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CI/CD runners without the headache

Self-hosted runners for GitHub Actions, GitLab CI, Buildkite, CircleCI, Azure DevOps, and more—managed, secured, and optimized by us. Your builds run faster at a fraction of the cost.

Up to 70% cheaper than cloud-hosted runners with better performance.

Service playbook

From problem to operating evidence

Main content is structured like a case study: context first, scoped work next, then the operating changes and evidence a team can use after handoff.

Service briefBuyer contextThe problemOur solutionWho it's for

Stop overpaying for CI/CD minutes and fighting with flaky runners. We deploy and manage self-hosted runners on your infrastructure—or ours—so every build is fast, reliable, and cost-effective.

Managed runners are useful when runner operations are important but not a product differentiator. We handle provisioning, registration, hardening, scaling, monitoring, patching, and troubleshooting so your engineering team can focus on workflows and code quality.

Case-study lens

Scoped

Problem, responsibility, and handoff boundaries before implementation.

Evidence

Dashboards, runbooks, reviews, and operating records over borrowed logos.

Outcomes

Conservative summaries focused on observable operational improvement.

EvidenceSection 01

Buyer context

Runbooks, dashboards, reviews, and handoff material make the work auditable.

Runner decisions usually involve engineering, finance, security, and platform stakeholders. Hosted minutes may be easy to start with, but expensive or slow at scale. Self-hosted runners can be faster and more controlled, but only if someone operates them carefully.

Buyer questionWhat we evaluate
Is self-hosting worth it?Current spend, queue time, build duration, concurrency, cache behavior, and security constraints
Where should runners live?Your cloud, Assistance-managed infrastructure, Kubernetes, autoscaling groups, or a hybrid model
How do we keep builds isolated?Ephemeral execution, token scope, network boundaries, image hygiene, and secret handling
What changes for developers?Runner labels, workflow selectors, cache behavior, failure triage, and support path
How do we avoid operating burden?Managed patching, monitoring, capacity reviews, incident response boundaries, and monthly reporting
Operating modelSection 02

The problem

Responsibilities, response paths, and technical changes are made explicit before work starts.

Teams running serious CI/CD pipelines hit these walls:

  • Expensive cloud-hosted minutes — GitHub Actions and GitLab SaaS minutes add up fast, especially for large teams
  • Slow builds — Shared runners have cold caches and limited resources
  • Security concerns — Your code runs on infrastructure you don't control
  • Self-hosted is a pain — Managing runners means OS patches, Docker cache, autoscaling, and monitoring
OutcomeSection 03

Our solution

Expected changes are framed as practical operating improvements, not unsupported guarantees.

We run your CI/CD runners as a managed service. You get the performance and cost benefits of self-hosted with none of the operational burden.

The service includes an assessment, a target architecture, a controlled rollout, and ongoing operations. We do not recommend self-hosted runners when the economics, security requirements, or workload profile do not justify the extra operating surface.

EvidenceSection 04

Who it's for

Runbooks, dashboards, reviews, and handoff material make the work auditable.

  • Teams spending $500+/month on CI/CD minutes or seeing runner spend grow faster than engineering headcount
  • Organizations with security requirements that preclude shared/cloud runners
  • Companies with large mono-repos, long build pipelines, or high queue time
  • Teams needing ARM64, GPU, larger disks, private networking, or specialized build images
  • Organizations migrating between CI/CD platforms and needing unified runner management
  • Teams running Jenkins or Woodpecker CI who want managed infrastructure without the ops burden
Operating modelSection 05

Example use cases

Responsibilities, response paths, and technical changes are made explicit before work starts.

Operating example

Monorepo with slow pull-request checks

A large workspace has repeated dependency installs, cold Docker layers, and serial tests on undersized hosted runners. We introduce right-sized runner profiles, cache strategy, labels, and workflow changes so the critical path is shorter and easier to observe.

Operating example

Security-sensitive builds

A company needs code, artifacts, and secrets to stay inside a defined network boundary. We deploy ephemeral runners with scoped access, isolated networks, minimal persistent state, and documented runner-registration controls.

Operating example

Cost reduction without pipeline migration

A team has high hosted-runner spend but does not want to change CI/CD platforms. We keep the existing workflows, replace selected jobs with self-hosted labels, track cost and duration changes, and expand only after validation.

