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Case studies

Selected delivery, reliability, and cloud optimization outcomes from past engagements.

Privacy and security note

Client names and architecture-specific details are intentionally anonymized due to NDA and security policy. Results and scope are representative of real delivery work.

Cloud cost reduction with safer scaling

Challenge: Several components required substantial capacity only during occasional traffic or processing peaks, but remained oversized during normal operation. Cloud spend kept accumulating despite limited resource usage.

Work delivered: Reviewed resource sizing, cleaned up unused capacity, adjusted lifecycle policies, and tuned autoscaling and resource rules around actual usage patterns.

Outcome highlights

  • Approximately 50% lower cloud spend
  • Capacity remained available for occasional high-demand periods
  • Less idle infrastructure and lower ongoing waste
  • Cost controls aligned with real workload behavior rather than peak capacity assumptions

Client profile

AdTech Platform North America

Technology tags

AWS Terraform Ansible Docker

Faster deployments through reusable build artifacts

Challenge: Each deployment rebuilt the complete application and infrastructure path from scratch. This provided a clean and predictable result, but made frequent deployments unnecessarily slow.

Work delivered: Split the process into reusable stages. Full builds produced stored artifacts that could be reused in later deployments. CI-level caching reduced repeated build work, including Python dependency builds. The optimized flow covered AWS resource creation, EC2 provisioning, and application installation.

Outcome highlights

  • Full deployment time reduced by approximately 40–50%
  • Clean, reproducible builds remained available when required
  • Reusable artifacts shortened subsequent deployment cycles
  • CI caching reduced repeated build work
  • Faster feedback for teams deploying infrastructure and applications frequently

Client profile

Financial Services Regulated UK

Technology tags

AWS Azure GitLab Kubernetes Terraform Ansible

From client-reported outages to observable operations

Challenge: The infrastructure had been configured manually and there was no monitoring. The team often learned about failures and service interruptions from the client.

Work delivered: Codified the existing infrastructure with Ansible and introduced an observability foundation based on Prometheus and Grafana for metrics, ELK for centralized logs, and Icinga2 for alerting.

Outcome highlights

  • Infrastructure became repeatable and reviewable
  • The team gained visibility into application and infrastructure health
  • Logs, metrics, dashboards, and alerts became available in a structured operating model
  • Problems could be detected internally instead of being reported first by the client
  • The environment gained a foundation for more proactive incident response

Client profile

Content Platform North America

Technology tags

AWS Ansible Prometheus Grafana ELK Icinga2

Repeatable application provisioning across customer environments

Challenge: The client’s application had to be installed in customer-provided environments, both on-premise and in the cloud. Each environment had a different host layout, which made manual installation slow and error-prone.

Work delivered: Created an Ansible-based provisioning process. The customer environment was described through an inventory defining which components should run on which hosts. Ansible then configured the hosts and installed the application components in a repeatable way, with fallback procedures for common provisioning failures.

Outcome highlights

  • Manual, host-by-host installation replaced with automated provisioning
  • Customer-specific environments handled through inventory configuration
  • Deployment became dramatically faster and more repeatable
  • Fallback procedures handled common provisioning failures automatically
  • The installation process became easier to maintain and support

Client profile

Industrial IoT Platform EU

Technology tags

Ansible VMware

From fixed VMware capacity to elastic AWS infrastructure

Challenge: The client relied on manually provisioned VMware virtual machines. Fixed capacity made it difficult to respond when demand increased or decreased.

Work delivered: Designed the AWS foundation and migrated internal systems, applications, and development environments from the VMware setup. The new model replaced manually managed VM capacity with infrastructure designed for more flexible scaling.

Outcome highlights

  • Internal systems and development environments moved from VMware to AWS
  • Capacity could be adjusted according to demand
  • Less dependence on manually provisioned virtual machines
  • A cloud foundation was established for future development and scaling
  • Ongoing maintenance and evolution of the AWS environment

Client profile

Software Consulting UK

Technology tags

AWS Docker Terraform Ansible Grafana

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