{"id":32218,"date":"2026-07-22T10:45:55","date_gmt":"2026-07-22T08:45:55","guid":{"rendered":"https:\/\/contabo.com\/blog\/?p=32218"},"modified":"2026-07-22T12:07:27","modified_gmt":"2026-07-22T10:07:27","slug":"self-hosted-ai-orchestration-platforms","status":"publish","type":"post","link":"https:\/\/contabo.com\/blog\/self-hosted-ai-orchestration-platforms\/","title":{"rendered":"Best Self-Hosted AI Orchestration Platforms for a VPS"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">The strongest self-hosted AI orchestration platforms for a <a href=\"https:\/\/contabo.com\/en\/vps\/\">VPS<\/a> in 2026 are n8n for visual workflow automation, Dify for building RAG and chat applications, and LangGraph or CrewAI for code-first, stateful multi-agent systems. All run comfortably on a standard VPS via <a href=\"https:\/\/contabo.com\/blog\/docker-explained\/\">Docker<\/a>, need no more than 2\u20134 GB RAM for the orchestration layer itself, and keep your prompts, credentials, and workflow data off a vendor&#8217;s servers entirely.<\/p>\n\n\n\n<h2 id=\"h-what-is-ai-orchestration\" class=\"wp-block-heading\">What Is AI Orchestration?<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">AI orchestration is the layer that connects large language models to the tools, data, and business systems they need to act on \u2014 routing tasks, managing state between steps, and coordinating multiple models or agents toward a goal. Where a single LLM call answers one prompt, an orchestration platform chains calls together: pull a document, retrieve context, call a model, act on the result, hand off to the next agent. For self-hosters, the appeal is straightforward: your prompts, your documents, and your API keys stay on infrastructure you control, instead of routing through a SaaS vendor&#8217;s pipeline.<\/p>\n\n\n\n<h2 id=\"h-top-self-hosted-ai-orchestration-platforms\" class=\"wp-block-heading\">Top Self-Hosted AI Orchestration Platforms<\/h2>\n\n\n\n<style>\n  .aiop-table-wrap {\n    width: 100%;\n    overflow-x: auto;\n    margin: 24px 0;\n    font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Roboto, Helvetica, Arial, sans-serif;\n  }\n  .aiop-table {\n    width: 100%;\n    border-collapse: collapse;\n    border-spacing: 0;\n    min-width: 720px;\n    background: #ffffff;\n    border-radius: 8px;\n    overflow: hidden;\n    box-shadow: 0 1px 3px rgba(0,0,0,0.08);\n  }\n  .aiop-table caption {\n    text-align: left;\n    font-size: 13px;\n    color: #6b7280;\n    padding-bottom: 8px;\n  }\n  .aiop-table thead th {\n    background: #365F91;\n    color: #ffffff;\n    font-weight: 600;\n    font-size: 14px;\n    text-align: left;\n    padding: 14px 16px;\n    letter-spacing: 0.2px;\n  }\n  .aiop-table thead th:first-child {\n    border-radius: 8px 0 0 0;\n  }\n  .aiop-table thead th:last-child {\n    border-radius: 0 8px 0 0;\n  }\n  .aiop-table tbody td {\n    padding: 13px 16px;\n    font-size: 14px;\n    line-height: 1.5;\n    color: #1f2937;\n    border-bottom: 1px solid #e5e7eb;\n    vertical-align: top;\n  }\n  .aiop-table tbody tr:last-child td {\n    border-bottom: none;\n  }\n  .aiop-table tbody tr:nth-child(even) {\n    background: #f7f9fc;\n  }\n  .aiop-table tbody tr:hover {\n    background: #eef2fa;\n    transition: background 0.15s ease-in-out;\n  }\n  .aiop-table td:first-child {\n    font-weight: 600;\n    color: #365F91;\n    white-space: nowrap;\n  }\n  .aiop-badge {\n    display: inline-block;\n    padding: 2px 8px;\n    border-radius: 4px;\n    font-size: 12px;\n    font-weight: 600;\n    background: #e8edf7;\n    color: #4F81BD;\n    white-space: nowrap;\n  }\n  @media (max-width: 600px) {\n    .aiop-table { min-width: 600px; }\n  }\n<\/style>\n\n<div class=\"aiop-table-wrap\">\n  <table class=\"aiop-table\">\n    <caption>Top self-hosted AI orchestration platforms compared \u2014 RAM, license, and deployment method.