Serving TensorFlow Models with a Custom Environment
Build a custom serving environment to run TensorFlow models with extra dependencies.
Model Serving
TensorFlow Serving: Handling Content Types
Explore how TensorFlow Serving handles different request content types for inference.
Serving TensorFlow Models with JSON Requests
Send and parse JSON prediction requests against a TensorFlow Serving model.
Serving Custom TensorFlow Models
Package and serve a custom TensorFlow model signature with TensorFlow Serving.
Serving Multiple TensorFlow Models with Monitoring
Serve multiple TensorFlow models simultaneously and monitor them with Prometheus and Swagger.
Deploying TensorFlow model as Canary Releases Kubernetes and Istio
Use Istio with Minikube and TensorFlow Serving to create canary deployments of TensorFlow machine learning models!
Prepare and Deploy a TensorFlow Model to Tensorflow Serving
Serve tensorflow model efficiently with customized model signatures
Integrating Seldon Core with Kafka
Stream predictions in and out of Seldon Core model deployments using Kafka.
Building Inference Graphs with Seldon Core
Compose multi-step inference graphs (transformers, combiners, routers) with Seldon Core.
Deploying Your First Model with Seldon Core
Deploy a first machine learning model on Kubernetes using Seldon Core, including authentication basics.