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Use when the user asks to connect AWS CloudWatch, set up Azure Monitor, configure\n  Confluent Cloud observability, install a Grafana integration, set up hosted exporters, use\n  AWS Firehose for CloudWatch logs, or troubleshoot a cloud integration. Triggers on phrases\n  like \"AWS CloudWatch\", \"Azure Monitor\", \"Confluent integration\", \"cloud integration\",\n  \"hosted exporter\", \"AWS Firehose\", \"install integration\", \"cloud metrics\", or \"cloud logs\".\n---\n\n# Grafana Cloud Integrations\n\nGrafana Cloud Integrations connect cloud provider monitoring APIs to your Grafana stack without\nrunning your own exporters. Hosted exporters scrape cloud APIs on your behalf and push metrics\nto your Grafana Cloud stack.\n\n**Supported hosted exporters:**\n- **AWS CloudWatch** - all CloudWatch namespaces via YACE (Yet Another CloudWatch Exporter)\n- **Azure Monitor** - Azure resource metrics via the Azure Monitor API\n- **Confluent Cloud** - Kafka cluster metrics via the Confluent Metrics API\n- **Generic HTTP endpoint** - any Prometheus-format `\u002Fmetrics` endpoint behind auth\n\n**AWS Firehose receiver** - ingests CloudWatch Logs and Metrics Streams pushed via Kinesis\nFirehose (near real-time, lower latency than API scraping).\n\n---\n\n## Step 1: Navigate to Connections\n\nIn Grafana Cloud: **Connections > Add new connection** (or `Connections > Cloud Provider`).\n\nAvailable paths:\n- **AWS CloudWatch** - hosted exporter + optional Firehose receiver\n- **Azure Monitor** - hosted exporter\n- **Confluent Cloud** - hosted exporter\n- **All integrations** - full catalog including Linux, MySQL, Kubernetes, etc.\n\n---\n\n## Step 2: AWS CloudWatch integration\n\n### Option A: Hosted exporter (polling)\n\nThe hosted exporter scrapes CloudWatch API every 60s. Latency: ~1-5 minutes.\n\n**Required IAM permissions (minimum):**\n\n```json\n{\n  \"Version\": \"2012-10-17\",\n  \"Statement\": [\n    {\n      \"Effect\": \"Allow\",\n      \"Action\": [\n        \"cloudwatch:GetMetricData\",\n        \"cloudwatch:GetMetricStatistics\",\n        \"cloudwatch:ListMetrics\",\n        \"tag:GetResources\",\n        \"ec2:DescribeInstances\",\n        \"ec2:DescribeRegions\"\n      ],\n      \"Resource\": \"*\"\n    }\n  ]\n}\n```\n\n**Setup steps:**\n1. Create an IAM user or role with the policy above\n2. Generate an access key pair (for IAM user) or configure cross-account role assumption\n3. In Grafana Cloud: Connections > AWS > Configure hosted exporter\n4. Enter: AWS Access Key ID, Secret Access Key, region(s), CloudWatch namespaces to scrape\n5. Grafana provisions the exporter and begins scraping within 2-3 minutes\n\n**Supported namespaces:** EC2, RDS, ELB\u002FALB, S3, Lambda, ECS, SQS, SNS, ElastiCache,\nKinesis, DynamoDB, and 50+ others.\n\n### Option B: AWS Firehose receiver (streaming)\n\nNear-real-time metrics and logs via CloudWatch Metric Streams and CloudWatch Logs subscriptions.\n\n**Architecture:**\n```\nCloudWatch Metric Streams → Kinesis Firehose → Grafana Cloud Firehose Receiver\nCloudWatch Logs (subscription filter) → Kinesis Firehose → Grafana Cloud Firehose Receiver\n```\n\n**Setup:**\n\n1. In Grafana Cloud: Connections > AWS > Firehose receiver\n2. Grafana provides an HTTPS endpoint URL and access token\n3. In AWS, create a Kinesis Firehose delivery stream:\n   - Destination: HTTP endpoint\n   - Endpoint URL: (from step 2)\n   - Access key: (from step 2)\n   - Content encoding: GZIP\n4. Create a CloudWatch Metric Stream pointing at the Firehose stream:\n   - Output format: `OpenTelemetry 1.0`\n   - Namespaces: select or include all\n5. For logs: add a CloudWatch Logs subscription filter pointing at the Firehose stream\n\n**Terraform for Firehose setup:**\n\n```hcl\nresource \"aws_cloudwatch_metric_stream\" \"grafana_cloud\" {\n  name          = \"grafana-cloud-metrics\"\n  role_arn      = aws_iam_role.firehose_role.arn\n  firehose_arn  = aws_kinesis_firehose_delivery_stream.grafana.arn\n  output_format = \"opentelemetry1.0\"\n\n  # Optionally scope to specific namespaces\n  # include_filter { namespace = \"AWS\u002FEC2\" }\n  # include_filter { namespace = \"AWS\u002FRDS\" }\n}\n\nresource \"aws_kinesis_firehose_delivery_stream\" \"grafana\" {\n  name        = \"grafana-cloud-stream\"\n  destination = \"http_endpoint\"\n\n  http_endpoint_configuration {\n    url            = var.grafana_firehose_endpoint\n    access_key     = var.grafana_firehose_access_key\n    name           = \"Grafana Cloud\"\n    content_encoding = \"GZIP\"\n\n    s3_configuration {\n      role_arn   = aws_iam_role.firehose_role.arn\n      bucket_arn = aws_s3_bucket.firehose_backup.arn\n    }\n  }\n}\n```\n\n---\n\n## Step 3: Azure Monitor integration\n\n**Required Azure permissions:**\n\nCreate a service principal with the **Monitoring Reader** role on the subscription(s) to monitor.\n\n```bash\n# Create service principal\naz ad sp create-for-rbac --name grafana-cloud-monitoring \\\n  --role \"Monitoring Reader\" \\\n  --scopes \u002Fsubscriptions\u002F\u003CSUBSCRIPTION_ID>\n\n# Output: appId (client ID), password (client secret), tenant\n```\n\n**Setup in Grafana Cloud:**\n1. Connections > Azure > Configure hosted exporter\n2. Enter: Tenant ID, Client ID, Client Secret, Subscription IDs\n3. Select resource types to monitor (VMs, App Services, AKS, SQL, etc.)