<\/caption>\n    <thead>\n      <tr>\n        <th scope=\"col\">Platform<\/th>\n        <th scope=\"col\">Best for<\/th>\n        <th scope=\"col\">Min RAM<\/th>\n        <th scope=\"col\">License<\/th>\n        <th scope=\"col\">Deployment<\/th>\n      <\/tr>\n    <\/thead>\n    <tbody>\n      <tr>\n        <td>n8n<\/td>\n        <td>Visual workflow automation + AI nodes<\/td>\n        <td><span class=\"aiop-badge\">1\u20132 GB<\/span><\/td>\n        <td>Sustainable Use License (source-available)<\/td>\n        <td>Docker \/ Docker Compose<\/td>\n      <\/tr>\n      <tr>\n        <td>Dify<\/td>\n        <td>RAG apps and LLM app building<\/td>\n        <td><span class=\"aiop-badge\">2\u20134 GB<\/span><\/td>\n        <td>Apache 2.0 + no-resale clause (source-available)<\/td>\n        <td>Docker Compose (multi-container)<\/td>\n      <\/tr>\n      <tr>\n        <td>LangGraph<\/td>\n        <td>Stateful, code-first multi-agent systems<\/td>\n        <td><span class=\"aiop-badge\">512 MB\u20131 GB<\/span><\/td>\n        <td>MIT<\/td>\n        <td>Python service via Docker<\/td>\n      <\/tr>\n      <tr>\n        <td>CrewAI<\/td>\n        <td>Role-based multi-agent teams<\/td>\n        <td><span class=\"aiop-badge\">512 MB\u20131 GB<\/span><\/td>\n        <td>MIT<\/td>\n        <td>Python service via Docker<\/td>\n      <\/tr>\n      <tr>\n        <td>Langflow<\/td>\n        <td>Visual RAG and agent prototyping<\/td>\n        <td><span class=\"aiop-badge\">2\u20134 GB<\/span><\/td>\n        <td>MIT<\/td>\n        <td>Docker Compose<\/td>\n      <\/tr>\n      <tr>\n        <td>Flowise<\/td>\n        <td>Lightweight drag-and-drop chatbot building<\/td>\n        <td><span class=\"aiop-badge\">1\u20132 GB<\/span><\/td>\n        <td>Open source (Workday-owned since Aug 2025)<\/td>\n        <td>Docker<\/td>\n      <\/tr>\n    <\/tbody>\n  <\/table>\n<\/div>\n\n\n\n<h3 id=\"h-n8n-best-for-visual-workflow-automation\" class=\"wp-block-heading\">n8n \u2014 Best for Visual Workflow Automation<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">n8n is a node-based workflow builder that has added dedicated AI Agent nodes on top of its existing 400+ app integrations, so a single canvas can route a Slack message into an LLM call and back out to a CRM update. It runs as a single lightweight container on a VPS \u2014 add Postgres if you outgrow the default SQLite store. n8n&#8217;s code is available under the Sustainable Use License: <a href=\"https:\/\/contabo.com\/blog\/self-hosting-n8n-a-comprehensive-docker-vps-guide\/\">n8n self-host<\/a> is for free and also modify for your own internal use, but you can&#8217;t resell it or host it for paying customers without a commercial agreement \u2014 it&#8217;s source-available, not a permissive open-source license. <\/p>\n\n\n\n<h3 id=\"h-dify-best-for-rag-and-llm-app-building\" class=\"wp-block-heading\">Dify \u2014 Best for RAG and LLM App Building<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Dify bundles a visual workflow canvas, RAG pipeline, and agent builder into one interface, aimed at teams shipping a chatbot or internal knowledge-base app rather than wiring individual API calls. It&#8217;s a heavier deployment than n8n \u2014 a multi-container Docker Compose stack with its own Postgres and vector store \u2014 so budget 2\u20134 GB of RAM. Dify&#8217;s license is a modified Apache 2.0: commercial and internal use is unrestricted, but running it as a multi-tenant hosted service for other customers requires written permission from the maintainers. See our dedicated guide for the full Docker Compose walkthrough.<\/p>\n\n\n\n<h3 id=\"h-langgraph-best-for-stateful-multi-agent-systems\" class=\"wp-block-heading\">LangGraph \u2014 Best for Stateful Multi-Agent Systems<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">LangGraph, built by the LangChain team, models an agent&#8217;s steps as an explicit graph \u2014 nodes for each action, edges for the transitions between them \u2014 with state that persists across the whole run. That makes it the natural pick when you need checkpointing, human-in-the-loop pauses, or the ability to roll back and retry a specific step rather than restart the whole workflow. It&#8217;s MIT-licensed and ships as a Python library, so the &#8220;deployment&#8221; is really deploying your own service; pair it with Redis or Postgres for persistent memory.