Services — DevOps
DevOps
We set up the delivery and monitoring practices that let a team ship without holding its breath, then hand them over documented. Useful whether we built your system or your own developers did.
Where this work shows up
Delivered systems rather than capability claims. The case studies carry the details.
- Multi-facility logistics platforms
- Commerce under seasonal load
- Systems with 24/7 availability requirements
- Regulated and payment workloads
Technology
The delivery toolchain
Pipelines
- GitHub Actions
- GitLab CI
- Azure DevOps
- AWS CodePipeline
- Trunk-based development
Infrastructure as code
- Terraform
- AWS CDK
- Pulumi
- Remote state management
Containers and runtime
- Docker
- Kubernetes
- Helm
- Blue/green and canary releases
Observability and security
- Metrics and SLO alerting
- Distributed tracing
- Structured logging
- Secrets management
- Image and dependency scanning
DevOps is the practice that decides whether a good system stays good. A platform running four port facilities or a commerce site under seasonal load cannot depend on a manual release process and someone remembering how the servers were configured. So the delivery pipeline, the infrastructure definitions, and the monitoring are part of how we build, not a phase that gets cut when a deadline tightens.
We also take this on as its own engagement, including for systems other teams built. That work starts with an audit of the current pipelines, environments, and incident history, then sequences improvements by how much time or risk each one removes. Manual deployments, environments that drift apart, and production issues discovered by customers are the usual first three.
What you keep is infrastructure defined in code that your developers can read and change, pipelines that run on every commit, monitoring that was in place before launch, and documentation with the training to use it. The measure of the work is that the system keeps shipping cleanly without us, which is the same standard behind long-time clients telling us they spend nothing on maintaining their systems years later.
What DevOps changes when delivery is automated
Releases stop being events
Automated build, test, and deploy on every change, so shipping is routine rather than a scheduled evening with everyone on standby.
Environments that match
Development, staging, and production built from the same definitions in version control, which removes configuration drift as a source of outages.
Problems surface first internally
Metrics, tracing, and structured logs in place before launch, so you learn about issues from your dashboards rather than from your customers.
Consistent deployments
Containerized services that behave the same on a laptop and in production, which ends the class of bug that only appears after release.
Security inside the pipeline
Secrets management, dependency and image scanning, and access controls enforced automatically on every change rather than reviewed after an incident.
How a DevOps engagement runs
- 1
Audit and Discovery
Measuring where the time and the risk actually go.
Current State Assessment
Reviewing existing pipelines, infrastructure, deployment steps, and incident history.
Pain Point Identification
Finding where teams lose time, whether that is slow builds, unreliable tests, manual deployment steps, or unclear ownership.
Risk Review
Identifying the manual steps and single points of knowledge that would hurt most if they failed.
- 2
Strategy and Roadmap
Sequenced improvements rather than a rebuild.
Toolchain Selection
Choosing delivery, infrastructure, and monitoring tools that fit your environment and the skills of your team.
Migration Plan
Improvements ordered to deliver value early, without a cutover that stops other work.
- 3
Pipeline Implementation
Automating the path from commit to production.
Pipeline Build
Automated build, unit test, integration test, and deployment stages for every service.
Branch Strategy
A branching and release model that matches how your team actually works and how often you want to ship.
Release Automation
Staged and reversible release patterns, so a bad deployment is a rollback rather than an emergency.
- 4
Infrastructure Automation
Moving environments into version control.
Infrastructure as Code
Bringing manually managed infrastructure into Terraform or CDK with managed state and review.
Environment Parity
Development and staging environments that match production closely enough to trust the results.
- 5
Monitoring and Response
Knowing before your customers do.
Metrics and Alerting
Alerting based on user-visible symptoms rather than every internal fluctuation, which keeps alerts meaningful.
Distributed Tracing
Request tracing across services, so an incident has a clear scope instead of a guess.
Runbooks
Common incident responses documented and scripted, so responding does not depend on one person being awake.
Why RothTech
The usual alternative is asking developers to handle delivery alongside feature work, which means it gets attention only after something breaks. Hiring a dedicated specialist is the other option, and it is a permanent cost for work that is heaviest at the start. We set the pipelines, infrastructure definitions, and monitoring up properly, document them, and train your team to own them. Nothing we hand over depends on us being on retainer, which is why clients who keep working with us do it because they want the same team on the next project rather than because leaving would be expensive.
Frequently Asked Questions
Related Case Studies
Retail Sourcing & Reseller Marketplace Platform
A marketplace connecting retailers sourcing products with individuals reselling them for rewards, covering marketing, inventory, and transactions in one system, down to the warehouse app that scans the package.
Transport Management System for Port Logistics & Cartage
A custom transport management system for port cartage and warehousing, deployed across four major sea ports: container tracking, vessel schedule integration, and automated billing on one platform.