\n4. The exporter begins scraping within 2-3 minutes\n\n**Supported resource types:** Virtual Machines, App Service Plans, AKS, Azure SQL, CosmosDB,\nStorage Accounts, Event Hubs, Service Bus, Application Gateway, and others.\n\n---\n\n## Step 4: Confluent Cloud integration\n\n**Required Confluent API credentials:**\n\n1. In Confluent Cloud: **Environment > API Keys** (or Cloud API Keys for organization-level)\n2. Create a **Metrics API key** (not a Kafka API key) with `MetricsViewer` role\n3. Note the API Key and Secret\n\n**Setup in Grafana Cloud:**\n1. Connections > Confluent > Configure hosted exporter\n2. Enter: Confluent API Key, API Secret, Environment ID(s), Cluster ID(s)\n3. The exporter scrapes the Confluent Metrics API every 60s\n\n**Available metrics:** Consumer lag, broker request rates, partition counts, replication lag,\nactive controller count, and cluster-level health metrics.\n\n---\n\n## Step 5: Verify the integration is working\n\n```bash\n# Check in Grafana Explore — query for the integration's job label\n# For AWS:\n{job=\"integrations\u002Fcloudwatch\"}\n\n# For Azure:\n{job=\"integrations\u002Fazure-monitor\"}\n\n# Check metric arrival (replace with your stack's Prometheus endpoint)\ncurl -s -H \"Authorization: Bearer \u003CUSER>:\u003CAPI_KEY>\" \\\n  \"https:\u002F\u002Fprometheus-prod-XX-XX-X.grafana.net\u002Fapi\u002Fprom\u002Fapi\u002Fv1\u002Flabels\" | \\\n  jq '.data | map(select(startswith(\"aws_\") or startswith(\"azure_\")))'\n```\n\nThe integration status is also visible in: **Connections > [Integration name] > Status**\n\n**Integration health indicators:**\n- `Last successful scrape` - should be within the last 2 minutes\n- `Series count` - should be non-zero and stable\n- `Error rate` - should be 0%\n\n---\n\n## Step 6: Pre-built dashboards and alerts\n\nEvery integration installs a set of pre-configured dashboards and alert rules automatically.\n\n**Find installed dashboards:**\n- Dashboards > Browse > folder named after the integration (e.g. \"AWS CloudWatch\")\n\n**Find installed alert rules:**\n- Alerting > Alert rules > filter by datasource or folder\n\n**Modify without losing updates:**\n1. Do not edit the provisioned dashboards directly (they may be overwritten on updates)\n2. Duplicate the dashboard (Dashboard settings > Save as copy)\n3. Edit the copy\n\n---\n\n## Step 7: Troubleshoot integration failures\n\n**Hosted exporter not receiving data:**\n\n```bash\n# Check the integration status via Grafana Cloud API\ncurl -s -H \"Authorization: Bearer \u003CSTACK_ID>:\u003CAPI_TOKEN>\" \\\n  \"https:\u002F\u002Fintegrations-api.grafana.net\u002Fapi\u002Fv1\u002Fintegrations\" | \\\n  jq '.integrations[] | {name, status, lastScrapeTime, errorMessage}'\n```\n\n**Common errors:**\n\n| Error | Cause | Fix |\n|---|---|---|\n| `AccessDenied` (AWS) | IAM policy missing permissions | Add required actions to the IAM policy |\n| `AuthorizationFailed` (Azure) | Service principal missing role | Grant Monitoring Reader on the subscription |\n| `401 Unauthorized` (Confluent) | Wrong API credentials | Re-enter credentials; confirm Metrics API key (not Kafka key) |\n| `No metrics found` | Wrong namespace\u002Fresource type selected | Add the namespace in integration settings |\n| `Scrape timeout` | Network restriction | Ensure Grafana Cloud's IPs can reach the cloud provider API |\n\n**AWS-specific: CloudWatch API rate limiting**\n\nCloudWatch GetMetricData has a rate limit. If you have many resources, enable Metric Streams\n(Option B) instead of API polling to avoid throttling.\n\n---\n\n## Step 8: Reduce costs with metric filtering\n\nHosted exporters scrape all metrics by default. Filter to reduce series count and cost.\n\n**AWS - select specific namespaces:**\nIn integration settings, switch from \"All namespaces\" to specific ones (e.g. EC2, RDS only).\n\n**AWS - filter by resource tags:**\n```yaml\n# In exporter configuration, add tag filters\ndiscovery:\n  - type: AWS\u002FEC2\n    filters:\n      - key: Environment\n        values: [\"production\"]\n```\n\n**Azure - select specific resource types:**\nOnly enable the resource types you actually have dashboards for.\n\n**Use Adaptive Metrics to aggregate away unused label dimensions:**\nSee the `grafana-cloud\u002Fadaptive-metrics` skill.\n\n---\n\n## References\n\n- [Grafana Cloud Connections documentation](https:\u002F\u002Fgrafana.com\u002Fdocs\u002Fgrafana-cloud\u002Fmonitor-infrastructure\u002Fintegrations\u002F)\n- [AWS CloudWatch integration](https:\u002F\u002Fgrafana.com\u002Fdocs\u002Fgrafana-cloud\u002Fmonitor-infrastructure\u002Fintegrations\u002Fintegration-reference\u002Fintegration-cloudwatch\u002F)\n- [Azure Monitor integration](https:\u002F\u002Fgrafana.com\u002Fdocs\u002Fgrafana-cloud\u002Fmonitor-infrastructure\u002Fintegrations\u002Fintegration-reference\u002Fintegration-azure\u002F)\n- [YACE (Yet Another CloudWatch Exporter)](https:\u002F\u002Fgithub.com\u002Fnerdswords\u002Fyet-another-cloudwatch-exporter)\n- [CloudWatch Metric