mirror of https://github.com/grafana/loki
docs: Cloud Deployment Azure (backport release-3.3.x) (#15651)
Co-authored-by: Jay Clifford <45856600+Jayclifford345@users.noreply.github.com>pull/15654/head
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--- |
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title: Deploy the Loki Helm chart on Azure |
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menuTitle: Deploy on Azure |
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description: Installing the Loki Helm chart on Azure. |
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keywords: |
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--- |
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|
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# Deploy the Loki Helm chart on Azure |
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|
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This guide shows how to deploy a minimally viable Loki in **microservice** mode on Azure using the Helm chart. In order to successfully complete this guide, you must have the necessary tools and permissions to deploy resources on Azure, such as: |
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- Full access to AKS (Azure Kubernetes Service) |
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- Full access to Azure Blob Storage |
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- Sufficient permissions to create federated credentials and roles in Azure AD (Active Directory) |
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|
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There are three primary ways to authenticate Loki with Azure: |
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- Hard coding a connection string - this is the simplest method but is not recommended for production environments. |
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- Manged identity |
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- Federated token |
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In this guide, we will use the federated token method to deploy Loki on Azure. This method is more secure than hard coding a connection string and is more suitable for production environments. |
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|
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## Considerations |
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|
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{{< admonition type="caution" >}} |
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This guide was accurate at the time it was last updated on **8th of January, 2025**. As cloud providers frequently update their services and offerings, as a best practice, you should refer to the [Azure documentation](https://learn.microsoft.com/en-us/azure/) before creating your storage account and assigning roles. |
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{{< /admonition >}} |
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|
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- **AD Role:** In this tutorial we will create a role in Azure Active Directory (Azure AD) to allow Loki to read and write from Azure Blob Storage. This role will be assigned to the Loki service account. You may want to adjust the permissions based on your requirements. |
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- **Authentication:** Grafana Loki comes with a basic authentication layer. The Loki gateway (NGINX) is exposed to the internet using basic authentication in this example. NGINX can also be replaced with other open-source reverse proxies. Refer to [Authentication](https://grafana.com/docs/loki/<LOKI_VERSION>/operations/authentication/) for more information. |
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|
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- **Retention:** The retention period is set to 28 days in the `values.yaml` file. You may wish to adjust this based on your requirements. |
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|
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- **Costs:** Running Loki on Azure will incur costs. Make sure to monitor your usage and costs to avoid any unexpected bills. In this guide we have used a simple AKS cluster with 3 nodes and `Standard_E2ds_v5` instances. You may wish to adjust the instance types and number of nodes based on your workload. |
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|
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## Prerequisites |
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- Helm 3 or above. Refer to [Installing Helm](https://helm.sh/docs/intro/install/). This should be installed on your local machine. |
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- Kubectl installed on your local machine. Refer to [Install and Set Up kubectl](https://kubernetes.io/docs/tasks/tools/install-kubectl/). |
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- Azure CLI installed on your local machine. Refer to [Installing the Azure CLI](https://learn.microsoft.com/en-us/cli/azure/install-azure-cli). This is a requirement for following this guide as all resources will be created using the Azure CLI. |
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|
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### AKS minimum requirements |
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Before creating an AKS cluster in Azure you need to create a resource group. You can create a resource group using the Azure CLI: |
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|
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```bash |
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az group create --name <INSERT-NAME> -location <INSERT-AZURE-REGION> |
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``` |
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|
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{{< admonition type="caution" >}} |
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These AKS requirements are the minimum specification needed to deploy Loki using this guide. You may wish to adjust the instance types based on your Azure environment and workload. **If you choose to do so, we cannot guarantee that this sample configuration will still meet your needs.** |
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In this guide, we deploy Loki using `Standard_E2ds_v5` instances. This is to make sure we remain within the free tier limits for Azure. Which allows us to deploy up to 10 vCPUs within a region. We recommend for large production workloads to scale these nodes up to `Standard_D4_v5`. |
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{{< /admonition >}} |
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|
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The minimum requirements for deploying Loki on AKS are: |
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- Kubernetes version `1.30` or above. |
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- `3` nodes for the AKS cluster. |
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- Instance type depends on your workload. A good starting point for a production cluster in the free tier is `Standard_E2ds_v5` instances and for large production workloads `Standard_D4_v5` instances. |
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Here is how to create an AKS cluster with the minimum requirements: |
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```bash |
