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Data Platform | Add dedicated K8s page and detailed descriptions (architecture/components) (#814)
* data platform for amp is available upon request * Add new Kubernetes page; Add detailed descriptions of Data Platform's architecture and components * Apply suggestions from code review Co-authored-by: Simran <[email protected]> * apply review suggestions * Apply suggestion from @nerpaula * review * Fix link --------- Co-authored-by: Simran <[email protected]> Co-authored-by: Simran Spiller <[email protected]>
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‎site/content/data-platform/_index.md‎

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@@ -21,6 +21,53 @@ AI solutions for GraphRAG, graph machine learning, data explorations, and more.
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run it on-premises or in the cloud yourself on top of Kubernetes to access all
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of the platform features with enterprise-grade automation and reliability.
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## What Makes Up the Arango Data Platform
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The Arango Data Platform is built on a layered architecture that combines powerful
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components into a unified solution:
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- **ArangoDB Enterprise Edition**: The multi-model database foundation supporting
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graphs, documents, key-value, vector search, and full-text search capabilities.
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- **Graph Visualizer**: A sophisticated web-based interface for graph exploration,
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smart search, and visual layouts.
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- **Arango Platform Suite**: Enterprise-grade features including high availability
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and monitoring, comprehensive APIs and connectors, centralized orchestration and
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resource management.
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All components are orchestrated through Kubernetes, providing automated deployment,
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scaling, and management with enterprise-grade reliability.
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For a detailed breakdown of each component, see [Features and Architecture](features/).
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## Extend the Arango Data Platform with AI capabilities
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Extend the Arango Data Platform with the [**AI Suite**](../ai-suite/_index.md)
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that offers advanced AI and machine learning capabilities that integrate seamlessly
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into the platform's unified web interface.
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What you get with the AI Suite:
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- [GraphRAG](../ai-suite/graphrag/): Generate knowledge graphs from documents and enable
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conversational querying of your data.
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- [GraphML](../ai-suite/graphml/): Apply machine learning algorithms that leverage graph
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structure for better predictions.
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- [Graph Analytics](../ai-suite/graph-analytics/): Run advanced algorithms like PageRank
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to discover influential nodes and patterns.
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- [AQLizer](../ai-suite/aqlizer.md): Generate AQL queries from natural language.
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- [Jupyter notebooks](../ai-suite/notebook-servers.md): Run Jupyter Notebooks to build and
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experiment with graph-powered data, AI, and machine learning workflows directly connected
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to ArangoDB databases.
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- Public and private LLM support: Use public LLMs such as OpenAI
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or private LLMs with [Triton Inference Server](../ai-suite/reference/triton-inference-server.md).
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- [MLflow integration](../ai-suite/reference/mlflow.md): Use the popular MLflow as a model registry
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for private LLMs or to run machine learning experiments as part of the Arango Data Platform.
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{{< tip >}}
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The AI Suite requires a separate license.
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{{< /tip >}}
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{{< cards >}}
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{{% card title="Get started with the Arango Data Platform" link="get-started/" %}}
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Explore the Kubernetes-native architecture, unified interface, and enterprise-grade capabilities of the Arango Data Platform.
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{{% /card %}}
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{{% card title="ArangoDB Kubernetes Operator" link="../../arangodb/3.12/deploy/kubernetes/" %}}
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Learn about the official ArangoDB Kubernetes Operator that powers the Arango Data Platform.
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{{% card title="Kubernetes-Native Architecture" link="kubernetes/" %}}
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Learn about the Kubernetes-native foundation that the Arango Data Platform is purpose-built on.
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{{% /card %}}
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{{% card title="Graph Visualizer" link="graph-visualizer/" %}}

