14 / Quality, cloud & infrastructure
Repeatable deployments and a cloud you actually control
We automate the path from code to production and bring order to infrastructure: CI/CD pipelines, Docker and Terraform, monitoring, backups and AWS costs.
If releasing a new version is a manual procedure only one person knows, and Friday-afternoon deployments are banned out of fear, your infrastructure is holding the product back. Every release costs nerves, defects reach production unnoticed, and nobody can explain why the code behaves differently on a laptop than on the server.
We fix this hands-on: we build CI/CD pipelines, containerise applications, describe infrastructure as code and set up monitoring that reports a problem before a customer does. You don't get a slide deck of recommendations — you get working infrastructure and releases nobody holds their breath for. You agree the scope with the engineer who builds that infrastructure and answers for it, and we keep the setup as simple as it can be: no Kubernetes where a single container will do.
Every change has to be repeatable and reversible — a rule that comes from the data platforms the firm's founder built in environments at PwC, Roche and E.ON, where manual deployment is not an option. We apply it to a single server running a single application too, because that is exactly where a manual deployment ends in a Friday-afternoon outage.
What the service covers
CI/CD and deployment automation
You release a new version with a single click — the pipeline builds, tests and publishes the application automatically on every code change. No more copying files to the server by hand or releases that are 'safer at night'.
- CI/CD pipelines in GitHub Actions (build, test, deploy)
- Automated deployments to staging and production
- Environment separation and configuration (dev, staging, production)
- Safe rollback strategies
Containerisation and infrastructure as code
You can rebuild any environment from scratch and see every infrastructure change in history — we package applications in Docker containers, describe infrastructure in Terraform and put every change through code review. 'Works on my machine' stops being an argument.
AWS configuration and architecture
You know what you are paying for and who has access to what — we configure AWS accounts and services from scratch or review an existing architecture: services matched to real needs, least-privilege permissions and cost control instead of invoice surprises.
- AWS service configuration: S3, Glue, Redshift and more
- IAM permissions and access on a least-privilege basis
- Architecture review for cost and reliability
- Secret-management recommendations
Monitoring, logging and backups
You hear about a problem from an alert, not from a customer's phone call — we set up monitoring and centralised logging (CloudWatch among others) with notifications that reach the right people, plus a backup strategy with a tested restore procedure. A backup nobody has ever restored is just a hope.
Production readiness and hands-on troubleshooting
You go live without guessing — we review the system before launch for security, performance, failure resilience and what-if procedures. We also help ad hoc, when something in the cloud is broken and nobody on the team knows why.
Typical situations
Releasing a new version is a manual, multi-step procedure known to exactly one person, and that person is about to go on holiday.
A startup before launch: the app runs fine on the developer's machine, but nobody has checked whether it will survive production and real users.
The cloud bill grows month after month and nobody in the company can say what you are actually paying for.
You learn about production outages from customers, because the system has no monitoring and no usable logs.
What you can count on
- Releases reduced to a single click: repeatable, automatically tested and reversible.
- Infrastructure described as code, rebuildable from scratch, with every change visible in history like any application change.
- You hear about defects before your customers do, not from them — monitoring and alerting report a problem before anyone has to call.
- Infrastructure any future team can take over — documentation and a knowledge handover mean it never depends on one person, ourselves included.
Technologies
- AWS
- Amazon S3
- AWS Glue
- Amazon Redshift
- AWS IAM
- Amazon CloudWatch
- Docker
- Terraform
- GitHub Actions
Projects in this area
Selected work where this scope was part of the delivery.
DevOps Engineering
Most of these projects start the same way: releases done by hand after hours, environments nobody can rebuild, deployment knowledge locked in one head. They end with a repeatable process — CI/CD pipelines, infrastructure described in code and monitoring that reports problems before users do — and with releases nobody holds their breath for.
Selected CI/CD, automation and infrastructure engagements
Data Reliability Platform
The most dangerous data failures are silent: jobs finish 'successfully' while the reports show something false. This enterprise platform on AWS catches such inconsistencies daily — automated validation, integration tests and monitoring, with results you can check rather than take on trust. The firm's founder worked on it as an engineer within a larger team, responsible for data-validation automation and testing.
Automated data validation and testing in an enterprise environment
Questions about this service
Usually not. For most small and mid-sized company applications, a simpler setup of Docker containers and well-configured managed services is cheaper to run and easier to understand. We propose the simplest solution that meets the requirements and tell you honestly at what point you would outgrow it.
We know AWS best and that is where our experience runs deepest. That said, a large part of this work — CI/CD, Docker, Terraform and deployment practice — is cloud-agnostic. If your infrastructure runs elsewhere, we'll tell you plainly in the first conversation what we can help with and what we would not take on.
Often yes, though we never promise percentages before a review — diagnosis first, decisions second. We analyse what you are actually paying for: unused resources, oversized instances, data kept in expensive storage classes. You get a list of potential savings with a risk assessment for each change, and you decide which ones we make.
Both work. The typical path is a review, implementation and a knowledge handover, after which the infrastructure is yours and does not require us. Some companies stay with us for ongoing infrastructure care. We work remotely with companies across Poland.
Related services
Databases and data
PostgreSQL design and optimisation, migrations, reporting and automated data validation, so the numbers across your company finally agree.
Automation and integrations
We replace copying data between systems, manual reports and retyping documents with scripts and integrations that run on their own.
Technical audits
Audits of code, applications, websites, QA processes and infrastructure. Instead of opinions and reassurances, a written report with priorities and an action plan.
Let's talk about your deployments and your cloud
The first conversation is free and commits you to nothing: you describe how code gets to production today, and you'll get a concrete answer — what we'd fix first, what it may cost, and where to start.