telegraf
$
npx mdskill add TerminalSkills/skills/telegrafConfigures Telegraf for metrics collection and monitoring
- Collects system and application metrics using input plugins
- Sends data to InfluxDB or Prometheus via output plugins
- Uses TOML configuration files to define inputs, outputs, and processors
- Delivers metrics at defined intervals for observability and analysis
SKILL.md
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---
name: telegraf
description: >-
Configure Telegraf as a metrics collection agent for infrastructure and
application monitoring. Use when a user needs to collect system metrics,
set up input plugins for databases and services, configure output to
InfluxDB or Prometheus, or build custom metric pipelines.
license: Apache-2.0
compatibility: "Telegraf 1.28+, InfluxDB 2.x/3.x"
metadata:
author: terminal-skills
version: "1.0.0"
category: devops
tags: ["telegraf", "metrics", "influxdb", "monitoring", "collection-agent", "observability"]
---
# Telegraf
## Overview
Set up Telegraf to collect, process, and forward metrics from systems, databases, and applications. Covers input/output plugin configuration, metric filtering, aggregation processors, and deployment patterns.
## Instructions
### Task A: Basic System Metrics Collection
```toml
# /etc/telegraf/telegraf.conf — Collect system metrics and send to InfluxDB
[global_tags]
environment = "production"
region = "us-east-1"
[agent]
interval = "10s"
round_interval = true
metric_batch_size = 1000
metric_buffer_limit = 10000
flush_interval = "10s"
hostname = ""
omit_hostname = false
[[outputs.influxdb_v2]]
urls = ["http://influxdb:8086"]
token = "$INFLUX_TOKEN"
organization = "myorg"
bucket = "infrastructure"
[[inputs.cpu]]
percpu = true
totalcpu = true
collect_cpu_time = false
[[inputs.mem]]
[[inputs.disk]]
ignore_fs = ["tmpfs", "devtmpfs", "devfs", "iso9660", "overlay", "aufs", "squashfs"]
[[inputs.diskio]]
[[inputs.net]]
interfaces = ["eth0", "ens5"]
[[inputs.system]]
[[inputs.processes]]
[[inputs.kernel]]
```
### Task B: Application and Database Inputs
```toml
# /etc/telegraf/telegraf.d/databases.conf — Database monitoring inputs
[[inputs.postgresql]]
address = "postgres://telegraf:password@localhost:5432/myapp?sslmode=disable"
databases = ["myapp"]
[inputs.postgresql.tags]
service = "postgres"
[[inputs.mysql]]
servers = ["telegraf:password@tcp(localhost:3306)/"]
metric_version = 2
gather_table_schema = true
gather_process_list = true
gather_slave_status = true
[inputs.mysql.tags]
service = "mysql"
[[inputs.redis]]
servers = ["tcp://localhost:6379"]
password = "$REDIS_PASSWORD"
[inputs.redis.tags]
service = "redis"
[[inputs.nginx]]
urls = ["http://localhost:8080/nginx_status"]
[inputs.nginx.tags]
service = "nginx"
```
```toml
# /etc/telegraf/telegraf.d/docker.conf — Container metrics
[[inputs.docker]]
endpoint = "unix:///var/run/docker.sock"
gather_services = false
container_names = []
perdevice = true
total = true
[inputs.docker.tags]
input = "docker"
```
### Task C: Prometheus Input/Output
```toml
# /etc/telegraf/telegraf.d/prometheus.conf — Scrape Prometheus endpoints
[[inputs.prometheus]]
urls = [
"http://app-server:8080/metrics",
"http://payment-service:8080/metrics",
]
metric_version = 2
url_tag = "scrape_url"
# Expose metrics as Prometheus endpoint for Prometheus to scrape
[[outputs.prometheus_client]]
listen = ":9273"
metric_version = 2
export_timestamp = true
```
### Task D: Metric Processing and Filtering
```toml
# /etc/telegraf/telegraf.d/processing.conf — Filter and transform metrics
[[processors.rename]]
[[processors.rename.replace]]
measurement = "cpu"
dest = "system_cpu"
[[processors.converter]]
[processors.converter.fields]
float = ["usage_idle", "usage_user", "usage_system"]
integer = ["uptime"]
# Drop noisy metrics
[[processors.filter]]
namepass = ["cpu", "mem", "disk", "net", "docker*", "postgresql*"]
fielddrop = ["inodes_*"]
# Aggregate metrics before sending
[[aggregators.basicstats]]
period = "60s"
drop_original = false
stats = ["mean", "max", "min", "count"]
namepass = ["http_response_time"]
# Tag metrics based on field values
[[processors.starlark]]
source = '''
def apply(metric):
cpu = metric.fields.get("usage_percent", 0)
if cpu > 90:
metric.tags["cpu_alert"] = "critical"
elif cpu > 70:
metric.tags["cpu_alert"] = "warning"
return metric
'''
```
### Task E: HTTP and Custom Inputs
```toml
# /etc/telegraf/telegraf.d/http.conf — HTTP endpoint checks and API polling
[[inputs.http_response]]
urls = [
"https://api.example.com/health",
"https://web.example.com",
]
response_timeout = "5s"
method = "GET"
follow_redirects = true
response_status_code = 200
[inputs.http_response.tags]
check = "uptime"
[[inputs.http]]
urls = ["http://app-server:8080/api/stats"]
method = "GET"
data_format = "json"
json_name_key = "metric_name"
json_time_key = "timestamp"
json_time_format = "unix"
[inputs.http.tags]
source = "app-api"
# Execute custom scripts for metrics
[[inputs.exec]]
commands = ["/opt/scripts/check_queue_depth.sh"]
timeout = "5s"
data_format = "influx"
interval = "30s"
```
### Task F: Docker Deployment
```yaml
# docker-compose.yml — Telegraf with InfluxDB
services:
telegraf:
image: telegraf:1.29
volumes:
- ./telegraf.conf:/etc/telegraf/telegraf.conf:ro
- ./telegraf.d:/etc/telegraf/telegraf.d:ro
- /var/run/docker.sock:/var/run/docker.sock:ro
- /proc:/host/proc:ro
- /sys:/host/sys:ro
environment:
- HOST_PROC=/host/proc
- HOST_SYS=/host/sys
- INFLUX_TOKEN=${INFLUX_TOKEN}
user: telegraf:$(stat -c '%g' /var/run/docker.sock)
influxdb:
image: influxdb:2.7
ports:
- "8086:8086"
volumes:
- influxdb_data:/var/lib/influxdb2
environment:
- DOCKER_INFLUXDB_INIT_MODE=setup
- DOCKER_INFLUXDB_INIT_USERNAME=admin
- DOCKER_INFLUXDB_INIT_PASSWORD=changeme123
- DOCKER_INFLUXDB_INIT_ORG=myorg
- DOCKER_INFLUXDB_INIT_BUCKET=infrastructure
volumes:
influxdb_data:
```
## Best Practices
- Use `telegraf.d/` directory for modular configs — one file per input category
- Set `metric_buffer_limit` high enough to handle output destination outages
- Use `namepass`/`namedrop` filters to reduce cardinality and storage costs
- Run Telegraf with `--test` flag to verify plugin configuration before deploying
- Use Starlark processor for complex transformations instead of chaining multiple processors
- Monitor Telegraf's internal metrics with `[[inputs.internal]]` to detect collection issues
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