<\/p>\n\n\n\n<h3 id=\"h-crewai-best-for-role-based-multi-agent-teams\" class=\"wp-block-heading\">CrewAI \u2014 Best for Role-Based Multi-Agent Teams<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">CrewAI takes a different framing: you define agents as roles with goals and tools, assemble them into a &#8220;crew,&#8221; and let the framework handle how they hand tasks to each other. It&#8217;s the fastest of the code-first frameworks to get a first multi-agent workflow running, at the cost of less granular control than LangGraph over exactly how each step executes. MIT-licensed, lightweight Python footprint, and it runs comfortably alongside other services on a small VPS.<\/p>\n\n\n\n<h3 id=\"h-langflow-best-for-visual-rag-prototyping\" class=\"wp-block-heading\">Langflow \u2014 Best for Visual RAG Prototyping<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Langflow is a visual, node-based canvas built on top of LangChain, aimed at developers who want to prototype a RAG pipeline or agent chain quickly and then export it as code (or as an MCP server, letting another agent call the workflow as a tool). It&#8217;s MIT-licensed and deploys via Docker Compose; expect similar resource needs to Dify since it also runs a vector store alongside the app.<\/p>\n\n\n\n<h3 id=\"h-flowise-best-for-lightweight-chatbot-building\" class=\"wp-block-heading\">Flowise \u2014 Best for Lightweight Chatbot Building<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Flowise offers a LangChain-based drag-and-drop UI aimed at getting a working chatbot or simple agent running with minimal code. Workday acquired Flowise in August 2025 and has stated it plans to keep investing in the open-source project, so it remains self-hostable \u2014 but it&#8217;s worth checking the current license terms before building a long-term dependency on it, since ownership changes can shift a project&#8217;s roadmap and licensing over time.<\/p>\n\n\n\n<div class=\"wp-block-uagb-advanced-heading uagb-block-1864f52e\"><h2 class=\"uagb-heading-text\">How Much VPS Do Self-Hosted AI Agents Need?<\/h2><\/div>\n\n\n\n<style>\n  .aiop-vps-wrap {\n    width: 100%;\n    overflow-x: auto;\n    margin: 24px 0;\n    font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Roboto, Helvetica, Arial, sans-serif;\n  }\n  .aiop-vps-table {\n    width: 100%;\n    border-collapse: collapse;\n    border-spacing: 0;\n    min-width: 760px;\n    background: #ffffff;\n    border-radius: 8px;\n    overflow: hidden;\n    box-shadow: 0 1px 3px rgba(0,0,0,0.08);\n  }\n  .aiop-vps-table caption {\n    text-align: left;\n    font-size: 13px;\n    color: #6b7280;\n    padding-bottom: 8px;\n  }\n  .aiop-vps-table thead th {\n    background: #365F91;\n    color: #ffffff;\n    font-weight: 600;\n    font-size: 14px;\n    text-align: left;\n    padding: 14px 16px;\n    letter-spacing: 0.2px;\n  }\n  .aiop-vps-table thead th:first-child { border-radius: 8px 0 0 0; }\n  .aiop-vps-table thead th:last-child { border-radius: 0 8px 0 0; }\n  .aiop-vps-table tbody td {\n    padding: 13px 16px;\n    font-size: 14px;\n    line-height: 1.5;\n    color: #1f2937;\n    border-bottom: 1px solid #e5e7eb;\n    vertical-align: top;\n  }\n  .aiop-vps-table tbody tr:last-child td { border-bottom: none; }\n  .aiop-vps-table tbody tr:nth-child(even) { background: #f7f9fc; }\n  .aiop-vps-table tbody tr:hover {\n    background: #eef2fa;\n    transition: background 0.15s ease-in-out;\n  }\n  .aiop-vps-table td:first-child {\n    font-weight: 600;\n    color: #365F91;\n    white-space: nowrap;\n  }\n  .aiop-vps-badge {\n    display: inline-block;\n    padding: 2px 8px;\n    border-radius: 4px;\n    font-size: 12px;\n    font-weight: 600;\n    white-space: nowrap;\n  }\n  .aiop-vps-badge--min {\n    background: #fdecea;\n    color: #c0392b;\n  }\n  .aiop-vps-badge--rec {\n    background: #e6f4ea;\n    color: #1e7e34;\n  }\n  .aiop-vps-notes {\n    color: #4b5563;\n    font-size: 13.5px;\n  }\n  @media (max-width: 600px) {\n    .aiop-vps-table { min-width: 640px; }\n  }\n<\/style>\n\n<div class=\"aiop-vps-wrap\">\n  <table class=\"aiop-vps-table\">\n    <caption>Minimum vs. recommended VPS sizing for self-hosted AI orchestration platforms.