Service 02
DevOps and automation
We make CI/CD faster and cheaper, package applications into containers and move deployments to GitOps with a clear view of what runs where. Less manual work for your team and more predictable changes in operation.
Typical situations
Our developers spend too much time on infrastructure.
We automate deployments, prepare environments and take over agreed operational tasks, so your team has more room for the product.
Deployments are manual and slightly different every time.
We set up a repeatable, documented process that runs the same way every time.
Our CI/CD is slow and expensive.
We find where the pipeline loses time and money and shorten it: caching, parallel jobs, smaller images and runners you pay for only when they work.
We don’t know which version runs where.
We move deployments to GitOps. You then see the state of every application and environment in one place, including the deployment history.
What we do
Deployment and CI/CD review
We follow a change from commit to production and measure where it waits and what it costs. The output is a list of bottlenecks and the order to tackle them in. We look at:
- how long the pipeline takes and which steps slow it down most
- what runners and build minutes cost, and how much of that is waiting and retries
- what is done by hand during a deployment and what only one person knows
- flaky tests that get re-run until they pass
- the size and age of images and dependencies
- how a previous version is restored today and how long it takes
Faster, cheaper CI/CD
A slow pipeline holds up every change, and expensive runners are paid for while they wait. We shorten the pipeline so it only builds and tests what is needed. We put in place:
- caching of dependencies and image layers, so nothing is downloaded and rebuilt over and over
- parallel test runs, and jobs that run only for the parts that changed
- your own or autoscaled runners instead of expensive shared minutes, where it pays off
- build once: the same artifact for test and production
- fast feedback: linting and unit tests before slow integration tests
- pipeline duration and cost tracked over time, so you see when it slows down again
Containers and orchestration
Applications are packaged into containers so they run the same way on a developer’s machine, in test and in production. We propose orchestration where it makes operations or scaling simpler. Where less is enough, we keep a simpler setup. We put in place:
- Dockerfiles with multi-stage builds and small images without clutter
- vulnerability scanning of images and regular image updates
- an image registry with versioning and clean-up rules for old versions
- Kubernetes, or a simpler container runtime (for example Cloud Run or Docker Compose), depending on the size and needs of your applications
- application deployments described in Helm or Kustomize
- resource limits, health checks and autoscaling
- consistent application logs and metrics that monitoring builds on
GitOps and an overview of deployed applications
The desired state of every application is described in Git, and a tool such as Argo CD or Flux continuously compares it with what actually runs. One place shows what runs where, and in which version. We put in place:
- an application overview: which version runs in which environment, when and by whom it was deployed
- deployments through a merge request with approval instead of manual commands
- continuous sync, and alerts when production drifts from Git
- rollback to a previous version by reverting the change in Git
- application health and deployment history in one place
- access to the overview for developers, without access to the cluster
Controlled rollouts
A new version doesn’t have to reach every user at once. We roll out gradually (for example with Argo Rollouts) and let the metrics decide whether to continue. Depending on your needs, we put in place:
- gradual rollout to a small share of traffic (canary), widened based on error rates and response times
- blue-green deployments with a switch-over and a quick way back
- automatic rollback to the previous version when the metrics don’t look right
- feature flags, so a new feature can be switched off without a new deployment
- database changes designed to work with both the old and the new version of the application
- an approval step before production where you need one
Environments and configuration
Development, test and production are built from the same definition, so they don’t drift apart. The infrastructure under your applications is described in IaC (Terraform, Ansible). We put in place:
- separate development, test and production environments that differ only in configuration values
- temporary environments for merge requests that disappear after the merge
- application configuration in Git, separate from the code and versioned
- local environments for developers (Docker Compose, dev containers) that behave like production
- infrastructure in IaC, so a new environment is created from code
Secrets and access
Passwords, keys and certificates belong in a vault, not in the code or in variables everyone can see. We put in place:
- a secrets vault (for example Vault or your cloud’s secret manager) that applications and deployments read from
- short-lived credentials for CI/CD instead of long-lived keys (OIDC, Workload Identity)
- checks that no password or key gets into the repository
- regular key rotation and automatic certificate renewal
- least-privilege permissions for pipelines and applications
- personal accounts whose access can be removed quickly
How to start
We can start with a review of your current deployment process. It shows what to automate first and how to build on the tools you already use.
FAQ
Questions about this service
Do we have to move to Kubernetes?
No. We recommend containers and orchestration only where they make sense. A simpler, well-automated deployment is often enough.
Will you build on the tools we already use?
We first review your existing tools and processes and build on them. We propose switching to a different solution only with a clear reason.
Who manages the automation once it is in place?
That depends on the agreement. We hand it over to your team with documentation, or we can keep managing it as part of ongoing operations.
Other services
- Infrastructure modernisation and cloudWe build new infrastructure from scratch (greenfield), or shape your existing one around what your applications and team actually need — in the cloud, hybrid or on your own servers.
- Security and technical assessmentsWe turn security findings into clear priorities and measures that actually work in operation.
- Ongoing operationsWe take over an agreed part of your operations and look after the environment continuously — in your environment or on our platform.
- AI platformWe set up a shared environment for company AI: an approved chat for employees, controlled model access for applications and agents, and a clear view of data, costs and results.
Contact
Request a consultation
A short description of your environment and what you need solved is enough. We reply within one working day. If your team already covers operations, security and cover, we will tell you.