Documentation Grafana Loki Set up Install Install using Helm Cloud Deployment Guides Deploy on GCP

Deploy the Loki Helm chart on GCP

This guide shows how to deploy a minimally viable Loki in microservices mode on Google Cloud Platform (GCP) using the Helm chart. To run through this guide, we expect you to have the necessary tools and permissions to deploy resources on GCP, such as:

• Full access to Google Kubernetes Engine (GKE)
• Full access to Google Cloud Storage (GCS)
• Sufficient permissions to create Identity Access Management (IAM) roles and policies

There are two methods for authenticating and connecting Loki to GCP GCS. We will guide you through the recommended method of granting access via an IAM role: using Workload Identity Federation.

Considerations

• IAM Role: The IAM role created in this guide is a basic role that allows Loki to read and write to the GCS bucket. You may wish to add more granular permissions based on your requirements.

• 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 for more information.

• Retention: The retention period is set to 28 days in the values.yaml file. You may wish to adjust this based on your requirements.

• Costs: Running Loki on GCP will incur costs. Make sure to monitor your usage and costs to avoid any unexpected bills. In this guide we have used a simple GKE cluster with 3 nodes (n2-standard-8 instances). You may wish to adjust the instance types and number of nodes based on your workload.

Prerequisites

• Helm 3 or above. Refer to Installing Helm. This should be installed on your local machine.
• A running Kubernetes cluster on GCP. Refer to Create a cluster and deploy a workload in the Google Cloud console.
• Kubectl installed on your local machine. Refer to Install and Set Up kubectl.
• gcloud CLI installed on your local machine. Refer to Install the Google Cloud CLI. In this guide, we use gcloud CLI to create the GKE cluster and modify the IAM roles and policies locally.

GKE Minimum Requirements

The minimum requirements for deploying Loki on GKE are:

• Kubernetes version 1.30 or above.
• 3 nodes for the GKE cluster.
• Instance type depends on your workload. A good starting point for a production cluster is n2-standard-8.

To allow kubectl to support GKE, install the gcloud kubectl auth plugin:

bash Copy

gcloud components install gke-gcloud-auth-plugin

This plugin is necessary to use kubectl to authenticate with GKE. Click here for more details on this plugin.

Here is an example of a command you can run using gcloud CLI to create a new cluster:

bash Copy

gcloud container clusters create loki-gcp \
  --location=europe-west4 \
  --num-nodes=1 \
  --machine-type=n2-standard-8 \
  --release-channel=regular \
  --workload-pool=<PROJECT_ID>.svc.id.goog \
  --enable-ip-alias \
  --no-enable-basic-auth \
  --no-issue-client-certificate

Replace <PROJECT_ID> with the ID of the project you want to create the cluster in. This should be something like my-project-123456.

Create GCS buckets

Before deploying Loki, you need to create two GCS buckets: one to store logs (chunks) and another to store alert rules (ruler). You can create the bucket using the GCP Management Console or the GCP CLI. The bucket name must be globally unique.

bash Copy

gcloud storage buckets create gs://<CHUNKS_BUCKET_NAME> gs://<RULER_BUCKET_NAME> \
  --location=<REGION> \
  --default-storage-class=STANDARD \
  --public-access-prevention \
  --uniform-bucket-level-access \
  --soft-delete-duration=7d

Make sure to replace the region and bucket name with your desired values. We will revisit the bucket policy later in this guide.

Here’s an example with all the variables filled in:

bash Copy

gcloud storage buckets create gs://loki-gcp-chunks gs://loki-gcp-ruler \
  --location=europe-west4 \
  --default-storage-class=STANDARD \
  --public-access-prevention \
  --uniform-bucket-level-access \
  --soft-delete-duration=7d

When you run this command, you should get something like this in response:

console Copy

Creating gs://loki-gcp-chunks/...
Creating gs://loki-gcp-ruler/...

Defining IAM roles and policies

IAM determines who can access which resources on GCP and can be configured in several ways. The recommended method for allowing Loki to access GCS is to use Workload Identity Federation. This method is more secure than creating and distributing a service account key. The following steps show how to create the role and policy using the gcloud CLI.