‎site/content/data-platform/features.md‎

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---
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title: Feature list of the Arango Data Platform
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menuTitle: Features
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title: Architecture and Features of the Arango Data Platform
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menuTitle: Architecture and Features
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weight: 5
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description: >-
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The Arango Data Platform is a scalable Kubernetes-native architecture that gets you all features
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of ArangoDB as a single solution with a unified interface
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Discover how the Arango Data Platform combines database, visualization, and enterprise
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features into a unified, Kubernetes-native architecture
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---
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## Architecture
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enterprise-grade database management and high availability.
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{{< /tip >}}
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- **Core Database**: The ArangoDB database system forms the solid core
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of the Arango Data Platform.
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### Kubernetes-Native
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At its core, the Arango Data Platform is purpose-built for Kubernetes environments, leveraging the
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[official ArangoDB Kubernetes Operator](https://arangodb.github.io/kube-arangodb/docs/)
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(`kube-arangodb`) to deliver enterprise-grade automation, scalability, and operational excellence.
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For detailed information about the Kubernetes foundation, see [Kubernetes Integration](kubernetes/).
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### Technical Infrastructure
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- **Helm**: A package manager for Kubernetes that enables consistent, repeatable
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installations and version control.
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- **Envoy**: A high-performance service proxy that acts as the gateway for the
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Arango Data Platform for centralizing authentication and routing.
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- **Web interface**: The Platform includes a unified, browser-based UI that lets
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you access its features in an intuitive way. Optional products like the
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AI Suite seamlessly integrate into the UI if installed.
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## Platform Components
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## Kubernetes Integration
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The Arango Data Platform consists of multiple integrated components that work together
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to provide a complete, enterprise-ready solution.
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At its core, the Arango Data Platform is purpose-built for Kubernetes environments, leveraging the
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[official ArangoDB Kubernetes Operator](https://arangodb.github.io/kube-arangodb/docs/)
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(`kube-arangodb`) to deliver enterprise-grade automation, scalability, and operational excellence.
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### ArangoDB Enterprise Edition
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## Features
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At the foundation is [**ArangoDB Enterprise Edition**](../../arangodb/3.12/), the
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powerful multi-model database that provides:
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The Arango Data Platform provides these core capabilities out of the box:
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- **Graph**: Native graph database capabilities with efficient traversals and pattern matching
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- **Document**: Flexible JSON document storage with schema validation
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- **Key-Value**: High-performance key-value operations
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- **Vector**: Vector embeddings and similarity search for AI applications
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- **Search**: Full-text search and complex query capabilities
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- [**ArangoDB Core**](../arangodb/3.12/_index.md): The ArangoDB database system with support for
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graphs, documents, key-value, full-text search, and vector search.
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### Graph Visualizer
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- [**Graph Visualizer**](graph-visualizer.md):
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A web-based tool for exploring your graph data with an intuitive interface and
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sophisticated querying capabilities.
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The [**Graph Visualizer**](graph-visualizer/) provides an intuitive web-based interface
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that brings your data to life with:
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## Extend the Arango Data Platform with AI capabilities
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- **Interactive Graph Exploration**: Visualize named graphs with node expansion,
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shortest path discovery, and AQL-powered queries including Canvas Actions that
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work with your selection to discover related data
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- **Visual Customization and Layouts**: Customize node colors, icons, and labels
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with saveable themes, and apply automatic layout algorithms (force-directed,
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hierarchical, circular) with zoom controls and minimap navigation
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- **Direct Graph Editing**: Create, modify, and delete nodes and edges directly
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from the canvas with an intuitive properties dialog supporting both form and
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JSON editing modes
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Take your Arango Data Platform to the next level with the [**AI Suite**](../ai-suite/_index.md) that offers advanced AI and machine learning capabilities that integrate seamlessly into the platform's unified web interface.
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The Graph Visualizer seamlessly integrates with the ArangoDB database and provides the
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primary interface for data exploration and analysis.
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What you get with the AI Suite:
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### Arango Platform Suite
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- [GraphRAG](../ai-suite/graphrag/): Generate knowledge graphs from documents and enable
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conversational querying of your data.
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- [GraphML](../ai-suite/graphml/): Apply machine learning algorithms that leverage graph
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structure for better predictions.
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- [Graph Analytics](../ai-suite/graph-analytics/): Run advanced algorithms like PageRank
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to discover influential nodes and patterns.
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- [Jupyter notebooks](../ai-suite/notebook-servers.md): Run Jupyter Notebooks to build and
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experiment with graph-powered data, AI, and machine learning workflows directly connected
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to ArangoDB databases.
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- Public and private LLM support: Use public LLMs such as OpenAI
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or private LLMs with [Triton Inference Server](../ai-suite/reference/triton-inference-server.md).
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- [MLflow integration](../ai-suite/reference/mlflow.md): Use the popular MLflow as a model registry
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for private LLMs or to run machine learning experiments as part of the Arango Data Platform.
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The **Arango Platform Suite** adds enterprise-grade capabilities such as:
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{{< tip >}}
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The AI Suite integrate directly into the existing platform interface, no need for
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separate systems to manage or learn. A separate license is required.
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{{< /tip >}}
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- **High Availability and Monitoring**: Comprehensive health checks, metrics collection,
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alerting, and automatic failover mechanisms ensure your data platform stays operational.
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Real-time monitoring dashboards provide visibility into cluster performance,
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resource utilization, and query patterns.
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- **APIs, Drivers and Connectors**: Comprehensive programmatic access through
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RESTful APIs, native drivers for popular programming languages (Java, Python,
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JavaScript, Go, PHP, and more), and connectors for data integration tools
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and BI platforms.
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- **Centralized Orchestration and Resource Management**: Unified control plane
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for managing all platform resources, deployments, and configurations.
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Kubernetes-powered orchestration handles scaling, updates, and resource
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allocation automatically across all components.
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These enterprise features are orchestrated through Kubernetes and the ArangoDB
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Kubernetes Operator, providing automated management and enterprise-grade reliability.