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az aks create \ |
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--resource-group <MY_RESOURCE_GROUP_NAME> \ |
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--name <MY_AKS_CLUSTER_NAME> \ |
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--node-count 3 \ |
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--node-vm-size Standard_E2ds_v5 \ |
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--generate-ssh-keys \ |
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--enable-workload-identity \ |
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--enable-oidc-issuer |
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``` |
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Note in the above command we have enabled workload identity and OIDC issuer. This is required for the Loki service account to authenticate with Azure AD. If you have already created an AKS cluster, you can enable these features using the following command: |
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```bash |
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az aks update \ |
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--resource-group <MY_RESOURCE_GROUP_NAME> \ |
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--name <MY_AKS_CLUSTER_NAME> \ |
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--enable-workload-identity \ |
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--enable-oidc-issuer |
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``` |
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|
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The Azure CLI also lets you bind the AKS cluster to kubectl. You can do this by running the following command: |
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|
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```bash |
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az aks get-credentials --resource-group <MY_RESOURCE_GROUP_NAME> --name <MY_AKS_CLUSTER_NAME> |
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``` |
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|
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## Configuring Azure Blob Storage |
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{{< admonition type="tip" >}} |
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Consider using unique bucket names rather than: `chunk`, `ruler`, and `admin`. Although Azure Blog Storage is not directly affected by this [security update](https://grafana.com/blog/2024/06/27/grafana-security-update-grafana-loki-and-unintended-data-write-attempts-to-amazon-s3-buckets/) it is a best practice to use unique container names for buckets. |
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{{< /admonition >}} |
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Before deploying Loki, you need to create two Azure storage containers; one to store logs (chunks), the second to store alert rules. You can create the containers using the Azure CLI. Containers must exist inside a storage account. |
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{{< admonition type="note" >}} |
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GEL customers will require a third container to store the admin data. This container is not required for OSS users. |
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{{< /admonition >}} |
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1. Create a storage account: |
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```bash |
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az storage account create \ |
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--name <NAME> \ |
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--location <REGION> \ |
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--sku Standard_ZRS \ |
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--encryption-services blob \ |
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--resource-group <MY_RESOURCE_GROUP_NAME> |
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``` |
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Replace the placeholders with your desired values. |
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1. Create the containers for chunks and ruler: |
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|
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```bash |
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az storage container create --account-name <STORAGE-ACCOUNT-NAME> --name <CHUNK-BUCKET-NAME> --auth-mode login && \ |
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az storage container create --account-name <STORAGE-ACCOUNT-NAME> --name <RULER-BUCKET-NAME> --auth-mode login |
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``` |
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Make sure `--account-name` matches the account you just created |
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With the storage account and containers created, you can now proceed to creating the Azure AD role and federated credentials. |
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|
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## Creating the Azure AD role and federated credentials |
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The recommended way to authenticate Loki with Azure Blob Storage is to use federated credentials. This method is more secure than hard coding a connection string directly into the Loki configuration. In this next section, we will create an Azure AD role and federated credentials for Loki to allow it to read and write from Azure Blob Storage: |
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|
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1. Locate the OpenID Connect (OIDC) issuer URL: |
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|
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```bash |
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az aks show \ |
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--resource-group <MY_RESOURCE_GROUP_NAME> \ |
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--name <MY_AKS_CLUSTER_NAME> \ |
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--query "oidcIssuerProfile.issuerUrl" \ |
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-o tsv |
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``` |
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This command will return the OIDC issuer URL. You will need this URL to create the federated credentials. |
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1. Generate a `credentials.json` file with the following content: |
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```json |
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{ |
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"name": "LokiFederatedIdentity", |
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"issuer": "<OIDC-ISSUER-URL>", |
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"subject": "system:serviceaccount:loki:loki", |
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"description": "Federated identity for Loki accessing Azure resources", |
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"audiences": [ |
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"api://AzureADTokenExchange" |
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] |
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} |
