I'm building a SaaS app on Kubernetes and need observability for app metrics logs and tracing, what stack makes sense?

A solid, practical observability stack for a SaaS app on Kubernetes usually looks like this:

Recommended default stack

1. Metrics

• Prometheus for scraping and alerting
• Grafana for dashboards
• Alertmanager for routing alerts

Why:

• Kubernetes-native
• Huge ecosystem
• Easy to instrument apps with OpenTelemetry or Prometheus client libs

2. Logs

• Loki for log aggregation
• Promtail or Grafana Alloy as the log collector/agent
• Grafana for viewing logs alongside metrics

Why:

• Cheaper and simpler than running full Elasticsearch for many teams
• Good enough for most app/container logs
• Integrates well with Kubernetes labels

3. Traces

• OpenTelemetry instrumentation in your app
• OpenTelemetry Collector or Grafana Alloy as the pipeline/agent
• Tempo for trace storage and querying
• Grafana to correlate traces with metrics/logs

Why:

• OpenTelemetry is the standard for vendor-neutral instrumentation
• Tempo is lightweight compared with Jaeger/Elasticsearch-based trace storage

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Best “modern” combo

If you want one coherent stack that works well together:

OpenTelemetry + Prometheus + Loki + Tempo + Grafana

This is a very common choice because:

• OpenTelemetry handles app instrumentation for metrics/logs/traces
• Grafana gives one UI
• Prometheus/Loki/Tempo each focus on one signal
• Works well on Kubernetes

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If you want managed instead of self-hosted

If you’d rather avoid operating all of that yourself:

• Grafana Cloud: managed Prometheus, Loki, Tempo, dashboards
• Datadog: excellent all-in-one SaaS, usually fastest time to value, but pricier
• New Relic: also strong all-in-one option
• Honeycomb: especially strong for tracing and high-cardinality analysis

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What I’d choose by company stage

Early-stage startup / small platform team

• Grafana Cloud + OpenTelemetry
• Use managed metrics/logs/traces so your team focuses on product

Growing SaaS with platform ownership

• Self-host or hybrid
• Prometheus + Loki + Tempo + Grafana
• OpenTelemetry Collector and/or Grafana Alloy
• Consider managed object storage for logs/traces backends if supported

Enterprise / strict compliance

• Often self-hosted stack or a vendor like Datadog with compliance controls
• Add long-term retention and audit requirements early

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Key design choice: instrumentation standard

Use OpenTelemetry everywhere if possible:

• metrics
• traces
• log correlation

That gives you:

• consistent context propagation
• easier vendor switching
• better trace-log correlation via trace/span IDs

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Kubernetes-specific notes

• Use DaemonSet collectors for node-level log/telemetry collection if needed
• Expose app metrics on /metrics
• Use service discovery for Prometheus
• Add Kubernetes labels/annotations carefully for filtering
• Make sure you set up:
  • request IDs / trace IDs in logs
  • RED metrics for services:
    • Rate
    • Errors
    • Duration

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Minimal production-ready starting point

If you want the shortest path to “good observability”:

1. Instrument app with OpenTelemetry
2. Deploy Grafana
3. Deploy Prometheus
4. Deploy Loki
5. Deploy Tempo
6. Use OpenTelemetry Collector or Grafana Alloy
7. Set up alerting for SLIs/SLOs

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My practical recommendation

If you’re building a SaaS on Kubernetes and want a sensible balance of power, cost, and operational complexity:

Best default:

OpenTelemetry + Grafana + Prometheus + Loki + Tempo

Best low-ops version:

Grafana Cloud + OpenTelemetry

Best all-in-one paid alternative:

Datadog

If you want, I can also give you:

• a reference architecture diagram
• a Helm chart-based setup
• or a “choose between Grafana Cloud vs Datadog vs self-hosted” comparison based on your team size and budget.