DevOps & AWS Fundamentals
Containers, automation and the fundamentals of AWS cloud architecture.
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Infrastructure
DevOps Consulting
We speed up and stabilise your software development and delivery through automation. With CI/CD, container infrastructure and infrastructure as code, your teams release more often and with fewer errors.
What we offer
- Designing and setting up CI/CD pipelines
- Container infrastructure with Docker and Kubernetes
- Infrastructure as code (IaC)
- Observability: logging, metrics and alerting
- DevOps process and culture transformation
When you need it
- Software releases are slow, manual and error-prone
- There are inconsistencies between environments
- Infrastructure changes are uncontrolled and undocumented
How we work
Assess
We analyse your current development and release processes.
Design
We define the target DevOps architecture and toolset.
Implement
We build pipelines, container infrastructure and automation.
Hand over
We train your team and transfer the processes.
What you get
- Working CI/CD pipelines
- Container and IaC infrastructure
- Monitoring and alerting setup
- Documentation and team training
Related courses
MLOps: Taking Models to Production
CI/CD, model versioning, monitoring and data drift, plus LLMOps for LLM applications: keeping models reliable in production.
Learn more →Frequently Asked Questions
Which tools do you work with?
Git-based workflows, common CI/CD tools, Docker and Kubernetes, and infrastructure-as-code tools, chosen to fit your existing setup.
Do we have to change our processes?
Change is planned gradually, starting with the steps that waste the most time or cause the most errors.
Can our team maintain the new processes?
Yes. Training and documentation are part of the deliverables.
Does it work on on-premise infrastructure?
Yes. DevOps practices can be built on the same principles in the cloud and on-premise.
Free assessment · 4 min
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MLOps Maturity Assessment
Measure the MLOps maturity of your model development and deployment in 12 questions; see your level (0–4) and next steps.
Related articles
MLOps Maturity Levels: A Roadmap from Level 0 to 4
MLOps maturity determines how fast and reliably your models reach production. The levels in Microsoft's and Google's models, what characterises each level and the next step.
Read more →What Is MLOps? Why Models Never Reach Production
MLOps is the discipline of getting machine learning models into production reliably, and keeping them there. Its components, maturity levels, LLMOps and how it differs from AIOps.
Read more →Let's talk about your project
Tell us about your training, consulting or software needs and we will get back to you within 2 business days.