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Start by treating “microVM-only” as a comparison clue, not proof that the hypervisor is broken. Run the same evaluation case in a known-good environment and the microVM, then identify the first repeatable difference in initialization, files, credentials, network route, process placement, architecture, or resource limits. Preserve the failed environment before cleanup, collect the evaluator’s artifacts, and change one boundary at a time. This approach distinguishes an agent behavior regression from a missing fixture, failed dependency request, stale snapshot, or guest boot problem.
The exact commands depend on your evaluator, microVM provider, guest operating system, and image. The workflow below is provider-neutral, with vendor-specific behavior labeled as examples.
What does a microVM-only eval failure actually tell you?
It tells you that at least one condition differs between the passing and failing executions. It does not, by itself, show that virtualization is defective. A microVM can change the agent’s visible filesystem, startup order, network path, credential delivery, CPU architecture, available resources, or amount of retained state. Any of those differences can alter an evaluation result.
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- Deterministic failure: the same case fails on every fresh microVM run. Look first for a missing file, dependency, permission, credential, route, or startup error.
- Intermittent failure: repeated runs alternate between pass and fail. Investigate timing, resource pressure, network reliability, snapshot state, and evaluator or judge variance.
- Pre-agent failure: the agent never begins its normal tool or conversation sequence. Prioritize boot, startup, architecture, image, and resource evidence.
- Agent-level failure: the agent starts but behaves differently. Compare the guest-visible environment and the complete tool-call history with the passing run.
How should I pin down the failing evaluation first?
Reduce the problem to one case and preserve enough information to replay it. Do this before editing the image or changing several sandbox settings at once.
- Record the case. Save the case identifier, complete input, expected tool calls or scoring criteria, agent configuration, evaluator version, image digest or template identifier, and start and end timestamps.
- Run it in isolation. Remove unrelated parallel cases so CPU, memory, disk, and network contention cannot obscure the result.
- Repeat when the harness allows it. Several fresh runs show whether the defect is deterministic. If your evaluator supports a saved baseline, compare the isolated case with that baseline rather than relying on a single score.
- Separate judge variance from execution evidence. A language-model judge can vary between runs even when the agent execution is identical. Preserve the transcript, tool calls, exit status, and infrastructure logs so a changed score is not mistaken for a changed guest behavior.
Do not overwrite the original failing run with a “fixed” attempt. Give every run a unique identifier and keep the exact image, configuration, and timestamps attached to it.
Which parts of the execution envelope should I compare?
Create a compact pass/fail record and compare it line by line. Capture the values before trying a fix; otherwise you may lose the only evidence of what changed.
| Comparison axis | Questions to answer | Why it can change an eval |
|---|---|---|
| Architecture | What are the host and guest CPU architectures? | A guest image or kernel built for a different architecture may fail before agent code runs. |
| Image and kernel | What guest base image, kernel, digest, and runtime versions are used? | A package, shell, certificate store, or system call can differ even when application code is unchanged. |
| Initialization | Is the startup command and setup script byte-for-byte equivalent? | A failed install, skipped migration, or changed working directory can leave the agent partially initialized. |
| Workspace | Is the workspace directly mounted, privately cloned, or absent? Is it writable? | The agent may see different fixtures, permissions, symlinks, or generated files. |
| Environment | Which variable names are present in each run? | Explicit forwarding and host inheritance are not interchangeable; the guest may lack a required setting. |
| Network | Which proxy, DNS resolver, routes, and allow/deny rules apply? | A request can succeed from the host and fail from the guest, or resolve to a different service. |
| State | Is the run a fresh boot, resumed instance, or snapshot restore? | Layers and snapshots can retain stale files, caches, processes, or expired credentials. |
| Resources | What CPU, memory, disk, and timeout limits are enforced? | Slow installs, OOM kills, full disks, and short deadlines can look like agent errors. |
| Process placement | Where do the agent, evaluator, and judge execute? | Host-side authentication or files are not automatically visible inside the guest. |
After recording the baseline, change one dimension at a time. If changing two settings fixes the run, revert both and test them separately; otherwise you will not know which boundary mattered.
How do I preserve and inspect a failed microVM?
Keep the failed environment alive long enough to inspect it. Cleanup often removes the only evidence of a setup error.
