Merge branch 'relocate-links-to-cloud' into feature/testing-linodedocs

Author: nmelehan-akamai

.github/workflows/build-testing-site.yaml

@@ -229,6 +229,10 @@ jobs:
         sed -i "s|<loc>$SED_ESCAPED_URL\([a-z0-9\/-]*\)/</loc>|<loc>https://akamai.com/cloud/\1</loc>|g" ${{ vars.DUPE_SITEMAP_NAME }}
         sed -i "s|<loc>$SED_ESCAPED_URL</loc>|<loc>https://akamai.com/cloud</loc>|g" ${{ vars.DUPE_SITEMAP_NAME }}
 
+        SED_ESCAPED_URL=$(echo ${{ secrets.DOCS_WEBSITE_URL }} | sed 's|\.|\\\.|g')
+        sed -i 's|<loc>$SED_ESCAPED_URL\([a-z0-9\/-]*\)/</loc>|<loc>https://akamai.com/cloud/\1</loc>|g' ${{ vars.DUPE_SITEMAP_NAME }}
+        sed -i 's|<loc>$SED_ESCAPED_URL</loc>|<loc>https://akamai.com/cloud</loc>|' ${{ vars.DUPE_SITEMAP_NAME }}
+
       # Make a tarball of the site, because it will upload much, much quicker
       # than the uncompressed rendered site. The commit for this workflow run
       # is encoded in the name of the tarball.

.gitignore

@@ -45,4 +45,5 @@ hugo_stats.json
 .hugo_build.lock
 redirects.conf
 scripts/duplicates.csv
+scripts/.product_link_cache.json
 algolia_out/

_vendor/modules.txt

@@ -1,4 +1,4 @@
-# github.com/linode/linode-docs-theme v0.0.0-20260421192844-79f2fb85e92a
+# github.com/linode/linode-docs-theme v0.0.0-20260527191020-967a1fed9ff8
 # github.com/gohugoio/hugo-mod-jslibs-dist/alpinejs/v3 v3.21300.20800
 # github.com/gohugoio/hugo-mod-jslibs/turbo/v8 v8.20000.20400
 # github.com/hotwired/turbo v8.0.4+incompatible

ci/vale/dictionary.txt

@@ -211,6 +211,7 @@ bitwise
 Bjarne
 blkid
 blockchain
+blocklisted
 blocklists
 Blockly
 blockwise
@@ -812,6 +813,7 @@ fpm
 FQCNs
 fqdns
 fragging
+Fragnesia
 frakti
 framebuffer
 framesets
@@ -1821,6 +1823,7 @@ OKConfig
 okta
 oldfashioned
 oldstable
+Ollama
 omnichannel
 onboarding
 oneof
@@ -2321,6 +2324,7 @@ seafile
 seahub
 searchbots
 searchterm
+seccomp
 secondsite
 secretpassword
 sed

docs/guides/_shortguides/email-warning-shortguide/index.md

@@ -14,5 +14,5 @@ aliases: ['/email-warning-shortguide/']
 ---
 
 {{< note type="warning" title="Email restrictions on the Linode Platform" >}}
-In an effort to fight spam originating from our platform, outbound connections on ports 25, 465, and 587 are blocked by default on Compute Instances for *some* new accounts. These restrictions prevent applications from sending email. If you intend to send email from a Compute Instance, review the [Send Email on the Linode Platform](/docs/products/platform/get-started/guides/send-email/) guide to learn more about our email policies and to request the removal of these restrictions.
+In an effort to fight spam originating from our platform, outbound connections on ports 25, 465, and 587 are blocked by default on Compute Instances for *some* new accounts. These restrictions prevent applications from sending email. If you intend to send email from a Compute Instance, review the [Send Email on the Linode Platform](https://techdocs.akamai.com/cloud-computing/docs/send-email) guide to learn more about our email policies and to request the removal of these restrictions.
 {{< /note >}}

docs/guides/_shortguides/limited-user-note-shortguide/index.md

@@ -13,7 +13,7 @@ aliases: ['/limited-user-note-shortguide/']
 ---
 
 {{< note >}}
-This guide is written for a non-root user. Commands that require elevated privileges are prefixed with `sudo`. If you're not familiar with the `sudo` command, visit our [Users and Groups](/docs/guides/linux-users-and-groups/) guide.
+This guide is written for a non-root user. Commands that require elevated privileges are prefixed with `sudo`. If you're not familiar with the `sudo` command, visit our [Users and Groups](/cloud/guides/linux-users-and-groups/) guide.
 
