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

Deploy the Loki Helm chart on AWS

This guide shows how to deploy a minimally viable Loki in microservice mode on AWS using the Helm chart. To run through this guide, we expect you to have the necessary tools and permissions to deploy resources on AWS, such as:

• Full access to EKS (Amazon Elastic Kubernetes Service)
• Full access to S3 (Amazon Simple Storage Service)
• Sufficient permissions to create IAM (Identity Access Management) roles and policies

There are two methods for authenticating and connecting Loki to AWS S3. We will guide you through the recommended method of granting access via an IAM role.

Considerations

• IAM Role: The IAM role created in this guide is a basic role that allows Loki to read and write to the S3 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 AWS will incur costs. Make sure to monitor your usage and costs to avoid any unexpected bills. In this guide we have used a simple EKS cluster with 3 nodes and m5.xlarge 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 AWS. A simple way to get started is by using EKSctl. Refer to Getting started with EKSctl.
• Kubectl installed on your local machine. Refer to Install and Set Up kubectl.
• (Optional) AWS CLI installed on your local machine. Refer to Installing the AWS CLI. This is required if you plan to use EKSctl to create the EKS cluster and modify the IAM roles and policies locally.

EKS Minimum Requirements

The minimum requirements for deploying Loki on EKS are:

• Kubernetes version 1.30 or above.
• 3 nodes for the EKS cluster.
• Instance type depends on your workload. A good starting point for a production cluster is m7i.2xlarge.

Here is the EKSctl cluster configuration file used in this guide:

yaml Copy

# A simple example of ClusterConfig object:
---
apiVersion: eksctl.io/v1alpha5
kind: ClusterConfig

metadata:
  name: <INSERT-CLUSTER-NAME>
  region: <INSERT-REGION-FOR-CLUSTER>
  version: "1.31"

iam:
  withOIDC: true

addons:
  - name: aws-ebs-csi-driver

managedNodeGroups:
  - name: loki-workers
    instanceType: m7i.2xlarge
    desiredCapacity: 3
    minSize: 2
    maxSize: 3
    amiFamily: AmazonLinux2023
    iam:
      withAddonPolicies:
        ebs: true
    volumeSize: 80
    volumeType: gp3
    ebsOptimized: true

The following plugins must also be installed within the EKS cluster:

• Amazon EBS CSI Driver: Enables Kubernetes to dynamically provision and manage EBS volumes as persistent storage for applications. We use this to provision the node volumes for Loki.
• CoreDNS: Provides internal DNS service for Kubernetes clusters, ensuring that services and pods can communicate with each other using DNS names.
• kube-proxy: Maintains network rules on nodes, enabling communication between pods and services within the cluster.

You must also install an OIDC (OpenID Connect) provider on the EKS cluster. This is required for the IAM roles and policies to work correctly. If you are using EKSctl, you can install the OIDC provider using the following command:

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eksctl utils associate-iam-oidc-provider --cluster loki --approve

Create S3 buckets

Before deploying Loki, you need to create two S3 buckets; one to store logs (chunks), the second to store alert rules. You can create the bucket using the AWS Management Console or the AWS CLI. The bucket name must be globally unique.

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aws s3api create-bucket --bucket  <YOUR CHUNK BUCKET NAME e.g. `loki-aws-dev-chunks`> --region <S3 region your account is on, e.g. `eu-west-2`> --create-bucket-configuration LocationConstraint=<S3 region your account is on, e.g. `eu-west-2`> \
aws s3api create-bucket --bucket  <YOUR RULER BUCKET NAME e.g. `loki-aws-dev-ruler`> --region <S3 REGION your account is on, e.g. `eu-west-2`> --create-bucket-configuration LocationConstraint=<S3 REGION your account is on, e.g. `eu-west-2`>

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

Defining IAM roles and policies

The recommended method for connecting Loki to AWS S3 is to use an IAM role. This method is more secure than using access keys and secret keys which are directly stored in the Loki configuration. The role and policy can be created using the AWS CLI or the AWS Management Console. The below steps show how to create the role and policy using the AWS CLI.

1. Create a new directory and navigate to it. Make sure to create the files in this directory. All commands in this guide assume you are in this directory.

2. Create a loki-s3-policy.json file with the following content:

   json Copy

   {
       "Version": "2012-10-17",
       "Statement": [
           {
               "Sid": "LokiStorage",
               "Effect": "Allow",
               "Action": [
                   "s3:ListBucket",
                   "s3:PutObject",
                   "s3:GetObject",
                   "s3:DeleteObject"
               ],
               "Resource": [
                   "arn:aws:s3:::< CHUNK BUCKET NAME >",
                   "arn:aws:s3:::< CHUNK BUCKET NAME >/*",
                   "arn:aws:s3:::< RULER BUCKET NAME >",
                   "arn:aws:s3:::< RULER BUCKET NAME >/*"
               ]
           }
       ]
   }

   Make sure to replace the placeholders with the names of the buckets you created earlier.