Authenticating to the GKE cluster

You need to be able to run kubectl commands on the cluster, so make sure you have it installed (run gcloud components install kubectl if not) and then run this command:

bash Copy

gcloud container clusters get-credentials <CLUSTER_NAME> \
  --region=<REGION>

Here’s an example of that command with the variables filled in:

bash Copy

gcloud container clusters get-credentials loki-gcp \
  --region=europe-west4

This will authenticate you via your GCP IAM identity, write the cluster’s access info to your local kubeconfig (usually ~/.kube/config), and then allow kubectl commands to talk to the right cluster from now on.

Then check that you’re connected to the GKE cluster and that you’re accessing it via kubectl by running:

bash Copy

kubectl config current-context

You should get something like this in return:

bash Copy

gke_my-project-123456_europe-west4_loki-gcp

Create a Kubernetes Namespace

Create a Kubernetes namespace where you’ll install your Loki workloads:

bash Copy

kubectl create namespace <NAMESPACE>

Replace <NAMESPACE> with the namespace where your Loki workloads will be located.

Example:

bash Copy

kubectl create namespace loki

You should get the output:

bash Copy

namespace/loki created

Create Kubernetes Service Account (KSA)

A KSA is a cluster identity (service account, named default by default) assigned to pods that allows pods to interact with each other.

Create a KSA on your Kubernetes cluster:

bash Copy

kubectl create serviceaccount <KSA_NAME> \
  --namespace <NAMESPACE>

Replace <KSA_NAME> with the name of the KSA created above, and <NAMESPACE> with the namespace where your Loki workloads are located.

Example:

bash Copy

kubectl create serviceaccount loki-gcp-ksa \
  --namespace loki

You should get this in response:

bash Copy

serviceaccount/loki-gcp-ksa created

Add IAM Policy to Buckets

Create an IAM policy binding on the buckets using the KSA created previously and the roles of your choice. Use a separate command for each bucket, one for chunks, and another for the ruler.

bash Copy

gcloud storage buckets add-iam-policy-binding gs://<BUCKET_NAME> \
 --role=roles/storage.objectAdmin \
  --member=principal://iam.googleapis.com/projects/<PROJECT_NUMBER>/locations/global/workloadIdentityPools/<PROJECT_ID>.svc.id.goog/subject/ns/<NAMESPACE>/sa/<KSA_NAME> \
  --condition=None

Replace <PROJECT_ID> with the GCP project ID (for example, project-name), <PROJECT_NUMBER> with the project number (for example, 1234567890), <NAMESPACE> with the namespace where Loki is installed, and <KSA_NAME> with the name of the KSA you created above.

Then do the same thing for the other bucket.

Examples:

bash Copy

gcloud storage buckets add-iam-policy-binding gs://loki-gcp-chunks \
  --role=roles/storage.objectAdmin \
  --member=principal://iam.googleapis.com/projects/12345678901/locations/global/workloadIdentityPools/my-project-123456.svc.id.goog/subject/ns/loki/sa/loki-gcp-ksa \
  --condition=None

and

bash Copy

gcloud storage buckets add-iam-policy-binding gs://loki-gcp-ruler \
  --role=roles/storage.objectAdmin \
  --member=principal://iam.googleapis.com/projects/12345678901/locations/global/workloadIdentityPools/my-project-123456.svc.id.goog/subject/ns/loki/sa/loki-gcp-ksa \
  --condition=None

You should get something like this in response:

bash Copy

bindings:
- members:
  - projectEditor:my-project-123456
  - projectOwner:my-project-123456
  role: roles/storage.legacyBucketOwner
- members:
  - projectViewer:my-project-123456
  role: roles/storage.legacyBucketReader
- members:
  - projectEditor:my-project-123456
  - projectOwner:my-project-123456
  role: roles/storage.legacyObjectOwner
- members:
  - projectViewer:my-project-123456
  role: roles/storage.legacyObjectReader
- members:
  - principal://iam.googleapis.com/projects/12345678901/locations/global/workloadIdentityPools/my-project-123456.svc.id.goog/subject/ns/loki/sa/loki-gcp-ksa
  role: roles/storage.objectViewer
etag: CAI=
kind: storage#policy
resourceId: projects/_/buckets/loki-gcp-chunks
version: 1

Deploying the Helm chart

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.