Streams](https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonCloudWatch\u002Flatest\u002Fmonitoring\u002FCloudWatch-Metric-Streams.html)\n",{"data":38,"body":39},{"name":4,"license":29,"description":6},{"type":40,"children":41},"root",[42,51,57,66,120,130,134,141,161,166,205,208,214,221,226,234,595,603,632,642,648,653,661,671,679,749,757,987,990,996,1004,1016,1145,1153,1176,1186,1189,1195,1203,1243,1250,1268,1278,1281,1287,1439,1456,1464,1500,1503,1509,1514,1522,1530,1538,1546,1554,1572,1575,1581,1589,1680,1688,1837,1845,1850,1853,1859,1864,1874,1882,2004,2014,2032,2035,2041,2096],{"type":43,"tag":44,"props":45,"children":47},"element","h1",{"id":46},"grafana-cloud-integrations",[48],{"type":49,"value":50},"text","Grafana Cloud Integrations",{"type":43,"tag":52,"props":53,"children":54},"p",{},[55],{"type":49,"value":56},"Grafana Cloud Integrations connect cloud provider monitoring APIs to your Grafana stack without\nrunning your own exporters. 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Filter to reduce series count and cost.",{"type":43,"tag":52,"props":1865,"children":1866},{},[1867,1872],{"type":43,"tag":61,"props":1868,"children":1869},{},[1870],{"type":49,"value":1871},"AWS - select specific namespaces:",{"type":49,"value":1873},"\nIn integration settings, switch from \"All namespaces\" to specific ones (e.g. EC2, RDS only).",{"type":43,"tag":52,"props":1875,"children":1876},{},[1877],{"type":43,"tag":61,"props":1878,"children":1879},{},[1880],{"type":49,"value":1881},"AWS - filter by resource tags:",{"type":43,"tag":235,"props":1883,"children":1887},{"className":1884,"code":1885,"language":1886,"meta":240,"style":240},"language-yaml shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","# In exporter configuration, add tag filters\ndiscovery:\n  - type: AWS\u002FEC2\n    filters:\n      - key: Environment\n        values: [\"production\"]\n","yaml",[1888],{"type":43,"tag":112,"props":1889,"children":1890},{"__ignoreMap":240},[1891,1899,1913,1935,1947,1969],{"type":43,"tag":246,"props":1892,"children":1893},{"class":248,"line":249},[1894],{"type":43,"tag":246,"props":1895,"children":1896},{"style":1030},[1897],{"type":49,"value":1898},"# In exporter configuration, add tag filters\n",{"type":43,"tag":246,"props":1900,"children":1901},{"class":248,"line":259},[1902,1908],{"type":43,"tag":246,"props":1903,"children":1905},{"style":1904},"--shiki-light:#E53935;--shiki-default:#F07178;--shiki-dark:#F07178",[1906],{"type":49,"value":1907},"discovery",{"type":43,"tag":246,"props":1909,"children":1910},{"style":253},[1911],{"type":49,"value":1912},":\n",{"type":43,"tag":246,"props":1914,"children":1915},{"class":248,"line":304},[1916,1921,1926,1930],{"type":43,"tag":246,"props":1917,"children":1918},{"style":253},[1919],{"type":49,"value":1920},"  -",{"type":43,"tag":246,"props":1922,"children":1923},{"style":1904},[1924],{"type":49,"value":1925}," type",{"type":43,"tag":246,"props":1927,"children":1928},{"style":253},[1929],{"type":49,"value":281},{"type":43,"tag":246,"props":1931,"children":1932},{"style":289},[1933],{"type":49,"value":1934}," AWS\u002FEC2\n",{"type":43,"tag":246,"props":1936,"children":1937},{"class":248,"line":330},[1938,1943],{"type":43,"tag":246,"props":1939,"children":1940},{"style":1904},[1941],{"type":49,"value":1942},"    filters",{"type":43,"tag":246,"props":1944,"children":1945},{"style":253},[1946],{"type":49,"value":1912},{"type":43,"tag":246,"props":1948,"children":1949},{"class":248,"line":339},[1950,1955,1960,1964],{"type":43,"tag":246,"props":1951,"children":1952},{"style":253},[1953],{"type":49,"value":1954},"      -",{"type":43,"tag":246,"props":1956,"children":1957},{"style":1904},[1958],{"type":49,"value":1959}," key",{"type":43,"tag":246,"props":1961,"children":1962},{"style":253},[1963],{"type":49,"value":281},{"type":43,"tag":246,"props":1965,"children":1966},{"style":289},[1967],{"type":49,"value":1968}," Environment\n",{"type":43,"tag":246,"props":1970,"children":1971},{"class":248,"line":379},[1972,1977,1981,1986,1990,1995,1999],{"type":43,"tag":246,"props":1973,"children":1974},{"style":1904},[1975],{"type":49,"value":1976},"        values",{"type":43,"tag":246,"props":1978,"children":1979},{"style":253},[1980],{"type":49,"value":281},{"type":43,"tag":246,"props":1982,"children":1983},{"style":253},[1984],{"type":49,"value":1985}," [",{"type":43,"tag":246,"props":1987,"children":1988},{"style":253},[1989],{"type":49,"value":276},{"type":43,"tag":246,"props":1991,"children":1992},{"style":289},[1993],{"type":49,"value":1994},"production",{"type":43,"tag":246,"props":1996,"children":1997},{"style":253},[1998],{"type":49,"value":276},{"type":43,"tag":246,"props":2000,"children":2001},{"style":253},[2002],{"type":49,"value":2003},"]\n",{"type":43,"tag":52,"props":2005,"children":2006},{},[2007,2012],{"type":43,"tag":61,"props":2008,"children":2009},{},[2010],{"type":49,"value":2011},"Azure - select specific resource types:",{"type":49,"value":2013},"\nOnly enable the resource types you actually have dashboards for.",{"type":43,"tag":52,"props":2015,"children":2016},{},[2017,2022,2024,2030],{"type":43,"tag":61,"props":2018,"children":2019},{},[2020],{"type":49,"value":2021},"Use Adaptive Metrics to aggregate away unused label dimensions:",{"type":49,"value":2023},"\nSee the ",{"type":43,"tag":112,"props":2025,"children":2027},{"className":2026},[],[2028],{"type":49,"value":2029},"grafana-cloud\u002Fadaptive-metrics",{"type":49,"value":2031}," skill.",{"type":43,"tag":131,"props":2033,"children":2034},{},[],{"type":43,"tag":135,"props":2036,"children":2038},{"id":2037},"references",[2039],{"type":49,"value":2040},"References",{"type":43,"tag":67,"props":2042,"children":2043},{},[2044,2056,2066,2076,2086],{"type":43,"tag":71,"props":2045,"children":2046},{},[2047],{"type":43,"tag":2048,"props":2049,"children":2053},"a",{"href":2050,"rel":2051},"https:\u002F\u002Fgrafana.com\u002Fdocs\u002Fgrafana-cloud\u002Fmonitor-infrastructure\u002Fintegrations\u002F",[2052],"nofollow",[2054],{"type":49,"value":2055},"Grafana Cloud Connections documentation",{"type":43,"tag":71,"props":2057,"children":2058},{},[2059],{"type":43,"tag":2048,"props":2060,"children":2063},{"href":2061,"rel":2062},"https:\u002F\u002Fgrafana.com\u002Fdocs\u002Fgrafana-cloud\u002Fmonitor-infrastructure\u002Fintegrations\u002Fintegration-reference\u002Fintegration-cloudwatch\u002F",[2052],[2064],{"type":49,"value":2065},"AWS CloudWatch integration",{"type":43,"tag":71,"props":2067,"children":2068},{},[2069],{"type":43,"tag":2048,"props":2070,"children":2073},{"href":2071,"rel":2072},"https:\u002F\u002Fgrafana.com\u002Fdocs\u002Fgrafana-cloud\u002Fmonitor-infrastructure\u002Fintegrations\u002Fintegration-reference\u002Fintegration-azure\u002F",[2052],[2074],{"type":49,"value":2075},"Azure Monitor integration",{"type":43,"tag":71,"props":2077,"children":2078},{},[2079],{"type":43,"tag":2048,"props":2080,"children":2083},{"href":2081,"rel":2082},"https:\u002F\u002Fgithub.com\u002Fnerdswords\u002Fyet-another-cloudwatch-exporter",[2052],[2084],{"type":49,"value":2085},"YACE (Yet Another CloudWatch Exporter)",{"type":43,"tag":71,"props":2087,"children":2088},{},[2089],{"type":43,"tag":2048,"props":2090,"children":2093},{"href":2091,"rel":2092},"https:\u002F\u002Fdocs.aws.amazon.com\u002FAmazonCloudWatch\u002Flatest\u002Fmonitoring\u002FCloudWatch-Metric-Streams.html",[2052],[2094],{"type":49,"value":2095},"CloudWatch Metric Streams",{"type":43,"tag":2097,"props":2098,"children":2099},"style",{},[2100],{"type":49,"value":2101},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":2103,"total":2218},[2104,2121,2138,2154,2169,2185,2203],{"slug":2105,"name":2105,"fn":2106,"description":2107,"org":2108,"tags":2109,"stars":26,"repoUrl":27,"updatedAt":2120},"adaptive-metrics","optimize Grafana Cloud metrics costs","Cut Grafana Cloud Metrics cost by shrinking active-series count with Adaptive Metrics aggregation rules — auto-recommendations from query history, custom exact\u002Fregex rules, label-drop config, unused-metric detection, and Alloy remote_write fallback. Use when investigating a high Mimir\u002FGrafana Cloud bill, hunting high-cardinality labels (`pod_uid`, `service_instance_id`, `version`), pre-aggregating counters\u002Fgauges, dropping unused metrics, or measuring `grafanacloud_instance_active_series` before\u002Fafter — even when the user says \"reduce cardinality\", \"too many series\", \"metrics spend\", \"active series count is exploding\", or \"drop the version label\" without naming Adaptive Metrics.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2110,2113,2114,2117],{"name":2111,"slug":2112,"type":15},"Cost Optimization","cost-optimization",{"name":9,"slug":8,"type":15},{"name":2115,"slug":2116,"type":15},"Metrics","metrics",{"name":2118,"slug":2119,"type":15},"Observability","observability","2026-07-12T07:44:27.451068",{"slug":2122,"name":2122,"fn":2123,"description":2124,"org":2125,"tags":2126,"stars":26,"repoUrl":27,"updatedAt":2137},"admin","manage Grafana Cloud accounts and RBAC","Manage Grafana Cloud accounts — organizations, stacks, RBAC roles and assignments, SSO\u002FSAML\u002FOAuth\u002FGitHub auth, service accounts for CI\u002FCD, user invites, team membership, and API-driven provisioning. Creates stacks via the Cloud API, mints service-account tokens, applies role assignments, configures SSO providers, and provisions teams\u002Ffolders\u002Fdashboards via Terraform. Use when managing Grafana Cloud access, configuring SSO\u002FSAML\u002FOAuth, setting up service accounts for Terraform\u002FCI\u002FCD, assigning RBAC roles, inviting users, managing multiple stacks or organizations, provisioning cloud resources via API or Terraform, or auditing admin actions — even when the user says \"set up SSO\", \"create a stack\", \"make a service account\", or \"onboard a team\" without explicitly saying \"admin\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2127,2130,2133,2134],{"name":2128,"slug":2129,"type":15},"Access Control","access-control",{"name":2131,"slug":2132,"type":15},"Auth","auth",{"name":9,"slug":8,"type":15},{"name":2135,"slug":2136,"type":15},"Operations","operations","2026-07-12T07:44:12.078436",{"slug":2139,"name":2139,"fn":2140,"description":2141,"org":2142,"tags":2143,"stars":26,"repoUrl":27,"updatedAt":2153},"admission-control","implement admission control webhooks","Use when the user asks to \"write a validator\", \"add validation\", \"implement admission control\", \"write a mutating webhook\", \"add a mutation handler\", \"validate incoming resources\", \"implement admission logic\", \"add admission webhooks\", \"write ingress validation\", or asks how to validate or mutate resources before they are persisted in a grafana-app-sdk app. Provides guidance on implementing validation and mutation admission handlers for grafana-app-sdk apps.