Self-hosted runners vs cloud CI/CD: A complete decision guide

Your CFO just asked about operational efficiencies across the engineering org. Tooling budgets are under the microscope, and suddenly CI/CD costs are getting attention. Sound familiar?

When the pressure’s on to cut software spend, CI/CD often looks like a tempting target. It’s visible, measurable, and seemingly easy to move. Maybe someone’s even asked, “Why don’t we just run this ourselves?”

Before you dive into self-hosting your CI infrastructure, it’s worth taking a step back.

This guide is here to help you navigate the real tradeoffs: not just cost, but complexity, reliability, and the hidden work that comes with managing your own runners. Whether you’re weighing your options or just trying to answer hard questions from leadership, this decision guide will help you make the right call for your team.

Why teams consider self-hosted runners

Most teams start evaluating alternatives when they encounter specific constraints or pressures that make their current setup feel limiting.

Budget scrutiny and cost optimization pressure

When leadership looks for operational efficiencies, tooling budgets often come under scrutiny first. CI/CD spending represents a clear line item that teams are asked to review.

Managing your own infrastructure can appear to offer straightforward savings: pay your cloud provider directly for compute rather than paying a third-party platform to manage it for you. However, this analysis often focuses on the most visible costs while overlooking the operational complexity.

Resource limitations and customization needs

Some teams hit walls with standard cloud offerings. You might need specialized hardware configurations, custom software installations, or specific operating system requirements that aren’t available through shared infrastructure.

Teams working with specialized requirements often feel constrained by standardized environments, even when those limitations affect only a subset of their workloads.

Performance bottlenecks

Teams experiencing slow build times or resource constraints sometimes look to self-hosted infrastructure as a solution. Network latency, limited caching options, or inability to pre-configure environments can create friction in development workflows.

The appeal of complete control over the execution environment becomes stronger when current performance doesn’t meet expectations.

Compliance and security constraints

Organizations in heavily regulated industries may face requirements that feel difficult to meet with shared cloud infrastructure. Concerns about data isolation, network access controls, or audit trail requirements can drive teams toward solutions they can fully control and monitor.

Existing infrastructure challenges

Teams already managing significant cloud infrastructure may find it complex to integrate CI/CD workflows with their existing systems. VPC configurations, IAM policies, and internal service access can create friction when using external platforms.

The desire to consolidate infrastructure management under existing cloud accounts and tooling makes self-hosting appear simpler from an operational perspective.

On paper, these reasons can make self-hosting seem like the logical next step.

The promise of cost control, customization, and tighter integration is compelling, especially when framed against perceived limitations of managed platforms.

But many teams make the leap without fully understanding what they’re signing up for.

The hidden costs you haven’t considered

Most teams focus heavily on the compute cost comparison while underestimating the full complexity of becoming their own CI infrastructure provider. The sticker price difference is just the beginning.

Infrastructure management overhead

Getting self-hosted runners working isn’t a weekend project. Self-hosted runners often mean Kubernetes, and Kubernetes has a steep learning curve.

You’ll need significant engineering time to set up clusters, configure autoscaling, implement monitoring, and build deployment pipelines.

And once your runners are operational, they need ongoing care. Kubernetes clusters require regular security patches, capacity planning, performance optimization, and incident response when things break. You’ll need expertise in container orchestration and pod scheduling, distributed systems networking, storage management and persistent volumes, plus security policies and RBAC configuration. This goes well beyond typical application development skills.

Most teams underestimate the initial effort significantly. What looks like a few days of work often stretches into months of development and testing, and a never-ending amount of maintenance and troubleshooting.

Scaling challenges

CircleCI’s cloud platform handles scaling transparently. When your PR creates a burst of concurrent jobs, new capacity appears instantly. With self-hosted runners, you manage the infrastructure that provides that capacity.

