Scale / Cloud, data & platform engineering
Cloud, data and delivery platforms built for reliable growth
We connect cloud foundations, Kubernetes, CI/CD, storage, databases, search and observability into a platform the engineering team can operate and change safely.
Intended outcomes
What this engagement is designed to achieve.
- A platform aligned with actual load and team size
- Faster, safer and repeatable production releases
- Observable reliability, capacity and cloud cost
- Data and search systems that remain responsive as they grow
Engineering capabilities
Capabilities applied where the system needs them.
We select technology based on the product, team and operating constraints. The list reflects established areas of delivery, not a mandatory stack.
- AWS, Hetzner & Cloudflare
- Kubernetes, Docker & Helm
- Terraform & Ansible
- GitLab CI/CD
- MySQL/Aurora & PostgreSQL
- MongoDB & Redis
- Elasticsearch
- Observability & SRE
When to bring us in
When this service is a good fit.
- Infrastructure has grown through one-off fixes
- Database or search performance is blocking the roadmap
- Kubernetes or cloud migration is stalled
- The team needs a reliable delivery platform rather than more scripts
What you receive
Concrete deliverables and a clear path forward.
- Cloud and platform architecture
- Kubernetes, infrastructure as code and CI/CD
- Database, index and query optimization
- Search, data pipelines and object storage
- Observability, reliability and cost controls
Questions
Common questions.
Do we need Kubernetes?+
Not necessarily. Kubernetes is useful when its operational model solves a real scaling or ownership problem. For smaller systems, a simpler deployment can be more reliable.
Can you improve a database without replacing it?+
Often yes. Query plans, indexes, data shape, pagination, connection behavior and workload isolation can produce larger gains than a database migration.
Direct access to the delivery team