The field of cloud computing and autonomous systems is moving towards greater interoperability and automation. Researchers are developing innovative solutions to overcome the barriers that prevent the full exploitation of cloud technology, such as provider lock-in and the lack of expertise among consumers. One of the key directions is the development of vendor-neutral metrics and intelligent knowledge-based systems that can automatically translate service-level agreements into measurable objectives. Another area of focus is the creation of autonomous agents that can orchestrate complex tasks and make decisions based on meta-learning. These advancements have the potential to enable more efficient and effective use of cloud resources, as well as improved decision-making and automation. Noteworthy papers include:

• A paper that presents a solution to the problem of automatically translating SLAs into vendor-neutral metrics, enabling cloud consumers to exploit the advantages of multi-cloud environments.
• A survey that introduces a systematic hierarchical taxonomy for data agents, clarifying capability boundaries and responsibility allocation, and offering a structured review of existing research.
• A paper that proposes an Agentic Meta-orchestrator for handling multiple tasks and scalable agents in copilot services, demonstrating its effectiveness through two production use cases.