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``` |
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Replace `<OIDC-ISSUER-URL>` with the OIDC issuer URL you found in the previous step. |
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1. Make sure you to save the `credentials.json` file before continuing. |
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1. Next generate an Azure directory `app`. We will use this to assign our federated credentials to: |
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```bash |
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az ad app create \ |
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--display-name loki \ |
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--query appId \ |
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-o tsv |
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``` |
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This will return the app ID. Save this for later use. If you need to find the app ID later you can run the following command: |
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```bash |
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az ad app list --display-name loki --query "[].appId" -o tsv |
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``` |
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1. The app requires a service principal to authenticate with Azure AD. Create a service principal for the app: |
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```bash |
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az ad sp create --id <APP-ID> |
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``` |
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Replace `<APP-ID>` with the app ID you generated in the previous step. |
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1. Next assign the federated credentials to the app: |
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```bash |
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az ad app federated-credential create \ |
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--id <APP-ID> \ |
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--parameters credentials.json |
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``` |
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Replace `<APP-ID>` with the app ID you generated in the previous step. |
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1. Lastly add a role assignment to the app: |
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```bash |
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az role assignment create \ |
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--role "Storage Blob Data Contributor" \ |
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--assignee <APP-ID> \ |
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--scope /subscriptions/<SUBSCRIPTION-ID>/resourceGroups/<RESOURCE-GROUP>/providers/Microsoft.Storage/storageAccounts/<STORAGE-ACCOUNT-NAME> |
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``` |
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Replace the placeholders with your actual values. |
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Now that you have created the Azure AD role and federated credentials, you can proceed to deploying Loki using the Helm chart. |
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## Deploying the Helm chart |
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The following steps require the use of `helm` and `kubectl`. Make sure you have run the `az` command to bind your AKS cluster to `kubectl`: |
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```bash |
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az aks get-credentials --resource-group <MY_RESOURCE_GROUP_NAME> --name <MY_AKS_CLUSTER_NAME> |
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``` |
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Before we can deploy the Loki Helm chart, we need to add the Grafana chart repository to Helm. This repository contains the Loki Helm chart. |
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1. Add the Grafana chart repository to Helm: |
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```bash |
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helm repo add grafana https://grafana.github.io/helm-charts |
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``` |
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1. Update the chart repository: |
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```bash |
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helm repo update |
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``` |
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1. Create a new namespace for Loki: |
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```bash |
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kubectl create namespace loki |
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``` |
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### Loki basic authentication |
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Loki by default does not come with any authentication. Since we will be deploying Loki to Azure and exposing the gateway to the internet, we recommend adding at least basic authentication. In this guide we will give Loki a username and password: |
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1. To start we will need create a `.htpasswd` file with the username and password. You can use the `htpasswd` command to create the file: |
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{{< admonition type="tip" >}} |
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If you don't have the `htpasswd` command installed, you can install it using `brew` or `apt-get` or `yum` depending on your OS. |
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{{< /admonition >}} |
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```bash |
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htpasswd -c .htpasswd <username> |
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``` |
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This will create a file called `auth` with the username `loki`. You will be prompted to enter a password. |
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1. Create a Kubernetes secret with the `.htpasswd` file: |
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```bash |
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kubectl create secret generic loki-basic-auth --from-file=.htpasswd -n loki |
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``` |
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This will create a secret called `loki-basic-auth` in the `loki` namespace. We will reference this secret in the Loki Helm chart configuration. |
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1. Create a `canary-basic-auth` secret for the canary: |
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```bash |
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kubectl create secret generic canary-basic-auth \ |
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--from-literal=username=<USERNAME> \ |
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--from-literal=password=<PASSWORD> \ |
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-n loki |
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``` |