1. Add the Grafana chart repository to Helm:

   bash Copy

   helm repo add grafana https://grafana.github.io/helm-charts

2. Update the chart repository:

   bash Copy

   helm repo update

Loki Basic Authentication

Loki by default does not come with any authentication. Since we will be deploying Loki to GCP 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:

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:

   Tip

   If you don’t have the htpasswd command installed, you can install it using brew or apt-get or yum depending on your OS.

   bash Copy

   htpasswd -c .htpasswd <username>

   This will create a file called auth with the username loki. You will be prompted to enter a password.

2. Create a Kubernetes secret with the .htpasswd file:

   bash Copy

   kubectl create secret generic loki-basic-auth --from-file=.htpasswd -n loki

   This will create a secret called loki-basic-auth in the loki namespace. We will reference this secret in the Loki Helm chart configuration.

3. Create a canary-basic-auth secret for the canary:

   bash Copy

   kubectl create secret generic canary-basic-auth \
     --from-literal=username=<USERNAME> \
     --from-literal=password=<PASSWORD> \
     -n loki

   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.

Loki Helm chart configuration

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 mode.

yaml Copy

loki:
   schemaConfig:
     configs:
       - from: "2024-04-01"
         store: tsdb
         object_store: gcs
         schema: v13
         index:
           prefix: loki_index_
           period: 24h
   storage_config:
     gcs:
       bucket_name: <CHUNK_BUCKET_NAME> # Your actual gcs bucket name, for example, loki-gcp-chunks
   ingester:
       chunk_encoding: snappy
   pattern_ingester:
       enabled: true
   limits_config:
     allow_structured_metadata: true
     volume_enabled: true
     retention_period: 672h # 28 days retention
   compactor:
     retention_enabled: true 
     delete_request_store: gcs
   ruler:
    enable_api: true
    storage_config:
      type: gcs
      gcs_storage_config:
        region: <REGION> # The GCS region, for example europe-west4
        bucketnames: <RULER_BUCKET_NAME> # Your actual gcs bucket name, for example, loki-gcp-ruler
      alertmanager_url: http://prom:9093 # The URL of the Alertmanager to send alerts (Prometheus, Mimir, etc.)

   querier:
      max_concurrent: 4

   storage:
      type: gcs
      bucketNames:
        chunks: <CHUNK_BUCKET_NAME> # Your actual gcs bucket name, for example, loki-gcp-chunks
        ruler: <RULER_BUCKET_NAME> # Your actual gcs bucket name, for example, loki-gcp-ruler
      
serviceAccount:
 create: false
 name: <KSA_NAME>

deploymentMode: Distributed

ingester:
 replicas: 3
 zoneAwareReplication:
  enabled: false

querier:
 replicas: 3
 maxUnavailable: 2

queryFrontend:
 replicas: 2
 maxUnavailable: 1

queryScheduler:
 replicas: 2

distributor:
 replicas: 3
 maxUnavailable: 2
 
compactor:
 replicas: 1

indexGateway:
 replicas: 2
 maxUnavailable: 1

ruler:
 replicas: 1
 maxUnavailable: 1


# This exposes the Loki gateway so it can be written to and queried externaly
gateway:
 service:
   type: LoadBalancer
 basicAuth: 
     enabled: true
     existingSecret: loki-basic-auth

# Since we are using basic auth, we need to pass the username and password to the canary
lokiCanary:
  extraArgs:
    - -pass=$(LOKI_PASS)
    - -user=$(LOKI_USER)
  extraEnv:
    - name: LOKI_PASS
      valueFrom:
        secretKeyRef:
          name: canary-basic-auth
          key: password
    - name: LOKI_USER
      valueFrom:
        secretKeyRef:
          name: canary-basic-auth
          key: username

