DevOps as a service, without the retainer.
Most providers sell an ongoing engagement or an engineering team to manage. We sell the outcome: send a GitHub repository, get it deployed and running — as a fully managed API, or inside your own AWS, GCP, or Azure account.
What DevOps as a service actually covers.
Strip away the branding and every provider is offering the same underlying work — the delivery path between a repository and a running application.
Hire it, rent it, or buy the outcome.
These are genuinely different purchases, and the right one depends on whether your constraint is capacity, expertise, or simply getting one application live.
Three steps. Zero DevOps on your side.
You bring the repository. We bring the pipeline, the infrastructure, and the on-call know-how.
Connect repository
Send us your GitHub link. Public or private, monolith or microservice — it doesn't matter.
We configure
We detect your stack, wire up the build, environment, and secrets, and provision the infrastructure.
Ready to deploy
Your API goes live with a URL, logs, and monitoring. Managed by us, or handed to your cloud.
Managed for you, or on your infrastructure.
Start fully hands-off, or keep everything inside your own cloud account. Switch whenever you like.
When buying the outcome makes more sense.
You built something with AI tools and it stops at localhost
Code from Lovable, Bolt, Replit, v0, or Cursor is usually fine. What is missing is everything around it — environments, secrets, a database that persists, a domain, and a build that runs somewhere other than your laptop. That is a deployment problem, not a coding problem. We cover the reasons this happens in the production readiness checklist, and the platform trade-offs in Railway vs Render vs Vercel vs hiring an expert.
A customer wants your software inside their own cloud
Enterprise buyers increasingly ask vendors to run inside the customer's account rather than a shared multi-tenant platform. Doing that once, properly, is a different exercise from running your own SaaS — we walk through the architecture in deploying SaaS inside a customer's AWS VPC.
You have a model and you need it behind an API
A trained model in a notebook is not a service. Getting to an endpoint that other systems can call means packaging, provisioning, and a deploy path — the same delivery work, applied to a different artifact. See from Jupyter notebook to production API.
You are moving off a platform you have outgrown
Leaving a host like Heroku is bounded work with a working application on either side of it — which makes it an unusually good fit for outside help, since there is nothing ongoing to commit to. The four directions that migration can take, and what tends to break along the way, are in our honest comparison of Heroku alternatives.
Your team can do this — but not this quarter
Plenty of teams have the skills and no spare attention. Handing one deployment to an outside provider is often cheaper than the context-switch, and it does not commit you to an ongoing engagement.
Frequently asked questions
What is DevOps as a Service?
DevOps as a Service means an outside provider runs the build, deployment, and infrastructure work that an in-house DevOps engineer would otherwise own — the CI pipeline, environments and secrets, provisioning, deploys, and the logging and monitoring around them. Most providers deliver it as an ongoing engagement. DeployForMe delivers it per project: you send a repository, we hand back a running deployment.
How is this different from outsourced DevOps or a consultancy retainer?
Outsourced DevOps normally means renting engineering capacity — a team works alongside yours on a recurring engagement, and you direct the scope. DeployForMe is scoped around an outcome instead: a specific repository, deployed and running. There is no team to direct and no recurring commitment required to get started.
Do I still need to hire a DevOps engineer?
Not to get an application deployed and running. Hiring makes sense when you need someone in the building every day — reacting to incidents in your own systems, owning long-term platform decisions, and carrying institutional context. If what you actually need right now is a repository turned into a working deployment, that does not require a full-time hire.
What do managed DevOps services usually include?
Typically: a build pipeline, environment and secret configuration, provisioned infrastructure, a repeatable deploy path, and logging and monitoring so failures are visible. Providers differ in how much they take on beyond that — some add ongoing platform work, security review, or cost management as separate engagements.
Can you deploy into our own AWS, GCP, or Azure account?
Yes. We can run the deployment as a fully managed API on our side, or set it up inside your own AWS, GCP, or Azure account, where your data, billing, and access controls stay under your organization's control. You can start with one model and move to the other later.
Do you work with applications built using AI coding tools?
Yes. Code generated with tools like Lovable, Bolt, Replit, v0, or Cursor deploys like any other codebase — the gap is usually configuration, environments, secrets, and infrastructure rather than the application code itself. Send the repository and we will tell you what it needs.
What do you need from us to get started?
A GitHub repository link — public or private — and a short description of what you are aiming for. A human reads every request, and we reply within 24 hours. There is no commitment required to get a quote.
Send us the repository.
Tell us where the code lives and what you are aiming for, and we will reply with a plan. A human reads every request, we reply within 24 hours, and there is no commitment to get a quote.
Request deployment →