Engineering Reliability Into Your Platform

SRE is not a job title — it's an engineering discipline. We implement SLOs, observability, and incident response practices that turn reliability from guesswork into measurement.

Duration: 4-10 weeks Team: 1 SRE Lead + 1 Observability Engineer
The Challenge

You might be experiencing...

You have no SLOs — you don't know what 'reliable enough' means for your platform, and neither do your customers.
Your monitoring is alert-heavy and signal-light — 200 Slack alerts per day, most of which are noise, some of which are P1 incidents waiting to happen.
Incidents take 3-4 hours to resolve because nobody knows whose job it is and there's no runbook.
Your on-call rotation is burning out your most senior engineers — every night something wakes someone up.

Site reliability engineering closes the gap between developing software and operating it reliably. The practices SRE teams use — SLO definition, error budgets, observability, blameless post-mortems — turn reliability from a vague aspiration into a measurable engineering outcome.

Contact us to book a free reliability assessment — we’ll review your current monitoring, incident history, and SLO maturity in a 30-minute call.

Our Approach

Engagement Phases

Week 1-2

Reliability Assessment

Measure current reliability: uptime, error rates, latency, and incident history. Identify the top three reliability risks. Define SLI candidates and initial SLO targets with your product and engineering stakeholders.

Weeks 3-6

Observability Stack

Implement metrics (Prometheus), logging (Loki or OpenSearch), tracing (Jaeger or Tempo), and dashboards (Grafana). Instrument key services with OpenTelemetry. Configure alert routing with actionable, low-noise alerts.

Weeks 7-8

SLO & Error Budget Implementation

Define SLOs for critical user journeys. Implement error budget burn rate alerts (the SRE golden signal for 'stop feature work'). Configure SLO dashboards for engineering and product teams.

Weeks 9-10

Incident Response Design

Design on-call rotation, severity levels, and escalation paths. Write runbooks for top 10 incident types. Implement post-mortem process. Train on-call engineers on incident command.

What You Get

Deliverables

Reliability assessment report with top risk areas
SLI/SLO definitions for critical user journeys
Observability stack (Prometheus, Grafana, OpenTelemetry)
Error budget burn rate alerting
On-call rotation design and tooling (PagerDuty or equivalent)
Incident runbooks (top 10 scenarios)
Post-mortem template and process
Expected Outcomes

Before & After

MetricBeforeAfter
Mean Time to Detect (MTTD)15-45 minutes — customers notice before monitoring does< 2 minutes — proactive alerting before user impact
Mean Time to Resolve (MTTR)3-6 hours — no runbooks, unclear ownership< 30 minutes — runbooks, clear escalation, practiced response
Alert Noise200+ alerts/day — on-call engineers ignore most of them< 10 actionable alerts/day — every alert requires action
Technology

Tools We Use

Prometheus + Grafana OpenTelemetry Loki / OpenSearch Jaeger / Tempo PagerDuty / OpsGenie
Common Questions

Frequently Asked Questions

What is an SLO and why do we need one?

A Service Level Objective (SLO) is a target reliability level for a specific user-facing behaviour — for example, '99.9% of checkout requests complete in under 2 seconds'. SLOs define what 'good enough' looks like for your platform. Without SLOs, reliability is opinion — every incident is either 'fine' or 'catastrophic' depending on who you ask. With SLOs, reliability is measurement — you know exactly how much error budget you have and when feature work should pause for reliability investment.

Do we need a dedicated SRE team?

Not initially. For most UAE engineering teams, the first step is implementing SLO thinking and basic observability within the existing team. A dedicated SRE function makes sense when you have 20+ engineers and reliability is a continuous bottleneck. We help you implement SRE practices at the right scale for your team — not over-engineer for a problem you don't have yet.

What observability stack do you recommend?

For Kubernetes-based platforms, we default to Prometheus + Grafana + Loki + Tempo (the LGTM stack) — open source, widely adopted, and deeply integrated with the Kubernetes ecosystem. For teams wanting managed services, we recommend Grafana Cloud or Datadog. We avoid vendor lock-in where possible but prioritise what your team will actually maintain.

Get Started for Free

Schedule a free consultation. 30-minute call, actionable results in days.

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