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

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

---

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)

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:

# 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

Related Skills

• render-deploy — Deploy new applications to Render
• render-debug — Diagnose and fix deployment failures
• render-mcp — MCP server setup and tool catalog