M.Sc. Anshul Jindal 

Technische Universität München Informatik 10

Lehrstuhl für Rechnerarchitektur & Parallele Systeme (Prof. Schulz)

Boltzmannstr. 3 85748

Garching b. München

Email: anshul.jindal[at]tum.de

Room: 01.04.057

LinkedIn, GitHub, Google Scholar

 

Research Interests

  • Resource management of Containers.
  • Performance Modeling of Microservices.
  • Autoscaling (Kubernetes HPA, AWS Autoscaling).
  • Anomalies detection, root cause analysis and predictive maintenance for Cloud Infrastructure. 
  • Functions scheduling on hetrogenous platforms in a FaaS cluster. 

Education

 

Publications

  • [ 2020 ] Fan, C.; Jindal, A. and Gerndt, M. (2020). Microservices vs Serverless: A Performance Comparison on a Cloud-native Web Application. In Proceedings of the 10th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER Link
  • [ 2020 ] Espe, L.; Jindal, A.; Podolskiy, V. and Gerndt, M. (2020). Performance Evaluation of Container Runtimes. In Proceedings of the 10th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER Link
  • [ 2020 ] A. Jindal, B. Strahm, V. Podolskiy and M. Gerndt, "Windsurfing with APPA: Automating Computational Fluid Dynamics Simulations of Wind Flow using Cloud Computing," 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), Västerås, Sweden, 2020 Link
  • [ 2020 ] A. Jindal, M. Gerndt, M. Bauch and H. Haddouti, "Scalable Infrastructure and Workflow for Anomaly Detection in an Automotive Industry," 2020 International Conference on Innovative Trends in Information Technology (ICITIIT), Kottayam, India, 2020. Link
  • [ 2019 ] A. Jindal, V. Podolskiy, M. Gerndt  "Performance Modeling for Cloud Microservice Applications" ICPE '19 Proceedings of the 2019 ACM/SPEC International Conference on Performance Engineering, Mumbai, India, 2019. Link
  • [ 2019, Patent ] Singh, Vikram, Anshul Jindal, Saurabh Pradeep Bondarde, and Aishwarya Ravichandran. "System and method of orchestrating execution of commands in a non-volatile memory express (NVMe) device." U.S. Patent 10,372,376, issued August 6, 2019. Link
  • [ 2018 ] V. Podolskiy, A. Jindal, M. Gerndt and Y. Oleynik, "Forecasting Models for Self-Adaptive Cloud Applications: A Comparative Study," 2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), Trento, Italy, 2018 Link
  • [ 2018 ] Vladimir Podolskiy, Anshul Jindal and Michael Gerndt. "IaaS Reactive Autoscaling Performance Challenges". The 2018 IEEE International Conference on Cloud Computing (CLOUD 2018). Link
  • [ 2018 ] Anshul Jindal, Vladimir Podolskiy, and Michael Gerndt. 2018. "Autoscaling Performance Measurement Tool". In Companion of the 2018 ACM/SPEC International Conference on Performance Engineering (ICPE '18). ACM, New York, NY, USA Link
  • [ 2017 ] Anshul Jindal, Vladimir Podolskiy and Michael Gerndt. 2017. "Multilayered Cloud Applications Autoscaling Performance Estimation". In Proceedings of the 2017 IEEE 7th International Symposium on Cloud and Service Computing. IEEE. Link

 

Work Experience

  • [ March 2017 - November 2018 ] Student assistant at the Chair of Computer Architecture & Parallel Systems, TUM
  • [ July 2014 -  August 2016 ] Senior Software Engineer at Samsung R&D Institute, Bangalore India. Involved in the design and development of the firmware for PCIe based NVMe Solid State Drives which includes the development of Reservation and Virtualization feature (SR-IOV) for a multifunction/ multi controller architecture based Solid state drive (Samsung SSD, PM1725).

 

Teaching