Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Configure New Relic observability platform for infrastructure and application monitoring. Set up APM agents, create dashboards, configure alerts, and implement distributed tracing. Use when implementing full-stack observability with New Relic One.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Monitor applications and infrastructure with New Relic's observability platform.
Use this skill when:
# Add repository and install
curl -Ls https://download.newrelic.com/install/newrelic-cli/scripts/install.sh | bash
# Configure license key
sudo NEW_RELIC_API_KEY=<YOUR_API_KEY> NEW_RELIC_ACCOUNT_ID=<ACCOUNT_ID> /usr/local/bin/newrelic install
# Or manual configuration
echo "license_key: YOUR_LICENSE_KEY" | sudo tee -a /etc/newrelic-infra.yml
sudo systemctl start newrelic-infra
# docker-compose.yml
version: '3.8'
services:
newrelic-infra:
image: newrelic/infrastructure:latest
cap_add:
- SYS_PTRACE
privileged: true
pid: "host"
network_mode: "host"
environment:
- NRIA_LICENSE_KEY=${NEW_RELIC_LICENSE_KEY}
- NRIA_DISPLAY_NAME=docker-host
volumes:
- /:/host:ro
- /var/run/docker.sock:/var/run/docker.sock
# Using Helm
helm repo add newrelic https://helm-charts.newrelic.com
helm install newrelic-bundle newrelic/nri-bundle \
--namespace newrelic \
--create-namespace \
--set global.licenseKey=${NEW_RELIC_LICENSE_KEY} \
--set global.cluster=my-cluster \
--set newrelic-infrastructure.privileged=true \
--set ksm.enabled=true \
--set kubeEvents.enabled=true \
--set logging.enabled=true
// At the very start of your application
require('newrelic');
// newrelic.js configuration
exports.config = {
app_name: ['My Application'],
license_key: process.env.NEW_RELIC_LICENSE_KEY,
distributed_tracing: {
enabled: true
},
logging: {
level: 'info'
},
error_collector: {
enabled: true,
ignore_status_codes: [404]
},
transaction_tracer: {
enabled: true,
transaction_threshold: 'apdex_f',
record_sql: 'obfuscated'
}
};
# Install agent
npm install newrelic
# Run application
NEW_RELIC_LICENSE_KEY=xxx node -r newrelic app.js
# newrelic.ini
[newrelic]
license_key = YOUR_LICENSE_KEY
app_name = My Application
distributed_tracing.enabled = true
transaction_tracer.enabled = true
error_collector.enabled = true
browser_monitoring.auto_instrument = true
# Install agent
pip install newrelic
# Generate config file
newrelic-admin generate-config YOUR_LICENSE_KEY newrelic.ini
# Run application
NEW_RELIC_CONFIG_FILE=newrelic.ini newrelic-admin run-program python app.py
# Or with gunicorn
NEW_RELIC_CONFIG_FILE=newrelic.ini newrelic-admin run-program gunicorn app:app
# Download agent
curl -O https://download.newrelic.com/newrelic/java-agent/newrelic-agent/current/newrelic-java.zip
unzip newrelic-java.zip
# Configure newrelic.yml
# license_key: YOUR_LICENSE_KEY
# app_name: My Application
# Run with agent
java -javaagent:/path/to/newrelic.jar -jar myapp.jar
package main
import (
"github.com/newrelic/go-agent/v3/newrelic"
"net/http"
)
func main() {
app, err := newrelic.NewApplication(
newrelic.ConfigAppName("My Application"),
newrelic.ConfigLicense("YOUR_LICENSE_KEY"),
newrelic.ConfigDistributedTracerEnabled(true),
)
if err != nil {
panic(err)
}
http.HandleFunc(newrelic.WrapHandleFunc(app, "/", indexHandler))
http.ListenAndServe(":8080", nil)
}
func indexHandler(w http.ResponseWriter, r *http.Request) {
txn := newrelic.FromContext(r.Context())
txn.AddAttribute("user_id", "12345")
w.Write([]byte("Hello, World!"))
