Seldon Core and Inference Graphs Quiz

Answers and explanations appear as you take the quiz.

1. What is the defining feature that distinguishes Seldon Core from a single-model server?
   • Inference graphs that chain multiple components
   • Built-in model training
   • A proprietary GPU driver
   • Automatic data labeling
2. Which Seldon graph component decides which child node to send a request to, enabling A/B tests?
   • Transformer
   • Router
   • Combiner
   • Model
3. Which component type aggregates outputs from multiple models for ensembling?
   • Router
   • Transformer
   • Combiner
   • Initializer
4. What kind of graph structure does a Seldon inference graph form?
   • A cyclic mesh
   • A flat list
   • A binary tree only
   • A directed acyclic graph (DAG)
5. In Seldon Core v2, which server and protocol enable multi-model serving across the graph?
   • MLServer and the Open Inference Protocol
   • TensorFlow Serving and gRPC-only
   • Nginx and REST
   • Spark and Parquet
6. In the Seldon Core 1 Router documentation, what can shift traffic toward better-performing models over time?
   • Nightly retraining only
   • A multi-armed bandit using live reward signals
   • Increasing the pod CPU limit
   • Caching every response
7. Which Seldon graph component can preprocess a request or postprocess a model response?
   • Combiner
   • Router
   • Transformer
   • Explainer
8. Which description of Seldon Core 2 observability is accurate?
   • Metrics, tracing and payload logging are all automatically enabled for every REST/gRPC prediction
   • It provides only GPU metrics and no tracing
   • Payload logging always stores every model request in a local file
   • Metrics are exposed; tracing requires configuration, and payload logging is limited to configured Kafka-backed pipeline paths