Site Reliability Engineering Services

What site reliability engineering is

Site reliability engineering (SRE) applies software engineering to operations. Instead of hoping systems stay up, SRE sets explicit reliability targets, measures them continuously, automates repetitive operational work and learns systematically from incidents.

For growing products, SRE practices bring reliability under control without slowing feature development — because the team agrees in advance how much risk is acceptable and spends its effort where it matters most.

Problems we solve

• Outages discovered by customers on social media
• Alert fatigue: hundreds of alerts, few of them useful
• Incidents handled differently each time, with no follow-up
• Performance degrading slowly as usage grows
• Debate between “ship faster” and “be more stable” with no shared data

What’s included

Service level objectives in practice

An SLO might say “99.9% of checkout requests succeed within 500 milliseconds over 28 days”. That target leaves an error budget — roughly 40 minutes of failures per month. If the budget is healthy, the team can ship riskier changes; if it is nearly spent, they focus on reliability. This turns an emotional debate into a data-driven decision both product and engineering accept.

Learning from incidents

Every significant incident is followed by a blameless review: a timeline, what made detection or recovery slow, and a short list of improvements with owners. Over time, these reviews remove whole classes of failure and make the system — and the team — more resilient.

Error budgets: balancing speed and stability

An SLO of 99.9% availability allows roughly 43 minutes of downtime in a 30-day month. That allowance is the error budget. When the service is well within budget, teams can ship faster and take more risk; when the budget is nearly spent, the focus shifts to reliability work. This turns arguments between “move fast” and “keep it stable” into a shared, data-driven decision.

On-call that people can sustain

• Alerts only for symptoms users feel, each with a linked runbook
• Rotations large enough that nobody is on call too often
• Clear escalation paths and severity levels
• Review of every page: was it actionable, and how can it be prevented?
• Time after heavy on-call shifts to recover and fix root causes

Reducing toil

Toil is repetitive, manual operational work that scales with the size of the service: restarting stuck jobs, rotating certificates by hand, resizing disks. We measure it, then automate the most frequent tasks so engineers spend their time on improvements rather than firefighting.

How an SRE engagement works

1. Reliability review2–3 weeks

   Map critical user journeys, dependencies, monitoring gaps and recent incidents.

2. Define SLIs and SLOs1–2 weeks

   Agree measurable indicators and targets with product and engineering owners.

3. Instrument and alert2–4 weeks

   Add the metrics, traces and dashboards needed; replace noisy alerts with symptom-based ones.

4. HardenOngoing

   Fix the top reliability risks: timeouts, retries, capacity limits, single points of failure.

5. Embed the practiceOngoing

   Error budget reviews, incident reviews and on-call improvements become part of normal work.

Durations are typical; we adjust them to the number of services and the maturity of existing monitoring.

Choosing service level indicators

Good indicators measure what users experience, not internal details such as CPU usage. CPU tells you why something might fail; an SLI tells you whether users are affected.

Capacity planning and load testing

Many outages happen during the moments that matter most: a product launch, a marketing campaign or a seasonal peak. We plan for them deliberately.

• Estimate expected peak traffic from business plans and past events
• Load test critical journeys to find the first bottleneck, not just to confirm the system survives
• Check limits beyond the application: database connections, third-party API rate limits, cloud quotas
• Configure autoscaling with sensible minimums so capacity is ready before the spike
• Prepare a launch-day runbook with clear owners and rollback decisions

Reliability and delivery speed together

Reliability work is sometimes seen as slowing teams down. In practice the opposite is usually true: good monitoring shortens debugging, automated rollbacks make deployments less risky and clear SLOs remove arguments about whether a release is “safe enough”. The error budget turns those conversations into data — when reliability is healthy, teams ship freely; when it is not, they focus on stability until it recovers.

Metrics we report monthly

• SLO attainment and error budget remaining for each critical service
• Number and severity of incidents, and time to detect and resolve them
• Alerts per on-call shift and the share that required action
• Progress on reliability improvements from incident reviews
• Toil hours identified and automated

These numbers show whether reliability is improving over time. SRE often works alongside DevOps consulting and Kubernetes consulting.

Dependencies and graceful degradation

Modern products rely on payment providers, email services, identity providers and internal APIs. Any of them can be slow or unavailable. We map these dependencies and design how each user journey behaves when one fails: timeouts that fail fast, retries with backoff and limits, circuit breakers that stop hammering a struggling service, and fallbacks such as cached data or queued work so users can continue with reduced functionality rather than seeing an error page.

• Timeouts on every outbound call
• Retries limited and spread out with jitter
• Circuit breakers on critical dependencies
• Clear user messaging when features are temporarily degraded

Getting started with a small team

SRE does not require a dedicated team. Many organisations begin with one or two engineers spending part of their time on reliability: defining SLOs for the most important journey, cleaning up alerts and running blameless reviews after incidents. Those habits deliver much of the value; dedicated SRE roles become worthwhile as the number of services and users grows.

Runbooks that help at 3 a.m.

A good runbook is short, linked directly from the alert and written for someone tired and under pressure. It explains what the alert means for users, the first checks to make, safe mitigation steps and when to escalate. We review runbooks after every incident so they stay accurate.

Each runbook names an owner and the date it was last checked, so stale instructions are easy to spot.

Related services

SRE builds on DevOps, Kubernetes and performance testing.

This page is part of Cloud & DevOps Services — see the full overview for related services, approach and pricing.