‎site/content/data-platform/get-started.md‎

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## Use the Arango Data Platform as a managed service
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The Arango Data Platform is not available as a managed service yet, but it will
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become available for the [Arango Managed Platform (AMP)](../../amp/_index.md)
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in the future. Until then, you can request early access to the self-hosted
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Arango Data Platform for testing.
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You can request the Arango Data Platform as a managed service for the
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[Arango Managed Platform (AMP)](../../amp/_index.md).
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[Get in touch](https://arango.ai/contact-us/) with the Arango team to learn more.
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## Self-host the Arango Data Platform
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‎site/content/data-platform/kubernetes.md‎

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---
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title: Kubernetes-Native Architecture
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menuTitle: Kubernetes
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weight: 15
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description: >-
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The Arango Data Platform is purpose-built for Kubernetes, leveraging
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container orchestration for automated deployment, scaling, and management
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---
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The Arango Data Platform is **Kubernetes-native** by design, meaning it is built
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from the ground up to run on [Kubernetes](https://kubernetes.io/) and requires
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it to function. This is not an optional feature, Kubernetes is the foundation
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that powers the entire platform architecture.
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{{< info >}}
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**Kubernetes Required**: The Arango Data Platform cannot operate without Kubernetes.
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It relies on Kubernetes orchestration and the
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[ArangoDB Kubernetes Operator](https://arangodb.github.io/kube-arangodb/) for
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all deployment, scaling, and management operations.
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{{< /info >}}
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## Why Kubernetes?
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By building exclusively on Kubernetes, the Arango Data Platform delivers
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enterprise-grade capabilities that would be difficult or impossible to achieve
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with traditional deployment approaches:
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- **Automated Management and Self-Healing**: Kubernetes handles deployment,
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scaling, node failures, and rolling updates automatically, with self-healing
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capabilities that restart failed containers and maintain high availability
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without manual intervention.
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- **Dynamic Scalability and Resource Optimization**: Scale your database cluster
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up or down based on workload demands, with efficient resource allocation and
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scheduling ensuring optimal utilization of CPU, memory, and storage.
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- **Declarative Configuration and Zero-Downtime Updates**: Define your desired
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state using Kubernetes manifests and deploy updates with zero downtime through
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controlled rolling updates and easy rollback capabilities.
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- **Cloud and On-Premises Flexibility**: Run on any Kubernetes-compatible
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environment—public cloud providers (AWS, Azure, GCP), private cloud, or
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on-premises infrastructure—with consistent deployment across all environments.
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## The ArangoDB Kubernetes Operator
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The Arango Data Platform is powered by the official
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[ArangoDB Kubernetes Operator](https://arangodb.github.io/kube-arangodb/)
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(`kube-arangodb`), which provides the following features:
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- **Custom Resource Definitions (CRDs)**: Extend Kubernetes with ArangoDB-specific
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resources like `ArangoDeployment`, `ArangoBackup`, and more.
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- **Intelligent Orchestration**: The operator understands ArangoDB's architecture
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and requirements, ensuring deployments follow best practices automatically.
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- **Backup and Restore**: Automated backup management integrated directly into
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the Kubernetes workflow.
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- **High Availability**: Built-in support for multi-datacenter replication,
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automatic failover, and disaster recovery scenarios.
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- **Enterprise Features**: Full support for ArangoDB Enterprise Edition features
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including encryption, auditing, and advanced security controls.
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For detailed information about the operator, see the
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[ArangoDB Kubernetes Operator documentation](https://arangodb.github.io/kube-arangodb/docs/).
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## Platform Services as Kubernetes Resources
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All components of the Arango Data Platform, from the core database to the optional
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AI Suite, are deployed and managed as native Kubernetes resources. This
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means you can do the following:
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- Use standard Kubernetes tools (`kubectl`, Helm, etc.) to manage your deployment
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- Monitor platform health using Kubernetes-native observability tools
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- Integrate with existing Kubernetes infrastructure and workflows
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- Apply your organization's Kubernetes policies and security controls
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This Kubernetes-native approach ensures the Arango Data Platform fits naturally
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into modern cloud-native environments and DevOps practices.
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