CLOUD INFRASTRUCTURE & DEVOPS
Cloud infrastructure engineering for AWS, Azure and GCP, with CI/CD, Terraform, Docker, Kubernetes where appropriate, monitoring, scaling and reliable releases.
Make deployments repeatable and operations observable.
We design cloud infrastructure and delivery systems for applications that need reliable releases, controlled access, backups and predictable operating costs. The work can include containerized services, infrastructure as code, monitoring and incident preparedness.
We assess workload characteristics, availability goals, existing systems and team capacity before selecting AWS, Azure, GCP or managed hosting. A well-operated small deployment is often preferable to a cluster that nobody can maintain.
CUSTOMIZED FOR YOU: Cloud provider, service boundaries, CI/CD, environments, secrets, network controls, capacity planning and observability.
TECHNOLOGIES WE CAN USE: AWS · Azure · GCP · Docker · Terraform · GitHub Actions · Kubernetes · OpenTelemetry. We choose the stack for your requirements, rather than forcing a fixed set of tools.
If releases require 90 minutes of manual operations twice a week, automation targets three hours of repeat deployment work; stability gains must be measured separately.
This is an illustrative calculation of manual effort, not a client case study or guaranteed time saving. Actual impact depends on your workflow.SPECIFIC. USEFUL. CUSTOM.
Cloud architecture and deployment topology reviews
↗Infrastructure as code, secrets and environment separation
↗CI/CD pipelines, logging, metrics, alerts and incident runbooks
↗Backup/restore plans, cost monitoring and scaling validation
↗We define the features, integrations, timeline, cost, and handover around your business process before starting work. Discuss your project with the team.
FROM PROBLEM TO WORKING SYSTEM.
Set reliability and cost objectives
Start by agreeing availability needs, recovery time, data retention and maximum operational complexity. These requirements drive compute, storage, networking and redundancy choices.
What we validate
- Identify critical services and their dependencies
- Set alert thresholds from user impact, not vanity metrics
- Estimate baseline and growth costs
Automate delivery and infrastructure configuration
Declarative infrastructure makes changes reviewable and reproducible. Pipelines should test changes and manage credentials securely, with approval steps where failures would be expensive.
What we validate
- Separate production and nonproduction secrets
- Run migrations with rollback planning
- Review least-privilege IAM and network exposure
Test failure, not just success
Recovery plans only work when practiced. We check backups, monitoring, degraded-mode behavior and the team response to provider or dependency outages.
What we validate
- Conduct a restore test with realistic data
- Measure recovery time for critical components
- Document who responds to alerts and how incidents are closed
Implementation starts with the business problem, continues through architecture reviews and ends with tested deployment and documentation. Explore our engineering guides ↗
THE PRACTICAL DETAILS.
What should we build first for cloud infrastructure, devops & deployment engineering?
We start with the core business task, users, integrations and constraints, then agree on a testable release. Our cloud infrastructure & devops approach includes real acceptance criteria rather than an assumed feature list.
Which technology stack is appropriate?
We may evaluate AWS, Azure, GCP, Docker, Terraform depending on the requirements. The final stack follows security, expected load, integrations and long-term maintainability.
What about integration, testing and launch?
We inspect the tools and API access before promising a connection. We plan data validation, permissions, failure handling, testing, deployment, monitoring and handover. Scope, timing and costs are discussed after discovery.