Operating example

Specialized workloads

Builds require ARM64, large memory, GPU, custom Docker daemon settings, private package mirrors, or access to internal services. We create runner profiles for those workloads and document which jobs are allowed to use them.

OutcomeSection 06

Supported platforms

Expected changes are framed as practical operating improvements, not unsupported guarantees.

We support all major CI/CD platforms with self-hosted runner management.

  • GitHub Actions — Native GitHub integration with Actions workflows
  • GitLab CI — GitLab CI/CD with self-hosted runners
  • Buildkite — Buildkite agents with Elastic CI Stack
  • CircleCI — CircleCI machine and container runners
  • Azure DevOps — Azure DevOps self-hosted agents
  • Jenkins — Enterprise Jenkins with distributed agents

We offer fully managed self-hosted runners for all these platforms—faster builds, lower costs, and zero maintenance for your team. Get a Runner Assessment →

What changes

Primary platforms

PlatformRunner typesKey features
GitHub ActionsLinux (x64, ARM64), macOSAutoscaling, ephemeral, Actions Runner Controller (ARC) for Kubernetes, org/repo/enterprise scopes
GitLab CILinux (x64, ARM64)Autoscaling, Docker-in-Docker, Kubernetes executor, shared/group/project runners

What changes

Additional platforms

PlatformRunner typesKey features
BuildkiteLinux, Windows, macOSElastic CI Stack (AWS), Agent Stack for Kubernetes, open-source agents
CircleCIContainer, MachineMachine Runner 3.0, container runners for Kubernetes, ephemeral pods
Azure DevOpsLinux, Windows, macOSSelf-hosted agents, Virtual Machine Scale Sets (VMSS) autoscaling, hybrid deployment
Woodpecker CILinuxLightweight Go-based engine, distributed agents, multi-workflow parallel execution
JenkinsAny platformDistributed build agents, Kubernetes plugin, maximum flexibility
ScopeSection 07

What's included

The work is broken into visible capabilities, acceptance points, and handoff artifacts.

  • Runner assessment — current spend, duration, queue time, runner labels, workload types, cache behavior, and security constraints
  • Runner infrastructure — provisioned, hardened, and monitored compute for your CI/CD jobs
  • Autoscaling — scale from zero to agreed concurrency based on queue depth and platform capability
  • Cache management — dependency, package, Docker layer, and artifact cache patterns appropriate to your workflows
  • Security hardening — ephemeral execution, network isolation, scoped tokens, image hygiene, and no persistent state between jobs where supported
  • Monitoring and alerting — job queue depth, build times, failure rates, runner availability, disk pressure, and infrastructure health
  • OS and runtime updates — patching and image refreshes with change notes and maintenance windows where needed
  • Developer handoff — runner labels, workflow examples, troubleshooting steps, and escalation path
Operating modelSection 08

Operating model

Responsibilities, response paths, and technical changes are made explicit before work starts.

ResponsibilityAssistanceYour team
Runner platformProvision, patch, monitor, scale, and troubleshoot agreed runner infrastructureApprove architecture, access, budget, and production-impacting changes
CI/CD workflowsRecommend labels, cache changes, and queue improvements; implement when scopedOwn application build logic, tests, quality gates, and merge decisions
SecurityHarden runners, reduce token scope, document network boundaries, rotate runner credentials when neededOwn source-code secrets, application credentials, and risk acceptance decisions
Cost and capacityTrack usage, right-size profiles, report waste, and recommend changesSet budget limits, priority workloads, and acceptable queue-time trade-offs
SupportTriage runner availability, registration, autoscaling, image, and capacity issuesTriage application test failures and pipeline logic failures outside runner behavior
OutcomeSection 09

Onboarding and discovery

Expected changes are framed as practical operating improvements, not unsupported guarantees.

