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Cloud & DevOps

Cloud architecture, deployment automation, and infrastructure that stays healthy under pressure.

Cloud & DevOps

Deploy with confidence, recover quickly, and stop paying for infrastructure you do not use.

Infrastructure decisions shape everything above them: performance, reliability, security, and cost. Datatech designs cloud architectures, automates deployment pipelines, and implements the monitoring and recovery practices that keep systems healthy — so releases become routine instead of risky.

Business Challenges We Address

  • Deployments that are manual, stressful, and risky.
  • Infrastructure costs growing faster than the business.
  • Outages discovered by customers instead of monitoring.
  • Environments that differ between development and production.

Our Approach

  1. We start with the workload: its traffic pattern, availability requirements, and cost sensitivity — then choose the right architecture, not the trendiest one.
  2. Deployment pipelines, automated testing, and infrastructure-as-code make every release repeatable and reversible.
  3. Monitoring, alerting, and runbooks mean incidents are detected early and resolved calmly.
  4. Cost reviews and right-sizing keep infrastructure spend proportional to actual usage.

Capabilities

  • Cloud architecture design (AWS, Azure, GCP)
  • CI/CD pipeline setup
  • Containerization with Docker and Kubernetes
  • Infrastructure as code
  • Monitoring, logging, and alerting
  • Backup, disaster recovery, and cost optimization

Use Cases

Moving an on-premise system to the cloud with minimal downtime.

A CI/CD pipeline turning weekly risky releases into daily safe ones.

Auto-scaling infrastructure for a traffic-heavy seasonal business.

A recovery plan that turns a potential disaster into a routine event.

What You Gain

  • Faster, safer, more frequent releases
  • Early detection of problems before customers notice
  • Infrastructure costs matched to actual need
  • Consistent, reproducible environments
  • Clear recovery path when things go wrong

Technology Considerations

AWS Azure GCP Docker Kubernetes GitHub Actions Terraform Prometheus Grafana

Common Questions

No. Some workloads genuinely run better on-premise. We assess each workload on its own merits and recommend a pragmatic path, including hybrid approaches.

Yes. We frequently work alongside internal teams, transferring knowledge and automating gradually rather than replacing everything at once.

Through right-sizing, reserved capacity where predictable, storage lifecycle policies, and removing unused resources — based on actual usage data, not guesses.

Have a Technology Challenge in Mind?

Tell us about your goals and constraints. We will respond with honest, practical advice on the best way forward.