| Optimizing Load Balancing and Autoscaling
for Large Language Model (LLM) Inference on Kubernetes |
David Gray |
| Engaging the KServe Community, The Impact of
Integrating a Solutions with Standardized CNCF Projects |
Adam Tetelman, Taneem Ibrahim, Johnu George, Tessa Pham, Andreea Munteanu |
| Advancing Cloud Native AI Innovation Through
Open Collaboration |
Yuan Tang |
| Unlocking Potential of Large Models in
Production |
Yuan Tang, Adam Tetelman |
| WG Serving: Accelerating AI/ML Inference
Workloads on Kubernetes |
Yuan Tang, Eduardo Arango Gutierrez |
| Best Practices for Deploying LLM Inference,
RAG and Fine Tuning Pipelines |
Meenakshi Kaushik, Shiva Krishna Merla |
| Production AI at Scale: Cloudera's Journey
Adopting KServe |
Zoram Thanga, Peter Ableda |
| From Bash Scripts to Kubeflow and
GitOps: Our Journey to Operationalizing ML at Scale |
Luca Grazioli, Dennis Ohrndorf |
| Production-Ready AI Platform on
Kubernetes |
Yuan Tang |
| Fortifying AI Security in Kubernetes
with Confidential Containers |
Suraj Deshmukh, Pradipta Banerjee |
| Platform Building Blocks: How to Build ML Infrastructure with
CNCF Projects |
Yuzhui Liu, Leon Zhou |
| Distributed Machine Learning
Patterns from Manning Publications |
Yuan Tang |
| KubeCon 2019: Introducing KFServing:
Serverless Model Serving on Kubernetes |
Dan Sun, Ellis Tarn |
| KubeCon 2019: Advanced Model Inferencing
Leveraging KNative, Istio & Kubeflow Serving |
Animesh Singh, Clive Cox |
| KubeflowDojo: KFServing - Production Model
Serving Platform |
Animesh Singh, Tommy Li |
| NVIDIA: Accelerate and Autoscale
Deep Learning Inference on GPUs with KFServing |
Dan Sun, David Goodwin |
| KF Community: KFServing - Enabling
Serverless Workloads Across Model Frameworks |
Ellis Tarn |
| KubeflowDojo: Demo - KFServing End to End
through Notebook |
Animesh Singh, Tommy Li |
| KubeflowDojo: Demo - KFServing with Kafka
and Kubeflow Pipelines |
Animesh Singh |
| Anchor
MLOps Podcast: Serving Models with KFServing |
David Aponte, Demetrios Brinkmann |
| Kubeflow 101: What is KFServing? |
Stephanie Wong |
| ICML
2020, Workshop on Challenges in Deploying and Monitoring Machine Learning Systems : Serverless
inferencing on Kubernetes |
Clive Cox |
| Serverless Practitioners Summit 2020:
Serverless Machine Learning Inference with KFServing |
Clive Cox, Yuzhui Liu |
| MLOps Meetup: KServe Live Coding Session
|
Theofilos Papapanagiotou |
| KubeCon AI Days 2021: Serving Machine
Learning Models at Scale Using KServe |
Yuzhui Liu |
| KubeCon 2021: Serving Machine Learning
Models at Scale Using KServe |
Animesh Singh |
| KubeCon China 2021: Accelerate Federated
Learning Model Deployment with KServe |
Fangchi Wang & Jiahao Chen |
| KubeCon AI Days 2022: Exploring ML Model
Serving with KServe |
Alexa Nicole Griffith |
| KubeCon AI Days 2022: Enhancing the
Performance Testing Process for gRPC Model Inferencing at Scale |
Ted Chang, Paul Van Eck |
| KubeCon Edge Days 2022: Model Serving at the
Edge Made Easier |
Paul Van Eck |
| KnativeCon 2022: How We Built an ML
inference Platform with Knative |
Dan Sun |
| KubeCon EU 2023: The state and future of cloud native model
serving |
Dan Sun, Theofilos Papapanagiotou |
| Kubeflow Summit 2023: Scale your Models
to Zero with Knative and KServe |
Jooho Lee |
| Kubeflow Summit 2023: What to choose?
ModelMesh vs Model Serving? |
Vaibhav Jain |