render-monitor

# Monitor Render Services Real-time monitoring of Render services including health checks, performance metrics, and logs. ## When to Use This Skill Activate this skill when users want to: - Check if services are healthy - View performance metrics - Monitor logs - Verify a deployment is working - Investigate slow performance - Check database health ## Prerequisites **MCP tools (preferred):** Test with `list_services()` - provides structured data **CLI (fallback):** `render --version` - use if MCP tools unavailable **Authentication:** For MCP, use an API key (set in the MCP config or via the `RENDER_API_KEY` env var, depending on tool). For CLI, verify with `render whoami -o json`. **Workspace:** `get_selected_workspace()` or `render workspace current -o json` > **Note:** MCP tools require the Render MCP server. If unavailable, use the CLI for status and logs; metrics and database queries require MCP. ## MCP Setup If `list_services()` fails, set up the Render MCP server. For detailed per-tool walkthroughs, see **render-mcp**. **Quick setup:** Add the Render MCP server to your AI tool's MCP config: - **URL:** `https://mcp.render.com/mcp` - **Auth header:** `Authorization: Bearer <YOUR_API_KEY>` - **API key:** `https://dashboard.render.com/u/*/settings#api-keys` After configuring, restart your tool and retry `list_services()`. Then set your workspace with `list_workspaces()` / `get_selected_workspace()`. --- ## Quick Health Check Run these 5 checks to assess service health: ``` # 1. Check service status list_services() # 2. Check latest deploy list_deploys(serviceId: "<service-id>", limit: 1) # 3. Check for errors list_logs(resource: ["<service-id>"], level: ["error"], limit: 20) # 4. Check resource usage get_metrics(resourceId: "<service-id>", metricTypes: ["cpu_usage", "memory_usage"]) # 5. Check latency get_metrics(resourceId: "<service-id>", metricTypes: ["http_latency"], httpLatencyQuantile: 0.95) ``` --- ## Service Health ### Check Status ``` list_services() ``` ``` get_service(serviceId: "<id>") ``` ### Check Deployments ``` list_deploys(serviceId: "<service-id>", limit: 5) ``` | Status | Meaning | |--------|---------| | `live` | Deployment successful | | `build_in_progress` | Building | | `build_failed` | Build failed | | `deactivated` | Replaced by newer deploy | ### Check Errors ``` list_logs(resource: ["<service-id>"], level: ["error"], limit: 50) ``` ``` list_logs(resource: ["<service-id>"], statusCode: ["500", "502", "503"], limit: 50) ``` --- ## Performance Metrics ### CPU & Memory ``` get_metrics( resourceId: "<service-id>", metricTypes: ["cpu_usage", "memory_usage", "cpu_limit", "memory_limit"] ) ``` | Metric | Healthy | Warning | Critical | |--------|---------|---------|----------| | CPU | <70% | 70-85% | >85% | | Memory | <80% | 80-90% | >90% | ### HTTP Latency ``` get_metrics( resourceId: "<service-id>", metricTypes: ["http_latency"], httpLatencyQuantile: 0.95 ) ``` | p95 Latency | Status | |-------------|--------| | <200ms | Excellent | | 200-500ms | Good | | 500ms-1s | Concerning | | >1s | Problem | ### Request Count ``` get_metrics( resourceId: "<service-id>", metricTypes: ["http_request_count"] ) ``` ### Filter by Endpoint ``` get_metrics( resourceId: "<service-id>", metricTypes: ["http_latency"], httpPath: "/api/users" ) ``` Detailed metrics guide: [references/metrics-guide.md](references/metrics-guide.md) --- ## Database Monitoring ### PostgreSQL Status ``` list_postgres_instances() get_postgres(postgresId: "<postgres-id>") ``` ### Connection Count ``` get_metrics(resourceId: "<postgres-id>", metricTypes: ["active_connections"]) ``` ### Query Database ``` query_render_postgres( postgresId: "<postgres-id>", sql: "SELECT state, count(*) FROM pg_stat_activity GROUP BY state" ) ``` ### Find Slow Queries ``` query_render_postgres( postgresId: "<postgres-id>", sql: "SELECT query, mean_exec_time FROM pg_stat_statements ORDER BY mean_exec_time DESC LIMIT 10" ) ``` ### Key-Value Store ``` list_key_value() get_key_value(keyValueId: "<kv-id>") ``` --- ## Log Monitoring ### Recent Logs ``` list_logs(resource: ["<service-id>"], limit: 100) ``` ### Error Logs ``` list_logs(resource: ["<service-id>"], level: ["error"], limit: 50) ``` ### Search Logs ``` list_logs(resource: ["<service-id>"], text: ["timeout", "error"], limit: 50) ``` ### Filter by Time ``` list_logs( resource: ["<service-id>"], startTime: "2024-01-15T10:00:00Z", endTime: "2024-01-15T11:00:00Z" ) ``` ### Stream Logs (CLI) ```bash render logs -r <service-id> --tail -o text ``` --- ## Quick Reference ### MCP Tools ``` # Services list_services() get_service(serviceId: "<id>") list_deploys(serviceId: "<id>", limit: 5) # Logs list_logs(resource: ["<id>"], level: ["error"], limit: 100) list_logs(resource: ["<id>"], text: ["search"], limit: 50) # Metrics get_metrics(resourceId: "<id>", metricTypes: ["cpu_usage", "memory_usage"]) get_metrics(resourceId: "<id>", metricTypes: ["http_latency"], httpLatencyQuantile: 0.95) get_metrics(resourceId: "<id>", metricTypes: ["http_request_count"]) # Database list_postgres_instances() get_postgres(postgresId: "<id>") query_render_postgres(postgresId: "<id>", sql: "SELECT ...") get_metrics(resourceId: "<postgres-id>", metricTypes: ["active_connections"]) # Key-Value list_key_value() get_key_value(keyValueId: "<id>") ``` ### CLI Commands (Fallback) Use these if MCP tools are unavailable: ```bash # Service status render services -o json render services instances <service-id> # Deployments render deploys list <service-id> -o json # Logs render logs -r <service-id> --tail -o text # Stream logs render logs -r <service-id> --level error -o json # Error logs render logs -r <service-id> --type deploy -o json # Build logs # Database render psql <database-id> # Connect to PostgreSQL # SSH for live debugging render ssh <service-id> ``` ### Healthy Service Indicators | Indicator | Healthy | Warning | Critical | |-----------|---------|---------|----------| | Deploy Status | `live` | `update_in_progress` | `build_failed` | | Error Rate | <0.1% | 0.1-1% | >1% | | p95 Latency | <500ms | 500ms-2s | >2s | | CPU Usage | <70% | 70-90% | >90% | | Memory Usage | <80% | 80-95% | >95% | --- ## References - **Metrics guide:** [references/metrics-guide.md](references/metrics-guide.md) ## Related Skills - **render-deploy** — Deploy new applications to Render - **render-debug** — Diagnose and fix deployment failures - **render-mcp** — MCP server setup and tool catalog