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We create a literal secret with the username and password for Loki canary to authenticate with the Loki gateway. Make sure to replace the placeholders with your desired username and password. |
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### Loki Helm chart configuration |
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Create a `values.yaml` file choosing the configuration options that best suit your requirements. Below there is an example of `values.yaml` files for the Loki Helm chart in [microservices](https://grafana.com/docs/loki/<LOKI_VERSION>/get-started/deployment-modes/#microservices-mode) mode. |
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```yaml |
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loki: |
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podLabels: |
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"azure.workload.identity/use": "true" # Add this label to the Loki pods to enable workload identity |
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schemaConfig: |
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configs: |
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- from: "2024-04-01" |
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store: tsdb |
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object_store: azure |
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schema: v13 |
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index: |
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prefix: loki_index_ |
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period: 24h |
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storage_config: |
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azure: |
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account_name: "<INSERT-STORAGE-ACCOUNT-NAME>" |
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container_name: "<CHUNK-CONTAINER-NAME>" # Your actual Azure Blob Storage container name (loki-azure-dev-chunks) |
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use_federated_token: true # Use federated token for authentication |
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ingester: |
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chunk_encoding: snappy |
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pattern_ingester: |
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enabled: true |
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limits_config: |
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allow_structured_metadata: true |
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volume_enabled: true |
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retention_period: 672h # 28 days retention |
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compactor: |
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retention_enabled: true |
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delete_request_store: azure |
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ruler: |
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enable_api: true |
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storage: |
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type: azure |
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azure: |
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account_name: <INSERT-STORAGE-ACCOUNT-NAME> |
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container_name: <RULER-CONTAINER-NAME> # Your actual Azure Blob Storage container name (loki-azure-dev-ruler) |
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use_federated_token: true # Use federated token for authentication |
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alertmanager_url: http://prom:9093 # The URL of the Alertmanager to send alerts (Prometheus, Mimir, etc.) |
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querier: |
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max_concurrent: 4 |
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storage: |
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type: azure |
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bucketNames: |
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chunks: "<CHUNK-CONTAINER-NAME>" # Your actual Azure Blob Storage container name (loki-azure-dev-chunks) |
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ruler: "<RULER-CONTAINER-NAME>" # Your actual Azure Blob Storage container name (loki-azure-dev-ruler) |
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# admin: "admin-loki-devrel" # Your actual Azure Blob Storage container name (loki-azure-dev-admin) |
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azure: |
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accountName: <INSERT-STORAGE-ACCOUNT-NAME> |
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useFederatedToken: true # Use federated token for authentication |
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|
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# Define the Azure workload identity |
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serviceAccount: |
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name: loki |
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annotations: |
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"azure.workload.identity/client-id": "<APP-ID>" # The app ID of the Azure AD app |
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labels: |
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"azure.workload.identity/use": "true" |
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deploymentMode: Distributed |
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ingester: |
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replicas: 3 |
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zoneAwareReplication: |
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enabled: false |
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|
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querier: |
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replicas: 3 |
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maxUnavailable: 2 |
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|
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queryFrontend: |
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replicas: 2 |
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maxUnavailable: 1 |
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|
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queryScheduler: |
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replicas: 2 |
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|
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distributor: |
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replicas: 3 |
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maxUnavailable: 2 |
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compactor: |
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replicas: 1 |
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|
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indexGateway: |
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replicas: 2 |
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maxUnavailable: 1 |
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|
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ruler: |
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replicas: 1 |
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maxUnavailable: 1 |
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|
