Publications

Patents

Issued:
  • USPTO - 14030 Path Selection in Hybrid NetworksUtility-ORGUS (8/9/2016)
  • USPTO - 13148 Dynamic Border Line Tracing for Tracking Message Flows Across Distributed Systems (1/3/2017)
  • USPTO - 13062 Transparent Performance Inference of Whole Software Layers and Context Sensitive Performance Debugging (6/14/2016)
  • USPTO - 13035 Method and Apparatus for managing Hybrid Network Systems (9/20/2016)
  • USPTO - 12155 Guarding a Monitoring Scope and Interpreting Partial Control Flow (10/18/2016)
  • USPTO - 12082 Method and System for Computer Assisted Hot-Tracing Mechanism (11/8/2016)
  • USPTO - 12049 Blackbox Memory Monitoring with a Calling Context Memory Map and Semantic ExtractionUtility (4/7/2015)
  • USPTO - 12016 Efficient Unified Tracing of Kernel and User Events with Multi-Mode Stacking (11/25/2014)
  • USPTO - 12010 Method and Apparatus for Correlated Tracing with Automated Multi-Layer Function Instrumentation Localization (7/28/2015)
  • Japan Patent Office - 13035J Hybrid Network Management (11/10/2015)
Pending:

Pending patents available on request.

Recent Posts

This is a reading list I have prepared for Large Scale Systems Debugging and Monitoring The following is a list of papers and recent work done in different areas in Large scale Application Debugging and Monitoring. The main focus is Section 2 Analytics, with topics covered in Section 1 Monitoring section as an enabling mechanism. Section 3 talks about Testing for completion’s sake Section 1: Monitoring Buck, Bryan, and Jeffrey K.

CONTINUE READING

If you are looking into cloud infrastructures, and a basic understanding of how existing cloud computing frameworks work and the functionality they provide, I would suggest going through Salman. A. Baset’s tutorial from SoCC 2012. Conferences: Top Tier Distributed Systems Conferences: ICDCS, SoCC Related Systems Conferences: OSDI, SOSP, NSDI, Usenix ATC Section 1: Introduction and Overview Above the Clouds: A Berkeley View of Cloud Computing: M.

CONTINUE READING

Projects

NGLA: Next Generation Log Analytics

Most modern day softwares generate human readable logs for developers/administrators to understand and realize the cause of any error or behavior of the system. However, both the volume, velocity and non-uniform log formats make it difficult for administrators to easily find root-cause of errors in their systems. NGLA is a log analytics framework which automatically detects log patterns and leverages these patterns to give state-of-the-art automated real-time log anomaly detection

CLUE

Modern computer systems, from single servers to large cloud deployments, generate billions of events that reflect the state and operation of the system. CLUE provides a black-box, unsupervised debugging tool to mine event patterns and diagnose performance issues in these systems. CLUE uses novel data mining technologies for automated information retrieval and a state-of-the-art debugging toolset to integrate and profile event transactions.

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