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.
How To Read This Page
Capability areas first, tooling second
We organize our technical practice into four domains: cloud and infrastructure, delivery and automation, data and analytics, and security and operations. The tools listed under each domain are the ones our engineers actively work with — chosen for maturity, support, and the ability for a client team to operate them after handover.
- Infrastructure defined in code and stored in version control.
- Builds, tests, and security scans automated rather than run by hand.
- Monitoring, logging, and alerting configured before production.
- Runbooks and architecture documentation delivered with the work.
Cloud & Infrastructure
Environments provisioned as code, rebuildable from a repository
Domain 01
Cloud platforms and infrastructure as code
Environments are designed for the workload rather than assembled by hand. Compute, storage, networking, and managed services are provisioned through version-controlled templates so every environment can be rebuilt, reviewed, and audited.
- Cloud Platforms
- AWS EC2 · AWS S3 · AWS RDS · Aurora · AWS Lambda · API Gateway · CloudFront · Route 53
- Infrastructure as Code
- Terraform · AWS CloudFormation
- Operating Systems & Networking
- Linux (RHEL / Ubuntu) · Windows Server · Amazon VPC · Nginx · Load Balancing
Domain 02
Delivery pipelines, containers, and automation
Build, test, security scanning, and deployment run as automated pipelines. Containerized workloads are orchestrated with mature schedulers, and configuration drift is closed out with automation instead of manual remediation.
- DevOps & CI/CD
- Jenkins · GitLab CI/CD · GitHub Actions · Azure DevOps
- Containers & Orchestration
- Docker · Kubernetes · Helm · Amazon EKS · Amazon ECS · AWS Fargate
- Automation & Configuration
- Ansible · Python · Bash
Data & Decisions
Pipelines, governed storage, and reporting the mission can act on
Domain 03
Data engineering, analytics, and platforms
Pipelines move batch and streaming data into governed storage, where analysts and mission owners consume it through reporting layers. Database work covers schema design, performance, and migration off legacy systems.
- 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
- Programming & Scripting
- Python · Bash · SQL
Domain 04
Security engineering and operational visibility
Identity, encryption, and boundary controls are configured as part of the build, not retrofitted. Logging, metrics, and audit trails are in place before a workload is considered production ready.
- Security
- AWS IAM · AWS WAF · AWS KMS · CloudTrail Auditing
- Monitoring & Observability
- Amazon CloudWatch · AWS CloudTrail
Reference
Full technology stack
A consolidated list for technical evaluators. Presence here indicates working familiarity within our engineering team.
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
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