kfserving
community
| kfserving | community | |
|---|---|---|
| 1 | 1 | |
| 2,113 | 150 | |
| - | 0.0% | |
| 10.0 | 7.7 | |
| about 1 year ago | 4 days ago | |
| Python | Jsonnet | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
kfserving
-
How do we assign pods properly so that KFServing can scale down GPU Instances to zero?
We are using KFServing as well. KFServing allows us to auto-scale our GPU up and down, specifically scaling to zero when its not in use. The components in KFServing also get assigned to GPU nodes when applying them to our cluster.
community
-
How can we read variables from file and use them in promql?
However I am not able to figure it out, how can I feed the string xyz_stack_1 to grafana. I have setup docker-compose.yaml file to start up all the containers. The configuration is done through prometheus.yaml, grafana.ini, dashboards.yaml and datasources.yaml
What are some alternatives?
soopervisor - ☁️ Export Ploomber pipelines to Kubernetes (Argo), Airflow, AWS Batch, SLURM, and Kubeflow.
kserve - Standardized Serverless ML Inference Platform on Kubernetes
pipelines - Machine Learning Pipelines for Kubeflow
mosec - A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
couler - Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
examples - 📝 Examples of how to use Neptune for different use cases and with various MLOps tools
elyra - Elyra extends JupyterLab with an AI centric approach.
inferencedb - 🚀 Stream inferences of real-time ML models in production to any data lake (Experimental)
prometheus - A docker-compose stack for Prometheus monitoring
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
kubeflow - Machine Learning Toolkit for Kubernetes