--- name: render-monitor description: Monitor Render services in real-time. Check health, performance metrics, logs, and resource usage. Use when users want to check service status, view metrics, monitor performance, or verify deployments are healthy. license: MIT compatibility: Requires Render MCP tools or CLI metadata: author: Render version: "1.0.0" category: monitoring --- # 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 (Per Tool) If `list_services()` fails because MCP isn't configured, guide the user to set up the hosted Render MCP server. Ask which AI tool they're using, then provide the matching instructions below. Always use their API key. ### Cursor Walk the user through these steps: 1) Get a Render API key: ``` https://dashboard.render.com/u/*/settings#api-keys ``` 2) Add this to `~/.cursor/mcp.json` (replace ``): ```json { "mcpServers": { "render": { "url": "https://mcp.render.com/mcp", "headers": { "Authorization": "Bearer " } } } } ``` 3) Restart Cursor, then retry `list_services()`. ### Claude Code Walk the user through these steps: 1) Get a Render API key: ``` https://dashboard.render.com/u/*/settings#api-keys ``` 2) Add the MCP server with Claude Code (replace ``): ```bash claude mcp add --transport http render https://mcp.render.com/mcp --header "Authorization: Bearer " ``` 3) Restart Claude Code, then retry `list_services()`. ### Codex Walk the user through these steps: 1) Get a Render API key: ``` https://dashboard.render.com/u/*/settings#api-keys ``` 2) Set it in their shell: ```bash export RENDER_API_KEY="" ``` 3) Add the MCP server with the Codex CLI: ```bash codex mcp add render --url https://mcp.render.com/mcp --bearer-token-env-var RENDER_API_KEY ``` 4) Restart Codex, then retry `list_services()`. ### Other Tools If the user is on another AI app, direct them to the Render MCP docs for that tool's setup steps and install method. ### Workspace Selection After MCP is configured, have the user set the active Render workspace with a prompt like: ``` Set my Render workspace to [WORKSPACE_NAME] ``` --- ## Quick Health Check Run these 5 checks to assess service health: ``` # 1. Check service status list_services() # 2. Check latest deploy list_deploys(serviceId: "", limit: 1) # 3. Check for errors list_logs(resource: [""], level: ["error"], limit: 20) # 4. Check resource usage get_metrics(resourceId: "", metricTypes: ["cpu_usage", "memory_usage"]) # 5. Check latency get_metrics(resourceId: "", metricTypes: ["http_latency"], httpLatencyQuantile: 0.95) ``` --- ## Service Health ### Check Status ``` list_services() ``` ``` get_service(serviceId: "") ``` ### Check Deployments ``` list_deploys(serviceId: "", 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: [""], level: ["error"], limit: 50) ``` ``` list_logs(resource: [""], statusCode: ["500", "502", "503"], limit: 50) ``` --- ## Performance Metrics ### CPU & Memory ``` get_metrics( resourceId: "", 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: "", metricTypes: ["http_latency"], httpLatencyQuantile: 0.95 ) ``` | p95 Latency | Status | |-------------|--------| | <200ms | Excellent | | 200-500ms | Good | | 500ms-1s | Concerning | | >1s | Problem | ### Request Count ``` get_metrics( resourceId: "", metricTypes: ["http_request_count"] ) ``` ### Filter by Endpoint ``` get_metrics( resourceId: "", 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: "") ``` ### Connection Count ``` get_metrics(resourceId: "", metricTypes: ["active_connections"]) ``` ### Query Database ``` query_render_postgres( postgresId: "", sql: "SELECT state, count(*) FROM pg_stat_activity GROUP BY state" ) ``` ### Find Slow Queries ``` query_render_postgres( postgresId: "", 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: "") ``` --- ## Log Monitoring ### Recent Logs ``` list_logs(resource: [""], limit: 100) ``` ### Error Logs ``` list_logs(resource: [""], level: ["error"], limit: 50) ``` ### Search Logs ``` list_logs(resource: [""], text: ["timeout", "error"], limit: 50) ``` ### Filter by Time ``` list_logs( resource: [""], startTime: "2024-01-15T10:00:00Z", endTime: "2024-01-15T11:00:00Z" ) ``` ### Stream Logs (CLI) ```bash render logs -r --tail -o text ``` --- ## Quick Reference ### MCP Tools ``` # Services list_services() get_service(serviceId: "") list_deploys(serviceId: "", limit: 5) # Logs list_logs(resource: [""], level: ["error"], limit: 100) list_logs(resource: [""], text: ["search"], limit: 50) # Metrics get_metrics(resourceId: "", metricTypes: ["cpu_usage", "memory_usage"]) get_metrics(resourceId: "", metricTypes: ["http_latency"], httpLatencyQuantile: 0.95) get_metrics(resourceId: "", metricTypes: ["http_request_count"]) # Database list_postgres_instances() get_postgres(postgresId: "") query_render_postgres(postgresId: "", sql: "SELECT ...") get_metrics(resourceId: "", metricTypes: ["active_connections"]) # Key-Value list_key_value() get_key_value(keyValueId: "") ``` ### CLI Commands (Fallback) Use these if MCP tools are unavailable: ```bash # Service status render services -o json render services instances # Deployments render deploys list -o json # Logs render logs -r --tail -o text # Stream logs render logs -r --level error -o json # Error logs render logs -r --type deploy -o json # Build logs # Database render psql # Connect to PostgreSQL # SSH for live debugging render ssh ``` ### 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 - **deploy:** Deploy new applications to Render - **debug:** Diagnose and fix deployment failures --- Source attribution: ilderaj Original project: https://github.com/ilderaj/agent-plugin-marketplace/blob/main/plugins/codex--render/skills/render-monitor/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Dave AI. ## Upstream license notice MIT License Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Dave AI resource metadata Creator / publisher: ilderaj Original project: https://github.com/ilderaj/agent-plugin-marketplace/blob/main/plugins/codex--render/skills/render-monitor/SKILL.md Attribution basis: Source repository record Fields of work: Development & Engineering, Customer Support Roles: Backend Developer, DevOps / SRE, Technical Support Specialties: Backend, DevOps Tools: Render Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 3430312c1eea95688dae31a84dbe613c03fade705e7774780015d3644ef3aadb