Observability Stack
Full visibility into your systems — metrics, logs, traces, profiling, and synthetic monitoring. Alert the right person at the right time. Reduce MTTR from hours to minutes.
Six pillars of observability
We cover the full spectrum — not just metrics and logs.
Metrics
Time-series metrics from every layer: infra, app, and business. RED method per service. SLO/SLI dashboards. Long-term storage with Thanos, Mimir, or VictoriaMetrics.
Logs
Centralized log aggregation from all services, pods, and infra. Structured JSON logging. Correlated with metrics — click a spike, see the logs for that exact window.
Traces
Distributed tracing across every microservice call. Identify exact latency bottlenecks, slow DB queries, and N+1 API calls. Instrument once, trace everywhere.
Alerting & On-call
SLO-based alerting — alert on burn rate, not raw metrics. No alert storms. Right person, right time, with runbook attached and auto-escalation.
Profiling & APM
Continuous profiling for CPU, memory, goroutines, and heap. Identify hotspots in production without reproducing in dev. Application performance baselines.
Synthetic & RUM
Synthetic monitoring: probe endpoints every minute globally. Real User Monitoring: track Core Web Vitals, JS errors, and user sessions from real traffic.
Full tool coverage
We work with every major observability tool — open-source and commercial.
Metrics & Visualization
Logs
Distributed Tracing
Alerting & On-call
Profiling
Synthetic & RUM
Exporters & Agents
Instrumentation
Long-term Storage
What you get
| Aspect | Self-hosted (Grafana Stack) | SaaS (Datadog / New Relic) |
|---|---|---|
| Cost | ~$200–500/mo (infra only) | $2,000–20,000+/mo at scale |
| Setup time | 1–2 weeks | Hours to days |
| Data ownership | Full — stays in your infra | Data leaves your infra |
| Customization | Unlimited | Limited to platform features |
| Ops overhead | Requires DevOps to maintain | Zero — fully managed |
| Vendor lock-in | None (open standards) | High |
| Best for | Teams with DevOps capacity | Teams wanting zero ops overhead |
Questions
Self-hosted (Grafana/Prometheus) vs SaaS (Datadog/New Relic)?
Self-hosted is 80–90% cheaper at scale and gives full data control — ideal for teams with DevOps capacity. Datadog/New Relic are faster to start, better for teams that want zero ops overhead. We implement both and help you choose based on your scale, budget, and team size.
What's the difference between metrics, logs, and traces?
Metrics tell you something is wrong (latency up 3x). Logs tell you what happened (which request, which error). Traces tell you where the time was spent across services. You need all three for fast incident resolution — each answers a different question.
How do you avoid alert fatigue?
We use SLO-based alerting: alert on error budget burn rate, not individual thresholds. A 5xx spike that burns 1% of your monthly budget in 5 minutes pages. A transient spike that resolves in 30 seconds doesn't. This cuts alert volume by 70–90% while catching real incidents faster.
What is OpenTelemetry and should we use it?
OpenTelemetry (OTel) is the open standard for instrumentation — one SDK that emits metrics, logs, and traces. We recommend it for all new instrumentation: it's vendor-neutral, meaning you can switch from Jaeger to Tempo to Datadog without changing app code.
Datadog is expensive — can you reduce our bill?
Yes. Common fixes: drop high-cardinality metrics before ingestion, use log exclusion filters on noisy low-value logs, move old traces to cheap storage, and switch infrastructure metrics to Prometheus + Grafana Cloud (much cheaper). We've cut Datadog bills by 40–60%.
Can you set up Sentry for error tracking?
Yes. Sentry for frontend/backend error tracking integrates well with the rest of the stack. We connect Sentry alerts to PagerDuty and link Sentry issues to Grafana traces for full context during debugging.
What about GPU / ML workload monitoring?
Yes. We set up DCGM exporter (NVIDIA Data Center GPU Manager) for GPU utilization, memory, temperature, and power metrics — displayed in Grafana alongside your application metrics.
Can you set up on-call rotations?
Yes. PagerDuty or OpsGenie schedule setup, escalation policies, alert routing, and runbook creation. We also tune alert thresholds so the on-call engineer gets actionable pages, not noise.
Stop flying blind
Book a call. We'll assess your current visibility gaps and recommend the right stack for your team size, budget, and infra.
Book Discovery Call