Autonomous Financial DevOps Using Agentic AI in Cloud-Native Enterprise Environments
DOI:
https://doi.org/10.64137/31079458/IJCSEI-V2I3P102Keywords:
Cloud-Native Financial DevOps, Agentic FinOps Systems, Autonomous Financial Operations, Risk-Based Reliability Engineering, AI-Driven FinOps Analytics, Cloud Cost Optimization, Financial Governance Frameworks, Data-Driven Decision Systems, DevOps Risk Management, Enterprise FinOps ArchitectureAbstract
Modern cloud-native Financial DevOps should harness the full predictive and optimizing power of data and analytics. Organizations need sufficient and suitably specialized expertise and experience to implement Financial DevOps that are agentic, autonomous, and orchestrated in support of a senior business executive, while ensuring observability and risk management. These capabilities allow for the migration away from traditional budgeting cycles and resource-allocation models towards the establishment of cloud-native consumption-based FinOps at the enterprise level. A framework for Risk-based Reliability Engineering supports quantifying and mitigating the operational risk introduced by autonomy. Ethical, legal, and governance considerations relevant to implementation define an agentic fiduciary office responsible for ensuring suitable design and implementation balanced with sufficient and suitably specialized expertise and experience. While many technical stakeholders in cloud-native FinOps teams are naturally drawn to Cloud FinOps principles and processes, benefits would accrue from having others take on distinct business-facing Agentic AI-Driven Autonomous Financial DevOps responsibilities, thus allowing the business and technical sides of the organization to communicate more easily around financial topics. Achieving seamless Cloud Financial Operations (FinOps) delivery requires the establishment of sound Data Governance, Security, and Compliance capabilities; permanent focus on sufficient Data Quality; harmonious complementarity of the Cloud FinOps technical stack with Data Analytics and decision-making tools; a Clear Decision-Making Framework suited to Data-driven Digital Business Operations; incorporation of Risk-based Reliability Engineering within DevOps; and Agentic AI-Driven Autonomous Financial DevOps.
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