In Docker Agent’s documented workflow, the --keep-containers option retains failed containers for inspection. The same workflow emits a log, result JSON, session exports, and a SQLite session database. Other evaluators use different retention controls, so look for an equivalent “keep,” “retain,” or “preserve on failure” setting in your runner.
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- Enable failure retention before launching the reproducer.
- Save the evaluator output and infrastructure logs outside the guest so they survive teardown.
- Use the selected container or VM runtime’s inspection command to enter or examine the retained environment.
- Collect the complete conversation and tool-call history, not just the final score.
- Record process status, exit codes, disk usage, and timestamps around setup and failure.
Inspect secrets safely. You can record that a variable is present, absent, or empty without printing its value. Redact tokens, cookies, private keys, authorization headers, and full credential files before sharing logs.
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Yes. Filesystem assumptions are among the most common explanations for a local pass and a sandbox failure. Verify what the agent actually sees, not what the host project directory contains.
Check the working directory and fixtures
Inside the guest, print the current working directory, list the expected fixture and configuration paths, and check their ownership and read/write mode. Confirm that setup completed before the evaluator started the agent. On a Linux guest, ordinary inspection commands such as pwd, ls -la, find, id, and stat are examples; use the equivalent tools for another guest operating system.
- Check exact capitalization. A case-insensitive host filesystem can hide a filename error that a case-sensitive guest exposes.
- Resolve symlinks and verify that their targets exist inside the guest.
- Check file ownership and the user that launches the agent.
- Confirm that generated files are written to the path the evaluator later reads.
- Look for a setup command that returned a nonzero status but did not stop the overall launch sequence.
Identify the workspace mode
Three arrangements behave differently:
| Workspace arrangement | What the guest normally receives | Typical diagnostic question |
|---|---|---|
| Direct workspace mount | A host directory exposed at a guest path, subject to mount mode and permissions. | Is the expected host path mounted at the path the agent uses, and is it writable? |
| Private clone | A separate copy created for the run. | Did the clone contain the same revision, generated fixtures, and ignored files as the passing run? |
| Mountless sandbox | No host workspace unless setup creates or downloads one. | Which step creates the files, and did that step complete inside the guest? |
Snapshot-backed or layered environments add another variable. A resumed instance may contain stale build output, a previous agent’s edits, old caches, or a process that a fresh run would not have. Compare a fresh boot with a snapshot restore using the same case. If only the restored state fails, discard or rebuild the snapshot rather than changing the agent.
How do I test network access and credentials from inside the guest?
Run connectivity checks from the guest process context, through the same route the agent uses. A host-side success proves only that the host can reach the service.
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Test DNS, routing, and policy
- Resolve the required hostname from inside the guest.
- Attempt a harmless request to the exact endpoint or a documented health endpoint, using the guest’s proxy settings.
- Record status, timing, and error class without logging authorization headers or response bodies that may contain secrets.
- Compare the guest’s DNS resolver, proxy variables, egress allowlist, and blocked destinations with the passing environment.
A timeout, DNS error, connection refusal, TLS failure, and HTTP authorization error point to different boundaries. Preserve the exact error and timestamp; replacing all of them with “network failed” loses useful evidence.
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Check how credentials enter the guest
Do not assume host environment inheritance. In Docker’s documented architecture, credentials can be injected through a host-side proxy while the agent remains isolated. In a different implementation, the guest may need explicitly forwarded variables or a mounted credential helper. Vercel’s sandbox documentation, for example, says application environment values are supplied through an SDK option rather than inherited automatically. These are implementation examples, not universal microVM rules.
- List the names of required variables in both runs and mark each as present, empty, or absent.
- Check that the agent process, not only an interactive shell, receives them.
- Verify that the credential’s audience, region, and expiration are valid for the guest’s request.
- Keep evaluator or judge credentials separate from agent credentials; host-side judge authentication can succeed while the guest agent cannot authenticate.
If the service is intentionally unreachable from the guest, make the evaluation explicit about that constraint. A local test that silently uses a host credential or unrestricted network is not equivalent to a sandbox test.
Are the evaluator and judge running in different places?
Often they are. Docker’s documented setup runs the evaluated agent in isolation while its judge runs on the host. That arrangement can produce a misleading result: the judge can authenticate, read host-side files, and score a session even though the agent cannot reach the same service or path.
Draw the execution map for one run:
- Where is the agent process?
- Where are tool servers and credential proxies?
- Where does the evaluator collect transcripts and artifacts?
- Where does the judge run, and which network and filesystem does it use?
