CI and test infrastructure / StarSling alternative

StarSling runners alternative

StarSling supplies GitHub Actions runners and AI agents that propose CI optimizations. Its per-job VM and retained workflow logs support that CI workflow. A returning agent computer has different lifecycle needs from a disposable runner or an agent that opens optimization pull requests.

Reviewed 2026-10-18 · Published by the Sandbox0 team

When StarSling fits

StarSling fits teams keeping GitHub Actions while changing runner labels and using optimization analysis, review jobs or specialized GPU runners. Preserve that workflow integration when CI acceleration is the requirement.

When to consider Sandbox0

Consider Sandbox0 when the agent itself needs a durable Linux environment across tasks, including installed tools and a growing RootFS. You supply CI scheduling, workflow adapters and optimization agents; GPU availability and full-VM requirements need separate qualification.

Capabilities

StarSling and Sandbox0: what persists?

Feature comparison with documentation and verification status
Environment and runtime lifetimeStarSlingNot established in this reviewSandbox0ttl and hard_ttl default to 0 (disabled). Configure idle pause and deletion policies for the same persistent sandbox identity; an idle running sandbox still accrues compute charges.Read documentation →
Persistent filesStarSlingRunner VMs are single-use and destroyed with the job; retained workflow logs are separate.View evidence ↗Sandbox0The writable RootFS survives successful checkpoints, including software, system configuration, dependencies, and user data.Read documentation →
Whole RootFSStarSlingThe job machine is destroyed, not retained as a returning complete filesystem.View evidence ↗Sandbox0Persistence extends beyond /workspace to paths such as /usr/local, /etc, and /home. Runtime tmpfs and virtual filesystems are excluded.Read documentation →
Release compute, keep stateStarSlingNo arbitrary saved-runner process checkpoint interface is established.View evidence ↗Sandbox0Pause compute between tasks; resume on available capacity. Default resume starts fresh processes from the saved filesystem.Read documentation →
Memory and process stateStarSlingCode-review agents and CI job orchestration do not establish arbitrary RAM capture.View evidence ↗Sandbox0Experimental memory checkpoints can preserve compatible process state. Use memory: true on both pause and resume on a compatible deployment. A filesystem checkpoint alone does not preserve running processes.Read documentation →

Online RootFS growth

On growth-enabled images, Sandbox0 automatically expands the writable RootFS as free space runs low, within a configured sparse logical ceiling up to 64 TiB. Agent processes keep running. Growth is enabled in the qualified Cloud region; confirm activation for other regions. Existing images and snapshots retain their captured storage geometry. The ceiling is logical capacity, not preallocated host disk.

StarSling job VMs are destroyed after execution. Dependency caches, artifacts and historical logs are useful CI data but do not establish a returning automatically growing whole RootFS. Sandbox0 can retain the agent toolchain between tasks while you retain or replace the CI control plane separately.

Files while compute is paused

Sandbox0's Files API reads persistent files without resuming compute. Filesystem-only pauses also permit edits; retained-memory pauses are read-only and reject mutations with 409. SSH, SFTP, file watching, and runtime-only mounts require running compute.

Reading retained CI logs is different from reading a paused machine’s RootFS. The reviewed StarSling sources do not establish a supported full-filesystem interface while a guest remains paused.

See paused file operations →

A single-use runner is not a saved agent computer

The security FAQ says a runner VM contains job secrets/code during execution and is destroyed with the job. Workflow logs can be retained for analysis; source used for AI analysis has separate retention. Logs, artifacts and caches should not be equated with preserving the whole live machine for the next task.

CPU time has a per-job rounding boundary

Current CPU rates start at $0.004/minute for 2 vCPU/8 GB and $0.008 for 4 vCPU/16 GB, scaling through 64 vCPU. The usage reference rounds each job up to whole minutes with a one-minute minimum. Queue time is not billed according to the product index; a short job still incurs the minimum execution minute.

Review Runner prices disagree across current sources

The pricing page says Review Runners use the same CPU rates. The compute and usage references instead describe a blended-CPU 4 vCPU/16 GB starsling-review runner at $0.004 per billed minute, with beta/access conditions. Confirm the runner label, access and account quote; this page does not present either as a universal review-runner rate.

Pricing

Compare billing models, then price your workload

CPU allocation, memory, billing minimums, disk, plan fees, and supported workload differ. These meters are not equal-performance machine quotes. Confirm region, resource units, and included allowances before estimating a total.

StarSling

Pricing reviewed 2026-10-18

CPU runner 2 vCPU /8 GB
$0.004 per minute
USD; one-minute minimum and whole-minute job rounding per usage docs.
Rate source ↗
CPU runner 4 vCPU /16 GB
$0.008 per minute
Standard CPU family; Review Runner pricing is separately disputed across current sources.
Rate source ↗
CPU runner 8 vCPU /32 GB
$0.016 per minute
A different resource tier, not a per-memory unit rate.
Rate source ↗
Review Runner
Confirm current label-specific quote
Docs list $0.004/minute for 4 vCPU/16 GB; the pricing page says same CPU rates. Access conditions also apply.
Rate source ↗

Rates describe CPU runners, not an equal-throughput comparison with Sandbox0. GPU runners have separate hardware-inclusive rates and access conditions; H100 is marked coming soon on the price page. Afterburner is early access. Optimization PRs for new accounts require paid usage and are not enabled by default in the index. Vendor speed/combined-savings examples are not independently measured guarantees for your repository.

Check current StarSling pricing ↗

Sandbox0

$0.015/GiB-hour compute (billed by the second at approximately $0.000004167/GiB-second), plus $0.02/GiB-month of retained incremental RootFS and memory checkpoint data. Shared base images and platform recovery retention are excluded; paused sandboxes accrue storage charges only.

Compute / GiB-hour
$0.015
Retained data / GiB-month
$0.02
Paused compute
$0.00

A 4 GiB agent, 100 running hours

$6.00 compute

4 GiB × 100 hours, billed by the second. Keeping 20 GiB of billable incremental data for a full billing month adds $0.40. CPU is derived from memory by the platform; choose a tier that fits your workload.

Understand storage billing →

Before migrating from StarSling

  1. Inventory GitHub workflow labels, architecture, caches/artifacts, model permissions and any Review/GPU runner dependencies.
  2. Keep or choose a CI runner for normal jobs; integrate Sandbox0 explicitly where a returning agent environment is needed.
  3. Test workflow cancellation/retry, repeated agent tasks, full system retention, growing outputs, paused files and all runner/runtime/storage/model charges.

Common questions

Is Sandbox0 a drop-in StarSling replacement?

Evaluate API compatibility and product scope. These products serve different core workflows, so a change may require a different architecture.

Does keeping files also keep a running agent?

Filesystem state and volatile process state are separate. Sandbox0 requires explicit compatible memory checkpoints to preserve running processes; its default filesystem resume starts fresh processes.

Sources and review scope

The Boat team's Battleships directory is the discovery source. References below describe the product and plan discussed on this page. Check current availability, regional terms and billing units before migrating. Where the cited material does not establish a capability or price, the comparison identifies that uncertainty.

Related comparisons