Intelligent Orchestration of Cloud-Native Applications Using Google Cloud Platform and Microservices-Based Architectures
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V5I4P111Keywords:
Cloud-native applications, Google Cloud Platform (GCP), Kubernetes, DevOps, OrchestrationAbstract
The emergence of cloud computing has essentially changed software engineering, where cloud-native applications have provided elastic, scalable and resilient services. The research work describes an intelligent orchestration strategy for managing cloud-native applications that utilise the microservices architecture on the Google Cloud Platform (GCP). The orchestration layer has the capability of connecting DevOps pipelines, Kubernetes deployments, service meshes, and intelligent automation to AI-enabled performance-tuning and resource-effectiveness analytics. This paper discusses architectural solution patterns, key services on GCP, container-based orchestration through GKE, serverless integration, and monitoring systems. The methodology is based on the application of real-world benchmarks and features the orchestration efficiency, cost optimization and scalability. The findings show that an intelligent orchestration model can generate better resource utilization of up to 35 percent, 28 percent reduced operational expenditures, and fault tolerance, together with a high deployment rate, giving a large jump. The issues are pointed out in discussions concerning the prevailing limitations, design tradeoffs, and future challenges of enterprise cloud-native adoption. This work can be used as a guide by cloud architects, DevOps specialists, and scientists who want to study cloud-native patterns and orchestration modalities on GCP
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