Deployment automation across ecosystems
Shipped production applications through Kamal, Capistrano, Mina, Gigalixir, Fly.io, and Heroku, alongside container-based deploys built on Docker, docker-compose, and private registries.
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Expertise
I ship and operate what I build — pipelines, servers, containers, and the monitoring that proves it works.
I'm not a dedicated DevOps engineer and I don't present myself as one. I'm a backend engineer and architect who has spent twenty years staying responsible for what happens after the merge: provisioning VPS boxes by hand, tuning Nginx in front of production traffic, moving projects onto container-based deploys, and standing up monitoring that makes a problem visible before a user reports it. I'd argue that makes me a better architect rather than a second-rate SRE — when I design a system, I already know how it will be deployed, what it will cost to run, and which parts will be unpleasant to operate.
Evidence
Shipped production applications through Kamal, Capistrano, Mina, Gigalixir, Fly.io, and Heroku, alongside container-based deploys built on Docker, docker-compose, and private registries.
Provisioned and configured Ubuntu and Debian VDS/VPS environments by hand, and tuned Nginx and Apache for production: routing, caching, and performance. AWS EC2 and S3 where managed infrastructure was the better fit — including the GPU instances behind the LLM inference work.
Introduced and maintained pipelines on GitHub Actions and GitLab CI, moving teams off manual release steps onto automated, repeatable delivery.
Deployed and operated Prometheus, Grafana, Grafana Alloy, and Zabbix for infrastructure and application monitoring and integrated Sentry, Rollbar, and Bugsnag so failures arrive with context instead of as user complaints.
Tools & practices
Where this came from
Contact
Happy to talk through the specifics — what worked, what didn't, and what I'd do differently.
panov.eduard.k@gmail.com