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DevOps and IT Infrastructure

Ship faster, with fewer surprises. Measured against DORA, not opinion.

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Overview

DevOps is a measurement problem first, a tooling problem second.

The annual DORA / State of DevOps research has tracked the same four delivery metrics for over a decade, and the gap between "elite" and "low" performers keeps widening. Elite teams deploy 973× more frequently than low performers, with lead times under an hour and change-failure rates below 5%. The good news: every team we've worked with already has the data to know which quartile they're in. They just haven't measured.

We engage by baselining deploy frequency, lead time, change-fail rate, and MTTR for your real workloads, finding the bottlenecks (almost always testing, environments, or approvals), and removing them with infrastructure-as-code, trunk-based development, automated testing, and continuous delivery. Where it makes sense, we build the internal developer platform (IDP) that turns those capabilities into a self-service product for your engineers.

The result isn't a faster pipeline — it's a smaller blast radius on every change, a calmer on-call rotation, and a delivery cadence the business can actually count on.

Engagement at a glance

  • DORA baseline in week one
  • 100% IaC, GitOps where it fits
  • SLOs & error budgets that drive decisions
  • Platform engineering — Backstage / TBP-style

973×

Elite vs. low deploy frequency (DORA)

<1 hr

Commit-to-prod lead time at elite teams

<5%

Change-fail rate at elite teams

4 keys

Every engagement, measured

What we deliver

Delivery, infrastructure, and operations — as one practice

CI/CD

Trunk-based development, automated testing gates, blue/green and canary deploys, progressive delivery with feature flags, one-click rollback. Friday deploys, normalized.

Infrastructure-as-Code

Terraform, Pulumi, Crossplane. Modules, policy-as-code (OPA / Sentinel), and the review process that makes "click here in the console" a relic.

Kubernetes Platforms

EKS / AKS / GKE clusters, multi-tenant namespacing, network policies, service mesh (Istio / Linkerd) only where it earns its keep, GitOps via Argo or Flux.

Observability & SRE

OpenTelemetry across logs / metrics / traces, SLOs with error budgets, on-call rotations that don't burn the team out, post-incident reviews that change things.

Release Engineering

Versioning strategy, branching model, environment promotion, dependency management, supply-chain security (SLSA, SBOMs). Production isn't a vibe.

Internal Developer Platforms

Backstage or equivalent: a self-service catalog of golden paths, scaffolds, and paved-road services so application teams ship without filing tickets.

How we work

A phased, outcome-driven approach

01
Baseline

DORA + reliability data

02
Bottlenecks

Where time goes

03
Automate

CI, IaC, tests

04
Platform

Paved road, golden paths

05
Improve

Quarterly DORA review

Toolchain

Standard, durable, low-magic

CI/CD

GitHub Actions, GitLab CI, Buildkite, CircleCI

IaC

Terraform, Pulumi, Crossplane

GitOps

ArgoCD, Flux

Orchestration

Kubernetes, Nomad, ECS

Observability

OpenTelemetry, Prometheus, Grafana

Logging

Loki, OpenSearch, Datadog, Splunk

Incident mgmt

PagerDuty, Opsgenie, Incident.io

Platform

Backstage, Port, Cortex

Outcomes

What good looks like

Deploy frequency

Up — measurably

Lead time

Down — measurably

Change-fail %

Under 15, trending lower

MTTR

Hours, alarmed correctly

FAQ

Common questions

Roughly when application teams start solving the same infra problems independently — three to five product squads is a common inflection. Below that, embed platform work in the squads. Above, a small platform team (3–6 engineers) that treats developers as customers usually pays for itself in a quarter.

Start with Backstage (open source) or one of the commercial offerings, then build the golden-path templates that are specific to your stack. The platform itself is a commodity; the templates and policies are where the value lives. We've shipped both shapes — pure Backstage and Port / Cortex setups.

Often, yes. For a single-service backend or a handful of microservices, managed services (Cloud Run, App Runner, ECS Fargate) get you 90% of the value at 20% of the operational cost. We recommend Kubernetes when you have 15+ services, real multi-tenancy needs, or specialty workloads (ML, stateful, GPU) that justify it.

SLO-based alerting on user-visible behavior, not raw resource metrics. Symptom alerts page humans; cause alerts go to dashboards. Every page that fires gets reviewed in a weekly on-call retro — if it isn't actionable, it's killed or auto-resolved. The on-call rotation is a feature, not a punishment.

Industries we apply this in

Other services that often pair with this

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Want a candid DORA-quartile assessment?

30 minutes with our delivery lead. We'll measure your current state and tell you the three smallest changes that move you a quartile.