DevOps consulting services from build to 24×7 operations

DevOps consulting is an engagement where an outside team reviews how you build, test, deploy and operate software, then designs and implements the missing automation. A typical scope covers CI/CD pipelines, infrastructure as code, container platforms, observability and security gates. What you get back is working infrastructure in your own cloud accounts and Git repositories, plus the runbooks and training your engineers need to own it.

Our DevOps consulting services cover six areas: assessment and roadmap, CI/CD pipeline engineering, infrastructure as code with Terraform, Kubernetes and container platforms, DevSecOps and compliance automation, and monitoring and observability. Ongoing managed DevOps operations can be added under the same agreement, covering 24/7 monitoring, on-call, patching and monthly cost reviews. Scope is fixed after the assessment, so you pay only for the gaps we find.

Cost depends on the engagement model. A fixed-scope DevOps assessment is the usual starting point and runs one to two weeks. Project work such as a CI/CD build-out, a Terraform migration or a Kubernetes platform is quoted against a defined scope. Ongoing managed DevOps typically runs $2,000 to $15,000 per month depending on environment size, number of clouds and whether you need 24/7 cover. For comparison, one senior DevOps engineer costs $150,000 to $250,000 per year and cannot staff a 24/7 rotation alone. Our DevOps consulting pricing guide breaks the models down further.

Managed DevOps services are an ongoing engagement where we run your delivery platform and cloud operations rather than handing them back at the end of a project. Scope covers monitoring and alerting, on-call and incident response under SLA, patching and version upgrades, release support, backup and disaster recovery testing, and monthly cost and reliability reviews. Consulting finishes when the build is done. Managed DevOps has no end date, and a named team stays on the environment.

DevOps as a service is the subscription form of DevOps: instead of hiring engineers, you pay a monthly fee for a team that runs your pipelines, infrastructure and on-call rotation. At SquareOps that maps to our managed DevOps engagement — a named pod of DevOps engineers and SREs, an agreed SLA, and a monthly report on uptime, incidents, deployment frequency and cloud spend. It suits teams that need production-grade operations before they can justify three or four full-time hires.

DevOps consulting is project work with a defined scope and an end date, such as an assessment, a pipeline build or a migration. Managed DevOps is an ongoing operational engagement with no end date, covering monitoring, on-call, patching and optimization under an SLA. Most clients start with consulting to get the platform built correctly, then move to managed DevOps so the same engineers keep running it. Buying both from one provider removes the handover gap where the team operating a system never designed it.

Hire in-house when your delivery platform is a competitive differentiator and you can fund at least three engineers, because one person cannot cover a 24/7 rotation, holidays and the full tooling surface. Outsource DevOps when you need production-grade delivery now, cover across time zones, or depth across AWS, Kubernetes, Terraform and security that a single hire will not have. Many teams run both: an internal platform lead who owns direction, with an external pod doing the build and the on-call. We break the maths down in in-house vs managed DevOps.

An assessment takes one to two weeks. A first production-ready CI/CD pipeline and Terraform baseline usually takes four to eight weeks. A full platform — pipelines, infrastructure as code, Kubernetes, observability and security gates across every environment — typically runs three to six months, depending on how many services and environments exist. We sequence the work so the highest-risk gap closes first instead of waiting for the whole programme to land.

We baseline the four DORA metrics before any work starts — deployment frequency, lead time for changes, change failure rate and mean time to restore — and report them monthly. Alongside those we track uptime against the SLA, cloud spend per environment, and how many manual steps remain in a release. Taking the baseline first is what makes the improvement provable instead of anecdotal.

AWS, Google Cloud and Azure, with most of our work on AWS as an AWS Advanced Tier Services Partner. The toolchain includes GitHub Actions, GitLab CI and Jenkins for CI/CD; Terraform for infrastructure as code; EKS, GKE and AKS for Kubernetes; ArgoCD and Flux for GitOps; Prometheus, Grafana, Loki and New Relic for observability; and SonarQube, Trivy and Checkov for security scanning. We build on the stack you already run rather than requiring a rewrite.

Ask for four things. Case studies in your industry with named outcomes rather than logos. Credentials you can verify, such as AWS partner tier, ISO 27001 certification and CKA-certified engineers. A written scope that names deliverables: pipeline stages, runbooks, reliability targets and who carries the pager. And an exit path, where code, documentation and access live in your accounts so changing provider is a decision rather than a rebuild.

Yes. Everything we build lives in your cloud accounts, your Git repositories and your CI system. We work through scoped IAM roles with audit logging, never shared credentials or resources held in our name. Terraform code, Helm charts, runbooks and dashboards are yours from the first commit, so if the engagement ends your team is left with a documented, working platform instead of a black box.

Yes, and that is how most engagements run. We pair with your engineers, review pull requests in your repositories, join your standups and hand over each component as it stabilises. Where you already have a platform lead, they set direction while we supply capacity and specialist depth in Kubernetes, Terraform or security that a small team cannot keep staffed year-round.