<\/caption>\n    <thead>\n      <tr>\n        <th scope=\"col\">Platform<\/th>\n        <th scope=\"col\">Min RAM<\/th>\n        <th scope=\"col\">Recommended RAM<\/th>\n        <th scope=\"col\">vCPU<\/th>\n        <th scope=\"col\">Notes<\/th>\n      <\/tr>\n    <\/thead>\n    <tbody>\n      <tr>\n        <td>n8n<\/td>\n        <td><span class=\"aiop-vps-badge aiop-vps-badge--min\">1 GB<\/span><\/td>\n        <td><span class=\"aiop-vps-badge aiop-vps-badge--rec\">2\u20134 GB<\/span><\/td>\n        <td>1\u20132<\/td>\n        <td class=\"aiop-vps-notes\">Add RAM if running concurrent workflows<\/td>\n      <\/tr>\n      <tr>\n        <td>Dify<\/td>\n        <td><span class=\"aiop-vps-badge aiop-vps-badge--min\">2 GB<\/span><\/td>\n        <td><span class=\"aiop-vps-badge aiop-vps-badge--rec\">4\u20138 GB<\/span><\/td>\n        <td>2<\/td>\n        <td class=\"aiop-vps-notes\">More RAM needed for document embedding\/indexing<\/td>\n      <\/tr>\n      <tr>\n        <td>LangGraph \/ CrewAI<\/td>\n        <td><span class=\"aiop-vps-badge aiop-vps-badge--min\">512 MB<\/span><\/td>\n        <td><span class=\"aiop-vps-badge aiop-vps-badge--rec\">2\u20134 GB<\/span><\/td>\n        <td>1\u20132<\/td>\n        <td class=\"aiop-vps-notes\">Framework only \u2014 add more if self-hosting the LLM<\/td>\n      <\/tr>\n      <tr>\n        <td>Langflow \/ Flowise<\/td>\n        <td><span class=\"aiop-vps-badge aiop-vps-badge--min\">2 GB<\/span><\/td>\n        <td><span class=\"aiop-vps-badge aiop-vps-badge--rec\">4 GB<\/span><\/td>\n        <td>2<\/td>\n        <td class=\"aiop-vps-notes\">Vector store adds overhead<\/td>\n      <\/tr>\n    <\/tbody>\n  <\/table>\n<\/div>\n\n\n\n<p class=\"wp-block-paragraph\">These figures assume you&#8217;re calling external model APIs (OpenAI, Anthropic, DeepSeek). If you also want to self-host the language model itself \u2014 running Llama or a similar model locally via Ollama \u2014 you&#8217;ll need a GPU-enabled instance instead; the orchestration layer&#8217;s RAM needs above stay the same either way.<\/p>\n\n\n\n<h2 id=\"h-why-run-your-ai-orchestration-stack-on-contabo\" class=\"wp-block-heading\">Why Run Your AI Orchestration Stack on Contabo<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A Cloud VPS 8 gives you 24 GB of RAM for 14 \u20ac\/month \u2014 comfortable headroom to <a href=\"https:\/\/contabo.com\/en\/n8n-hosting\/\">run n8n<\/a> or Dify alongside a Postgres instance and a vector store, with room to add a second platform if you want to compare tools side by side. For teams running multiple orchestration platforms together, or expecting to grow into embedding-heavy RAG workloads, the NVMe-backed <a href=\"https:\/\/contabo.com\/en\/vps-performance\/\">Cloud VPS Performance<\/a> line adds faster storage for vector indexing at a similar RAM-per-Euro value. <a href=\"https:\/\/contabo.com\/en\/locations\/europe\/\">EU data centers<\/a> keep prompt and document data inside <a href=\"https:\/\/gdpr-info.eu\/\" rel=\"nofollow\">GDPR<\/a>-friendly infrastructure, which matters for any team routing customer data through these platforms.<\/p>\n\n\n\n<h2 id=\"h-faq-self-hosted-ai-orchestration\" class=\"wp-block-heading\">FAQ: Self-Hosted AI Orchestration<\/h2>\n\n\n\n<div class=\"schema-faq wp-block-yoast-faq-block\"><div class=\"schema-faq-section\" id=\"faq-question-1784709035461\"><strong class=\"schema-faq-question\">What is the best self-hosted AI orchestration platform?