}
import newrelic.agent
# Record custom event
newrelic.agent.record_custom_event('OrderPlaced', {
'order_id': '12345',
'amount': 99.99,
'customer_id': 'cust_001'
})
import newrelic.agent
# Record custom metric
newrelic.agent.record_custom_metric('Custom/OrderValue', 99.99)
# With attributes
newrelic.agent.record_custom_metric('Custom/ProcessingTime',
processing_time,
{'unit': 'milliseconds'}
)
import newrelic.agent
@newrelic.agent.function_trace(name='process_payment')
def process_payment(order_id, amount):
# This creates a custom span in the trace
pass
# Manual span creation
with newrelic.agent.FunctionTrace(name='custom_operation'):
# Traced code
pass
-- Transaction throughput
SELECT rate(count(*), 1 minute) FROM Transaction
WHERE appName = 'My Application'
SINCE 1 hour ago
-- Average response time
SELECT average(duration) FROM Transaction
WHERE appName = 'My Application'
SINCE 1 hour ago
-- Error rate
SELECT percentage(count(*), WHERE error IS true) FROM Transaction
WHERE appName = 'My Application'
SINCE 1 hour ago
-- Apdex score
SELECT apdex(duration, t: 0.5) FROM Transaction
WHERE appName = 'My Application'
SINCE 1 hour ago
-- Slowest transactions
SELECT average(duration) FROM Transaction
WHERE appName = 'My Application'
FACET name
SINCE 1 hour ago
ORDER BY average(duration) DESC
LIMIT 10
-- Error breakdown
SELECT count(*) FROM TransactionError
WHERE appName = 'My Application'
FACET error.class
SINCE 1 hour ago
-- Percentile response times
SELECT percentile(duration, 50, 90, 95, 99) FROM Transaction
WHERE appName = 'My Application'
SINCE 1 hour ago TIMESERIES
-- Custom event analysis
SELECT average(amount), count(*) FROM OrderPlaced
FACET customer_id
SINCE 1 day ago
{
"name": "Application Dashboard",
"pages": [
{
"name": "Overview",
"widgets": [
{
"title": "Throughput",
"visualization": {"id": "viz.line"},
"configuration": {
"nrqlQueries": [
{
"accountId": 12345,
"query": "SELECT rate(count(*), 1 minute) FROM Transaction WHERE appName = 'My Application' SINCE 1 hour ago TIMESERIES"
}
]
}
},
{
"title": "Error Rate",
"visualization": {"id": "viz.billboard"},
"configuration": {
"nrqlQueries": [
{
"accountId": 12345,
"query": "SELECT percentage(count(*), WHERE error IS true) FROM Transaction WHERE appName = 'My Application' SINCE 1 hour ago"
}
]
}
}
]
}
]
}
{
"name": "High Error Rate",
"type": "static",
"nrql": {
"query": "SELECT percentage(count(*), WHERE error IS true) FROM Transaction WHERE appName = 'My Application'"
},
"valueFunction": "single_value",
"terms": [
{
"threshold": 5,
"thresholdOccurrences": "all",
"thresholdDuration": 300,
"operator": "above",
"priority": "critical"
},
{
"threshold": 2,
"thresholdOccurrences": "all",
"thresholdDuration": 300,
"operator": "above",
"priority": "warning"
}
]
}
{
"name": "Application Alerts",
"incident_preference": "PER_CONDITION_AND_TARGET",
"conditions": [
{
"name": "High Response Time",
"type": "apm_app_metric",
"entities": ["My Application"],
"metric": "response_time_web",
"condition_scope": "application",
"terms": [
{
"duration": "5",
"operator": "above",
"threshold": "1",
"priority": "critical"
}
]
}
]
}
# newrelic.ini
[newrelic]
application_logging.enabled = true
application_logging.forwarding.enabled = true
application_logging.metrics.enabled = true
application_logging.local_decorating.enabled = true
# newrelic-infra.yml
log:
- name: application-logs
file: /var/log/myapp/*.log
attributes:
service: myapp
environment: production
Problem: Agent not reporting to New Relic Solution: Verify license key, check network connectivity, review agent logs
Problem: Some transactions not captured Solution: Check instrumentation coverage, verify framework support
Problem: APM agent impacting performance Solution: Adjust sampling rate, disable unnecessary features
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Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.