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โšก Calmops

Metrics Collection: Prometheus, InfluxDB, Telegraf

Introduction

Metrics are the backbone of observability. From system resource usage to business KPIs, collecting and analyzing time-series data enables alerting, dashboards, and capacity planning.

Key Statistics:

  • Prometheus: 70% of Kubernetes monitoring
  • InfluxDB: 1M metrics/second ingestion
  • Time-series DB market: $4B by 2025

Prometheus Architecture

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                    Prometheus Architecture                            โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚                                                                  โ”‚
โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”   โ”‚
โ”‚  โ”‚              Targets (Scrape Targets)                      โ”‚   โ”‚
โ”‚  โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”     โ”‚   โ”‚
โ”‚  โ”‚  โ”‚ Node   โ”‚  โ”‚  App   โ”‚  โ”‚  K8s   โ”‚  โ”‚  App   โ”‚     โ”‚   โ”‚
โ”‚  โ”‚  โ”‚Exporterโ”‚  โ”‚Metrics โ”‚  โ”‚ cAdvisorโ”‚ โ”‚SDK     โ”‚     โ”‚   โ”‚
โ”‚  โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜     โ”‚   โ”‚
โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜   โ”‚
โ”‚                              โ”‚                                   โ”‚
โ”‚                              โ–ผ                                   โ”‚
โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”   โ”‚
โ”‚  โ”‚              Prometheus Server                             โ”‚   โ”‚
โ”‚  โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”                โ”‚   โ”‚
โ”‚  โ”‚  โ”‚ TSDB   โ”‚  โ”‚Scrape  โ”‚  โ”‚  Rules  โ”‚                โ”‚   โ”‚
โ”‚  โ”‚  โ”‚(Storage)โ”‚  โ”‚ Engine โ”‚  โ”‚(Alerts)โ”‚                โ”‚   โ”‚
โ”‚  โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜                โ”‚   โ”‚
โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜   โ”‚
โ”‚                              โ”‚                                   โ”‚
โ”‚                              โ–ผ                                   โ”‚
โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”   โ”‚
โ”‚  โ”‚              Query & Visualization                         โ”‚   โ”‚
โ”‚  โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”                  โ”‚   โ”‚
โ”‚  โ”‚  โ”‚PromQL โ”‚  โ”‚Grafana โ”‚  โ”‚Alerts โ”‚                  โ”‚   โ”‚
โ”‚  โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜                  โ”‚   โ”‚
โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜   โ”‚
โ”‚                                                                  โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

Prometheus Configuration

# prometheus.yml
global:
  scrape_interval: 15s
  evaluation_interval: 15s

alerting:
  alertmanagers:
    - static_configs:
        - targets: ['alertmanager:9093']

rule_files:
  - '/etc/prometheus/rules/*.yml'

scrape_configs:
  - job_name: 'prometheus'
    static_configs:
      - targets: ['localhost:9090']
  
  - job_name: 'node'
    static_configs:
      - targets: ['node-exporter:9100']
  
  - job_name: 'kubernetes-apiservers'
    kubernetes_sd_configs:
      - role: endpoints
    relabel_configs:
      - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
        action: keep
        regex: default;kubernetes;https
  
  - job_name: 'kubernetes-nodes'
    kubernetes_sd_configs:
      - role: node
    relabel_configs:
      - action: labelmap
        regex: __meta_kubernetes_node_label_(.+)
  
  - job_name: 'kubernetes-pods'
    kubernetes_sd_configs:
      - role: pod
    relabel_configs:
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
        action: keep
        regex: true
      - action: replace
        source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
        target_label: __metrics_path__
        regex: (.+)

Metric Types

# Counter: Always increasing
# Example: http_requests_total
- name: http_requests_total
  type: counter
  help: Total HTTP requests
  metrics:
    - labels:
        method: GET
        status: 200
      value: 15234

# Gauge: Can go up or down
# Example: memory_usage_bytes
- name: memory_usage_bytes
  type: gauge
  help: Current memory usage
  metrics:
    - labels:
        pod: api-0
      value: 536870912

# Histogram: Distributions
# Example: http_request_duration_seconds
- name: http_request_duration_seconds
  type: histogram
  help: HTTP request duration
  buckets: [0.1, 0.25, 0.5, 1.0, 2.5, 5.0]
  metrics:
    - labels:
        method: GET
        le: 0.1
      value: 12345

# Summary: Percentiles
# Example: rpc_duration_seconds
- name: rpc_duration_seconds
  type: summary
  quantiles:
    - quantile: 0.5
      value: 0.05
    - quantile: 0.9
      value: 0.12

InfluxDB

Data Model

#!/usr/bin/env python3
"""InfluxDB client."""

from influxdb_client import InfluxDBClient, Point
from influxdb_client.client.write_api import SYNCHRONOUS

class MetricsCollector:
    """Collect metrics to InfluxDB."""
    
    def __init__(self, url, token, org):
        self.client = InfluxDBClient(url=url, token=token, org=org)
        self.write_api = self.client.write_api(write_options=SYNCHRONOUS)
        self.query_api = self.client.query_api()
    
    def write_point(self, measurement, tags, fields, timestamp=None):
        """Write a single point."""
        
        point = (
            Point(measurement)
            .tag("host", tags.get("host"))
            .tag("service", tags.get("service"))
            .field("value", fields["value"])
        )
        
        if timestamp:
            point.time(timestamp)
        
        self.write_api.write(bucket="metrics", org="my-org", record=point)
    
    def write_line_protocol(self, line_protocol):
        """Write line protocol directly."""
        
        self.write_api.write(bucket="metrics", org="my-org", record=line_protocol)
    
    def query(self, query):
        """Query metrics."""
        
        return self.query_api.query_data_frame(query)
    
    def create_bucket(self, name, retention_days=30):
        """Create measurement bucket."""
        
        from influxdb_client.client.bucket_api import BucketApi
        
        bucket_api = BucketApi(self.client)
        
        bucket = bucket_api.create_bucket(
            bucket_name=name,
            org="my-org",
            retention_rules=[
                {"everySeconds": retention_days * 86400}
            ]
        )
        
        return bucket

Telegraf

# telegraf.conf

[agent]
  interval = "10s"
  round_interval = true
  metric_batch_size = 1000
  metric_buffer_limit = 10000
  collection_jitter = "0s"
  flush_interval = "10s"
  flush_jitter = "0s"

# Inputs
[[inputs.cpu]]
  percpu = false
  totalcpu = true
  collect_cpu_time = false

[[inputs.mem]]
  
[[inputs.disk]]
  ignore_fs = ["tmpfs", "devtmpfs", "devfs"]

[[inputs.processes]]
  
[[inputs.net]]
  interfaces = ["eth0"]

[[inputs.kubernetes]]
  url = "https://kubernetes.default.svc"
  bearer_token = "/var/run/secrets/kubernetes.io/serviceaccount/token"
  insecure_skip_verify = true

[[inputs.prometheus]]
  urls = ["http://prometheus:9090/metrics"]
  
[[inputs.mysql]]
  servers = ["user:password@tcp(localhost:3306)/"]

# Outputs
[[outputs.influxdb]]
  urls = ["http://influxdb:8086"]
  database = "telegraf"
  retention_policy = "autogen"

[[outputs.elasticsearch]]
  urls = ["http://elasticsearch:9200"]
  index_name = "telegraf"

# Processors
[[processors.rename]]
  [[processors.rename.rename]]
    old = "host"
    dest = "hostname"

External Resources


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