Services — DevOps Consulting

Deployment shouldn't be the scariest part of your week.

CI/CD pipelines, infrastructure as code, container orchestration, and observability — built by a team that's shipped 600+ products over 18 years. We know exactly where deployment processes break, because we've fixed them all.

See our work
18Years in delivery
4xAverage deployment frequency increase
73%Reduction in change failure rate

CI/CD Pipelines

From commit to production in minutes, not meetings.

Most teams we meet deploy weekly — or less. Manual steps, flaky tests, and tribal knowledge slow every release. We build automated pipelines that enforce quality gates, run comprehensive tests, and promote builds to production without a single manual approval bottleneck. Your engineers push code. The pipeline handles the rest.

Our average client moves from bi-weekly releases to multiple daily deployments within the first 60 days of engagement.

15 min

Average pipeline cycle time

99.7%

Build success rate

Engineering team reviewing CI/CD pipeline dashboard with green build status indicators

Infrastructure as Code

Every environment reproducible. Every change reviewable.

Manual infrastructure configuration creates snowflake servers that nobody can replicate and everyone is afraid to touch. We codify your entire infrastructure — networking, compute, storage, security groups — in Terraform, Pulumi, or CloudFormation. Every change goes through pull request review. Every environment is a mirror of production.

100%

Infrastructure defined in version-controlled code

SDTC client baseline

01

Terraform & Pulumi

Multi-cloud infrastructure provisioning with state management, drift detection, and modular composition.

02

GitOps workflows

Infrastructure changes deployed through the same pull request process as application code — reviewed, approved, and auditable.

03

Environment parity

Development, staging, and production environments generated from the same templates — eliminating 'works on my machine' infrastructure problems.

04

Cost optimisation

Right-sizing, reserved instances, and automated scaling policies defined in code — so cost savings are repeatable, not one-off manual adjustments.

Tooling selected for your context, not our preferences.

We are technology-agnostic. The right DevOps toolchain depends on your team size, cloud provider, compliance requirements, and existing investment. Here's how we typically approach each layer.

Continuous integration and delivery pipelines tailored to your repository structure and deployment targets.

GitHub ActionsRecommended

Native GitHub integration with matrix builds, reusable workflows, and OIDC authentication to cloud providers.

GitLab CI/CDRecommended

Tightly integrated pipeline-as-code for teams already invested in the GitLab ecosystem.

Azure DevOps PipelinesWhen needed

Enterprise-grade pipelines with deep Azure integration and YAML-based configuration.

JenkinsAlternative

Self-hosted option for teams with strict data residency requirements or complex legacy pipeline logic.

ArgoCDRecommended

GitOps-native continuous delivery for Kubernetes workloads with automated sync and rollback.

Common questions about DevOps consulting

Straight answers from 18 years of building deployment pipelines and platform infrastructure.

Most teams see meaningful improvement within 30 days. In the first two weeks we baseline your DORA metrics and implement the CI/CD pipeline changes with the highest impact. By week four you typically have automated testing running on every commit and deployment frequency measured in days rather than weeks. The cultural changes — blameless postmortems, shared ownership, on-call practices — take longer. But the pipeline improvements are immediate and measurable.

DevOps engineers collaborating around monitoring dashboards showing real-time deployment metrics

SDTC engineering team during a platform migration — monitoring deployment health across three availability zones.

Grafana dashboard showing distributed tracing and metrics across microservices

Observability & SRE

You can't improve what you can't see.

Centralised logging, distributed tracing, and metrics dashboards that make your system's behaviour visible and debuggable. We implement SRE practices — SLOs, error budgets, and on-call runbooks — so your team knows exactly when something is wrong and has a clear path to resolution. No more guessing. No more log-grepping across 15 servers at 2am.

< 60s

Mean time to detection

99.95%

Average uptime across clients

  • AWS Advanced Partner
  • Google Cloud Partner
  • Datadog Partner

How we approach DevOps consulting

01

Baseline and assess

We measure your current DORA metrics, map your toolchain, and interview your engineering team. DevOps improvement without a baseline produces effort without measurable results.

02

Pipeline architecture

We design and build CI/CD pipelines that automate the path from commit to production — with quality gates, security scanning, and automated rollback at every stage.

03

Infrastructure codification

All existing infrastructure defined in Terraform or equivalent — making every change reviewable, repeatable, and reversible. Environments become reproducible artefacts.

04

Observability and alerting

Metrics, logging, and distributed tracing deployed across all services. SLOs defined, dashboards built, and on-call runbooks documented for common failure scenarios.

05

Culture and handover

DevOps is a culture change as much as a tooling change. We pair with your team, run blameless postmortems, and transfer knowledge until your engineers own the platform independently.

Measured improvement

We don't just implement DevOps. We measure it.

Every engagement starts and ends with DORA metrics — the industry standard for software delivery performance. We baseline where you are, set targets for where you need to be, and track progress weekly. No vanity metrics. No hand-waving about 'improved velocity.' Four numbers that tell you exactly how your engineering organisation is performing.

4xAverage improvement in deployment frequency across SDTC clients
01

Deployment frequency

01 / 04

Deployment frequency

How often your team deploys to production — from monthly releases to multiple daily deployments.

02

Lead time for changes

02 / 04

Lead time for changes

Time from code commit to running in production — targeting under one hour for high performers.

03

Change failure rate

03 / 04

Change failure rate

Percentage of deployments that cause a degradation or require rollback — targeting under 5%.

04

Time to restore

04 / 04

Time to restore

How quickly your team recovers from incidents — targeting under one hour with automated rollback and clear runbooks.

Ready to ship with confidence?

Tell us about your current deployment process. We'll come back with a clear assessment of where the bottlenecks are, what to fix first, and how quickly we can improve your DORA metrics.

See our DevOps work