  1. Usage baseline — collect hosted-runner spend, job duration, queue time, concurrency, failure samples, and workload profile.
  2. Security review — confirm repository trust model, token permissions, secrets usage, network access, artifact retention, and compliance constraints.
  3. Architecture choice — select dedicated infrastructure, Kubernetes, cloud autoscaling, managed Assistance infrastructure, or hybrid.
  4. Access and registration — configure CI/CD platform registration, runner groups, labels, tokens, and owner boundaries.
  5. Pilot rollout — migrate representative workflows or jobs first, compare timing and reliability, and tune images and caches.
  6. Production rollout — expand to agreed repositories and concurrency levels with documented rollback to hosted runners where appropriate.
  7. Managed operations — monitor, patch, right-size, and review usage on the agreed cadence.
EvidenceSection 10

Ongoing cadence

Runbooks, dashboards, reviews, and handoff material make the work auditable.

CadenceActivity
ContinuousMonitor runner health, queue depth, registration, disk pressure, and autoscaling behavior
Weekly during rolloutReview pilot metrics, workflow changes, developer feedback, and blocked jobs
MonthlyCost, utilization, build-duration, cache-hit, failure-rate, and capacity review
Before major changesConfirm maintenance window, image or runtime changes, rollback plan, and affected repositories
After incidentsProvide action log, impact notes, root-cause summary when feasible, and remediation backlog
Operating modelSection 11

Architecture options

Responsibilities, response paths, and technical changes are made explicit before work starts.

What changes

Runners on dedicated compute in your cloud account or our managed infrastructure. Full isolation, predictable performance. Works with all platforms.

What changes

Kubernetes-based

Runners as Kubernetes pods for dynamic scaling and efficient resource utilization:

  • GitHub Actions — Actions Runner Controller (ARC)
  • GitLab CI — Kubernetes executor
  • Buildkite — Agent Stack for Kubernetes
  • CircleCI — Container runners
  • Azure DevOps — Kubernetes agent pools
  • Woodpecker CI — Native Kubernetes support

What changes

Cloud autoscaling

Leverage cloud-native autoscaling for burst capacity:

  • AWS — Buildkite Elastic CI Stack, EC2 Auto Scaling Groups
  • Azure — Virtual Machine Scale Sets (VMSS) for Azure DevOps
  • GCP — Managed Instance Groups

What changes

Hybrid

Mix of dedicated runners for heavy workloads and on-demand spot/preemptible instances for burst capacity. Optimize costs while maintaining performance SLAs.

ScopeSection 12

Concrete deliverables

The work is broken into visible capabilities, acceptance points, and handoff artifacts.

  • runner assessment with current-state spend, duration, queue, and workload notes
  • target runner architecture with isolation, network, cache, scaling, and operating assumptions
  • runner registration and label strategy for agreed repositories, groups, or organizations
  • hardened runner images or configuration baselines where applicable
  • workflow changes or examples for moving selected jobs to self-hosted runners
  • monitoring dashboards or checks for runner availability, queue depth, capacity, and disk or cache pressure
  • runbooks for stuck jobs, unavailable runners, registration failures, cache problems, and rollback to hosted runners
  • monthly runner operations report with usage, incidents, capacity, cost notes, and recommended changes
EvidenceSection 13

Key benefits

Runbooks, dashboards, reviews, and handoff material make the work auditable.

  • 50-70% cost savings vs cloud-hosted runner minutes when workload profile and utilization support it
  • 2-5x faster builds with persistent caches and right-sized compute on suitable workloads
  • Ephemeral execution — every job starts clean, no cross-contamination where platform and architecture support it
  • Your infrastructure — code and artifacts can remain inside your security boundary
  • Zero ops for your team — we handle agreed runner operations
Operating modelSection 14

Boundaries and prerequisites

Responsibilities, response paths, and technical changes are made explicit before work starts.

What changes

We need from you

  • CI/CD administration access or a platform owner who can create runner groups, tokens, labels, and permissions
  • representative pipeline history for timing, cost, queue, and failure analysis
  • cloud, Kubernetes, network, or infrastructure access if runners run in your environment
  • security requirements for repository trust, secrets, outbound access, artifact retention, and data residency
  • an agreed budget, concurrency target, and maintenance-window policy

Scope boundary

Not included unless scoped

  • rewriting application build systems or tests beyond runner-related workflow changes
  • broad DevOps, cloud, Kubernetes, or security remediation outside the runner surface
  • macOS, Windows, GPU, or specialized hardware operations without explicit architecture and pricing
  • unlimited concurrency, unbounded storage, or guaranteed savings before workload validation
  • production incident response unrelated to runner infrastructure
OutcomeSection 15

Escalation and handoff

Expected changes are framed as practical operating improvements, not unsupported guarantees.

