--- title: Quick Start | LlamaIndex OSS Documentation --- ## Self-Hosting Documentation Access This section requires a password to access. Interested in self-hosting? [Contact sales](https://www.llamaindex.ai/contact) to learn more. Password: Access Documentation Self-Hosting Documentation Access Granted Logout Note This page assumes that you are deploying the latest version of LlamaCloud. Please refer to the [release notes](https://github.com/run-llama/helm-charts/releases) for more information about previous versions. ## Before You Get Started Welcome to LlamaCloud! Before you get started, please make sure you have the following prerequisites: - **LlamaCloud License Key**. To obtain a LlamaCloud License Key, please contact us at [support@llamaindex.ai](mailto:contact@llamaindex.ai). - **Kubernetes cluster `>=1.28.0`** and a working installation of `kubectl`. - We are largely aligned with the versions supported in [EKS](https://endoflife.date/amazon-eks), [AKS](https://learn.microsoft.com/en-us/azure/aks/supported-kubernetes-versions?tabs=azure-cli), and [GKE](https://cloud.google.com/kubernetes-engine/versioning). - **Helm `v3.7.0+`** - To install Helm, please refer to the [official Helm Documentation](https://helm.sh/docs/intro/install/). - **OpenAI API Key** or **Azure OpenAI Credentials**. Configuring OpenAI credentials is the easiest way to get started with your deployment. - LlamaCloud tries to meet you at your organization’s needs and supports configuring more than OpenAI LLMs in including Anthropic, Bedrock, Vertex AI, and more. - Please refer to the docs in the **Configuration** section of the sidebar to learn more about configuring other LLMs. - **File Storage**: LlamaCloud must leverage your cloud provider’s object storage to store files. - Please follow the [File Storage](/llamaparse/self_hosting/configuration/file-storage/index.md) documentation to configure your deployment. - **Authentication Settings**: - **OIDC**. OIDC is our recommended authentication mode for production deployments. - **Basic Auth** (email/password): As of July 24th, 2025 (`v0.5.0`), we support both `oidc` and `basic` authentication methods. This is a simpler authentication mode more suitable for staging deployments. - For more information, please refer to the [Authentication Modes](/llamaparse/self_hosting/configuration/auth-modes/index.md) documentation. - **Credentials to External Services (See below)**. ## External Services **LLamaCloud** requires the following external services to be available: **Postgres**, **MongoDB**, **Temporal**, **RabbitMQ** and **Redis**. Tip **Temporal** can be deployed as a subchart within LlamaCloud by setting `temporal.deploy: true`. This is the recommended approach for getting started quickly. For production deployments, you may prefer to manage Temporal separately. Please follow the [Database and Queues](/llamaparse/self_hosting/configuration/db_and_queues/overview/index.md) documentation to configure these services for your deployment. ## Hardware Requirements - **Linux Instances running x86 CPUs** - We currently only linux/amd64 images. arm64 is not supported at this moment. - **Ubuntu >=22.04** - **>=12 vCPUs** - **>=80Gbi Memory** **Warning #1**: LlamaParse, LlamaIndex’s proprietary document parser, can be a very resource-intensive deployment to run, especially if you want to maximize performance. **Warning #2**: The base CPU/memory requirements may increase if you are running containerized deployments of LlamaCloud dependencies. (More information in the following section) ## Configure and Install Your Deployment This section will walk you through the steps to configure a minimal LlamaCloud deployment. ### Minimal `values.yaml` configuration To get a minimal LlamaCloud deployment up and running, you can create a `values.yaml` file with the following content: - [OpenAI w/ OIDC Auth](#tab-panel-36) - [Azure OpenAI w/ OIDC Auth](#tab-panel-37) - [OpenAI w/ Basic Auth](#tab-panel-38) - [Azure OpenAI w/ Basic Auth](#tab-panel-39) ``` license: key: postgresql: host: "postgresql" port: "5432" database: "llamacloud" username: password: mongodb: host: "mongodb" port: "27017" username: password: rabbitmq: scheme: "amqp" host: "rabbitmq" port: "5672" username: password: redis: scheme: "redis" host: "redis-master" port: "6379" db: 0 # Deploy Temporal as a subchart (host/port auto-configured) temporal: deploy: true # Temporal subchart configuration (uses same PostgreSQL instance) temporal-subchart: server: config: persistence: default: sql: driver: postgres12 host: "postgresql" port: 5432 database: temporal user: password: visibility: sql: driver: postgres12 host: "postgresql" port: 5432 database: temporal_visibility user: password: config: llms: openAi: apiKey: frontend: enabled: true parseOcr: gpu: true authentication: oidc: enabled: true discoveryUrl: "https://login.microsoftonline.com//v2.0/.well-known/openid-configuration" clientId: clientSecret: ``` ``` license: key: postgresql: host: "postgresql" port: "5432" database: "llamacloud" username: password: mongodb: host: "mongodb" port: "27017" username: password: rabbitmq: scheme: "amqp" host: "rabbitmq" port: "5672" username: password: redis: scheme: "redis" host: "redis-master" port: "6379" db: 0 # Deploy Temporal as a subchart (host/port auto-configured) temporal: deploy: true # Temporal subchart configuration (uses same PostgreSQL instance) temporal-subchart: server: config: persistence: default: sql: driver: postgres12 host: "postgresql" port: 5432 database: temporal user: password: visibility: sql: driver: postgres12 host: "postgresql" port: 5432 database: temporal_visibility user: password: config: llms: azureOpenAi: secret: "" deployments: [] frontend: enabled: true parseOcr: gpu: true authentication: oidc: enabled: true discoveryUrl: "https://login.microsoftonline.com//v2.0/.well-known/openid-configuration" clientId: clientSecret: ``` ``` license: key: postgresql: host: "postgresql" port: "5432" database: "llamacloud" username: password: mongodb: host: "mongodb" port: "27017" username: password: rabbitmq: scheme: "amqp" host: "rabbitmq" port: "5672" username: password: redis: scheme: "redis" host: "redis-master" port: "6379" db: 0 # Deploy Temporal as a subchart (host/port auto-configured) temporal: deploy: true # Temporal subchart configuration (uses same PostgreSQL instance) temporal-subchart: server: config: persistence: default: sql: driver: postgres12 host: "postgresql" port: 5432 database: temporal user: password: visibility: sql: driver: postgres12 host: "postgresql" port: 5432 database: temporal_visibility user: password: config: llms: openAi: apiKey: frontend: enabled: true parseOcr: gpu: true authentication: basicAuth: enabled: true validEmailDomain: "llamaindex.ai" # this is optional, but recommended for production deployments jwtSecret: ``` ``` license: key: postgresql: host: "postgresql" port: "5432" database: "llamacloud" username: password: mongodb: host: "mongodb" port: "27017" username: password: rabbitmq: scheme: "amqp" host: "rabbitmq" port: "5672" username: password: redis: scheme: "redis" host: "redis-master" port: "6379" db: 0 # Deploy Temporal as a subchart (host/port auto-configured) temporal: deploy: true # Temporal subchart configuration (uses same PostgreSQL instance) temporal-subchart: server: config: persistence: default: sql: driver: postgres12 host: "postgresql" port: 5432 database: temporal user: password: visibility: sql: driver: postgres12 host: "postgresql" port: 5432 database: temporal_visibility user: password: config: llms: azureOpenAi: secret: "" deployments: [] frontend: enabled: true parseOcr: gpu: true authentication: basicAuth: enabled: true validEmailDomain: "llamaindex.ai" # this is optional, but recommended for production deployments jwtSecret: ``` ## Install the Helm chart Terminal window ``` # Add the Helm repository helm repo add llamaindex https://run-llama.github.io/helm-charts # Update your local Helm chart cache helm repo update # Create the llamacloud namespace kubectl create ns llamacloud # Install the Helm chart helm install llamacloud llamaindex/llamacloud -f values.yaml --namespace llamacloud ``` If you want to install a specific