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Verwandte Berufe SOC
Basierend auf der SOC-Berufsklassifikation
name monitoring description System monitoring and observability implementation using Prometheus, Grafana, and related tools license MIT compatibility opencode metadata {"audience":"devops-engineers","category":"systems-administration"}
What I do
Configure Prometheus metrics collection
Create Grafana dashboards
Set up alerting rules and notifications
Monitor application and infrastructure metrics
Implement distributed tracing
Configure log aggregation
Design observability strategies
Create SLOs and SLIs
Analyze performance bottlenecks
Debug production issues using metrics
When to use me
When setting up monitoring systems, creating dashboards, configuring alerts, or troubleshooting performance issues.
Core Concepts
Prometheus metrics types (counter, gauge, histogram, summary)
Service discovery and scraping configurations
PromQL query language
Grafana visualization and alerting
Alertmanager routing and silencing
Kubernetes metrics (kube-state-metrics, node-exporter)
Application performance monitoring (APM)
Distributed tracing (Jaeger, Zipkin)
Log aggregation (ELK, Loki)
SLO/SLI/Error budget design
Code Examples
Prometheus Configuration
global:
scrape_interval: 15s
evaluation_interval: 15s
external_labels:
cluster: 'prod-us-east-1'
env: 'production'
alerting:
alertmanagers:
- static_configs:
- targets:
- alertmanager:9093
timeout: 10s
api_version: v2
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' ]
relabel_configs:
- source_labels: [__address__ ]
target_label: instance
regex: '(.+):\\d+'
replacement: '${1}'
groups:
- name: default-alerts
rules:
- alert: HighCPUUsage
expr: |
sum(rate(container_cpu_usage_seconds_total{namespace!="kube-system"}[5m]))
/
sum(machine_cpu_cores) > 0.85
for: 5m
labels:
severity: warning
annotations:
summary: "High CPU usage on {{ $labels.node }} "
description: "CPU usage is above 85% for more than 5 minutes"
- alert: HighMemoryUsage
expr: |
(1 - (node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes)) > 0.90
for: 5m
labels:
severity: warning
annotations:
summary: "High memory usage on {{ $labels.instance }} "
description: "Memory usage is above 90% for more than 5 minutes"
- alert: LowDiskSpace
expr: |
(1 - (node_filesystem_avail_bytes{mountpoint="/"} / node_filesystem_size_bytes{mountpoint="/"})) > 0.85
AlertManager Configuration
global:
resolve_timeout: 5m
smtp_smarthost: 'smtp.example.com:587'
smtp_from: 'alertmanager@example.com'
smtp_auth_username: 'alertmanager'
smtp_auth_password: '${SMTP_PASSWORD}'
route:
group_by: ['alertname' , 'severity' ]
group_wait: 30s
group_interval: 5m
repeat_interval: 4h
receiver: 'default'
routes:
- match:
severity: critical
receiver: 'critical-pager'
continue: true
- match:
severity: warning
receiver: 'warning-slack'
continue: true
- match_re:
alertname: '.*Info'
receiver: 'informational'
group_interval: 15m
receivers:
- name: 'default'
email_configs:
Grafana Dashboard
{
"dashboard" : {
"title" : "Application Overview" ,
"uid" : "app-overview" ,
"tags" : [ "application" , "overview" ] ,
"timezone" : "browser" ,
"refresh" : "30s" ,
"panels" : [
{
"title" : "Request Rate" ,
"type" : "graph" ,
"gridPos" : { "x" : 0 , "y" : 0 , "w" : 12 , "h" : 8 } Best Practices
Use histograms for values with many distinct values (latency, sizes)
Set appropriate recording rules for complex queries
Implement labels consistently across metrics
Use appropriate alert thresholds based on SLOs
Avoid alert fatigue with proper grouping and routing
Use service discovery instead of static configurations
Monitor not just infrastructure but business metrics too
Implement proper error budget policies
Use annotations for rich alert information
Test alerting rules before deploying to production
-
job_name:
'kubernetes-service-endpoints'
kubernetes_sd_configs:
-
role:
endpoints
relabel_configs:
-
source_labels:
__meta_kubernetes_service_annotation_prometheus_io_scrape
action:
keep
regex:
true
-
source_labels:
__meta_kubernetes_service_annotation_prometheus_io_path
action:
