Source Project, Documentation of Turmeric SOA platform, https://www.ebayopensource.org/wiki/display/ TURMERICDOC110GA/Turmeric+Documentation+Overview [5] eBay Open Source Project, Turmeric Source Code, http://www.github.com/ebayopensource [6] Internal eBay documentation [7] Google Web Toolkit, http://code.google.com/webtoolkit [8] Apache Cassandra, http://cassandra.apache.org/

×