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CNCF and SlashData Report Shed Light on AI Tools in Cloud Native Ecosystems

In a recent report released by the Cloud Native Computing Foundation (CNCF) in partnership with SlashData, significant insights were uncovered regarding the adoption of leading AI tools within cloud native ecosystems. This report offers a comprehensive analysis of AI inference, ML orchestration, and agentic AI platforms, showcasing the tools and strategies developers are gravitating towards in today's digital landscape.

Key Findings from the Report

The report identifies four primary AI tools that have gained substantial traction among developers in cloud environments: NVIDIA Triton, Metaflow, Airflow, and Model Context Protocol (MCP). These tools have shown outstanding maturity and developer confidence, indicating a clear shift in the technological preferences of organizations leveraging AI capabilities.

AI Inference Tools

Within the realm of AI inference, NVIDIA Triton emerged as a frontrunner, earning the highest maturity and usefulness ratings among developers. It was noted that 50% of users rated Triton with a 5-star maturity score and 41% with a 5-star usefulness score, reflecting its growing reliance in production-grade AI workloads. Other notable mentions included DeepSpeed, TensorFlow Serving, and BentoML, which also received positive endorsements, reinforcing their value in enterprise settings.

Conversely, Adlik, while less utilized, garnered a remarkable recommendation score of 92%, highlighting how niche tools that meet specific enterprise needs can cultivate loyal user bases despite not being dominant overall. These findings emphasize the necessity for AI tools that cater to specialized requirements, such as model optimization and hardware-centric deployments.

ML Orchestration Tools

When examining ML orchestration, Airflow and Metaflow have emerged as leaders, with Metaflow achieving top marks for maturity (84% received 4 or 5 stars) and Airflow excelling in both usefulness and recommendation scores. Impressively, Airflow did not receive any low ratings, a testament to its growing reputation in the developer community. Tools like BentoML have shown versatility by earning ratings in both inference and orchestration categories, indicating that multi-functional tools can succeed even in competitive markets.

Moreover, CNCF projects Argo Workflows and Kubeflow were categorized as trials, suggesting they are on a growth trajectory but still not fully recognized as leading solutions.

Agentic AI Platforms

The adoption of agentic AI platforms has also gained traction, with MCP and Llama Stack classified as adopt tools. MCP achieved a remarkable 80% combined score for usefulness among developers, indicating a strong foothold in enterprise applications, such as AI-driven customer support services. Meanwhile, Agent2Agent (A2A), although less mature, boasts an exceptional recommendation rate of 94%, demonstrating that developers are enthusiastic about its future potential, even if it's still developing its capabilities.

The Importance of Cloud Native Principles

One of the compelling takeaways from the report is the necessity of cloud native principles for AI and ML systems. Even developers who do not explicitly identify as cloud native are increasingly incorporating these architectures into their AI systems. Presently, it is estimated that 41% of AI/ML developers recognize themselves as cloud native, a percentage expected to rise as more organizations embrace these models.

Chris Aniszczyk, CTO of CNCF, remarked on the changing landscape: "Organizations building and operating AI systems can't treat tooling the way they did five years ago. Cloud native principles are foundational not just for backend apps but also for inference pipelines and agentic AI systems. By selecting technologies labeled 'adopt', organizations mitigate risks and enhance productivity."

The findings from this report will be elaborated upon during KubeCon + CloudNativeCon North America 2025, taking place in Atlanta, where further discussions on the evolution of cloud native technologies will unfold.

Conclusion

The CNCF and SlashData report paints a vivid portrait of the current AI tooling landscape in cloud native environments. As developers seek more reliable and effective solutions, focusing on technology rated as 'adopt' could be key for organizations aiming to thrive in a competitive AI-driven market. This increased attention towards AI tool maturity and developer trust underscores the need for continuous innovation and adaptation within the industry.