replace
target_label:
__metrics_path__
regex:
(.+)
-
source_labels:
__address__
__meta_kubernetes_service_annotation_prometheus_io_port
action:
replace
target_label:
__address__
regex:
([^:]+)(?::\\d+)?;(\\d+)
replacement:
${1}:${2}
-
job_name:
'kubernetes-pods'
kubernetes_sd_configs:
-
role:
pod
relabel_configs:
-
action:
keep
source_labels:
__meta_kubernetes_pod_annotation_prometheus_io_scrape
for:
10m
labels:
severity:
warning
annotations:
summary:
"Low disk space on {{ $labels.instance }} "
description:
"Disk usage is above 85% on {{ $labels.mountpoint }} "
-
alert:
PodNotReady
expr:
|
kube_pod_status_ready{namespace!="kube-system",condition="true"} == 0
for:
3m
labels:
severity:
warning
annotations:
summary:
"Pod {{ $labels.namespace }} /{{ $labels.pod }} not ready"
description:
"Pod has been not ready for more than 3 minutes"
-
alert:
PodCrashing
expr:
|
increase(kube_pod_container_status_restarts_total[1h]) > 3
labels:
severity:
critical
annotations:
summary:
"Pod {{ $labels.namespace }} /{{ $labels.pod }} is crashing"
description:
"Container restarted more than 3 times in the last hour"
-
alert:
HighErrorRate
expr:
|
sum(rate(http_requests_total{status=~"5.."}[5m]))
/
sum(rate(http_requests_total[5m])) > 0.05
for:
5m
labels:
severity:
critical
annotations:
summary:
"High HTTP error rate"
description:
"More than 5% of requests are returning 5xx errors"
-
name:
sli-metrics
rules:
-
record:
service:http_requests:ratio5m
expr:
|
sum(rate(http_requests_total{handler!~"/health|/metrics"}[5m]))
/
sum(rate(http_requests_total{handler!~"/health|/metrics"}[5m]))
-
record:
service:http_request_duration_seconds:p99
expr:
|
histogram_quantile(0.99,
sum(rate(http_request_duration_seconds_bucket{handler!~"/health|/metrics"}[5m])) by (le))
-
to:
'team@example.com'
send_resolved:
true
html:
|
{{ define "email.default.html" }}
<!DOCTYPE html>
<html>
<body>
<h2>{{ .Status }} - {{ .GroupLabels.alertname }}</h2>
{{ range .Alerts }}
<p><strong>{{ .Labels.severity | upper }}</strong></p>
<p>{{ .Annotations.summary }}</p>
<pre>{{ .Annotations.description }}</pre>
{{ end }}
</body>
</html>
{{ end }}
{{ template "email.default.html" . }}
-
name:
'critical-pager'
pagerduty_configs:
-
service_key:
'${PAGERDUTY_SERVICE_KEY}'
severity:
critical
-
name:
'warning-slack'
slack_configs:
-
channel:
'#alerts-warning'
api_url:
'${SLACK_WEBHOOK_URL}'
title:
'{{ range .Alerts }}{{ .Labels.alertname }} {{ end }}'
text:
'{{ range .Alerts }}{{ .Annotations.summary }} {{ end }}'
severity:
'{{ .Labels.severity }}'
color:
'{{ if eq .Labels.severity "critical" }}danger{{ else }}warning{{ end }}'
inhibit_rules:
-
source_match:
severity:
'critical'
target_match:
severity:
'warning'
equal:
'alertname'
'instance'
,
"targets"
:
[
{
"expr"
:
"sum(rate(http_requests_total[5m])) by (method, status)"
,
"legendFormat"
:
"{{method}} {{status}}"
}
]
}
,
{
"title"
:
"Error Rate"
,
"type"
:
"stat"
,
"gridPos"
:
{
"x"
:
12
,
"y"
:
0
,
"w"
:
12
,
"h"
:
4
}
,
"targets"
:
[
{
"expr"
:
"sum(rate(http_requests_total{status=~\"5..\"}[5m])) / sum(rate(http_requests_total[5m])) * 100"
,
"legendFormat"
:
"Error Rate %"
}
]
,
"fieldConfig"
:
{
"defaults"
:
{
"unit"
:
"percent"
,
"thresholds"
:
{
"mode"
:
"absolute"
,
"steps"
:
[
{
"color"
:
"green"
,
"value"
:
null
}
,
{
"color"
:
"yellow"
,
"value"
:
1
}
,
{
"color"
:
"red"
,
"value"
:
5
}
]
}
}
}
}
,
{
"title"
:
"P99 Latency"
,
"type"
:
"graph"
,
"gridPos"
:
{
"x"
:
0
,
"y"
:
8
,
"w"
:
12
,
"h"
:
8
}
,
"targets"
:
[
{
"expr"
:
"histogram_quantile(0.99, sum(rate(http_request_duration_seconds_bucket[5m])) by (le))"
,
"legendFormat"
:
"p99"
}
,
{
"expr"
:
"histogram_quantile(0.95, sum(rate(http_request_duration_seconds_bucket[5m])) by (le))"
,
"legendFormat"
:
"p95"
}
]
}
,
{
"title"
:
"Active Pods"
,
"type"
:
"timeseries"
,
"gridPos"
:
{
"x"
:
12
,
"y"
:
8
,
"w"
:
12
,
"h"
:
8
}
,
"targets"
:
[
{
"expr"
:
"count(kube_pod_container_status_ready{namespace=\"$namespace\"})"
,
"legendFormat"
:
"Ready"
}
,
{
"expr"
:
"count(kube_pod_container_status_ready{namespace=\"$namespace\"} == 0)"
,
"legendFormat"
:
"Not Ready"
}
]
}
]
}
}
