What are AWS and cloud services?
AWS and cloud services cover renting computing infrastructure, such as servers, databases, storage and networking, from providers like Amazon Web Services, Google Cloud or Microsoft Azure instead of running your own hardware. Cloud engineering is the work of setting that infrastructure up, deploying software to it and keeping it secure, monitored and affordable.
We set up the environments our systems run in: separate development, staging and production, automatic deployments, monitoring, backups and access controls. For simpler products we use managed platforms such as Vercel, Supabase, Firebase and Cloudflare, which remove a lot of work. For larger or regulated systems we use AWS, Google Cloud or Azure directly.
Not everything belongs in a public cloud. When patient records or other sensitive data must stay with you, we deploy to a private cloud or to your own servers, with the same deployment and backup discipline.
- How many manual steps does a release take today?
- When were your backups last restored as a test?
- Do you know what each part of your cloud bill pays for?
How a cloud engagement runs
Changes to live infrastructure are planned, tested and reversible.
1. Review
We look at what runs where, how releases happen, what it costs and what would hurt most if it failed.
2. Plan
Target setup, migration order, risks, timeline and cost, approved by you before anything changes.
3. Build and test
Environments, pipelines, monitoring and backups set up in stages, with a tested restore before go-live.
4. Run in parallel
For migrations, the new environment runs alongside the old one until traffic and data are confirmed.
5. Switch over and hand over
A planned cut-over with a way back, then runbooks and access handed to your team.
6. Support and improve
A named support contact, alert response and regular checks on cost, security and backups.
Why cloud setups cause trouble
The cloud makes it easy to start. Without care, it is just as easy to end up with something fragile and expensive.
Manual deployments
Releases depend on one person running commands by hand, so they are rare, stressful and hard to undo.
Bills nobody understands
Oversized servers, forgotten resources and no tagging, so costs grow without anyone deciding they should.
Untested backups
Backups exist on paper, but nobody has restored one, so no one knows if they work.
No monitoring
Outages and slow pages are reported by users, not spotted by the team running the system.
Loose access
Shared root accounts, keys in code and no record of who changed what.
Data in the wrong place
Sensitive data stored in a region or service that does not meet the client's own rules.
What we set up and run
Every environment is documented and handed over, with a named support contact.
- 01
Cloud architecture and environments
Development, staging and production on AWS, Google Cloud or Azure, sized for today's load and documented.
- 02
CI/CD pipelines
Automatic tests and deployments with GitHub Actions or GitLab CI, so releasing is routine and reversible.
- 03
Containers and orchestration
Docker for consistent environments, and Kubernetes where the system is large enough to justify it.
- 04
Monitoring and alerts
Uptime, errors, performance and logs in one place, with alerts sent to the person who owns the fix.
- 05
Backups, recovery and access
Scheduled backups, tested restores, least-privilege access and secrets kept out of code.
- 06
Private and on-premise hosting
Deployments to a private cloud or your own servers when data must stay with you.
Which platform fits which job
We choose per project, based on what the system needs, who will run it and where the data must live.
| Platform | Good fit for | Things to weigh |
|---|---|---|
| Vercel | Next.js sites and web apps that need fast, simple deployments | Costs can rise with heavy traffic or long-running back-end work |
| Supabase or Firebase | MVPs and small products that need a database, auth and storage quickly | Less control over data location and some vendor lock-in |
| Cloudflare | DNS, caching, security at the edge and light serverless work | Usually paired with another platform for the main application |
| AWS, Google Cloud or Azure | Larger systems, integrations, AI workloads and regulated data | More to configure and manage, so setup and monitoring matter |
| Private cloud or on-premise | Systems where data must stay inside the client's own infrastructure | Hardware, power and updates become the client's responsibility |
Ways to work with us
Pick the model that matches where your infrastructure is today.
| Model | Best when | How it is priced |
|---|---|---|
| Bottleneck review | Deployments are painful, outages recur or the bill is out of control | Fixed fee for a short, defined engagement |
| Defined build | A new environment, migration or pipeline is scoped | Fixed scope, paid against agreed milestones |
| Managed team | You need a team to run and improve your infrastructure for a set period | Monthly, based on the team composition you need |
We quote after the first conversation, once we know the scope. Every system is handed over with documentation and a named support contact.
Platforms and tools
We work across providers and do not resell any of them.
Cloud providers
- AWS
- Google Cloud
- Microsoft Azure
Managed platforms
- Vercel
- Cloudflare
- Supabase
- Firebase
Build and deploy
- GitHub Actions
- GitLab CI
- Docker
- Kubernetes
- Terraform
Monitoring
- CloudWatch
- Grafana
- Prometheus
- Sentry
- Uptime checks
Data and backups
- PostgreSQL
- Amazon RDS
- S3
- Automated snapshots
Where to go next
DevOps in Healthcare
DevOps for healthcare systems in daily clinical use: staged releases, monitoring, backups, audit logging and access control, on cloud or private hosting.
Learn moreManaged Engineering Services
Managed engineering services: a dedicated ALGON team for a defined project and period, working inside your process and reporting on outcomes, not hours.
Learn moreApplication Modernization
Application modernisation for systems that no longer fit: a staged move off old software, data migrated and checked, and both running until staff trust the new one.
Learn more
Frequently asked questions
The one that fits the system, your team and where your data must live. Many products start on Vercel or Supabase and move to AWS, Google Cloud or Azure as they grow.
No. We work across AWS, Google Cloud and Azure and recommend whichever suits the project. We do not resell cloud services.
Often. We look for oversized resources, unused services and missing reserved pricing, and show what each change saves before making it.
Yes. Where data must stay with you, we deploy to a private cloud or on-premise servers with the same deployment, monitoring and backup practices.
Usually not at first. Many systems run well on simpler managed services. We recommend Kubernetes only when the size of the system justifies it.
Automated, stored separately from the main system, and restored as a test on a regular schedule so we know they work.
Yes. Accounts are in your name, and access, documentation and runbooks are handed over.
Bring us your bottleneck.
If a process in your organisation depends on one person remembering to follow up, describe it to us. You will get a straight answer on whether it needs automation, software, a team, or none of these.
Or write directly to support@algonsolutions.com