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Merge pull request #1748 from jasonrandrews/review
Review first page and add next steps to Ollama on GKE Learning Path
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content/learning-paths/servers-and-cloud-computing/multiarch_ollama_on_gke/_index.md

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---
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title: Run ollama on both arm64 and amd64 nodes, using the same multi-architecture container image on GKE.
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title: Use GKE to run Ollama on arm64 and amd64 nodes using a multi-architecture container image
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minutes_to_complete: 30
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who_is_this_for: This learning path will show you how easy it is to migrate from homogenous amd64 k8s clusters, to a hybrid (arm64 and amd64) cluster with multi-architectural container images on GKE. Demonstrated with the ollama application, you'll see for yourself the price/performance advantages of running on arm64. Although tutorial will be GKE-specific with ollama, the provided YAML can act as a template for deployment on any on any multi-architectural application and cloud.
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who_is_this_for: This topic explains how migrate a homogenous amd64 k8s cluster to a hybrid (arm64 and amd64) cluster using a multi-architecture container image on GKE. Ollama is the application used to demonstrate the migration.
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learning_objectives:
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- Spin up a GKE cluster with amd64 and arm64 nodes.
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- Apply ollama amd64-based and arm64-based Deployments and Services using the same container image.
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- Ping, pull models, and make inferences to experience each architectures' performance first-hand.
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- Experiment further on your own by researching which existing, and future workloads could benefit most from single, or multi-architectural clusters.
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- Apply Ollama amd64-based and arm64-based deployments and services using the same container image.
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- Ping, pull models, and make inferences to experience the performance of each architecture.
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prerequisites:
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- A [Google Cloud account](https://console.cloud.google.com/).
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- A computer with [Google Cloud CLI](/install-guides/gcloud) and [kubectl](/install-guides/kubectl/) installed.
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- A local computer with the [Google Cloud CLI](/install-guides/gcloud) and [kubectl](/install-guides/kubectl/) installed.
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- The [GKE Cloud Plugin](https://cloud.google.com/kubernetes-engine/docs/how-to/cluster-access-for-kubectl#gcloud)
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2019

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subjects: Containers and Virtualization
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cloud_service_providers: Google Cloud
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armips:
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- Neoverse
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operatingsystems:
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- Linux
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- MacOs
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- macOS
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tools_software_languages:
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- LLM
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- ollama
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- GenAI
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- LLM
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- Ollama
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- GenAI
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further_reading:
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- resource:
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title: ollama - Get up and running with large language models
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title: Ollama - Get up and running with large language models
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link: https://ollama.com/
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type: documentation
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- resource:
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title: ollama API calls
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title: Ollama API calls
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link: https://github.com/ollama/ollama/blob/main/docs/api.md
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type: documentation
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- resource:
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title: Dockerhub for Ollama
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link: https://hub.docker.com/r/ollama/ollama
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type: documentation
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- resource:
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title: ollama build docs
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title: Ollama build docs
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link: https://github.com/ollama/ollama/blob/main/docs/development.md
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type: documentation
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- resource:
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---
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# ================================================================================
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# FIXED, DO NOT MODIFY THIS FILE
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# ================================================================================
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weight: 21 # Set to always be larger than the content in this path to be at the end of the navigation.
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title: "Next Steps" # Always the same, html page title.
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layout: "learningpathall" # All files under learning paths have this same wrapper for Hugo processing.
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---

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