 All configuration files should be edited with elevated privileges. Remember to include `sudo` before running your text editor.
 {{< /note >}}

docs/guides/akamai/solutions/complete-observability-for-live-stream-events-with-trafficpeak/index.md

@@ -43,7 +43,7 @@ TrafficPeak offers sub-second querying and optimizes log indexing with fully cus
 
 1.  [Akamai Media Services Live (Akamai MSL)](https://www.akamai.com/resources/product-brief/media-services-live) ingests the live stream feeds in a duplicated fashion. MSL logs are sent to TrafficPeak to ensure full visibility for any ingest-related issues in real-time.
 
-1.  [Linode Object Storage](/docs/products/storage/object-storage/) stores all live streaming content for instantaneous, low-latency delivery, as well as playback. Object Storage logs are sent to TrafficPeak.
+1.  [Linode Object Storage](https://techdocs.akamai.com/cloud-computing/docs/object-storage) stores all live streaming content for instantaneous, low-latency delivery, as well as playback. Object Storage logs are sent to TrafficPeak.
 
 1.  [Akamai CDN](https://www.akamai.com/solutions/content-delivery-network) caches and delivers live streaming content to millions of concurrent users. CDN logs are also sent to TrafficPeak via Akamai DataStream, including all relevant HTTP(S) information for troubleshooting purposes.
 

docs/guides/akamai/solutions/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/index.md

@@ -30,9 +30,9 @@ This guide deploys a chatbot written in Python using these open-source software
 
 - **FastAPI**: Provides components for building a REST API. The API for the example chatbot handles chat requests and responses.
 
-The [Using LangChain and LangGraph to Build a RAG-Powered Chatbot](/docs/guides/using-langchain-langgraph-build-rag-powered-chatbot/) guide explains the workflow of the application in more detail and provides a walkthrough of relevant code that leverages the LangChain, LangGraph, and FastAPI frameworks.
+The [Using LangChain and LangGraph to Build a RAG-Powered Chatbot](/cloud/guides/using-langchain-langgraph-build-rag-powered-chatbot/) guide explains the workflow of the application in more detail and provides a walkthrough of relevant code that leverages the LangChain, LangGraph, and FastAPI frameworks.
 
-If you prefer to deploy to Kubernetes, the [Deploy a RAG-Powered Chatbot with LangChain on LKE](/docs/guides/deploy-rag-powered-chatbot-langchain-lke) guide shows how to containerize and deploy this application on Linode Kubernetes Engine (LKE).
+If you prefer to deploy to Kubernetes, the [Deploy a RAG-Powered Chatbot with LangChain on LKE](/cloud/guides/deploy-rag-powered-chatbot-langchain-lke) guide shows how to containerize and deploy this application on Linode Kubernetes Engine (LKE).
 
 ## Systems and Components
 

docs/guides/akamai/solutions/deploy-rag-powered-chatbot-langchain-lke/index.md

@@ -26,9 +26,9 @@ This guide demonstrates deploying a Python-based RAG chatbot to Linode Kubernete
 
 Deploying to Kubernetes unlocks production capabilities essential for reliable applications. LKE distributes your chatbot across multiple pods for high availability, automatically replaces failed instances, performs rolling updates without downtime, and scales horizontally under load. This guide covers containerizing your application, creating Kubernetes manifests for secrets and configuration, and deploying to a managed cluster.
 
-The [Using LangChain and LangGraph to Build a RAG-Powered Chatbot](/docs/guides/using-langchain-langgraph-build-rag-powered-chatbot/) guide explains the workflow of the application in more detail and provides a walkthrough of relevant code that leverages the LangChain, LangGraph, and FastAPI frameworks.
+The [Using LangChain and LangGraph to Build a RAG-Powered Chatbot](/cloud/guides/using-langchain-langgraph-build-rag-powered-chatbot/) guide explains the workflow of the application in more detail and provides a walkthrough of relevant code that leverages the LangChain, LangGraph, and FastAPI frameworks.
 
-If you prefer a simpler deployment, the [Deploy a RAG-Powered Chatbot with LangChain on an Akamai Compute Instance](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance) guide shows how to run the chatbot on a single compute instance.
+If you prefer a simpler deployment, the [Deploy a RAG-Powered Chatbot with LangChain on an Akamai Compute Instance](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance) guide shows how to run the chatbot on a single compute instance.
 