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2144,2147,2150],{"name":2145,"slug":2146,"type":15},"Architecture","architecture",{"name":2148,"slug":2149,"type":15},"Security","security",{"name":2151,"slug":2152,"type":15},"Validation","validation","2026-07-12T07:45:06.148973",{"slug":2155,"name":2155,"fn":2156,"description":2157,"org":2158,"tags":2159,"stars":26,"repoUrl":27,"updatedAt":2168},"alerting-irm","configure Grafana Alerting and Incident Management","Configure Grafana Alerting, Incident Response Management (IRM), and SLOs end-to-end — provisions Grafana-managed and data-source-managed alert rules, contact points (Slack\u002FPagerDuty\u002Femail\u002Fwebhook), notification policies with hierarchical matchers, silences, mute timings, on-call schedules and escalation chains, incident-management integrations, and SLOs with multi-window burn-rate alerts. Use when configuring alerts, debugging notification routing, setting up on-call rotations, declaring or managing incidents, defining SLOs, provisioning alerting via YAML or API, picking matchers for a notification policy, building a PagerDuty\u002FSlack webhook receiver, or troubleshooting why an alert isn't firing — even when the user says \"page me on errors\", \"alert me when X happens\", \"route this to the platform team\", or \"set up an SLO\" without naming Alerting or IRM.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2160,2163,2164,2167],{"name":2161,"slug":2162,"type":15},"Alerting","alerting",{"name":9,"slug":8,"type":15},{"name":2165,"slug":2166,"type":15},"Incident Response","incident-response",{"name":17,"slug":18,"type":15},"2026-07-12T07:44:02.393397",{"slug":2170,"name":2170,"fn":2171,"description":2172,"org":2173,"tags":2174,"stars":26,"repoUrl":27,"updatedAt":2184},"alloy","build unified telemetry pipelines with Grafana Alloy","Build a unified telemetry pipeline with Grafana Alloy — one OpenTelemetry-compatible binary that collects metrics, logs, traces, and profiles and ships to Grafana Cloud \u002F Prometheus \u002F Loki \u002F Tempo \u002F Pyroscope. Covers the Alloy config language (blocks, `sys.env`, component refs), `prometheus.scrape` → `remote_write`, `loki.source.file` + `loki.process` → `loki.write`, `otelcol.receiver.otlp` → `otelcol.exporter.otlp`, `pyroscope.scrape`, K8s \u002F Docker \u002F EC2 discovery, relabeling, modules (`import.file\u002Fgit\u002Fhttp`), clustering, Fleet Management `remotecfg`, the Alloy UI at `:12345`, and `alloy fmt` \u002F `alloy validate`. Use when writing a `config.alloy`, replacing Grafana Agent \u002F OTel Collector, scraping K8s pods, parsing logs, ingesting OTLP, or debugging \"Alloy isn't sending anything\" — even when the user says \"set up the agent\", \"write me a scrape config\", \"drop these logs before sending\", or \"OTel collector config\" without naming Alloy.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2175,2176,2179,2180,2181],{"name":9,"slug":8,"type":15},{"name":2177,"slug":2178,"type":15},"Logs","logs",{"name":2115,"slug":2116,"type":15},{"name":2118,"slug":2119,"type":15},{"name":2182,"slug":2183,"type":15},"OpenTelemetry","opentelemetry","2026-07-12T07:43:54.817139",{"slug":2186,"name":2186,"fn":2187,"description":2188,"org":2189,"tags":2190,"stars":26,"repoUrl":27,"updatedAt":2202},"app-observability","monitor application performance in Grafana Cloud","Get RED metrics + service maps + frontend RUM + AI\u002FLLM monitoring out of Grafana Cloud — Application Observability (`traces_spanmetrics_*` from OTel traces, p50\u002Fp95\u002Fp99 latency, exemplar-to-trace, traces-to-logs \u002F profiles), Frontend Observability with the Faro Web SDK (Core Web Vitals, session replay, `pushError`, React + router integration, `TracingInstrumentation` for browser → backend trace correlation), and AI Observability via OpenLIT (token \u002F cost \u002F latency, GPU, hallucination + toxicity evals). Use when standing up APM for a service, wiring an Alloy OTLP receiver + forwarding to Cloud, instrumenting a React frontend for RUM, debugging why service-map edges are missing, monitoring LLM cost drift, or correlating a frontend error to its backend trace — even when the user says \"set up APM\", \"show service map\", \"monitor browser perf\", \"session replay\", \"RUM SDK\", or \"watch our OpenAI bill\" without naming App \u002F Frontend \u002F AI Observability.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2191,2194,2197,2198,2201],{"name":2192,"slug":2193,"type":15},"APM","apm",{"name":2195,"slug":2196,"type":15},"Distributed Tracing","distributed-tracing",{"name":9,"slug":8,"type":15},{"name":2199,"slug":2200,"type":15},"LLM","llm",{"name":2118,"slug":2119,"type":15},"2026-07-12T07:44:34.500406",{"slug":2204,"name":2204,"fn":2205,"description":2206,"org":2207,"tags":2208,"stars":26,"repoUrl":27,"updatedAt":2217},"app-sdk-concepts","scaffold and configure Grafana apps","Use when starting any grafana-app-sdk work — scaffolding a Grafana app, initializing a Grafana App Platform app, picking a deployment mode (standalone operator \u002F grafana\u002Fapps \u002F frontend-only), wiring app-specific config, or onboarding to the SDK. Covers `grafana-app-sdk` CLI install, `project init` per deployment mode, project layout, the schema-centric workflow (CUE kinds → generated code → reconciler\u002Fadmission logic), and `SpecificConfig` for env-driven app configuration. Use even if the user just says \"make a new app\", \"Grafana app platform\", \"kinds and watchers\", \"operator scaffold\", or asks about `apps\u002F` inside the Grafana repo, without naming the SDK explicitly.