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Optimizing Microservices in .NET 8: Performance, Security, and Scalability

Sohan Singh Chinthalapudi

Subject area: Science,Engineering and Technology  ·  Area of research: .NET

Abstract

The modern cloud-native application relies on a microservices architecture to develop applications through modules and achieve scalability and tolerance of faults. Many significant enhancements related to performance optimization, security improvements, and scalability features have been introduced in .NET 8. This paper examines the most effective techniques for optimizing .NET 8 microservices through containerization mechanisms, Kubernetes orchestration, and service mesh deployment strategies. This investigation shows how machine learning models can use historical water quality records to perform event prediction of contaminations while boosting treatment operation efficiency. The document provides solutions to important issues, including microservices resource management, service communication, and security vulnerabilities affecting microservices deployments.

Keywords

Microservices Optimization, .NET 8 Performance Tuning, Kubernetes and Service Mesh, Cloud Security in Microservices, Machine Learning in Water Quality Analysis

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How to cite this paper

Sohan Singh Chinthalapudi "Optimizing Microservices in .NET 8: Performance, Security, and Scalability" Iconic Research And Engineering Journals Volume 7 Issue 7 2024 Page 641-655
Sohan Singh Chinthalapudi "Optimizing Microservices in .NET 8: Performance, Security, and Scalability" Iconic Research And Engineering Journals, vol. 7, no. 7, Jan. 2024
Sohan Singh Chinthalapudi (2024). Optimizing Microservices in .NET 8: Performance, Security, and Scalability. Iconic Research And Engineering Journals, 7(7).
Sohan Singh Chinthalapudi "Optimizing Microservices in .NET 8: Performance, Security, and Scalability" Iconic Research And Engineering Journals, vol. 7, no. 7, Jan. 2024.
@article{1707655,
      author = {Sohan Singh Chinthalapudi},
      title = {Optimizing Microservices in .NET 8: Performance, Security, and Scalability},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {7},
      number = {7},
      pages = {641-655},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1707655.pdf},
      abstract = {The modern cloud-native application relies on a microservices architecture to develop applications through modules and achieve scalability and tolerance of faults. Many significant enhancements related to performance optimization, security improvements, and scalability features have been introduced in .NET 8. This paper examines the most effective techniques for optimizing .NET 8 microservices through containerization mechanisms, Kubernetes orchestration, and service mesh deployment strategies. This investigation shows how machine learning models can use historical water quality records to perform event prediction of contaminations while boosting treatment operation efficiency. The document provides solutions to important issues, including microservices resource management, service communication, and security vulnerabilities affecting microservices deployments.},
      keywords = {Microservices Optimization, .NET 8 Performance Tuning, Kubernetes and Service Mesh, Cloud Security in Microservices, Machine Learning in Water Quality Analysis},
      month = {January},
  }