Runner incidents are handled by scope: unavailable runners, autoscaling failures, registration failures, image defects, disk pressure, and cache infrastructure are Assistance-owned when they are part of the managed surface. Application test failures, dependency regressions, and workflow logic remain with your engineering team unless a broader DevOps as a Service plan is active.

For each rollout, we provide a handoff note that lists runner labels, supported workloads, known limits, operational dashboards, rollback steps, and who to contact when jobs are blocked.

Next stepSection 16

Getting started

Decision points and common questions are made explicit so follow-up work is scoped cleanly.

Want faster, cheaper CI/CD? We'll analyze your current runner usage and show you the practical savings and operating trade-offs.

Get a Runner Assessment →

Next stepSection 17

Decision points and common questions are made explicit so follow-up work is scoped cleanly.

  • CI/CD Audit — baseline pipeline performance, reliability, security, and runner cost before rollout
  • DevOps as a Service — ongoing delivery ownership beyond the runner surface
  • GitOps — release promotion and recovery through Git-driven workflows
  • Cloud Account Management — cost, governance, access, and billing hygiene for runner cloud accounts
  • Cloud Infrastructure — landing zones, networks, and infrastructure foundations for runner platforms
  • Managed Kubernetes — Kubernetes operations when runners use cluster-based execution
  • Security Audit — broader security review beyond runner isolation and CI/CD permissions
  • Engagement Models — compare managed operations, retainers, audits, and projects
Next stepSection 18

Frequently asked questions

Decision points and common questions are made explicit so follow-up work is scoped cleanly.

Do we have to migrate CI/CD platforms? No. Managed runners usually keep your existing CI/CD platform and change only selected jobs or labels.

Can runners run in our cloud account? Yes. Many teams choose their own account for security and data-boundary reasons. Assistance can also manage runner infrastructure in an agreed managed environment.

Are savings guaranteed? No generic savings are guaranteed. We baseline current usage, estimate likely savings, validate with a pilot, and report actual results before broader rollout.

Can you support private networking? Yes, when the architecture is scoped for it. We document network access, DNS, egress, package mirrors, and internal-service dependencies during discovery.

What happens if self-hosted runners fail? We define a rollback or fallback procedure during rollout, usually by retaining hosted-runner labels for critical workflows until the managed runner platform is validated.

How it works

1

Connect

We set up runner registration with your GitHub org or GitLab instance.

2

Configure

Define runner labels, resource profiles, and autoscaling rules for your workloads.

3

Run

Your workflows use self-hosted runners transparently—just update the runs-on label.

4

Optimize

We monitor build times and costs, tuning resources and caches continuously.

Ready to get started?

Book a quote review or talk to an engineer.

Get pricing

How we compare

FeatureDIY / In-HouseUsEnterprise Vendor
Cost vs cloud-hostedDepends on utilizationOptimized for workload patternsDepends on vendor plan
Setup & maintenanceYou manageWe manageVendor manages
Ephemeral execution
Custom environments
Autoscaling
Cache managementManualIncludedIncluded
Monthly cost€500-2K + ops time€300-1.5K€2-5K

Pricing

Flexible scopes available. if you need custom terms or bundled service pricing.

Per runners
35/runner/mo

Minimum 5 runners — from 175 €/mo

One-time setup fee: 0 €

Self-hosted CI/CD runners on dedicated infrastructure. Includes runner management, updates, monitoring, and autoscaling configuration. Works with GitHub Actions, GitLab CI, and other CI platforms.

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Estimated monthly total

0 €/mo

Does not include server infrastructure costs (compute, storage, egress).

What our clients say

Our CI builds went from 12 minutes to 3 minutes, and we're spending 60% less than GitHub-hosted runners.

Stefan D.

DevOps Lead, E-commerce Platform

Zero maintenance on our end. We just push code and the runners scale automatically. Exactly what we needed.

Jana M.

Engineering Manager, HealthTech

Talk to a senior engineer

Need a clearer path for Managed Self-Hosted Runners?

We'll help you understand fit, scope, pricing, and the fastest practical next step for your team.

No obligation • Senior engineer review • Recommendations grounded in your current stack