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|
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# This exposes the Loki gateway so it can be written to and queried externaly |
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gateway: |
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service: |
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type: LoadBalancer |
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basicAuth: |
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enabled: true |
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existingSecret: loki-basic-auth |
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|
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# Since we are using basic auth, we need to pass the username and password to the canary |
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lokiCanary: |
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extraArgs: |
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- -pass=$(LOKI_PASS) |
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- -user=$(LOKI_USER) |
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extraEnv: |
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- name: LOKI_PASS |
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valueFrom: |
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secretKeyRef: |
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name: canary-basic-auth |
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key: password |
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- name: LOKI_USER |
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valueFrom: |
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secretKeyRef: |
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name: canary-basic-auth |
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key: username |
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|
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# Enable minio for storage |
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minio: |
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enabled: false |
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|
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backend: |
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replicas: 0 |
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read: |
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replicas: 0 |
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write: |
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replicas: 0 |
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singleBinary: |
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replicas: 0 |
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``` |
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|
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{{< admonition type="caution" >}} |
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Make sure to replace the placeholders with your actual values. |
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{{< /admonition >}} |
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|
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It is critical to define a valid `values.yaml` file for the Loki deployment. To remove the risk of misconfiguration, let's break down the configuration options to keep in mind when deploying to Azure: |
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|
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- **Loki Config vs. Values Config:** |
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- The `values.yaml` file contains a section called `loki`, which contains a direct representation of the Loki configuration file. |
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- This section defines the Loki configuration, including the schema, storage, and querier configuration. |
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- The key configuration to focus on for chunks is the `storage_config` section, where you define the Azure container name and storage account. This tells Loki where to store the chunks. |
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- The `ruler` section defines the configuration for the ruler, including the Azure container name and storage account. This tells Loki where to store the alert and recording rules. |
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- For the full Loki configuration, refer to the [Loki Configuration](https://grafana.com/docs/loki/<LOKI_VERSION>/configure/) documentation. |
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|
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- **Storage:** |
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- Defines where the Helm chart stores data. |
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- Set the type to `azure` since we are using Azure Blob Storage. |
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- Configure the container names for the chunks and ruler to match the containers created earlier. |
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- The `azure` section specifies the storage account name and also sets `useFederatedToken` to `true`. This tells Loki to use federated credentials for authentication. |
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|
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- **Service Account:** |
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- The `serviceAccount` section is used to define the federated workload identity Loki will use to authenticate with Azure AD. |
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- We set the `azure.workload.identity/client-id` annotation to the app ID of the Azure AD app. |
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|
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- **Gateway:** |
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- Defines how the Loki gateway will be exposed. |
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- We are using a `LoadBalancer` service type in this configuration. |
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|
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|
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### Deploy Loki |
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|
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Now that you have created the `values.yaml` file, you can deploy Loki using the Helm chart. |
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|
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1. Deploy using the newly created `values.yaml` file: |
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|
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```bash |
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helm install --values values.yaml loki grafana/loki -n loki --create-namespace |
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``` |
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It is important to create a namespace called `loki` as our federated credentials were generated with the value `system:serviceaccount:loki:loki`. This translates to the `loki` service account in the `loki` namespace. This is configurable but make sure to update the federated credentials file first. |
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|
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1. Verify the deployment: |
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|
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```bash |