The complexity you’re taking on includes:

• Custom scaling scripts: Container runners can automatically spin up pods, but you’re still responsible for scaling the underlying Kubernetes cluster. Machine runners require even more custom automation using AWS Auto Scaling groups or similar mechanisms.

• Idle capacity management: Cloud platforms charge only for active job time. Self-hosted infrastructure often runs 24/7. To handle peak loads, you need spare capacity during quiet periods, and the cost of maintaining “warm” infrastructure adds up.

• Resource packing problems: Running different job sizes efficiently on shared infrastructure is harder than it looks. You might have aggregate capacity available but no single node with enough resources for a memory-intensive job. This leads to either over-provisioning or complex scheduling logic.

• Network egress considerations: Transmitting artifacts, test results, or routine communications with CircleCI involves network egress charges that can add up over time. These costs are frequently underestimated during initial planning. Teams often need to implement custom storage solutions or optimize workflows to keep budgets manageable.

• Boot time bottlenecks: Even with autoscaling solutions, instance boot times of several minutes are too slow for most CI workloads. Research from CircleCI’s own engineering team shows that compelling savings only materialize for very slow, infrequent builds, not the typical pattern of frequent, fast builds that most teams run.

And scaling is just one part of the operational burden. The challenges continue well beyond job execution.

Operational complexity

Self-hosted runners give you more control, but they also shift key responsibilities to your team. While CircleCI still manages orchestration, you’re now responsible for the infrastructure that runs your jobs, including uptime, performance, and incident response.

You’re also responsible for ensuring that jobs run reliably. That means provisioning enough runners so one failure doesn’t take down your pipeline, detecting and recovering from failed nodes automatically, and making sure each job runs in a clean environment without interference from others.

As you optimize for cost or customize your setup, you may even start rebuilding services that were once built in. Teams managing their own fleet of runners often need to implement their own caching, artifact storage, test result processing, and monitoring to fill the gaps.

Each new system adds complexity. Jobs can fail due to cluster issues, network configuration, or resource limits. Your team is now responsible for keeping the pipelines running and for maintaining the growing infrastructure behind them.

Decision framework: Is self-hosted right for you?

Given all these hidden factors, how do you decide if self-hosted runners make sense for your team? Use this framework to evaluate your situation objectively.

Step 1: Check your scale

Self-hosting only starts to make sense at higher volumes. Even if you have the appetite to take on additional maintenance overhead, if you’re not running 1000+ jobs per month, it’s unlikely the marginal compute savings will be enough for you to recoup the operational costs. If your usage is high and growing fast, you may be getting closer to the breakeven point.

Step 2: Compare true costs

Raw compute might be cheaper, but platform costs aren’t just about compute. Be sure to include network egress, storage, engineering time, monitoring, and the cost of maintaining reliability. If your projected savings hold up after factoring those in, you’re on solid ground.

Step 3: Evaluate your team’s capabilities

Do you have engineers comfortable with Kubernetes, infrastructure automation, and on-call responsibilities? Do you already have observability systems in place? If not, expect a steep learning curve and ongoing overhead that could outweigh any cost savings.

Step 4: Understand your risk tolerance

If CI downtime would block your delivery pipeline, the reliability of your infrastructure becomes mission-critical. Some teams have compliance or performance requirements that justify full control—but for most, managed platforms reduce risk and free up engineering time.

Summary: Self-hosted readiness checklist

Use this table to quickly gauge whether self-hosted runners make sense for your team right now.

Step	Key Considerations	If Yes	If No
1. Scale	• 1,000+ jobs/month? • Rapid usage growth?	Continue to Step 2	Stick with cloud; not worth the overhead
2. Cost model	• Infra, storage, egress, and team time accounted for? • Clear cost benefit?	Continue to Step 3	Reevaluate; cost case may not hold
3. Team readiness	• Infra/K8s experience? • Monitoring in place? • Time and staffing to support runners?	Continue to Step 4	Gaps may increase risk and effort
4. Risk tolerance	• CI impacts delivery timelines? • Compliance needs more control? • DR/on-call plans in place?	Pilot a limited rollout	Stick with managed CI

If you’re checking most of the “yes” boxes, you’re likely in a good position to explore self-hosted runners. If you’re hitting “no” in more than one area, focus on optimizing your current setup first. Either way, the goal is to make an informed, durable decision based on more than just cost.

