Kaslin Fields

What's the most important skill you can develop right now? I'd argue it's persuasive communication skills. I study this topic and practice it here, with my team, and with customers. These are the books that have impacted me the most: seroter.com/2026/02/25/the…

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We'd like to announce that @kubernetesio WG Serving has succeeded and will be disbanded! Thank you everyone who have participated and contributed to the discussions and initiatives! The Kubernetes Working Group Serving was created to support development of AI inference stack on Kubernetes. The goal of this working group is to ensure that the Kubernetes is an orchestration platform of choice for inference workload. This goal was accomplished and we are disbanding the working group. The WG Serving formed workstreams to collect requirements from various model servers, hardware providers, and inference vendors. This work resulted in a common understanding of inference workload specifics and trends and laid the foundation for improvements across many SIGs in Kubernetes. The working group oversaw several key evolutions to the role of load balancing and workloads - the inference gateway was adopted as a request scheduler, multiple groups have worked to standardize AI gateway functionality, and early inference gateway participants went on to seed agent networking in SIG Network. The use cases and problem statements informed the design of AIBrix. And many of the unresolved problems in distributed inference - especially benchmarking and recommended best practices - have been picked up by the @_llm_d_ project which hybridizes the infrastructure and ML ecosystems and is better able to steer model server co-evolution. In particular, we believe llm-d and AIBrix represent more appropriate forums for driving requirements to Kubernetes SIGs than this working group. llm-d's goal is to provide well-lit paths for achieving state-of-the-art inference and aims to provide recommendations that can compose into existing inference user platforms. AIBrix provides a complete platform solution for cost efficient LLM inference. More details can be found in the announcement email: groups.google.com/a/kubernetes.i… Cheers, Yuan Tang On behalf of Kubernetes WG Serving Co-Chairs