Every environment we run starts as code. Terraform, CloudFormation, or Ansible describes the network, compute, and identity for development, staging, and production, and a CI/CD pipeline builds, tests, and security scans every merge before it can reach any of them. Container images carry resource limits, orchestration manifests live next to the application code, and the toolchain is integrated so a developer sees build, scan, and deploy status in one place. That is the DevOps practice: assessment and strategy first, then pipelines, infrastructure as code, containerization and orchestration, monitoring and logging, and DevSecOps controls.
The applications that run through those pipelines are ours to build as well. Web platforms on Django, FastAPI, Node, React, and Next.js. Mobile apps on Flutter and React Native. REST and OData APIs, microservices, and event-driven architecture on Kafka, RabbitMQ, and SQS. Data stores from PostgreSQL and MySQL to MongoDB, DynamoDB, and InfluxDB, with serverless functions on Lambda and Google Cloud Functions. Foundation model integrations and ML and analytics tooling ship through the same pipeline as everything else, with the same tests and the same rollback.
Once a release is in production, monitoring and logging feed alerts with a defined escalation path, DevSecOps controls keep scanning dependencies, images, and configuration after deploy, and runbooks cover the incidents that actually happen. Every release is one command, and so is rolling it back. The team that built the pipeline is the team on call for it, on AWS, Azure, GCP, or a multi-cloud estate.
Reference architecture
DevOps and application delivery
Every merge is built, tested, and scanned by the CI pipeline, infrastructure as code and container images provision the runtime on your cloud, and the web, API, mobile, and data systems that run there report back through monitoring and logging.
What We Do
Where this practice does its work.
CI/CD pipelines
Build, test, and security scan on every merge, environment promotion from development to production, and one-command rollback, integrated with the toolchain your developers already use.
Infrastructure as code
Terraform, CloudFormation, and Ansible definitions for every environment, reviewed like application code, so development, staging, and production are reproducible from a repository.
Containers and orchestration
Container images with resource limits, orchestration manifests, and registries, on Kubernetes or the managed container services of AWS, Azure, and GCP.
Observability and DevSecOps
Monitoring, logging, and alerting with defined escalation, plus dependency, image, and configuration scanning that runs in the pipeline and keeps running after deploy.
Application delivery
Web platforms on Django, FastAPI, Node, React, and Next.js, mobile apps on Flutter and React Native, and REST and OData APIs and microservices, delivered through the pipeline to staging and then production.
Data and ML pipelines
Event-driven architecture on Kafka, RabbitMQ, and SQS, data stores from PostgreSQL and MySQL to MongoDB, DynamoDB, and InfluxDB, serverless functions on Lambda and Google Cloud Functions, and foundation model integrations and ML and analytics tooling on top.
How We Work
3 steps, each with a defined output before the next one starts.
Step 1 of 3
We review your architecture, operations, and compliance constraints, then deliver an assessment with a target design, a migration or build plan, and a business case.
01
Assess
We review your architecture, operations, and compliance constraints, then deliver an assessment with a target design, a migration or build plan, and a business case.
02
Build
We design, migrate, and automate on your cloud: infrastructure as code, pipelines, monitoring, and the application work that goes with it. Ends with a working system in staging.
03
Operate and Scale
We run production under an SLA: monitoring, patching, backups, incident response, and capacity reviews. Then we expand to the next system.
Tools and Platforms
What we work with.
Pipelines and IaC
Infrastructure as code for cloud accounts, networks, and compute
Pipelines and IaC
Configuration management and server provisioning
Pipelines and IaC
Container images for every service in the pipeline
Pipelines and IaC
Orchestration with resource limits and rolling deployments
Application
Python web framework for admin-heavy platforms
Application
Async Python APIs and integrations
Application
JavaScript services and APIs
Application
Component-based web front ends
Application
Server-rendered React applications
Application
Cross-platform mobile apps with native performance
Application
Cross-platform mobile apps for field and clinical use
Data and messaging
Relational store for transactional workloads
Data and messaging
Document store for flexible schemas
Data and messaging
Serverless key-value store on AWS
Data and messaging
Event streaming for event-driven architectures
Data and messaging
Message broker for service-to-service queues
Data and messaging
Managed queues on AWS
Cloud
Primary cloud platform for delivery and operations
Cloud
Cloud platform for Microsoft-centric estates
Cloud
Google Cloud, including Cloud Functions for serverless workloads