KServe Insights

What is KServe?

KServe is an open-source model serving framework built on Kubernetes. It is designed to simplify the deployment and management of machine learning models, providing features like autoscaling, traffic management, and canary deployments. It is commonly used to serve models for online inference, enabling real-time predictions from machine learning models.

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What other technologies are related to KServe?

KServe Competitor Technologies

Seldon Core

Seldon Core is another open-source platform for deploying machine learning models on Kubernetes. It provides similar functionalities to KServe, making them direct competitors in the model serving space.

mentioned alongside KServe in 21% (83) of relevant job posts

AWS Sagemaker

AWS SageMaker is a managed machine learning service that provides model deployment capabilities, making it a competitor to KServe.

mentioned alongside KServe in 0% (103) of relevant job posts

KServe Complementary Technologies

Kubeflow

Kubeflow is a machine learning platform designed to run on Kubernetes. KServe can be used as a component within Kubeflow for model serving, making it a complementary technology.

mentioned alongside KServe in 3% (363) of relevant job posts

Triton

Triton Inference Server is a high-performance inference serving solution. KServe can use Triton as a backend for serving models, making them complementary.

mentioned alongside KServe in 5% (102) of relevant job posts

Knative

KServe is built on Knative for serverless deployments. Knative provides the underlying infrastructure for auto-scaling and request routing.

mentioned alongside KServe in 5% (66) of relevant job posts