render-monitor

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.

render-oss/skills320 installsMITSynced Aug 26

Works with

Claude CodeCursorCodex CLIGitHub CopilotGemini CLI
---
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
---

# 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:** If you installed the Render plugin (Cursor, Codex, Claude Code), it provides OAuth for MCP — complete the OAuth prompt. For manual MCP clients, use a Render API key. 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**.

**Plugin setup:** If the Render plugin is installed, complete Render OAuth when prompted, then reload your tool and retry `list_services()`.

**Manual MCP 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

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