DevOps Consulting Services

DevOps consulting services cover the work of getting software from a commit to production reliably:

• Automated build and release pipelines

• Infrastructure defined as code

• Container orchestration

• Monitoring

• Security checks that run alongside all of it.

A consulting engagement usually starts by assessing how you release today, then designs and builds the delivery system you actually need.

The distinction worth knowing is between advice and delivery. Some firms return a roadmap and a maturity score. We build the pipeline, then hand it to your team with the code and documentation to run it.

You do, and you get four things to prove it:

• Terraform code for your infrastructure

• Runbooks for operating it

• Documentation covering how it works and how to extend it

• A walkthrough with the engineers who built it

Provisioning everything as code is what makes that possible. Infrastructure that lives in version control can be reviewed, rebuilt, and changed by anyone on your team who can read a pull request. On Lakera's platform, every environment across AWS and GCP is managed this way, which is what keeps the setup auditable and reproducible rather than dependent on whoever set it up.

No, and the handover is designed to make that concrete. Everything we build is open, standard tooling in your repositories and your cloud accounts: Terraform, Helm, ArgoCD, GitLab CI or GitHub Actions. There is no DBB layer in the middle and no proprietary component you would have to unpick to leave.

On the toolchain itself, we start from what you already run. If your team knows GitHub Actions, we do not migrate you to GitLab to suit us.

Absolutely. We offer the option to hire DevOps engineers to complement your existing teams and enhance your in-house capacity. Choose the hiring route when you know what needs building and want engineers you direct day-to-day inside your own team, typically for three months or more.

Cloud Migration moves your workloads to the cloud. This page builds the delivery pipeline that ships changes to them once they are there.

The two often run in sequence. If your systems are still in a datacenter you are leaving, the migration comes first, and it makes little sense to build a deployment pipeline for infrastructure that is about to move. If you are already on AWS, Azure, or Google Cloud and releasing is the painful part, start here.

Yes, and it is one of the more common ways engagements start. A partial setup usually means some things are automated, and some are not, which is often harder to live with than nothing at all, because nobody is certain which is which.

We assess what exists first and keep whatever is working. Frequently the answer is that the pipeline is sound and the gaps are rollback, secrets handling, and documentation, which is a much smaller piece of work than a rebuild.

Across the market, DevOps consultants bill roughly $50 to $150 per hour in Eastern Europe and $150 to $250 per hour in the US and Western Europe, per industry averages rather than a DBB rate card. Total cost depends far more on the size of your estate and how much is already automated than on the hourly rate.

We conduct a Discovery session with you to develop a roadmap tailored to your needs, which ultimately determines the price. If you are interested in a conservative estimate of the cost and scope of work based on your requirements, use our scope generator!

A working pipeline on a single service typically takes about a week, and a full environment about a month. An assessment on its own runs two weeks and returns a ranked plan.

Larger programs, particularly ones involving multiple clouds or a migration running in parallel, are scoped in phases rather than quoted as a single duration. The Discovery Sprint exists to turn that into a fixed bid within ±15% before anyone commits.

AWS, Microsoft Azure, and Google Cloud, including estates that span more than one. Multicloud is not a theoretical capability here: Lakera's infrastructure is provisioned with Terraform across both AWS and GCP, and Doctify runs microservices on AWS and GCP together.

Our AWS DevOps consulting and Azure DevOps consulting work covers the native services on each, from CodePipeline and EKS through to Azure Pipelines and AKS. We are a certified partner for AWS, Microsoft Azure, and MongoDB, and our engineers hold current certifications across the three major clouds.

Yes. DevSecOps services put dependency scanning, container image scanning, secrets management, and policy checks inside the pipeline, where a failing check blocks the build rather than producing a report someone reads later.

Credentials go into a managed secret store with scoped roles and separate account boundaries, so no single key opens the whole estate. We work to ISO/IEC 27001-certified practices, and where you have HIPAA, GDPR, SOC 2, or PCI DSS obligations, the access boundaries and audit trails are designed around them from the start.

Yes. The practices that matter, which are version-controlled infrastructure, automated builds, tested rollback, and real monitoring, are not cloud-specific. Kubernetes, Terraform, and GitOps all run against on-premise and hybrid estates, so container orchestration services work the same way on your own hardware.

What changes is the provisioning layer and the pace of some feedback loops, since you cannot create a fresh environment on demand the way you can in a public cloud. We scope that difference explicitly rather than assuming a cloud-native default.

You own all of it, including the Terraform modules, pipeline definitions, Helm charts, and documentation we produce. It is written into your repositories and your cloud accounts throughout the engagement, not delivered as a package at the end.

We work under an NDA from the Discovery Sprint onward, and there is no license, subscription, or retained component on our side.

We can, and plenty of clients choose that. DevOps support services can continue after the handover while your team builds confidence, and the handover still happens regardless: continuing support is an option, not the condition for getting the code.

If what you actually need is long-term cover for the application itself, with L1-L3 support and agreed response targets, then IT Support covers that work.

We start from what your team already knows and what your cloud already supports, because the best pipeline is the one your engineers can maintain after we leave. A team fluent in GitHub Actions gets GitHub Actions.

Where there is no established preference, we default to widely-adopted, open tooling with large communities: Terraform, Helm, ArgoCD, Prometheus, and Grafana. That keeps hiring easy and keeps you off anything proprietary.