~/services/observability
user@techtronyx:~$ tail -f /var/log/prod/slo.json | jq '.burn_rate'
0.12
[ OK ] 04 of 06 services loaded

04  ·  observability

Monitoring
that matters.

Alerts that wake you up should be the ones worth waking up for. We build observability stacks rooted in SLOs, real user experience, and zero-noise alerting — across metrics, logs, and traces.

get a quote all services

what's included

Signal, not
noise.

Most dashboards are art projects. Ours are operations tools — built around the questions you'll actually ask at 3am.

// 01
Metrics & Dashboards
Golden-signal and RED dashboards per service, plus exec-level health views. Written in code, versioned in git, reviewable like any other PR.
// 02
Structured Logging
Centralised log pipelines with structured fields, PII scrubbing, retention policies, and indexed search — in Loki, Elastic, or whatever your stack runs.
// 03
Distributed Tracing
OpenTelemetry instrumentation across services. Find the 3-hop latency spike in seconds instead of spelunking through logs for an afternoon.
// 04
SLOs & Error Budgets
Every user-facing service gets an SLO, a burn-rate alert, and a budget you can spend on velocity when it's healthy.
// 05
Alert Routing
PagerDuty / Opsgenie / Slack routing configured per severity. Noisy alerts get rewritten or deleted — we never add one that doesn't require a human.
// 06
Synthetic & RUM
Synthetic probes from real regions plus Real User Monitoring for web/mobile. So you catch customer-visible issues before the customer complains.

slo-driven

Alerts you
can actually trust.

Pages based on multi-window, multi-burn-rate error-budget alerts — the Google SRE gold standard. If the pager fires, it matters.

  • Alert-as-code, reviewed and versioned alongside services
  • Auto-generated runbook links in every page
  • Severity-appropriate routing: P1 pages, P2 tickets, P3 Slack
  • Silencing and maintenance windows via self-service
  • Post-incident alert-tuning built into every retro
alertmanager — bash — 80×24
sre@obs-01:~$ txnx alerts status --service checkout
  » slo: availability 99.95%
  [ OK ] 30d actual: 99.97%
  » burn-rate (1h / 6h)
  [ OK ] 0.6x / 0.4x — within budget
  » checking firing alerts ...
  [ WARN ] p2 cert-renewal-approaching
  » routed → #platform, ticket PLAT-8412
 
  [ DONE ] 0 pages in last 7d

how we do it

From alert-fatigue
to actionable signal.

Most teams have too much monitoring and too little observability. We invert that — fewer, better signals, wired to the things that actually hurt your users.

  1. [step 1]
    Signal Audit
    We catalogue every dashboard, alert, and log pipeline. The ones that haven't fired in a year or have a 40% false-positive rate are flagged.
  2. [step 2]
    SLO Definition
    We workshop SLOs per user-facing service with product + engineering — availability, latency, and correctness targets that match actual customer expectations.
  3. [step 3]
    Instrumentation
    OpenTelemetry SDKs, structured logging, and standard dashboards rolled out service by service. No big-bang re-instrumentation.
  4. [step 4]
    Alert Re-wire
    Old alerts deleted or converted to burn-rate alerts. On-call load typically drops 60–80% in the first month — then we tune further.
  5. [step 5]
    Ongoing Hygiene
    Monthly alert reviews, quarterly SLO reviews. Stale dashboards archived, new signals added as the product evolves.

toolchain

Observability stack.

We're comfortable on the whole spectrum — fully self-hosted Prometheus / Grafana / Loki / Tempo, or fully SaaS on Datadog, New Relic, or Honeycomb.

metricsPrometheus
metricsDatadog
vizGrafana
vizNew Relic
logsLoki
logsElastic / OpenSearch
tracesTempo / Jaeger
tracesHoneycomb
instrumentOpenTelemetry
alertingAlertmanager
incidentPagerDuty
incidentOpsgenie

faq

Observability, answered.

contact

Tired of 3am pages?

Book a free 30-minute observability review. We'll look at your current alerts + dashboards and tell you which 80% can be deleted.

get a quote email us
privacy · terms