In distributed systems, failure is not a possibility but a certainty. Networks partition, services crash, databases slow down, and dependencies become unavailable. The difference between a system that gracefully handles failures and one that cascades into outages lies in observability. At Nexis Limited, we embed observability into every system we build, from Ultimate HRM to custom enterprise platforms for clients across Bangladesh.
Monitoring vs. Observability
Monitoring tells you when something is wrong. Observability tells you why. Traditional monitoring checks predefined conditions: is CPU above 90%, is disk space running low, is the service responding to health checks. Observability provides the tools and data to investigate novel failures that you did not anticipate when designing your monitoring. A truly observable system lets an engineer ask arbitrary questions about system behavior using metrics, logs, and traces without deploying new code.
The Three Pillars: Metrics, Logs, and Traces
Metrics are numerical measurements collected at regular intervals. They are the most efficient observability signal for detecting anomalies and triggering alerts. Prometheus has become the standard for metrics collection in cloud-native environments. Its pull-based model, powerful query language (PromQL), and extensive ecosystem of exporters make it suitable for everything from a single server to multi-cluster Kubernetes deployments.
Logs provide detailed records of discrete events. Structured JSON logs with consistent fields like timestamp, service name, request ID, and severity level are essential for effective log analysis. Centralize logs using Loki, Elasticsearch, or CloudWatch Logs. Always include correlation IDs that link logs across services for a single request.
Distributed Tracing
Distributed tracing follows a request as it traverses multiple services, capturing timing and metadata at each hop. Jaeger and Tempo are popular open-source tracing backends. OpenTelemetry provides vendor-neutral instrumentation libraries for all major languages. Tracing is invaluable for identifying latency bottlenecks in microservice architectures. When a user reports slow page loads, a single trace shows you exactly which service call is responsible.
Grafana: Unified Observability Dashboard
Grafana serves as the visualization layer that ties all observability data together. Configure data sources for Prometheus metrics, Loki logs, and Tempo traces. Build dashboards that show the golden signals for each service: request rate, error rate, latency distribution, and resource saturation. Use Grafana's Explore view for ad-hoc investigation during incidents. Template variables allow a single dashboard to serve multiple services and environments.
Alerting Strategy: Signal vs. Noise
Poorly configured alerts are worse than no alerts. Alert fatigue from noisy, low-impact notifications trains teams to ignore alerts entirely. Follow these principles: alert on symptoms that affect users, not on individual infrastructure metrics. Set thresholds based on SLOs (Service Level Objectives) rather than arbitrary values. Use multi-window, multi-burn-rate alerting for SLO-based alerts to catch both sudden failures and slow degradation.
Route alerts based on severity and ownership. Critical alerts that indicate user-facing impact should page the on-call engineer via PagerDuty or Opsgenie. Warning alerts should create tickets for investigation during business hours. Informational alerts should go to Slack channels for awareness without interruption.
Service Level Objectives and Error Budgets
SLOs define the target reliability for a service in terms that matter to users: 99.9% of requests complete within 500ms, or 99.95% of requests return successful responses. Error budgets are the inverse: a 99.9% availability target allows approximately 43 minutes of downtime per month. When error budgets are healthy, teams can move fast and ship features. When error budgets are depleted, teams shift focus to reliability improvements. This framework aligns business priorities with engineering efforts.
Building observable systems is an ongoing practice, not a one-time project. Nexis Limited helps teams implement comprehensive observability stacks and establish incident response processes. Explore our services or contact us to improve your system reliability.