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2209,2210,2213,2216],{"name":2145,"slug":2146,"type":15},{"name":2211,"slug":2212,"type":15},"Deployment","deployment",{"name":2214,"slug":2215,"type":15},"Engineering","engineering",{"name":9,"slug":8,"type":15},"2026-07-12T07:45:08.595757",48,{"items":2220,"total":2399},[2221,2236,2255,2274,2289,2303,2316,2331,2348,2361,2374,2387],{"slug":2222,"name":2222,"fn":2223,"description":2224,"org":2225,"tags":2226,"stars":2233,"repoUrl":2234,"updatedAt":2235},"faro-setup-web","instrument web apps with Grafana Faro","Instruments a web app with Grafana Faro Web SDK for frontend observability. Use when setting up error tracking, Web Vitals, session monitoring, or distributed tracing in a browser app.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2227,2228,2231,2232],{"name":2195,"slug":2196,"type":15},{"name":2229,"slug":2230,"type":15},"Frontend","frontend",{"name":17,"slug":18,"type":15},{"name":2118,"slug":2119,"type":15},1103,"https:\u002F\u002Fgithub.com\u002Fgrafana\u002Ffaro-web-sdk","2026-07-12T07:43:24.63314",{"slug":2237,"name":2237,"fn":2238,"description":2239,"org":2240,"tags":2241,"stars":2252,"repoUrl":2253,"updatedAt":2254},"configuring-yesoreyeram-infinity-datasource","configure Grafana Infinity data source","Configure the Infinity data source — base URL and allowed hosts, the authentication methods (basic, bearer token, API key, digest, OAuth passthrough, OAuth 2.0 client credentials\u002FJWT, Azure, Azure Blob, AWS), TLS, custom HTTP headers, network and security settings, the custom health check, and provisioning with a config file. Use when a user asks how to set up, configure, or change settings for the Infinity data source; how to authenticate to an API; how to allow hosts; how to provision it as YAML; or how to troubleshoot connection, authentication, or health-check issues.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2242,2245,2248,2251],{"name":2243,"slug":2244,"type":15},"API Development","api-development",{"name":2246,"slug":2247,"type":15},"Authentication","authentication",{"name":2249,"slug":2250,"type":15},"Configuration","configuration",{"name":9,"slug":8,"type":15},1056,"https:\u002F\u002Fgithub.com\u002Fgrafana\u002Fgrafana-infinity-datasource","2026-07-12T07:43:25.939136",{"slug":2256,"name":2256,"fn":2257,"description":2258,"org":2259,"tags":2260,"stars":2252,"repoUrl":2253,"updatedAt":2273},"querying-yesoreyeram-infinity-datasource","query data with Infinity datasource","Build queries with the Infinity data source — the query types (JSON, CSV, TSV, XML, GraphQL, HTML, UQL, GROQ, Google Sheets, Series, Transformations), the parsers (Frontend\u002Fsimple, Backend JSONata, JQ, UQL, GROQ) and which support alerting, the sources (URL, Inline, Reference, Azure Blob, Random walk), output formats (table, timeseries, logs, trace, node graph, dataframe), root selector and columns, computed columns\u002Ffilters\u002Fsummarize, pagination, and template variables. Use when a user asks how to query Infinity; how to fetch JSON\u002FCSV\u002FXML\u002FGraphQL\u002FHTML from a URL or inline; how to select rows and columns; how to transform data with UQL\u002FGROQ\u002FJSONata\u002FJQ; how to make a query work with alerting; how to paginate; or how to use variables in a query.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2261,2264,2267,2268,2271],{"name":2262,"slug":2263,"type":15},"CSV","csv",{"name":2265,"slug":2266,"type":15},"Data Analysis","data-analysis",{"name":9,"slug":8,"type":15},{"name":2269,"slug":2270,"type":15},"GraphQL","graphql",{"name":2272,"slug":239,"type":15},"JSON","2026-07-15T05:34:05.773947",{"slug":2275,"name":2275,"fn":2276,"description":2277,"org":2278,"tags":2279,"stars":2286,"repoUrl":2287,"updatedAt":2288},"agento11y","manage Grafana Agent Observability resources","Inspects and manages Grafana Agent Observability resources via gcx: conversations, generations, evaluators, rules, scores, and templates. Use when the user wants to list or search conversations, inspect generations, manage evaluators (upsert, test, delete), set up evaluation rules, check scores, or browse evaluator templates. Trigger on phrases like \"list conversations\", \"search generations\", \"what did the agent do\", \"debug LLM conversation\", \"create evaluator\", \"set up evaluation rule\", \"test evaluator\", \"check scores\", \"evaluate generation quality\", or \"set up online evaluation\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2280,2283,2284,2285],{"name":2281,"slug":2282,"type":15},"Agents","agents",{"name":9,"slug":8,"type":15},{"name":17,"slug":18,"type":15},{"name":2118,"slug":2119,"type":15},430,"https:\u002F\u002Fgithub.com\u002Fgrafana\u002Fgcx","2026-07-25T05:30:40.29622",{"slug":2290,"name":2290,"fn":2291,"description":2292,"org":2293,"tags":2294,"stars":2286,"repoUrl":2287,"updatedAt":2302},"agento11y-instrument","instrument