CloudMind Autonomous AI-Driven Industrial Analytics
Keywords:
Scalable AI, big data analytics, industry cloud operations, autonomous operation, objective-oriented operationAbstract
Scalable artificial intelligence (AI) and big data analytics methods are considered that enable the autonomous operation of cloud services configured for specific industry sectors. Recent research has shown how such services can be architected in a modular manner as interoperable microservices within a microservices ecosystem. The focal decision-centric operations are enabled by dissemination and consumption of application-specific information derived from system data through predictive models. Scalability covers a range of areas including service horizontal and vertical management, data locality considerations for edge devices, service latency, state consistency, data properties such as volume, and real-time versus batch constraints. The provision of cloud services within the industrial sector necessitate adherence to several standards and regulations through data governance, security, and compliance processes.
A framework targeting autonomous operation of cloud services is utilized to demonstrate the applicability and contribution of scalable AI and big data analytics. In addition to providing practical implementations of components required for autonomous service operation within a particular industrial sector, the research highlights new ways of utilizing established concepts and methods from AI, big data analytics, and distributed systems to achieve application-focused objectives in these contexts. Operational benefits accrue from automation of the decision-making processes concerning the cloud services. Responsive adaptation of models and procedures to optimize key business objectives are also enabled while satisfying the foreseeable requirements for service provision.
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