<\/strong> <p class=\"schema-faq-answer\">There isn&#8217;t one universal answer \u2014 it depends on the workflow. n8n is the best fit if you&#8217;re connecting AI to existing business systems (CRM, email, databases). Dify is the best fit for building a RAG-based chatbot or internal knowledge-base app. LangGraph and CrewAI are the best fit for developers who want full code control over multi-agent behavior rather than a visual builder.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1784709048248\"><strong class=\"schema-faq-question\">Can I run n8n and Dify on the same VPS?<\/strong> <p class=\"schema-faq-answer\">Yes. Both run as separate Docker containers, so they don&#8217;t conflict, and their combined RAM footprint (roughly 3\u20136 GB together) fits comfortably on a mid-tier VPS like a Cloud VPS 8. Many teams run n8n for scheduled automation and Dify for a user-facing chat interface side by side.<\/p> <\/div> <div class=\"schema-faq-section\" id=\"faq-question-1784709057984\"><strong class=\"schema-faq-question\">How much RAM do I need for AI agent orchestration?<\/strong> <p class=\"schema-faq-answer\">For the orchestration layer alone \u2014 calling external model APIs rather than hosting the LLM yourself \u2014 2\u20134 GB of RAM covers any of the platforms above comfortably. If you plan to self-host the model too (via <a href=\"https:\/\/contabo.com\/en\/ollama-phi-vps-hosting\/\">Ollama <\/a>or similar), budget 8 GB or more, or move to a <a href=\"https:\/\/contabo.com\/en\/gpu-cloud\/\">GPU<\/a>-enabled instance.<\/p> <\/div> <\/div>\n","protected":false},"excerpt":{"rendered":"<p>The strongest self-hosted AI orchestration platforms for a VPS in 2026 are n8n for visual workflow automation, Dify for building RAG and chat applications, and LangGraph or CrewAI for code-first, stateful multi-agent systems. All run comfortably on a standard VPS via Docker, need no more than 2\u20134 GB RAM for the orchestration layer itself, and [&hellip;]<\/p>\n","protected":false},"author":78,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":"","_members_access_role":[],"_members_access_error":""},"categories":[4489],"tags":[],"ppma_author":[4285],"class_list":["post-32218","post","type-post","status-publish","format-standard","hentry","category-listicle"],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"Jie Guo","author_link":"https:\/\/contabo.com\/blog\/author\/jieguo\/"},"uagb_comment_info":0,"uagb_excerpt":"The strongest self-hosted AI orchestration platforms for a VPS in 2026 are n8n for visual workflow automation, Dify for building RAG and chat applications, and LangGraph or CrewAI for code-first, stateful multi-agent systems. All run comfortably on a standard VPS via Docker, need no more than 2\u20134 GB RAM for the orchestration layer itself, and&hellip;","authors":[{"term_id":4285,"user_id":78,"is_guest":0,"slug":"jieguo","display_name":"Jie Guo","avatar_url":"https:\/\/secure.gravatar.com\/avatar\/4e0d981b06988d6d456834e9d55bc9e713e918fa8444325543d14f448154106b?s=96&d=mm&r=g","author_category":"","user_url":"","last_name":"Guo","first_name":"Jie","job_title":"","description":""}],"_links":{"self":[{"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/posts\/32218","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/comments?post=32218"}],"version-history":[{"count":2,"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/posts\/32218\/revisions"}],"predecessor-version":[{"id":32247,"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/posts\/32218\/revisions\/32247"}],"wp:attachment":[{"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/media?parent=32218"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/categories?post=32218"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/tags?post=32218"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/contabo.com\/blog\/wp-json\/wp\/v2\/ppma_author?post=32218"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}