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Monitoring & Observability

See Everything.
Know Before
Users Do.

We build full-stack observability — metrics, logs, traces, and alerts — so your team has complete visibility into your system at all times and gets notified of issues before they become outages.

<1min
Alert response time
From incident to notification
99.9%
Uptime visibility
Always-on dashboards
100%
Services covered
App, infra, database, network
0
Surprise outages
Proactive alerting
What You Get

Real-Time Visibility
Across Your Entire Stack

From infrastructure CPU to application error rates — every metric, every log, every trace in one place.

Production Dashboard — Grafana
Live
99.97%
Uptime (30d)
142ms
P95 Latency
0.02%
Error Rate
CPU Usage — last 1h
Memory Usage
Requests/sec
Active Alerts
api-pod — healthy3/3 pods
rds-primary — healthylag: 0ms
memory >70% — warningworker-2
📊 Metrics — Prometheus + Grafana
Time-series metrics from every pod, node, and service. Custom Grafana dashboards per team — infra, application, business KPIs.
📋 Logs — Loki / ELK Stack
Centralised log aggregation from all services. Full-text search, log correlation, and structured JSON log parsing. Retention policies per log level.
🔍 Traces — Jaeger / Tempo
Distributed tracing across microservices. See exactly where latency lives and which service in a chain is causing slow responses.
🔔 Alerts — AlertManager + PagerDuty
Multi-channel alerting — Slack, email, PagerDuty, OpsGenie. Alert routing by severity, silence rules, and deduplication to prevent alert fatigue.
⏱️ Uptime — Blackbox Exporter
External synthetic monitoring for every public endpoint. HTTP, HTTPS, TCP, DNS checks with SLA reporting and downtime history.
The Stack

Monitoring Tools
We Deploy

The three pillars of observability — metrics, logs, and traces — covered with best-in-class open-source tools.

🔥

Prometheus

Time-series metrics collection from all pods, nodes, and services via exporters. Custom recording rules, long-term retention, and federation for multi-cluster setups.

PrometheusNode Exporterkube-state-metricsCustom Exporters
📈

Grafana

Beautiful, interactive dashboards for every team. Pre-built dashboards for Kubernetes, AWS, PostgreSQL, Node.js, and custom business metrics. Role-based access control.

GrafanaDashboard LibraryRBACAlerting
🪵

Loki

Lightweight log aggregation built for Kubernetes. Promtail agent ships logs from every pod. LogQL queries for powerful log analysis — without the Elasticsearch cost.

LokiPromtailLogQLS3 storage backend
🔎

ELK Stack

For teams needing full-text search across massive log volumes — Elasticsearch, Logstash, and Kibana with Filebeat agents. Index lifecycle management for cost control.

ElasticsearchLogstashKibanaFilebeat
🗺️

Distributed Tracing

OpenTelemetry instrumentation for your services. Jaeger or Grafana Tempo for trace storage and visualisation. Trace correlation with logs and metrics.

OpenTelemetryJaegerGrafana TempoTrace correlation
🚨

AlertManager

Intelligent alert routing — critical alerts go to PagerDuty, warnings to Slack, info to email. Grouping, inhibition, and silencing rules to eliminate alert noise.

AlertManagerPagerDutyOpsGenieSlack Webhooks
SLA Dashboards

Track SLIs, SLOs &
Error Budgets

We implement Google SRE-style reliability tracking — Service Level Indicators, Objectives, and Error Budgets — so you always know exactly how reliable your service is.

SLI
Service Level Indicator
The actual measured metric — request success rate, latency percentile, or error count.
SLO
Service Level Objective
Your target — e.g. 99.9% of requests succeed within 200ms over a 30-day window.
Budget
Error Budget
Remaining tolerance before your SLO is breached. Drives deployment pace and reliability investment decisions.
FAQ

Monitoring Questions

Loki vs ELK Stack — which should we use?
+
Loki is the right choice for most Kubernetes-native teams — it's lightweight, cost-efficient (stores only indexes, not log content), and integrates perfectly with Prometheus and Grafana. ELK Stack is better when you need full-text search across very high log volumes, complex log parsing, or an existing Elasticsearch investment. We recommend based on your log volume and budget.
How long does a full monitoring stack setup take?
+
A Prometheus + Grafana + Loki stack on Kubernetes takes 3–5 days including custom dashboards for your application. A full ELK stack with custom pipelines and SLO dashboards takes 7–10 days.
Will you set up alerts for us or just the tooling?
+
Both. We configure the tooling AND define your initial alert rules based on your SLOs — CPU/memory thresholds, error rate spikes, latency breaches, pod restarts, and disk usage. We tune thresholds to eliminate false-positive alert fatigue before handoff.
Can you add monitoring to our existing Kubernetes cluster?
+
Yes. We deploy the kube-prometheus-stack Helm chart into your existing cluster, instrument your applications with exporters, and have dashboards live within 2–3 days without touching your running workloads.
Get Visibility

Ready to See Everything
in Your Infrastructure?

Book a free monitoring audit. We'll review your current observability gaps and design your full stack on the call.

Book Free Monitoring Audit