We cover the full DevOps spectrum - infrastructure, automation, cloud, security, and reliability. Here's where we can help.
Automated build, test, and deployment pipelines using GitHub Actions, GitLab CI, Jenkins, or CircleCI. Faster releases, fewer manual errors, and consistent deployments across every environment.
→ Removes manual handoffs and deployment bottlenecks
Common Use Cases
Provision, configure, and manage cloud environments on AWS, GCP, or Azure. Infrastructure as Code using Terraform and Pulumi so your environments are reproducible, version-controlled, and auditable.
→ Reproducible environments you can trust in production
Common Use Cases
Kubernetes cluster setup, configuration, scaling policies, and ongoing management. Helm chart development, namespace strategy, RBAC, and monitoring - for teams moving to containers or already running them.
→ Scales workloads reliably without hero operations
Common Use Cases
Audit your existing cloud spend, identify waste, and implement rightsizing, reserved instance planning, spot instance strategies, and automated resource scheduling. Most clients recover 30–50% of cloud cost within the first quarter.
→ Cuts cloud waste without sacrificing performance
Common Use Cases
Rewrite manual, undocumented infrastructure into version-controlled, repeatable Terraform or Pulumi code. Eliminates the 'only Dave knows how this works' problem and makes environment provisioning predictable.
→ Makes infrastructure repeatable and auditable
Common Use Cases
Define and implement SLOs, SLIs, and error budgets. Build runbooks, on-call rotations, incident response playbooks, and post-mortem processes that actually improve reliability over time.
→ Improves reliability with measurable targets
Common Use Cases
Most DevOps consultants will set up a pipeline and disappear. Here's what we do differently - and why it actually matters for your team long-term.
Every tool, every abstraction, and every automation we introduce is chosen with your team's skill set in mind. If your engineers don't know Kubernetes deeply, we either train them or choose a managed service that doesn't require them to. No hero infrastructure.
If deployments are slow, there's usually a reason beyond 'the pipeline is slow'. We look at your branching strategy, testing approach, environment parity, and deployment frequency together. Fast pipelines built on bad practices just break faster.
Every system we build comes with runbooks, architecture diagrams, and handover documentation written for the people who will maintain it - not just the people who built it. Your team shouldn't need us to explain what we built.
We can talk to your CTOs and VPs about reliability targets, release frequency, and compliance requirements - and then turn around and work directly with your engineers in GitHub pull requests. No translation layer required.
Security controls, secrets management, network policies, and compliance checks are built into the pipeline from day one - not added as an afterthought when an audit finds a gap. This is especially important for regulated industries.
More tooling is not always better. We recommend the simplest infrastructure that reliably meets your requirements, and we actively push back on over-engineering. Complexity is a hidden cost that compounds over time.
Whether we're starting from scratch or improving an existing setup, we follow a structured process that keeps your team informed and in control throughout.
We start by understanding what you have. We review your existing CI/CD setup, infrastructure configuration, cloud spend, deployment process, incident history, and monitoring coverage. We map what's working, what's broken, and what's missing.
Based on the audit, we design the target state - the infrastructure, tooling, and processes you need. We present options at different investment levels so you can make an informed decision, not just accept whatever we recommend.
We implement in prioritised phases, typically starting with the highest-pain or highest-risk areas. Every change is tested, peer-reviewed, and deployed incrementally. We don't do big bang cutovers unless there's no alternative.
Before we hand anything over, we ensure there's comprehensive monitoring, alerting, and logging in place. If something breaks at 2am, your team should know about it before your customers do - and have the context to fix it quickly.
We document everything - not in jargon-heavy tech specs, but in practical runbooks and architecture guides your team can follow under pressure. We run handover sessions, pair with your engineers, and don't consider a project complete until your team is confident.
Infrastructure needs ongoing attention - cost optimisation, security patching, capacity planning, and tooling upgrades. We offer retainer-based ongoing support for teams that want a DevOps partner rather than a one-time project vendor.
We're not tied to a single vendor or toolchain. We recommend what fits your team, your scale, and your existing investment.
AWS, GCP, Azure, DigitalOcean, and OVHcloud - chosen based on your workload, team familiarity, and compliance requirements.
GitHub Actions, GitLab CI, Jenkins, CircleCI, Bitbucket Pipelines, ArgoCD, and Flux for reliable automated delivery.
