Full-stack observability with Prometheus, Grafana, ELK Stack, Jaeger, and Datadog for metrics, logs, traces, and intelligent alerting.
IMPLEMENT MONITORINGModern observability requires collecting and correlating metrics, logs, and distributed traces to understand system behavior and diagnose issues quickly.
Time-series numerical data about system performance.
Timestamped records of discrete events in your system.
End-to-end request flow across distributed microservices.
Open-source metrics collection and alerting with PromQL query language and service discovery.
Visualization platform for creating beautiful dashboards with alerting and team collaboration.
Distributed search and analytics engine for log aggregation and full-text search.
Visualization layer for Elasticsearch with log exploration and dashboard creation.
Distributed tracing system for monitoring and troubleshooting microservices.
Cloud-native monitoring platform with infrastructure, APM, logs, and security monitoring.
Prometheus collects time-series metrics with PromQL queries. Grafana provides beautiful dashboards with alerting and anomaly detection.
Automatic discovery of Kubernetes pods, EC2 instances, and services without manual configuration.
Powerful query language for aggregating, filtering, and analyzing time-series data with mathematical operations.
Define alert conditions with PromQL. Route alerts to Slack, PagerDuty, email based on severity and team.
Scrape metrics from multiple Prometheus servers for centralized monitoring across regions and clusters.
# prometheus.yml
global:
scrape_interval: 15s
evaluation_interval: 15s
external_labels:
cluster: 'production'
region: 'us-east-1'
alerting:
alertmanagers:
- static_configs:
- targets: ['alertmanager:9093']
rule_files:
- '/etc/prometheus/rules/*.yml'
scrape_configs:
- job_name: 'kubernetes-pods'
kubernetes_sd_configs:
- role: pod
relabel_configs:
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
action: keep
regex: true
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
action: replace
target_label: __metrics_path__
regex: (.+)
- job_name: 'node-exporter'
static_configs:
- targets: ['node-exporter:9100']
- job_name: 'blackbox-http'
metrics_path: /probe
params:
module: [http_2xx]
static_configs:
- targets:
- https://api.myapp.com
- https://www.myapp.com
relabel_configs:
- source_labels: [__address__]
target_label: __param_target
- source_labels: [__param_target]
target_label: instance
- target_label: __address__
replacement: blackbox-exporter:9115Elasticsearch, Logstash, and Kibana for centralized log collection, processing, and visualization with full-text search and analytics.
Store and index logs with full-text search, aggregations, and near real-time analytics at petabyte scale.
Ingest, transform, and enrich logs from multiple sources with filters and plugins before indexing.
Visualize logs with powerful search, dashboard creation, and machine learning anomaly detection.
Lightweight log shipper for forwarding logs from servers and containers to Logstash or Elasticsearch.
Track requests across microservices with distributed tracing. Visualize latency bottlenecks and dependencies with Jaeger and OpenTelemetry.
See complete request path across microservices with timing for each hop. Identify bottlenecks and slow database queries visually.
Automatic service dependency graph showing which services call which. Understand system architecture and identify circular dependencies.
When errors occur, traces show exact service and line of code that failed. Correlate with logs and metrics for complete context.
Identify slow spans within traces. Compare latency percentiles (p50, p95, p99) across services and time periods for optimization.
Smart alerting with Prometheus Alertmanager, PagerDuty integration, escalation policies, and alert grouping to reduce noise.
High CPU/memory usage, disk space low, node down, network issues
High error rates, increased latency, failed deployments, memory leaks
Drop in revenue, decreased signups, payment failures, unusual traffic patterns
Failed login attempts, unusual access patterns, certificate expiry, vulnerability detected
Service down, health check failures, DNS issues, SSL certificate problems
Cloud spending threshold exceeded, unused resources detected, budget forecast overrun
Pre-built and custom Grafana dashboards for complete infrastructure visibility with real-time metrics and historical trends.
K8s cluster health, node status, pod count
Request rate, latency, error rate, throughput
Query performance, connections, slow queries
CPU, memory, disk, network across all nodes
Cloud spending by service and resource type
Revenue, signups, active users, conversions
Mean time to detect (MTTD) reduced from hours to minutes. Mean time to resolve (MTTR) reduced by 60% with correlated metrics, logs, and traces.
Catch issues before users notice. Anomaly detection and predictive alerting prevent outages and performance degradation.
Historical metrics inform infrastructure scaling decisions. Predict future resource needs based on growth trends and usage patterns.
Identify over-provisioned resources and idle instances. Right-size infrastructure based on actual usage metrics to reduce cloud costs.
Developers debug production issues faster with distributed tracing. Reduce context switching with unified observability platform.
Centralized logging provides audit trail for compliance (SOC2, HIPAA, GDPR). Security events tracked and alerted in real-time.
Let's implement a comprehensive monitoring and observability stack for your infrastructure.
IMPLEMENT OBSERVABILITY