CCsolutions.io
Platform Engineering

Observability & Monitoring: Knowing What's Happening in Your System

A dashboard that nobody looks at is overhead. Alerts that fire too often are ignored. Observability that works is the foundation for reliable operations.

RED
Alerts
Rate, Errors, Duration, alerts that measure real user impact
< 30s
Log Search
Loki enables second-level queries across all container logs
SLO
Dashboards
Service-Level Objectives as the central monitoring foundation
Auto
Onboarding
New services automatically start with complete monitoring

Observability is not the same as monitoring. Monitoring tells you when something is broken. Observability lets you understand why something is broken. without having to poke around in the system. The difference is measurable: teams with good observability have significantly lower Mean Time to Resolution (MTTR).

The most common challenges

1

Customers discover problems before the monitoring system alerts

When customer reports are the first sign of a production issue, the monitoring is too reactive. Good alerting is based on Service-Level Objectives (SLOs), not binary up/down checks.

2

Log searches take minutes, not seconds

When investigating an incident and searching through logs is a manual, time-consuming task, every incident is unnecessarily prolonged. Centralized log management with fast queries is not a comfort feature, it's a fundamental operational tool.

3

New services get deployed without monitoring

When setting up monitoring for each new service is a manual task, it gets postponed. The result: critical services run blind. Template-based monitoring solves this structurally.

The CCsolutions approach

CCsolutions implements the Prometheus/Grafana/Loki stack as a standardized observability layer: Prometheus scrapes metrics from all Kubernetes workloads, Loki aggregates logs from all containers, and Tempo captures distributed traces. Grafana visualizes everything in configured dashboards.

Alerts are configured using the RED model (Rate, Errors, Duration) and SLO principles: not 'CPU > 80%', but 'Error Rate > 1% over 5 minutes'. Alerts have defined severity levels, runbooks, and escalation paths. Alert fatigue is prevented through careful threshold definition.

Monitoring is template-based: every new service template automatically includes metric endpoints, dashboard configuration, and baseline alerting rules. No service goes live without observability, it's not optional, it's architecture.

Technologies

Prometheus Grafana Loki Tempo (Distributed Tracing) Alertmanager PagerDuty / OpsGenie OpenTelemetry Mimir (Long-term Metrics)

Frequently asked questions

What's the difference between observability and monitoring?

Monitoring tells you if a system is 'up' or 'down'. Observability lets you understand the internal state of a system from the outside, through metrics, logs, and traces. An observable system can be understood without adding additional debug code.

Do we really need Prometheus, Grafana, Loki, and Tempo? Isn't CloudWatch enough?

CloudWatch is tied to AWS and has significant costs at high log volumes. The open-source stack (Prometheus/Grafana/Loki) is cloud-agnostic, cheaper at scale, and offers better Kubernetes integration. Anyone operating across multiple clouds or on-premises needs the independent stack.

How is alert fatigue prevented?

Through two principles: first, alerts only for things requiring human intervention, not symptoms that self-remediate. Second, SLO-based alerts (end-user impact) rather than resource metrics. A server at 85% CPU is not an alert, an elevated error rate is.

Ready to get started?

We analyse your situation for free and show what is possible in your specific case.

Request Observability Assessment