Docker, Kubernetes on EKS/GKE/AKS, Helm, Kustomize, Rancher, and OpenShift for containerised workloads at scale.
Terraform, Pulumi, AWS CDK, Ansible, and CloudFormation for version-controlled, repeatable infrastructure.
Prometheus, Grafana, Datadog, New Relic, ELK, Jaeger, and OpenTelemetry for end-to-end visibility.
HashiCorp Vault, AWS Secrets Manager, Trivy, Snyk, OPA, Falco, and Checkov for security built into delivery.
Engineering teams invest in DevOps because of the downstream business impact - not because CI/CD is interesting. Here's what that impact looks like in practice.
Automated pipelines remove manual handoffs, approval bottlenecks, and error-prone deployment steps. Teams that deploy once a week start deploying daily. Teams that deploy daily start deploying on demand.
Proper testing gates, environment parity, progressive delivery (canary and blue/green deployments), and observability catch problems before they reach users - and cut mean time to recovery when they do.
Cloud environments without governance tend to accumulate waste. Rightsized instances, auto-scaling policies, reserved capacity planning, and scheduled shutdowns of non-production environments typically reduce cloud spend by 30–50%.
When deployments are automated and infrastructure is self-service, your senior engineers stop spending half their time on operational work and start spending it on the product. That's a significant productivity gain.
Reproducible infrastructure as code means new developers can get a fully working local environment and be deploying to staging within hours - not days of manual setup and Slack messages asking 'how do I get this to work'.
Automated compliance checks, immutable audit trails, and policy-as-code mean you're not scrambling when SOC 2, ISO 27001, or a customer security questionnaire asks how your deployments are controlled.
Tell us where the friction is - deployments, infrastructure, cloud costs, reliability, security - and we'll have a direct conversation about what it would take to fix it. No generic pitch, no long sales process.
Typically responds within one business day
Everything you need to know.
DevOps is the combination of practices, automation, and culture that lets engineering teams deliver software reliably and frequently. If your team struggles with slow deployments, unpredictable releases, production incidents that take hours to diagnose, or cloud bills that keep climbing - you need it. It's not a tool you buy; it's a set of capabilities you build. We help you build them faster.
A DevOps assessment typically runs $5,000–$15,000 USD. A project-based implementation - building a CI/CD pipeline, migrating to Kubernetes, or standing up an observability stack - usually costs $20,000–$80,000 depending on complexity. Embedded engineers are typically $4,000–$8,000 per month per person. Managed retainers vary based on environment size and SLA requirements. We provide a detailed quote after understanding your specific situation.
Yes - and this is the more common scenario. Very few teams are starting from zero. We assess what you have, identify what's causing the most pain or risk, and improve incrementally. We don't throw away working infrastructure to replace it with our preferred stack.
It depends on your workload, your team's familiarity, your existing software agreements, and your geographic requirements. AWS has the broadest service catalogue and is the default choice for most startups and SMEs. GCP has strong advantages for data and ML workloads. Azure is typically the best fit for enterprises with existing Microsoft infrastructure. We're certified across all three and will recommend what fits, not what we happen to prefer.
An assessment is 2–4 weeks. A focused implementation project (e.g. building a CI/CD pipeline or migrating to Kubernetes) typically takes 6–12 weeks. A cloud migration or full DevOps transformation is usually a 3–6 month engagement. Embedded and managed engagements are ongoing. We'll give you a realistic timeline after a scoping conversation.
This is a question we're glad you're asking - because a lot of DevOps consultants build things only they can maintain. Our approach explicitly avoids this. We document everything, run handover sessions, pair with your engineers during implementation, and make tooling choices with your team's skill set in mind. If something requires expertise your team doesn't have, we'll either train them or choose a managed service that doesn't require it.
We help teams build the technical controls that compliance frameworks require - automated access management, audit logging, secrets handling, network segmentation, vulnerability scanning, and deployment controls. We're not a certified auditor, but we work alongside your compliance team or auditor to implement the infrastructure and process controls that map to your chosen framework.
We've worked across fintech, healthtech, SaaS, logistics, e-commerce, and enterprise software. DevOps practices are largely industry-agnostic at the technical level, though regulated industries (finance, healthcare) have specific compliance requirements we're experienced with.