 ## Systems and Components
 
@@ -101,33 +101,33 @@ This design means you can destroy any pod without losing data. A replacement pod
 
 ### Set Up the Code Repository, Object Storage, Databases, and OpenAI API Key
 
-Follow these sections from the [Deploy a RAG-Powered Chatbot with LangChain on an Akamai Compute Instance](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance) guide:
+Follow these sections from the [Deploy a RAG-Powered Chatbot with LangChain on an Akamai Compute Instance](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance) guide:
 
 {{< note >}}
 Wherever an instruction says to run a command on an Akamai compute instance, run that command locally on your workstation instead.
 {{< /note >}}
 
-1. [Clone the Chatbot Codebase](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#clone-the-chatbot-codebase)
+1. [Clone the Chatbot Codebase](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#clone-the-chatbot-codebase)
 
-1. [Start a Python Virtual Environment](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#start-a-python-virtual-environment)
+1. [Start a Python Virtual Environment](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#start-a-python-virtual-environment)
 
-1. [Copy the .env.example Template](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#copy-the-envexample-template)
+1. [Copy the .env.example Template](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#copy-the-envexample-template)
 
-1. [Install Python Dependencies](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#install-python-dependencies)
+1. [Install Python Dependencies](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#install-python-dependencies)
 
-1. [Create an OpenAI API Key](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#create-an-openai-api-key)
+1. [Create an OpenAI API Key](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#create-an-openai-api-key)
 
-1. [Provision Managed PostgreSQL Databases](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#provision-managed-postgresql-databases)
+1. [Provision Managed PostgreSQL Databases](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#provision-managed-postgresql-databases)
 
    - When selecting a region for your databases, use the same region as your LKE cluster.
 
    - When configuring network access for the database, add your workstation's IP address to the allowed list of IPs.
 
-1. [Set Up Linode Object Storage](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#set-up-linode-object-storage)
+1. [Set Up Linode Object Storage](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#set-up-linode-object-storage)
 
    - When selecting a region for your object storage bucket, use the same region as your LKE cluster.
 
-1. [Upload Documents to the Object Storage Bucket](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#upload-documents-to-the-object-storage-bucket)
+1. [Upload Documents to the Object Storage Bucket](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#upload-documents-to-the-object-storage-bucket)
 
 ### Verify Database Access from LKE
 
@@ -169,7 +169,7 @@ Your cluster can now reach your databases.
 
 ### Index Documents with LangChain
 
-Follow the [Index Documents with LangChain](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#index-documents-with-langchain) section of the [RAG Chatbot LangChain Compute Instance](/docs/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance) guide to initialize your vector database and generate the vector embeddings of your documents.
+Follow the [Index Documents with LangChain](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance/#index-documents-with-langchain) section of the [RAG Chatbot LangChain Compute Instance](/cloud/guides/deploy-rag-powered-chatbot-langchain-akamai-compute-instance) guide to initialize your vector database and generate the vector embeddings of your documents.
 
 ## Containerize your Chatbot Application
 

docs/guides/akamai/solutions/observability-with-datastream-and-multiplexing/index.md

@@ -13,7 +13,7 @@ Having real-time visibility into log data can help determine how applications ar
 
 One way to achieve an efficient, predictable, and cost-effective observability workflow is to implement a cloud-based multiplexing solution to ingest and parse log data before it’s sent to the relevant DevOps team. Combined with Akamai’s [DataStream](https://techdocs.akamai.com/datastream2/docs/welcome-datastream2) edge-based log reporting, multiplexing can help manage how and where logs are transmitted, improve data security, and reduce overall cost.
 
-This guide outlines the business challenges of observability workflows, integration and migration need-to-knows, and illustrates a working multiplexing reference architecture using [Linode Kubernetes Engine (LKE)](/docs/products/compute/kubernetes/) running [Elastic Stack (ELK)](https://www.elastic.co/elastic-stack/) and [Vector](https://vector.dev/).
+This guide outlines the business challenges of observability workflows, integration and migration need-to-knows, and illustrates a working multiplexing reference architecture using [Linode Kubernetes Engine (LKE)](https://techdocs.akamai.com/cloud-computing/docs/linode-kubernetes-engine) running [Elastic Stack (ELK)](https://www.elastic.co/elastic-stack/) and [Vector](https://vector.dev/).
 
 ## DataStream and Multiplexing Workflow