Most early SaaS teams don't need a DevOps hire. They need three or four pieces of managed infrastructure wired together correctly, and a pipeline that deploys without anyone touching a server by hand. Hiring for infrastructure too early is one of the more common ways an early-stage team burns runway on a role the product doesn't need yet.
Here's the setup we reach for most often when a team is ready to go to production on Google Cloud, and why each piece earns its place.
Cloud Run for the application
Cloud Run runs a container, scales it to zero when there's no traffic, and scales it back up when there is. For an application that doesn't have constant load — which describes most early-stage SaaS products — that scale-to-zero behavior is the difference between paying for idle compute around the clock and paying for what actually gets used.
It also removes an entire category of operational work: no OS patching, no instance fleet to manage, no capacity planning for a launch that might not happen on schedule. You ship a container image; Cloud Run runs it.
Cloud SQL for the database
A managed Postgres or MySQL instance handles backups, patching, and failover without anyone owning that as a manual task. The alternative — running your own database on a VM — means someone on the team is implicitly on call for it, whether or not that's written down anywhere. Cloud SQL makes that an explicit, managed service instead of an unspoken responsibility.
Firebase Hosting for the static frontend
If the frontend is a static build — a React or Next.js export, a marketing site, a docs site — Firebase Hosting serves it from a CDN with zero servers to manage and effectively no idle cost. It's a small piece, but it's one less thing running on infrastructure that needs to be watched.
Docker as the shared contract
Packaging the application as a Docker image is what makes the rest of this work. It's the same artifact that runs on a developer's laptop, in CI, and in production — which means "it works on my machine" stops being a debugging category. Cloud Run consumes that image directly, so there's no translation step between what was built and what gets deployed.
GitHub Actions for the deploy path
A small pipeline — build the image, run tests, push to a registry, deploy to Cloud Run — turns "someone SSHes in and updates the app" into a process that happens the same way every time, with a log of what shipped and when. That log is worth more than it sounds like on paper: the first time something breaks in production, being able to point at exactly which deploy changed what turns a guessing game into a five-minute diagnosis.
What this looked like in practice
Unmaze, a fast-growing English tutoring platform, had a fully built application that had never been deployed to the cloud, and it was showing performance and stability problems under real traffic. We moved it to Google Cloud Platform on exactly this stack — Cloud Run, Firebase Hosting, and Docker as the packaging format — which eliminated the instability that had been caused by high database connection volume, and meant the app cost effectively nothing during idle periods, with full cloud benefits from the first day in production.
None of this required Unmaze to hire an infrastructure engineer. It required choosing managed services that remove the operational work by default, and setting up a deploy path once, correctly.
If your application is built and ready but still isn't running anywhere production-grade, that first move to the cloud is exactly the gap cloud migration closes — and if the team you have is focused entirely on product, DevOps consulting is the way to get this in place without pulling anyone off the roadmap.
