Observability: Metrics, Logs & Traces

How it works

Three signals, one story

Metrics show the shape of the system: latency, error rates, saturation. Logs record structured events with context. Traces follow a single request across every service, showing where time is spent and where errors start. Linked by a shared trace ID, they let you move from an alert to the exact failing call in minutes.

Instrument once with OpenTelemetry

OpenTelemetry is the open standard for producing telemetry, and all three clouds accept it. Instrument code once and send data to any backend, or several, without rewriting the application. Alerts should fire on user-facing symptoms such as error rate and latency, and each should link to a runbook.

AWS, Azure and Google Cloud compared

What makes each cloud different

Design decisions that matter

1. 01Standardize on OpenTelemetry

   One instrumentation approach for every service and language.

2. 02Propagate one trace ID everywhere

   Including queues, functions and AI calls.

3. 03Alert on symptoms

   Page on user-facing error rate and latency, not on CPU.

4. 04Define SLOs for key journeys

   Use error budgets to balance speed and reliability.

5. 05Control log costs

   Sample, filter and tier logs by value.

Common mistakes we see

• Dashboards nobody watches. Build alerts and SLOs, not wall displays.
• Logging everything at debug. Costs explode while signal drowns in noise.
• Alerts without runbooks. On-call engineers lose time working out what to do.
• Separate tools per team. Incidents cross teams; telemetry must too.

A practical 30-day plan

1. Week 1

   Pick the top five user journeys and define SLOs.

2. Week 2

   Add OpenTelemetry to the services on those journeys.

3. Week 3

   Create symptom-based alerts with linked runbooks.

4. Week 4

   Tune log retention and sampling to cut cost.

How NTS helps

NTS designs observability platforms across AWS, Azure and Google Cloud: OpenTelemetry rollout, SLOs and alerting, log cost optimization and AI-assisted incident response. We help teams cut mean time to recovery and the size of their monitoring bill at the same time.

How we work with you

1. 1Assess

   A focused review of your observability across AWS, Azure and Google Cloud. We look for the gaps we find most often: dashboards nobody watches, logging everything at debug, alerts without runbooks and separate tools per team.

2. 2Design

   A target architecture and roadmap built on the decisions that matter most: standardize on OpenTelemetry, propagate one trace ID everywhere, alert on symptoms, define SLOs for key journeys and control log costs.

3. 3Build

   Hands-on delivery alongside your team. We pick the top five user journeys and define SLOs, add OpenTelemetry to the services on those journeys, create symptom-based alerts with linked runbooks, and finally tune log retention and sampling to cut cost.

4. 4Run and improve

   We review SLOs, alert quality and telemetry costs regularly, and extend coverage as new services launch.

Why teams choose NTS for observability

• Signals that matter

  We start with user journeys and SLOs, so alerts mean something when they fire.

• Open standards

  OpenTelemetry keeps your telemetry portable across clouds and tools.

• Cost-aware telemetry

  We sample, tier and retain data deliberately, so observability does not become your biggest bill.