Technologies
The engineering toolset behind our delivery
These are the platforms and tools our engineers work with across cloud, automation, and data engagements. They represent capability areas, not claimed contract past performance.
Cloud Platforms
- AWS EC2
- AWS S3
- AWS RDS
- Aurora
- AWS Lambda
- API Gateway
- CloudFront
- Route 53
DevOps & CI/CD
- Jenkins
- GitLab CI/CD
- GitHub Actions
- Azure DevOps
Infrastructure as Code
- Terraform
- AWS CloudFormation
Containers & Orchestration
- Docker
- Kubernetes
- Helm
- Amazon EKS
- Amazon ECS
- AWS Fargate
Data Engineering
- AWS Glue
- Amazon Kinesis
- MSK / Apache Kafka
- Apache Spark
Analytics & Business Intelligence
- Power BI
- Tableau
- SQL
Databases
- PostgreSQL
- MySQL
- Amazon RDS
- Amazon Aurora
Automation & Configuration
- Ansible
- Python
- Bash
Monitoring & Observability
- Amazon CloudWatch
- AWS CloudTrail
Security
- AWS IAM
- AWS WAF
- AWS KMS
- CloudTrail Auditing
Programming & Scripting
- Python
- Bash
- SQL
Operating Systems & Networking
- Linux (RHEL / Ubuntu)
- Windows Server
- Amazon VPC
- Nginx
- Load Balancing
How We Apply Them
Tools chosen for the environment, not for novelty
We favor mature, well-supported technologies that client teams can operate after we hand work over. Every deployment is codified, documented, and reviewable.
- Infrastructure defined in Terraform or CloudFormation and stored in version control.
- Builds, tests, and security scans automated in CI/CD rather than run by hand.
- Monitoring, logging, and alerting configured before a workload goes to production.
- Runbooks and architecture documentation delivered with the engineering work.
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