I keep payment infrastructure up, and write down why.
I’m Chris Roos, a Site Reliability Engineer at Fortis.
Five years across infrastructure-as-code, deployment pipelines, containerized delivery, and observability. The pages below are the reasoning, not the résumé.
Open to Senior SRE and DevOps roles
How I think about the work
The opinions I've arrived at after five years of keeping payment infrastructure running, written down with the reasoning and the trade-offs.
Strategy
What I optimize for
Toil, delivery speed, and reliability as a constraint rather than a goal, plus why contract tests beat end-to-end suites.
ReadPlaybooks
How I use the tools
Terraform, containers, pipelines, observability, and Python, with real configuration and the anti-patterns I've had to unwind.
ReadAI Workflow
Working with Claude
Briefs, guardrails, and scheduled agents: how I get real operational work out of AI without letting it near production.
ReadReading
Where it came from
Thirty-four books that moved a position I hold, each pointing at the page here where the idea shows up.
ReadExperience
Five years of infrastructure, and a route into it that did not start there. How I got here.
October 2021 — Current
Site Reliability Engineer / Fortis
- Design and maintain cloud infrastructure using Terraform and Spacelift across a large multi-account AWS environment.
- Build and maintain CI/CD pipelines (Jenkins, Bitbucket Pipelines, GitLab CI) supporting continuous delivery for production systems.
- Support containerized services on ECS/Fargate, including deployment strategies like blue-green releases.
- Work on cloud cost optimization, database infrastructure (RDS), and right-sizing initiatives.
- Contribute to security and compliance efforts, including credential management, secrets handling, and data encryption practices.
- Use observability tooling (Datadog, CloudWatch, ELK) to monitor system health and support incident response.
- Explore and apply AI-assisted tooling to improve engineering workflows and automation.
June 2017 — Current
Freelancer / Freelance IT Services
- Built and maintained client websites and custom web apps (Python, HTML/CSS/JS), focused on performance and UX.
- Built web scraping and data collection tools for lead generation and competitor/market analysis, delivered as automated reports for client decision-making.
- Managed Microsoft 365 and AWS accounts for clients.
Before infrastructure
I came to this work from the data side. Both of these are where the automation habit started, and neither is the job I am selling.
Marketing Director, OmniFund
Used Elasticsearch to index and analyze competitor websites, informing market research and strategy.
2021
Data Analyst, Stukent
Built predictive models and web scraping projects to collect and analyze market data.
2017 – 2018
The stack, and what I do with it
Grouped the way the work is grouped rather than by category. Every tool links to where I explain how I use it.
Infrastructure as code
Terraform playbookRemote state from day one, modules as components rather than as environments, and a plan a reviewer will actually read.
Containers & runtime
Containers playbookConfiguration comes in, the container doesn't go out. It boots with no cloud credentials, and blue/green means you can really roll back.
CI/CD
Pipelines playbookThe pipeline is the single source of truth for whether a change is safe. Logic lives in scripts, it stays under fifteen minutes, and every failure has a class.
Observability
Observability playbookLogs, metrics, and traces answer different questions. Structured logs are the prerequisite, SLOs do the arguing, and alerts point at symptoms.
Automation & AI
Python playbookMost operational work is glue. Make it safe to run twice and dry run by default, and brief the model before you prompt it.
Projects
Two I owned end to end, from the argument for doing them through to running them afterward.
Elasticsearch Observability
Built the logging and search layer for services running across several environments, so that answering "what just happened" stopped meaning connecting to boxes and grepping.
I carried it from the argument for doing it through to operating it afterward, which is the part that decides whether an observability project survives its first quiet quarter. The lasting lesson is that structured logs are the prerequisite: an index full of unparsed strings is a slower grep, not observability.
Spacelift & Terraform
Moved infrastructure changes out of the console and into reviewed, reproducible Terraform runs, with Spacelift as the one place a plan gets proposed, read, and applied.
The goal was not automation for its own sake. It was making the gap between what was approved and what actually shipped visible, because drift you cannot see is drift nobody fixes. That is also why I treat state as production data.
Writing
Short pieces on one problem each: alerting, on-call, incidents, toil, cost. The longer positions are in the strategy and the playbooks above.
Tech debt
Site Reliability Engineering: Your Secret Weapon Against Tech Debt
How SREs turn mounting technical debt into a manageable, scalable system.
Alerting
Alerts That Earn the Page
If it fires at 3am and there is nothing to do, it is not a page. How to build a rotation that believes its own pager.
Incidents
The First Hour of an Incident
Three roles and one shared document. What a small team actually needs, and why mitigation comes before understanding.