Self-hosting CI Runners is a Trap

And why third-party SaaS runners are a better path for most teams

In the quest for faster and more cost-effective development pipelines, many engineering teams eventually ask the same question: what if we self-host our CI runners?

It sounds smart. By running your own infrastructure, you expect lower costs, faster builds, and more control. GitHub even encourages it. Self-hosted runners come with no per-minute billing and no built-in concurrency limits.

But many teams who go down this path discover that what starts as a simple optimization quickly becomes a long-term engineering distraction. Over time, almost every company lands in one of two situations:

1. They run suboptimal CI infrastructure, never quite reaching the cost and performance goals they hoped for.

2. Or they pour time and resources into building and maintaining tools that have nothing to do with their actual product.

Let’s explore why teams self-host, what it really takes to do it well, and why more companies are turning to external platforms to handle CI at scale.

Why Teams Choose to Self-Host

Engineering teams often turn to self-hosted CI runners in search of better performance, lower costs, and more control than GitHub-hosted runners can offer.

• Performance gains: GitHub-hosted runners rely on outdated hardware with weak single-core CPU performance, limited disk I/O, and a 1 Gbps network cap (around 125 MB per second). This affects test speed and caching. Self-hosted runners can use modern CPUs, NVMe storage, and higher bandwidth to significantly accelerate pipelines.

• Lower cost: At $0.008 per minute, GitHub-hosted runners become expensive at scale. Comparable or better EC2 instances often cost four times less or up to fifteen times less with spot instances. However, comparing raw infrastructure cost to a managed service involves trade-offs in reliability and effort.

• Full environment control: Self-hosting allows teams to select the exact hardware they need, including GPUs or ARM-based processors. It also makes it possible to enforce internal security policies and compliance requirements, and to customize the build environment as needed.

• Unlimited parallelism: GitHub enforces concurrency limits based on plan tiers, typically sixty concurrent jobs for Team plans and five hundred for Enterprise. Self-hosted runners avoid these caps entirely. You can run as many jobs as your infrastructure can support.

What You Are Actually Signing Up For

Most teams start with persistent virtual machines running GitHub’s runner agent. It is quick to set up and gives an immediate speed boost. But problems arrive just as quickly:

• State leakage between jobs leads to flaky builds and security risks

• Manual maintenance becomes necessary to keep environments clean and secure

• Wasted capacity creeps in when runners sit idle outside peak hours

• Long queues and slow feedback loops during commit peaks, when limited concurrency causes job backlogs

• Low performance on installation and caching steps, as GitHub’s cache backend is located in remote Azure regions. This leads to slow job execution and increased network egress costs. To mitigate this, teams must implement colocated caching infrastructure—yet another system to build and operate, disconnected from their core business and tech stack

To improve isolation and scalability, many teams adopt Kubernetes-based approaches like GitHub’s Actions Runner Controller. These solutions offer more control, but come with significant complexity. They require deep Kubernetes expertise and hands-on management of job lifecycle, autoscaling, secrets, and scheduling. On top of that, teams must also:

• Maintain and update base images

• Monitor runner availability and health

• Set up alerting and incident response

At this point, you're not just configuring CI. You’re running a mini platform team to operate and scale your internal CI infrastructure.

The Real Costs of Self-Hosting

Operational overhead

When switching from GitHub hosted to self hosted runners, you become the owner of the service and its reliability. Jobs can get stuck, machines can malfunction, and concurrency issues can appear. Your team is now responsible for diagnosing CI failures, investigating developer complaints, and restoring service quickly. CI becomes a critical internal tool, close in importance to your production infrastructure. If a build is blocked, you may be unable to deploy a bug fix or security patch. Any downtime directly impacts your ability to deliver. Even with automation in place, someone must be accountable, available, and ready to intervene when issues occur.

Performance vs cost tradeoff

If you start a new machine instance for every CI job, jobs often wait over one minute to begin, sometimes more depending on the current capacity of the cloud region. Developers notice and complain. GitHub-hosted runners usually start jobs in under 30 seconds. To compensate, teams often preprovision standby instances to improve job startup time. But CI workloads are spiky and vary by time of day, so these machines often remain idle. This leads to low utilization and wasted compute. We've seen companies pay more with self-hosted runners than with GitHub-hosted ones. Public cloud providers do not offer the right abstractions to manage this tradeoff efficiently.

Security risk

GitHub’s hosted runners come with built-in isolation. When you self-host, you own the security surface. Malicious pull requests can run code on your machines. Improper secrets handling can lead to leaks. You need to implement strong access controls, isolate runners, regularly patch systems, and monitor for abuse. Any lapse can compromise your internal network.

Why Third-Party SaaS CI Runners Are a Better Fit for Most Teams

To avoid these challenges, many companies now rely on third-party SaaS CI runner platforms. These services integrate directly with GitHub Actions and provide high-performance runners without the need to manage infrastructure.

What they offer:

• Fast machines with modern CPUs, NVMe disks, and large memory

• Ephemeral job isolation to prevent state leakage and security risks

• Elastic concurrency that automatically scales with workload

• Clear, usage-based pricing with no surprise infrastructure costs

• Zero maintenance with no updates, patching, or autoscaling to manage

Adoption is often as simple as changing a line in your workflow configuration:

runs-on: provider-4vcpu-ubuntu

Some platforms also provide:

• Advanced caching and artifact storage

• A wider range of instance types (eco, standard, performance) to match workloads where single-core performance matters

• Flaky test detection and CI analytics

• Support for custom architectures (GPU, ARM)

• Deployments inside your own cloud account for compliance or data residency

Shipfox is one example in this category. It focuses on performance, developer experience, and CI visibility. But it is part of a broader shift toward platforms that give you the performance of self-hosted runners without the cost and complexity.

Here’s how GitHub-hosted, self-hosted, and third-party SaaS runners compare across key dimensions like performance, cost, and operational complexity:

Conclusion: Build What Matters, Delegate the Rest

Your CI pipeline is critical to your team’s workflow, but it is not your product. Unless you are a company specializing in infrastructure, managing CI runners is a distraction from your core mission.

Self-hosted runners may be the right fit in rare cases, such as highly specialized hardware requirements or extreme compliance constraints, but for most teams, the trade-offs are not worth it.

Third-party SaaS runners offer a balanced and cost-effective solution. They provide the speed and flexibility that growing teams need, without the maintenance burden that slows them down. They allow your engineers to focus on what truly matters: building and shipping software.

Instead of managing another layer of infrastructure, let someone else keep your runners fast, secure, and available.