LLM apps for agent observability","Sets up and instruments a developer's own LLM app or agent to send generations and agentic workflow to Grafana Agent Observability (the Agent Observability SDKs) — greenfield setup, fixing broken instrumentation, or filling gaps in existing instrumentation. Uses gcx for the parts a static prompt can't do: `gcx login` \u002F `gcx cloud stacks` to find the stack, and `gcx agento11y agents|conversations|generations` to VERIFY that data actually lands — so it iterates (instrument → run → verify → fix) until generations arrive, not blindly. Reads the app's code, detects language\u002Fframework, classifies instrumentation state (none \u002F partial \u002F broken), then runs a fixed gap checklist whose #1 item is the silent failure no other prompt catches: the SDK emits OTel spans\u002Fmetrics but never creates a TracerProvider\u002FMeterProvider, so without them all metrics go to a no-op and are lost. Also checks agent_version (required for per-version Performance charts), set_result completeness, SYNC vs STREAM, parent_generation_ids DAG links, and workflow-step coverage. Recommends changes citing file:line and, only with explicit confirmation, applies minimal diffs that don't change app behavior. Pulls SDK reference from agento11y's llms.txt rather than restating it, and hands off to `agento11y-test-starter` once data flows. It does NOT write test suites or set up tenant evaluations, rules, or guards — offline test suites are `agento11y-test-starter`, tenant eval rules + guards are `agento11y-prod-setup`; does NOT install coding-agent telemetry plugins (that is llms.txt \"Path A\"); does NOT mint or store credentials or invent endpoints. Trigger on phrases like \"instrument my app\", \"send my agent's traces to Grafana\", \"set up AI observability for my app\", \"my generations aren't showing up\", \"why is Performance empty\", \"add Agent Observability to my code\", \"fix my instrumentation\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2295,2296,2297,2300,2301],{"name":2281,"slug":2282,"type":15},{"name":9,"slug":8,"type":15},{"name":2298,"slug":2299,"type":15},"Instrumentation","instrumentation",{"name":2199,"slug":2200,"type":15},{"name":2118,"slug":2119,"type":15},"2026-07-31T05:53:52.580237",{"slug":2304,"name":2304,"fn":2305,"description":2306,"org":2307,"tags":2308,"stars":2286,"repoUrl":2287,"updatedAt":2315},"agento11y-prod-setup","setup production evaluation for AI agents","Sets up production evaluation and guardrails for a DEPLOYED AI agent in Grafana Agent Observability, grounded in the agent's own code and its real ingested traffic. The judgment layer on top of the `agento11y` skill: it reads the agent's source (system prompt, tools, entrypoint) AND samples its live traffic via gcx, checks what evaluators\u002Frules\u002Fguards already exist, then recommends only what's missing — online eval rules (score live conversations for regressions) and guards (warn-first request-path policies that redact \u002F tool-filter and may later be promoted to deny). It drafts reviewable YAML and, only with explicit confirmation, applies via `gcx agento11y`. New guards are drafted in warn mode (safe on live traffic — warn records but never blocks). It DOES create stack-level objects — that is the point — but every write is confirmed. It never rewrites or redeploys the agent. Trigger on phrases like \"set up production evaluation\", \"my agent is in prod what should I evaluate\", \"catch quality regressions\", \"add guardrails to my agent\", \"redact PII from my agent\", \"block dangerous tools\", \"set up online evals and guards\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2309,2310,2313,2314],{"name":2281,"slug":2282,"type":15},{"name":2311,"slug":2312,"type":15},"Evals","evals",{"name":9,"slug":8,"type":15},{"name":2118,"slug":2119,"type":15},"2026-07-31T05:53:53.576347",{"slug":2317,"name":2317,"fn":2318,"description":2319,"org":2320,"tags":2321,"stars":2286,"repoUrl":2287,"updatedAt":2330},"agento11y-test-starter","build and run agent test suites","Use early in an AI-agent project — before ship, before real traffic — to build a starter test suite for the agent and run it offline. Reads the agent's own code (system prompt, tools, task), writes a labeled draft suite of test cases (happy\u002Fedge\u002Fadversarial) grounded in real lines, and recommends how to score each case (the evaluators\u002Fjudges the offline runner uses). Assesses how runnable the agent is: for an easily-invoked agent it generates a runner stub (run_experiment.py) with two holes to fill and can optionally run it (only with permission, only against the endpoint the developer configured); for agents needing a harness or full runtime it points to the existing eval infra. It runs OFFLINE and never creates tenant-level evaluators, rules, or guards — that is `agento11y-prod-setup`, for a deployed agent with real traffic. Trigger on phrases like \"how do I test my agent before shipping\", \"write test cases for my agent\", \"set up tests for my agent\", \"check my agent before prod\", \"I have no traffic