Grafana Cloud Integrations

• AWS CloudWatch - all CloudWatch namespaces via YACE (Yet Another CloudWatch Exporter)
• Azure Monitor - Azure resource metrics via the Azure Monitor API
• Confluent Cloud - Kafka cluster metrics via the Confluent Metrics API
• Generic HTTP endpoint - any Prometheus-format

  /metrics

  endpoint behind auth

Step 1: Navigate to Connections

Connections > Cloud Provider

• AWS CloudWatch - hosted exporter + optional Firehose receiver
• Azure Monitor - hosted exporter
• Confluent Cloud - hosted exporter
• All integrations - full catalog including Linux, MySQL, Kubernetes, etc.

Step 2: AWS CloudWatch integration

Option A: Hosted exporter (polling)

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "cloudwatch:GetMetricData",
        "cloudwatch:GetMetricStatistics",
        "cloudwatch:ListMetrics",
        "tag:GetResources",
        "ec2:DescribeInstances",
        "ec2:DescribeRegions"
      ],
      "Resource": "*"
    }
  ]
}

1. Create an IAM user or role with the policy above
2. Generate an access key pair (for IAM user) or configure cross-account role assumption
3. In Grafana Cloud: Connections > AWS > Configure hosted exporter
4. Enter: AWS Access Key ID, Secret Access Key, region(s), CloudWatch namespaces to scrape
5. Grafana provisions the exporter and begins scraping within 2-3 minutes

Option B: AWS Firehose receiver (streaming)

CloudWatch Metric Streams → Kinesis Firehose → Grafana Cloud Firehose Receiver
CloudWatch Logs (subscription filter) → Kinesis Firehose → Grafana Cloud Firehose Receiver

1. In Grafana Cloud: Connections > AWS > Firehose receiver
2. Grafana provides an HTTPS endpoint URL and access token
3. In AWS, create a Kinesis Firehose delivery stream:
   • Destination: HTTP endpoint
   • Endpoint URL: (from step 2)
   • Access key: (from step 2)
   • Content encoding: GZIP
4. Create a CloudWatch Metric Stream pointing at the Firehose stream:
   • Output format:

     OpenTelemetry 1.0

   • Namespaces: select or include all
5. For logs: add a CloudWatch Logs subscription filter pointing at the Firehose stream

resource "aws_cloudwatch_metric_stream" "grafana_cloud" {
  name          = "grafana-cloud-metrics"
  role_arn      = aws_iam_role.firehose_role.arn
  firehose_arn  = aws_kinesis_firehose_delivery_stream.grafana.arn
  output_format = "opentelemetry1.0"

  # Optionally scope to specific namespaces
  # include_filter { namespace = "AWS/EC2" }
  # include_filter { namespace = "AWS/RDS" }
}

resource "aws_kinesis_firehose_delivery_stream" "grafana" {
  name        = "grafana-cloud-stream"
  destination = "http_endpoint"

  http_endpoint_configuration {
    url            = var.grafana_firehose_endpoint
    access_key     = var.grafana_firehose_access_key
    name           = "Grafana Cloud"
    content_encoding = "GZIP"

    s3_configuration {
      role_arn   = aws_iam_role.firehose_role.arn
      bucket_arn = aws_s3_bucket.firehose_backup.arn
    }
  }
}

Step 3: Azure Monitor integration

# Create service principal
az ad sp create-for-rbac --name grafana-cloud-monitoring \
  --role "Monitoring Reader" \
  --scopes /subscriptions/<SUBSCRIPTION_ID>

# Output: appId (client ID), password (client secret), tenant

1. Connections > Azure > Configure hosted exporter
2. Enter: Tenant ID, Client ID, Client Secret, Subscription IDs
3. Select resource types to monitor (VMs, App Services, AKS, SQL, etc.)
4. The exporter begins scraping within 2-3 minutes

Step 4: Confluent Cloud integration

1. In Confluent Cloud: Environment > API Keys (or Cloud API Keys for organization-level)
2. Create a Metrics API key (not a Kafka API key) with

   MetricsViewer

   role
3. Note the API Key and Secret

1. Connections > Confluent > Configure hosted exporter
2. Enter: Confluent API Key, API Secret, Environment ID(s), Cluster ID(s)
3. The exporter scrapes the Confluent Metrics API every 60s

Step 5: Verify the integration is working

# Check in Grafana Explore — query for the integration's job label
# For AWS:
{job="integrations/cloudwatch"}

# For Azure:
{job="integrations/azure-monitor"}

# Check metric arrival (replace with your stack's Prometheus endpoint)
curl -s -H "Authorization: Bearer <USER>:<API_KEY>" \
  "https://prometheus-prod-XX-XX-X.grafana.net/api/prom/api/v1/labels" | \
  jq '.data | map(select(startswith("aws_") or startswith("azure_")))'

• Last successful scrape

  - should be within the last 2 minutes

• Series count

  - should be non-zero and stable

• Error rate

  - should be 0%

Step 6: Pre-built dashboards and alerts

• Dashboards > Browse > folder named after the integration (e.g. "AWS CloudWatch")

• Alerting > Alert rules > filter by datasource or folder

1. Do not edit the provisioned dashboards directly (they may be overwritten on updates)
2. Duplicate the dashboard (Dashboard settings > Save as copy)
3. Edit the copy

Step 7: Troubleshoot integration failures

# Check the integration status via Grafana Cloud API
curl -s -H "Authorization: Bearer <STACK_ID>:<API_TOKEN>" \
  "https://integrations-api.grafana.net/api/v1/integrations" | \
  jq '.integrations[] | {name, status, lastScrapeTime, errorMessage}'

AccessDenied

AuthorizationFailed

401 Unauthorized

No metrics found

Scrape timeout

Step 8: Reduce costs with metric filtering

# In exporter configuration, add tag filters
discovery:
  - type: AWS/EC2
    filters:
      - key: Environment
        values: ["production"]

grafana-cloud/adaptive-metrics

References

• Grafana Cloud Connections documentation
• AWS CloudWatch integration
• Azure Monitor integration
• YACE (Yet Another CloudWatch Exporter)
• CloudWatch Metric Streams