Cloud Integrations

作者 grafana1ccacf29049fApache-2.0279 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫今天更新

Set up, configure, and troubleshoot Grafana Cloud integrations for AWS, Azure, and other cloud providers. Use when the user asks to connect AWS CloudWatch, set up Azure Monitor, configure Confluent Cloud observability, install a Grafana integration, set up hosted exporters, use AWS Firehose for CloudWatch logs, or troubleshoot a cloud integration. Triggers on phrases like "AWS CloudWatch", "Azure Monitor", "Confluent integration", "cloud integration", "hosted exporter", "AWS Firehose", "install integration", "cloud metrics", or "cloud logs".

僅含說明DevOps & Cloud
AI 產生的概覽

設定並排解 Grafana Cloud 針對 AWS CloudWatch、Azure Monitor 與 Confluent Cloud 的整合。

功能
指導設定 Grafana Cloud 託管匯出器與 AWS Firehose 接收器,以收集雲端監控資料。內容涵蓋所需的 AWS IAM 與 Azure 權限、Confluent Metrics API 認證、驗證查詢、預建儀表板與警示、常見錯誤排解,以及透過指標篩選降低成本。產出為設定步驟、設定片段與診斷指引,而非檔案。
適用情境
適用於將 AWS CloudWatch、Azure Monitor 或 Confluent Cloud 可觀測性接入 Grafana Cloud 堆疊時。也適用於安裝託管匯出器、為 CloudWatch 記錄與指標設定 AWS Firehose,或診斷失敗的雲端整合。
執行需求
需要一個可存取 Connections 的 Grafana Cloud 堆疊,以及雲端服務商認證:具備 CloudWatch 權限的 AWS IAM 使用者或角色、擁有 Monitoring Reader 角色的 Azure 服務主體,或 Confluent Metrics API 金鑰。需要能存取 Grafana Cloud 與雲端服務商 API 的網路。不附帶指令碼,僅為操作說明。

Grafana Cloud Integrations

Grafana Cloud Integrations connect cloud provider monitoring APIs to your Grafana stack without running your own exporters. Hosted exporters scrape cloud APIs on your behalf and push metrics to your Grafana Cloud stack.

Supported hosted exporters:

  • 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

AWS Firehose receiver - ingests CloudWatch Logs and Metrics Streams pushed via Kinesis Firehose (near real-time, lower latency than API scraping).


Step 1: Navigate to Connections

In Grafana Cloud: Connections > Add new connection (or Connections > Cloud Provider).

Available paths:

  • 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)

The hosted exporter scrapes CloudWatch API every 60s. Latency: ~1-5 minutes.

Required IAM permissions (minimum):

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

Setup steps:

  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

Supported namespaces: EC2, RDS, ELB/ALB, S3, Lambda, ECS, SQS, SNS, ElastiCache, Kinesis, DynamoDB, and 50+ others.

Option B: AWS Firehose receiver (streaming)

Near-real-time metrics and logs via CloudWatch Metric Streams and CloudWatch Logs subscriptions.

Architecture:

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

Setup:

  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

Terraform for Firehose setup:

hcl
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

Required Azure permissions:

Create a service principal with the Monitoring Reader role on the subscription(s) to monitor.

bash
# Create service principalaz ad sp create-for-rbac --name grafana-cloud-monitoring \  --role "Monitoring Reader" \  --scopes /subscriptions/<SUBSCRIPTION_ID>
# Output: appId (client ID), password (client secret), tenant

Setup in Grafana Cloud:

  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

Supported resource types: Virtual Machines, App Service Plans, AKS, Azure SQL, CosmosDB, Storage Accounts, Event Hubs, Service Bus, Application Gateway, and others.


Step 4: Confluent Cloud integration

Required Confluent API credentials:

  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

Setup in Grafana Cloud:

  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

Available metrics: Consumer lag, broker request rates, partition counts, replication lag, active controller count, and cluster-level health metrics.


Step 5: Verify the integration is working

bash
# 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_")))'

The integration status is also visible in: Connections > [Integration name] > Status

Integration health indicators:

  • 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

Every integration installs a set of pre-configured dashboards and alert rules automatically.

Find installed dashboards:

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

Find installed alert rules:

  • Alerting > Alert rules > filter by datasource or folder

Modify without losing updates:

  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

Hosted exporter not receiving data:

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

Common errors:

ErrorCauseFix
AccessDenied (AWS)IAM policy missing permissionsAdd required actions to the IAM policy
AuthorizationFailed (Azure)Service principal missing roleGrant Monitoring Reader on the subscription
401 Unauthorized (Confluent)Wrong API credentialsRe-enter credentials; confirm Metrics API key (not Kafka key)
No metrics foundWrong namespace/resource type selectedAdd the namespace in integration settings
Scrape timeoutNetwork restrictionEnsure Grafana Cloud's IPs can reach the cloud provider API

AWS-specific: CloudWatch API rate limiting

CloudWatch GetMetricData has a rate limit. If you have many resources, enable Metric Streams (Option B) instead of API polling to avoid throttling.


Step 8: Reduce costs with metric filtering

Hosted exporters scrape all metrics by default. Filter to reduce series count and cost.

AWS - select specific namespaces: In integration settings, switch from "All namespaces" to specific ones (e.g. EC2, RDS only).

AWS - filter by resource tags:

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

Azure - select specific resource types: Only enable the resource types you actually have dashboards for.

Use Adaptive Metrics to aggregate away unused label dimensions: See the grafana-cloud/adaptive-metrics skill.


References

來源與署名

來源:grafana/skills位於skills/grafana-cloud/cloud-integrations提交1ccacf2

授權條款: Apache-2.0

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

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