INTELLIGENT ENTERPRISE CLOUD DISTRIBUTED SYSTEMS FOR NEXT GENERATION DATA ENGINEERING
DOI:
https://doi.org/10.65009/2trrkv92Keywords:
Intelligent Cloud Systems, Distributed Enterprise Computing, Data Engineering Pipelines, AI-Driven Orchestration, Adaptive Workload Management, Policy-Aware Resource Allocation, Real-Time Analytics, Multi-Cloud Governance.,,Abstract
Modern business requires cloud-oriented architectures arduous to support extremely huge,
heterogeneous, and dynamically dynamic data engineering loads with dependability, savvy,
and government consciousness. Traditional architectures are mainly based on the principle of
scalability and throughput but fail to autonomously scale to the volatility of workloads, multi
cloud heterogeneity and real-time decision-focused computing. This paper provides a smart
enterprise cloud distributed architecture that combines AI-based coordination, policy-based
resource placement, workload scheduling based on behavioral dynamics and self-resilience,
and self-protect. It is an architecture that relies on predictive analytics to predict the changes in
demand, context-aware controllers to coordinate compute, storage, and network, and self
healing to reduce the inconvenience of the service. Data intelligence layer also improves
tracking of the lineage, quality as well as preserving compliance within dispersed settings. The
system also enhances secure multi-tenant execution, latency-sensitive data pipelines, and
learning-based optimization, which improves with the working conditions. The suggested
paradigm develops a structurally unified base of next-generation data engineering, which
allows consistent performance, effective use, and reliable governance of scattered enterprise
clouds. This policy-oriented, future-oriented and intelligent ecosystem responds to the new
requirements of a real-time analytics, mission-critical application, and future enterprise
innovation, positioning the framework as a healthy guide to sustainable large scale cloud data
engineering.
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