yet, how do I evaluate it\", \"test my agent offline\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2322,2323,2324,2327],{"name":2281,"slug":2282,"type":15},{"name":9,"slug":8,"type":15},{"name":2325,"slug":2326,"type":15},"QA","qa",{"name":2328,"slug":2329,"type":15},"Testing","testing","2026-07-31T05:53:51.62785",{"slug":2332,"name":2332,"fn":2333,"description":2334,"org":2335,"tags":2336,"stars":2286,"repoUrl":2287,"updatedAt":2347},"create-dashboard","create Grafana dashboards with gcx","Designs and creates Grafana dashboards with gcx, using `gcx dashboards snapshot` as a visual feedback loop. Use when the user wants to create a new Grafana dashboard, add panels, variables, or annotations to an existing dashboard, design dashboard panels, variables, queries, or layout, or make a material visual redesign. Triggers on \"create dashboard\", \"new dashboard\", \"build dashboard\", \"dashboard for \u003Cservice>\", \"add panels\", \"add variable\", \"add annotation\", \"improve this dashboard\", or \"iterate on a dashboard\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2337,2340,2343,2346],{"name":2338,"slug":2339,"type":15},"Dashboards","dashboards",{"name":2341,"slug":2342,"type":15},"Data Visualization","data-visualization",{"name":2344,"slug":2345,"type":15},"Design","design",{"name":9,"slug":8,"type":15},"2026-07-25T05:30:46.289717",{"slug":2349,"name":2349,"fn":2350,"description":2351,"org":2352,"tags":2353,"stars":2286,"repoUrl":2287,"updatedAt":2360},"debug-with-grafana","investigate application issues with Grafana","Structured workflow for investigating application problems with Grafana observability data (metrics, logs, traces) via gcx. Covers live firefighting AND retrospective incident analysis: incident triage, root-cause analysis, blast-radius checks (did an incident spill into other services), verifying whether a deployment or rollout triggered an incident, finding which service, endpoint, or path owns the most errors or slow requests, checking whether retries or queue backlogs piled up, and quantifying error or latency shares over a time window. Trigger on: \"my API is returning 500 errors\", \"latency is spiking\", \"investigate why requests are failing\", \"triage the incident\", \"blast radius\", \"root cause\", \"did the rollout cause it\", \"which endpoint owns the most 5xx\", \"did retries pile up\", or any request to analyse an earlier incident window using telemetry. For authoring dashboards use create-dashboard; for dashboard inventory use manage-dashboards.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2354,2357,2358,2359],{"name":2355,"slug":2356,"type":15},"Debugging","debugging",{"name":9,"slug":8,"type":15},{"name":2165,"slug":2166,"type":15},{"name":2118,"slug":2119,"type":15},"2026-07-18T05:11:10.445428",{"slug":2362,"name":2362,"fn":2363,"description":2364,"org":2365,"tags":2366,"stars":2286,"repoUrl":2287,"updatedAt":2373},"diagnose-entity-graph","diagnose Grafana Entity Graph issues","Diagnose Entity Graph problems: missing entities, missing edges, disconnected clusters, or filtering issues. Use when the user reports that Entity Graph doesn't look right, services are missing, edges aren't appearing, or environments can't be filtered. Triggers for: \"entity graph is empty\", \"services missing from entity graph\", \"no edges in entity graph\", \"disconnected services\", \"can't filter entity graph\", \"entity graph not working\", \"diagnose entity graph\", \"debug knowledge graph\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2367,2368,2369,2372],{"name":2355,"slug":2356,"type":15},{"name":9,"slug":8,"type":15},{"name":2370,"slug":2371,"type":15},"Graph Analysis","graph-analysis",{"name":2118,"slug":2119,"type":15},"2026-07-25T05:30:39.380934",{"slug":2375,"name":2375,"fn":2376,"description":2377,"org":2378,"tags":2379,"stars":2286,"repoUrl":2287,"updatedAt":2386},"gcx","manage Grafana Cloud resources via gcx","Manages Grafana Cloud resources via the gcx CLI. Trigger when the user wants to inspect, create, update, delete, query, or automate any Grafana resource - dashboards, datasources, alerts, SLOs, synthetic checks, oncall, incidents, fleet, k6, knowledge graph, or adaptive telemetry.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2380,2383,2384,2385],{"name":2381,"slug":2382,"type":15},"CLI","cli",{"name":9,"slug":8,"type":15},{"name":17,"slug":18,"type":15},{"name":2135,"slug":2136,"type":15},"2026-07-31T05:53:50.587304",{"slug":2388,"name":2388,"fn":2389,"description":2390,"org":2391,"tags":2392,"stars":2286,"repoUrl":2287,"updatedAt":2398},"gcx-demo","present gcx demo tours","Run a narrated, read-only demo tour of gcx for customer or colleague presentations. Showcases the breadth of gcx across every Grafana Cloud product area — resources, datasources, metrics, logs, traces, SLOs, alerts, synthetic monitoring, IRM, k6, fleet, and more. All commands are strictly read-only. Trigger when the user says \"demo gcx\", \"show off gcx\", \"customer demo\", \"gcx tour\", or \"\u002Fgcx-demo\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2393,2394,2395],{"name":2381,"slug":2382,"type":15},{"name":9,"slug":8,"type":15},{"name":2396,"slug":2397,"type":15},"Presentations","presentations","2026-07-25T05:30:45.282458",80]