Cloud bills you can read and deploys nobody dreads
Migrate to Google Cloud or AWS, automate the deploys, and get monitoring that tells you something. On your server, ours, or both.
For teams paying for servers nobody fully understands. Four to eight weeks for most migrations.
Deploy, example
Production
Pipeline
- 11:02:10Merged a1f3c9e to main
- 11:02:48Tests passed, image built
- 11:04:15Staging healthy, smoke checks green
- 11:06:30Traffic moved to the new version. The previous one stays running until the next release.
Rollback is one command back to the previous version.
The stack we reach for
| Layer | Tools |
|---|---|
| Cloud platforms | Google Cloud, AWS |
| Infrastructure as code | Terraform |
| Deploys | GitHub Actions, Docker, Cloud Run |
| Monitoring | Cloud Monitoring and Cloud Logging, or the AWS equivalents |
How Polaris ships
Polaris, our own ERP, deploys in stages on Cloud Run: a release starts with no traffic, takes a small share, and passes a health check before the rest follows. PgBouncer holds the database connections flat as it scales out, and reports read from a replica so a month-end report never slows the till.
A typical engagement
Four to eight weeks for most migrations. The assessment in the first phase is what sets the real dates, and we revise them out loud if the estate is larger than it looked.
- Weeks 1-2
Assessment and plan
We read your current setup, measure what it costs to run, and write the target architecture down before touching anything.
- Weeks 3-4
Migration
Workloads move behind a cutover plan with a tested rollback. Traffic switches when the new stack has already been serving a copy of it.
- Weeks 5-6
Pipelines and monitoring
Deploys become one merge. Dashboards, alert thresholds, and on-call routing go in with it.
- Weeks 7-8
Tuning and handover
Right-sizing, reserved capacity where it pays, and enough runbook and training that your team can operate it without us.
Work we get asked for
Most requests are one of these. If yours is not, the call is still free.
- Cloud migration
- Move off on-premise boxes or legacy hosting. We handle assessment, planning, the move itself, and the cost work after it.
- CI/CD pipelines
- Get from a merged commit to production without anyone SSHing into a server. Tests, staging, and a rollback path that has been used at least once.
- Containers
- Containerised applications on Cloud Run or a single VM, sized to the traffic they actually get, with the image built once and promoted through each stage.
- AI and ML infrastructure
- The infrastructure under model workloads: serving, GPU capacity, vector storage, and the pipelines that retrain and redeploy.
Written up from production
- 7 min read
Polaris ERP architecture: scaling lessons from Pakistani retail
How Polaris ERP is built: a Vue front end on Django and PostgreSQL, tenant isolation in the ORM, connection pooling, a read replica for reports and staged deploys.
Read the post - 7 min read
I shipped a race condition that double-charged customers, and other war stories
Five production bugs I shipped in Django, PostgreSQL and LangChain code, why each one happened, and the fix that held.
Read the post - 3 min read
Structured logging for AI debugging
Why one structured event per request, with errors that carry a why and a fix, makes logs an AI assistant can actually debug from.
Read the post
Questions we get asked
Send us your current bill and architecture.
Email or WhatsApp it over. We read it and come back the same working day with what we would change and what we would leave alone.
Book a call- First reply
- same working day
- Hours
- Set to your time zone
- Built in
- Lahore, Pakistan