# Enable minio for storage
minio:
 enabled: false

backend:
 replicas: 0
read:
 replicas: 0
write:
 replicas: 0

singleBinary:
 replicas: 0

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 GCP:

• Loki Config vs. Values Config:

  • The values.yaml file contains a section called loki, which contains a direct representation of the Loki configuration file.
  • This section defines the Loki configuration, including the schema, storage, and querier configuration.
  • The key configuration to focus on for chunks is the storage_config section, where you define the GCS bucket region and name. This tells Loki where to store the chunks.
  • The ruler section defines the configuration for the ruler, including the GCS bucket region and name. This tells Loki where to store the alert and recording rules.
  • For the full Loki configuration, refer to the Loki Configuration documentation.

• Storage:

  • Defines where the Helm chart stores data.
  • Set the type to GCS since we are using Amazon GCS.
  • Configure the bucket names for the chunks and ruler to match the buckets created earlier.
  • The GCS section specifies the region of the bucket.

• Service Account:

  • The serviceAccount section is used to define the IAM role for the Loki service account.
  • This is where the IAM role created earlier is linked.

• Gateway:

  • Defines how the Loki gateway will be exposed.
  • We are using a LoadBalancer service type in this configuration.

Deploy Loki

Now that you have created the values.yaml file, you can deploy Loki using the Helm chart.

1. Deploy using the newly created values.yaml file:

   bash Copy

   helm install --values values.yaml loki grafana/loki -n loki --create-namespace

   It is important to create a namespace called loki as our trust policy is set to allow the IAM role to be used by the loki service account in the loki namespace. This is configurable but make sure to update your service account.

2. Verify the deployment:

   bash Copy

   kubectl get pods -n loki

   You should see the Loki pods running.

   console Copy

   NAME                                    READY   STATUS    RESTARTS   AGE
   loki-canary-crqpg                       1/1     Running   0          10m
   loki-canary-hm26p                       1/1     Running   0          10m
   loki-canary-v9wv9                       1/1     Running   0          10m
   loki-chunks-cache-0                     2/2     Running   0          10m
   loki-compactor-0                        1/1     Running   0          10m
   loki-distributor-78ccdcc9b4-9wlhl       1/1     Running   0          10m
   loki-distributor-78ccdcc9b4-km6j2       1/1     Running   0          10m
   loki-distributor-78ccdcc9b4-ptwrb       1/1     Running   0          10m
   loki-gateway-5f97f78755-hm6mx           1/1     Running   0          10m
   loki-index-gateway-0                    1/1     Running   0          10m
   loki-index-gateway-1                    1/1     Running   0          10m
   loki-ingester-zone-a-0                  1/1     Running   0          10m
   loki-ingester-zone-b-0                  1/1     Running   0          10m
   loki-ingester-zone-c-0                  1/1     Running   0          10m
   loki-querier-89d4ff448-4vr9b            1/1     Running   0          10m
   loki-querier-89d4ff448-7nvrf            1/1     Running   0          10m
   loki-querier-89d4ff448-q89kh            1/1     Running   0          10m
   loki-query-frontend-678899db5-n5wc4     1/1     Running   0          10m
   loki-query-frontend-678899db5-tf69b     1/1     Running   0          10m
   loki-query-scheduler-7d666bf759-9xqb5   1/1     Running   0          10m
   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 LoadBalancer 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.

To find the Loki Gateway service, run the following command:

bash Copy

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 Copy

NAME           TYPE           CLUSTER-IP       EXTERNAL-IP     PORT(S)        AGE
loki-gateway   LoadBalancer   34.118.239.140   34.91.203.240   80:30566/TCP   25m

In this case, the external IP address is 34.91.203.240.

Congratulations! You have successfully deployed Loki on GCP 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.

2. Create a gcp-test.js file with the following content:

   JavaScript Copy

    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 Copy

   ./k6 run gcp-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 GCP, you may wish to explore the following:

• Monitor a Loki Cluster
• Sending data to Loki
• Querying Loki
• Manage