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content/learning-paths/servers-and-cloud-computing/storefront-ai-assistant-gke-axion/_index.md

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Engine using Arm-based Axion nodes, validate a baseline on N4A, and add a gRPC-driven AI shopping
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assistant. You'll build and push a single `linux/arm64` container image to Artifact Registry, then
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use Kustomize overlays to run the assistant on N4A before moving only that tier to C4A. After
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reviewing the assistant’s sources and runtime dependencies, you'll confirm scheduling on the intended
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reviewing the assistant’s source code and runtime dependencies, you'll confirm scheduling on the intended
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node pool and capture benchmark summaries to compare the same assistant workload across N4A
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and C4A. The end state is a mixed-placement deployment where the steady storefront remains
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and C4A. You'll finish with a mixed-placement deployment where the steady storefront remains
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on N4A and the burstier assistant runs on the selected pool.
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faqs:
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- question: How do I verify the cluster has both N4A and C4A node pools before I start?
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answer: >-
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The storefront runs on N4A, and `shoppingassistantservice` isn't present. This is intentional
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because you'll build and deploy the assistant in later steps.
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- question: Ive run this path before. What should I remove before I recreate the baseline?
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- question: I've run this path before. What should I remove before I recreate the baseline?
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answer: >-
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Delete any existing assistant deployment and related service so the baseline reflects a
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storefront without the assistant. The steps show removing old assistant resources before
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creating the baseline.
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Delete any existing assistant deployment, related service, and service account so the baseline reflects a
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storefront without the assistant.
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- question: Do I need different container images for N4A and C4A when I deploy the assistant?
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answer: >-
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No. You'll build one `linux/arm64` image targeted for Axion that'll run in either placement.

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