Making the final call & what to do next

You’ve weighed the tradeoffs, mapped them to your team’s reality, and made a call, whether that means staying on CircleCI cloud, moving to self-hosted runners, or somewhere in between.

Whichever path you’re taking, here’s how to move forward with focus:

If you’re staying on CircleCI cloud

Many teams find meaningful cost and performance gains just by tuning their existing pipelines:

• Optimize caching, parallelism, and test splitting to speed up jobs
• Right-size resource classes to match each job’s actual needs
• Use the Insights dashboard to spot inefficiencies and track improvements
• Optimize testing strategies to run larger jobs (such as integration tests) on the main branch only
• Avoid repeating successful downstream jobs, such as redundant image builds
• Conduct a self-guided config review or work with CircleCI support to identify high-impact config improvements

If you’re adopting self-hosted runners

Running your own infrastructure means more control and more to manage. Here’s how to start strong:

• Pilot with a single workflow to test and validate your setup
• Set up observability and alerting from day one
• Document infra decisions and failure scenarios
• Allocate engineering time for ongoing upkeep
• Define infra strategy: uptime targets, teardown rules, scaling thresholds, and a resource budget

Keep in mind that a hybrid approach works too. Many teams run most workloads in the cloud and use self-hosted runners only where they’re truly needed. This approach can give you control where it counts without adding unnecessary complexity.

Own your CI strategy

The decision between cloud and self-hosted CI/CD requires understanding the full scope of what you’re taking on and whether the benefits align with your team’s capabilities and constraints.

Most teams discover that optimizing their current cloud setup delivers faster results with less risk than building their own infrastructure. But for teams that have the scale, expertise, and requirements to justify self-hosting, the investment can pay off, so long as they approach it with realistic expectations and proper planning.

Still not sure which path is right for you? CircleCI support can provide personalized guidance based on your specific workloads and requirements. Our team can help you evaluate optimization opportunities and determine whether self-hosted runners make sense for your team.

FAQ

Q: Is CircleCI cloud more expensive than running my own infrastructure?
A: The compute costs may appear lower with self-hosted infrastructure, but total cost of ownership often ends up higher when you factor in engineering time, network egress, storage costs, and operational overhead. Most teams find optimization of their current cloud setup more cost-effective than self-hosting.

Q: How much can I actually save with self-hosted runners?
A: Savings vary significantly based on your usage patterns, team efficiency, and infrastructure management costs. While compute costs may be lower, factor in engineering time, network egress, storage, and operational overhead. Many teams find total cost of ownership is higher than initially projected.

Q: Do I need Kubernetes experience to run self-hosted runners?
A: For container runners, yes. Kubernetes knowledge is essential for reliable operation, troubleshooting, and scaling. Machine runners have lower infrastructure complexity but still require significant operational knowledge.

Q: Can I use both cloud and self-hosted runners?
A: Absolutely. Many teams use a hybrid approach, keeping most workloads on CircleCI’s cloud platform while using self-hosted runners for specific use cases like compliance-sensitive workloads or specialized hardware requirements.

Q: What happens if my self-hosted infrastructure fails?
A: You’re responsible for incident response, troubleshooting, and restoration. This includes having on-call procedures, backup infrastructure, and disaster recovery plans. The operational burden is significantly higher than cloud-hosted solutions.

Q: How long does it take to set up self-hosted runners?
A: Initial setup can range from weeks to months depending on your infrastructure requirements and team experience. Budget for significant engineering time beyond the basic installation to achieve production-grade reliability and monitoring.