3. Create the IAM policy using the AWS CLI:

   bash Copy

   aws iam create-policy --policy-name LokiS3AccessPolicy --policy-document file://loki-s3-policy.json

4. Create a trust policy document named trust-policy.json with the following content:

   json Copy

   {
       "Version": "2012-10-17",
       "Statement": [
           {
               "Effect": "Allow",
               "Principal": {
                   "Federated": "arn:aws:iam::< ACCOUNT ID >:oidc-provider/oidc.eks.<INSERT REGION>.amazonaws.com/id/< OIDC ID >"
               },
               "Action": "sts:AssumeRoleWithWebIdentity",
               "Condition": {
                   "StringEquals": {
                       "oidc.eks.<INSERT REGION>.amazonaws.com/id/< OIDC ID >:sub": "system:serviceaccount:loki:loki",
                       "oidc.eks.<INSERT REGION>.amazonaws.com/id/< OIDC ID >:aud": "sts.amazonaws.com"
                   }
               }
           }
       ]
   }

   Make sure to replace the placeholders with your AWS account ID, region, and the OIDC ID (you can find this in the EKS cluster configuration).

5. Create the IAM role using the AWS CLI:

   bash Copy

   aws iam create-role --role-name LokiServiceAccountRole --assume-role-policy-document file://trust-policy.json

6. Attach the policy to the role:

   bash Copy

   aws iam attach-role-policy --role-name LokiServiceAccountRole --policy-arn arn:aws:iam::<Account ID>:policy/LokiS3AccessPolicy

   Make sure to replace the placeholder with your AWS account ID.

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

3. Create a new namespace for Loki:

   bash Copy

   kubectl create namespace loki

Loki Basic Authentication

Loki by default does not come with any authentication. Since we will be deploying Loki to AWS 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: s3
         schema: v13
         index:
           prefix: loki_index_
           period: 24h
   storage_config:
     aws:
       region: <S3 BUCKET REGION> # for example, eu-west-2  
       bucketnames: <CHUNK BUCKET NAME> # Your actual S3 bucket name, for example, loki-aws-dev-chunks
       s3forcepathstyle: false
   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: s3
   ruler:
    enable_api: true
    storage:
      type: s3
      s3:
        region: <S3 BUCKET REGION> # for example, eu-west-2
        bucketnames: <RULER BUCKET NAME> # Your actual S3 bucket name, for example, loki-aws-dev-ruler
        s3forcepathstyle: false
      alertmanager_url: http://prom:9093 # The URL of the Alertmanager to send alerts (Prometheus, Mimir, etc.)

   querier:
      max_concurrent: 4

   storage:
      type: s3
      bucketNames:
        chunks: "<CHUNK BUCKET NAME>" # Your actual S3 bucket name (loki-aws-dev-chunks)
        ruler: "<RULER BUCKET NAME>" # Your actual S3 bucket name (loki-aws-dev-ruler)
        # admin: "<Insert s3 bucket name>" # Your actual S3 bucket name (loki-aws-dev-admin) - GEL customers only
      s3:
        region: <S3 BUCKET REGION> # eu-west-2
        #insecure: false
      # s3forcepathstyle: false

serviceAccount:
 create: true
 annotations:
   "eks.amazonaws.com/role-arn": "arn:aws:iam::<Account ID>:role/LokiServiceAccountRole" # The service role you created

deploymentMode: Distributed

ingester:
 replicas: 3
 persistence:
   storageClass: gp3
   accessModes:
     - ReadWriteOnce
   size: 10Gi

querier:
 replicas: 3
 maxUnavailable: 2
 persistence:
   storageClass: gp3
   accessModes:
     - ReadWriteOnce
   size: 10Gi
queryFrontend:
 replicas: 2
 maxUnavailable: 1
queryScheduler:
 replicas: 2
distributor:
 replicas: 3
 maxUnavailable: 2
compactor:
 replicas: 1
 persistence:
   storageClass: gp3
   accessModes:
     - ReadWriteOnce
   size: 10Gi
indexGateway:
 replicas: 2
 maxUnavailable: 1
 persistence:
   storageClass: gp3
   accessModes:
     - ReadWriteOnce
   size: 10Gi
ruler:
 replicas: 1
 maxUnavailable: 1
 persistence:
   storageClass: gp3
   accessModes:
     - ReadWriteOnce
   size: 10Gi


# 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 AWS:

• 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 S3 bucket region and name. This tells Loki where to store the chunks.
  • The ruler section defines the configuration for the ruler, including the S3 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 s3 since we are using Amazon S3.
  • Configure the bucket names for the chunks and ruler to match the buckets created earlier.
  • The s3 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:

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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   10.100.201.74    12345678975675456-1433434453245433545656563.eu-west-2.elb.amazonaws.com   80:30707/TCP         46m

Congratulations! You have successfully deployed Loki on AWS 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 aws-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,
    };
   
    **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.**
    * "main" function for each VU iteration
    */
    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 aws-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 AWS, you may wish to explore the following:

• Sending data to Loki
• Querying Loki
• Manage