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kubectl get pods -n loki |
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``` |
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You should see the Loki pods running. |
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|
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```console |
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NAME READY STATUS RESTARTS AGE |
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loki-canary-crqpg 1/1 Running 0 10m |
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loki-canary-hm26p 1/1 Running 0 10m |
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loki-canary-v9wv9 1/1 Running 0 10m |
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loki-chunks-cache-0 2/2 Running 0 10m |
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loki-compactor-0 1/1 Running 0 10m |
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loki-distributor-78ccdcc9b4-9wlhl 1/1 Running 0 10m |
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loki-distributor-78ccdcc9b4-km6j2 1/1 Running 0 10m |
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loki-distributor-78ccdcc9b4-ptwrb 1/1 Running 0 10m |
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loki-gateway-5f97f78755-hm6mx 1/1 Running 0 10m |
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loki-index-gateway-0 1/1 Running 0 10m |
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loki-index-gateway-1 1/1 Running 0 10m |
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loki-ingester-zone-a-0 1/1 Running 0 10m |
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loki-ingester-zone-b-0 1/1 Running 0 10m |
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loki-ingester-zone-c-0 1/1 Running 0 10m |
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loki-querier-89d4ff448-4vr9b 1/1 Running 0 10m |
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loki-querier-89d4ff448-7nvrf 1/1 Running 0 10m |
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loki-querier-89d4ff448-q89kh 1/1 Running 0 10m |
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loki-query-frontend-678899db5-n5wc4 1/1 Running 0 10m |
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loki-query-frontend-678899db5-tf69b 1/1 Running 0 10m |
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loki-query-scheduler-7d666bf759-9xqb5 1/1 Running 0 10m |
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loki-query-scheduler-7d666bf759-kpb5q 1/1 Running 0 10m |
||||
loki-results-cache-0 2/2 Running 0 10m |
||||
loki-ruler-0 1/1 Running 0 10m |
||||
``` |
||||
|
||||
### Find the Loki gateway service |
||||
|
||||
The Loki gateway service is a load balancer service that exposes the Loki gateway to the internet. This is where you will write logs to and query logs from. By default NGINX is used as the gateway. |
||||
|
||||
{{< admonition type="caution" >}} |
||||
The Loki gateway service is exposed to the internet. We provide basic authentication using a username and password in this tutorial. Refer to the [Authentication](https://grafana.com/docs/loki/<LOKI_VERSION>/operations/authentication/) documentation for more information. |
||||
{{< /admonition >}} |
||||
|
||||
To find the Loki gateway service, run the following command: |
||||
|
||||
```bash |
||||
kubectl get svc -n loki |
||||
``` |
||||
You should see the Loki gateway service with an external IP address. This is the address you will use to write to and query Loki. |
||||
|
||||
```console |
||||
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE |
||||
loki-gateway LoadBalancer 10.100.201.74 134.236.21.145 80:30707/TCP 46m |
||||
``` |
||||
|
||||
Congratulations! You have successfully deployed Loki on Azure using the Helm chart. Before we finish, let's test the deployment. |
||||
|
||||
## Testing Your Loki Deployment |
||||
|
||||
k6 is one of the fastest ways to test your Loki deployment. This will allow you to both write and query logs to Loki. To get started with k6, follow the steps below: |
||||
|
||||
1. Install k6 with the Loki extension on your local machine. Refer to [Installing k6 and the xk6-loki extension](https://grafana.com/docs/loki/<LOKI_VERSION>/send-data/k6/). |
||||
|
||||
2. Create a `azure-test.js` file with the following content: |
||||
|
||||
```javascript |
||||
import {sleep, check} from 'k6'; |
||||
import loki from 'k6/x/loki'; |
||||
|
||||
/** |
||||
* URL used for push and query requests |
||||
* Path is automatically appended by the client |
||||
* @constant {string} |
||||
*/ |
||||
|
||||
const username = '<USERNAME>'; |
||||
const password = '<PASSWORD>'; |
||||
const external_ip = '<EXTERNAL-IP>'; |
||||
|
||||
const credentials = `${username}:${password}`; |
||||
|
||||
const BASE_URL = `http://${credentials}@${external_ip}`; |
||||
|
||||
/** |
||||
* Helper constant for byte values |
||||
* @constant {number} |
||||
*/ |
||||
const KB = 1024; |
||||
|
||||
/** |
||||
* Helper constant for byte values |
||||
* @constant {number} |
||||
*/ |
||||
const MB = KB * KB; |
||||
|
||||
/** |
||||
* Instantiate config and Loki client |
||||
*/ |
||||
|
||||
const conf = new loki.Config(BASE_URL); |
||||
const client = new loki.Client(conf); |
||||
|
||||
/** |
||||
* Define test scenario |
||||
*/ |
||||
export const options = { |
||||
vus: 10, |
||||
iterations: 10, |
||||
}; |
||||
|
||||
export default () => { |
||||
// Push request with 10 streams and uncompressed logs between 800KB and 2MB |
||||
var res = client.pushParameterized(10, 800 * KB, 2 * MB); |
||||
// Check for successful write |
||||
check(res, { 'successful write': (res) => res.status == 204 }); |
||||
|
||||
// Pick a random log format from label pool |
||||
let format = randomChoice(conf.labels["format"]); |
||||
|
||||
// Execute instant query with limit 1 |
||||
res = client.instantQuery(`count_over_time({format="${format}"}[1m])`, 1) |
||||
// Check for successful read |
||||
check(res, { 'successful instant query': (res) => res.status == 200 }); |
||||
|
||||
// Execute range query over last 5m and limit 1000 |
||||
res = client.rangeQuery(`{format="${format}"}`, "5m", 1000) |
||||
// Check for successful read |
||||
check(res, { 'successful range query': (res) => res.status == 200 }); |
||||
|
||||
// Wait before next iteration |
||||
sleep(1); |
||||
} |
||||
|
||||
/** |
||||
* Helper function to get random item from array |
||||
*/ |
||||
function randomChoice(items) { |
||||
return items[Math.floor(Math.random() * items.length)]; |
||||
} |
||||
``` |
||||
|
||||
Replace `<EXTERNAL-IP>` with the external IP address of the Loki Gateway service. |
||||
|
||||
This script will write logs to Loki and query logs from Loki. It will write logs in a random format between 800KB and 2MB and query logs in a random format over the last 5 minutes. |
||||
|
||||
3. Run the test: |
||||
|
||||
```bash |
||||
./k6 run azure-test.js |
||||
``` |
||||
|
||||
This will run the test and output the results. You should see the test writing logs to Loki and querying logs from Loki. |
||||
|
||||
Now that you have successfully deployed Loki in microservices mode on Microsoft Azure, you may wish to explore the following: |
||||
|
||||
- [Sending data to Loki](https://grafana.com/docs/loki/<LOKI_VERSION/send-data/) |
||||
- [Querying Loki](https://grafana.com/docs/loki/<LOKI_VERSION>/query/) |
||||
- [Manage Loki](https://grafana.com/docs/loki/<LOKI_VERSION/operations/) |
||||
Loading…
Reference in new issue