version of the Helm chart, you can specify the version: Terminal window ``` helm install llamacloud llamaindex/llamacloud --version x.y.z -f values.yaml --namespace llamacloud ``` ## Validate the installation After installation, you will see the following output: ``` NNAME: llamacloud LAST DEPLOYED: Tue Nov 18 10:12:03 2025 NAMESPACE: llamacloud STATUS: deployed REVISION: 1 TEST SUITE: None NOTES: Welcome to LlamaCloud! View your deployment with the following: kubectl --namespace default get pods -n llamacloud To view LlamaCloud UI in your browser: Run the following command: kubectl --namespace llamacloud port-forward svc/llamacloud-web 3000:80 ``` If you list the pods with `kubectl get pods -n llamacloud`, you should see the following pods: ``` NAME READY STATUS RESTARTS AGE llamacloud-64f468d5cf-sqjq6 1/1 Running 0 2m56s llamacloud-layout-6d97b84c58-rld8x 1/1 Running 0 2m56s llamacloud-ocr-5cc459bdd-99xgt 1/1 Running 0 2m56s llamacloud-operator-5d4c58b854-dwnjk 1/1 Running 0 2m56s llamacloud-parse-7ffbc786b5-r98w2 1/1 Running 0 2m56s llamacloud-telemetry-5fc9ff8c67-fv8xj 1/1 Running 0 2m56s llamacloud-web-b88d95588-rprhc 1/1 Running 0 2m56s llamacloud-worker-58b95ccc6f-vqmgx 1/1 Running 0 2m56s ``` Port forward the frontend service to access the LlamaCloud UI: Terminal window ``` kubectl --namespace llamacloud port-forward svc/llamacloud-web 3000:80 ``` Open your web browser and navigate to `http://localhost:3000`. You should see the LlamaCloud UI. ## Next Steps Choose your deployment approach based on your needs: ### 🌩️ Cloud-Specific Deployment Guides **Recommended for most users** - Complete, opinionated guides for major cloud providers: **[📋 Choose Your Cloud Provider →](/llamaparse/self_hosting/cloud-specific-guides/overview/index.md)** - **Azure**: AKS + Azure-native services with Microsoft Entra ID - **AWS**: EKS + AWS-native services (coming soon) - **GCP**: GKE + GCP-native services (coming soon) *These guides provide end-to-end instructions using cloud-native services and enterprise authentication.* ### ⚙️ Custom Configuration Guides **For advanced users** with specific requirements or non-standard setups: - [Authentication Modes](/llamaparse/self_hosting/configuration/auth-modes/index.md) - Configure OIDC, basic auth, or custom authentication - [File Storage](/llamaparse/self_hosting/configuration/file-storage/index.md) - Set up S3, Azure Blob, GCS, or other storage - [Database and Queues](/llamaparse/self_hosting/configuration/db_and_queues/overview/index.md) - Configure external databases and message queues - [LLM Integrations](/llamaparse/self_hosting/configuration/llm_integrations/overview/index.md) - Set up OpenAI, Azure OpenAI, Bedrock, or other LLMs - [Ingress Configuration](/llamaparse/self_hosting/configuration/ingress/index.md) - Load balancers, SSL, and networking - [Autoscaling Configuration](/llamaparse/self_hosting/configuration/autoscaling-configuration/index.md) - HPA and KEDA-based scaling for services - [Service Tuning](/llamaparse/self_hosting/tuning/service-configurations/index.md) - Performance and scaling configurations *Use these guides if you need custom integrations, have specific compliance requirements, or want to mix and match different services.* ### 🚰 Data Sink Configuration Configure at least one [Data Sink](/llamaparse/cloud-index/integrations/data_sinks/index.md) to store the **vector embeddings** of your documents. ## More Examples and Guides - there are many more configuration options available for each component. to see the full values.yaml specification, please refer to the [values.yaml](https://github.com/run-llama/helm-charts/blob/main/charts/llamacloud/values.yaml) file in the helm chart repository. - To see how common scenarios are configured, please refer to the `values.yaml` [examples](https://github.com/run-llama/helm-charts/tree/main/charts/llamacloud/examples) directory in the Helm chart repository. - Similarly, we have other configuration [docs](https://github.com/run-llama/helm-charts/tree/main/charts/llamacloud/docs) available there too for more advanced configurations.