Then classify each failure as agent execution, evaluator orchestration, or judging. A judge error after a complete agent transcript is a different incident from an agent timeout before its first tool call. Keep those signals separate in dashboards and regression reports.
What should I check when the guest never reaches the eval?
If no normal agent activity appears, investigate boot and startup evidence before changing prompts or scoring rules.
Verify architecture and image compatibility
For Firecracker-based deployments, the guest operating-system architecture must match the host architecture. Confirm the architecture of the host, kernel, root filesystem, and any native dependencies. An image built for another architecture can fail at boot or when its first binary starts.
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Inspect the start response and console path
Firecracker’s FAQ recommends checking the InstanceStart response and the kernel command line when console output is missing. Apply that guidance specifically to Firecracker; other microVM stacks expose different APIs and logs. Capture the VMM process log, guest boot log, start API response, kernel command line, and the timestamp at which the evaluator declared a timeout.
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Distinguish startup timeout from agent timeout
Measure the phases separately: image preparation, VM launch, guest boot, setup script, dependency installation, agent startup, and evaluation case. A single end-to-end timeout hides which phase consumed the budget. Compare resource limits and disk space as well; an installation that is merely slow locally may be killed by a smaller guest limit.
How do I minimize and report a reproducible failure?
Once you know the failing boundary, reduce the case without removing the condition that triggers it.
- Keep the smallest prompt and tool set that still fails.
- Retain only the fixture files required to reproduce the behavior.
- Use a fresh environment and then a resumed or snapshot-restored environment to determine whether state is causal.
- Change one boundary dimension—workspace, network, credential forwarding, image, resource limit, or architecture—then rerun.
- Record the first changed outcome, not only the final successful configuration.
- Add the minimized case to the evaluation suite as a regression test.
A useful incident report includes the case ID, complete input, expected behavior, pass and fail transcripts, image or template digest, evaluator and runtime versions, host and guest architectures, startup command, workspace arrangement, variable names present, network policy, resource limits, fresh-versus-resumed state, sanitized logs, and the exact first failing phase.
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| Only resumed runs fail | Fresh boot versus snapshot restore | Snapshot age, retained processes, cache contents, and filesystem diff |
| Runs alternate between pass and fail | Resource pressure, timing, network reliability, and judge variance | Phase timings, memory and disk usage, retries, transcripts, and repeated outcomes |
| Score changes but transcript is identical | Evaluator or judge repeatability | Stable execution artifacts and each judge output separately |
What should become part of the permanent eval contract?
After fixing the immediate failure, make the relevant assumption explicit. Pin image digests and dependency versions, define the workspace mode and writable paths, document which environment-variable names are forwarded, state the guest network policy and proxy behavior, record supported architectures, and set separate startup and agent timeouts. Decide whether every case receives a fresh environment or an intentional snapshot.
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Retain a baseline run and a microVM run for the same case. A baseline gate is one possible workflow, not a requirement of every evaluator, but the principle is broadly useful: a change should fail clearly when it alters the execution envelope or agent behavior unexpectedly. Keep the minimized reproduction permanently so future image, runtime, or policy changes are tested against the boundary that once failed.
What is the practical diagnosis?
The reliable path is comparative and evidence-driven: pin one case, preserve the failed guest, compare the complete execution envelope, inspect files and state, test network and credentials from inside the guest, map where the evaluator and judge run, and examine boot and architecture evidence when execution never begins. Treat each vendor behavior as an implementation detail to verify, not as a rule for every microVM. Once a single boundary difference reproduces the failure, encode that difference in the evaluation and deployment contract instead of weakening isolation by guesswork.
Frequently Asked Questions
How can I tell whether the failure is caused by the judge rather than the agent?
Compare the complete agent transcript, tool-call sequence, exit status, and timing across repeated runs before comparing scores. If execution artifacts are identical but judge outputs differ, investigate judge variability or scoring configuration separately from the microVM.
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Should I disable the sandbox network to make the test deterministic?
Usually no. Disabling network can hide the boundary that production actually depends on. Define an explicit allowlist or proxy policy, add a fixture or mock for services that should not be contacted, and keep one regression case that verifies the intended restriction.
Can a snapshot make an eval fail after the image was fixed?
Yes. A restored snapshot can preserve stale files, caches, processes, or expired credentials that are absent from a fresh boot. Rebuild the snapshot and compare it with a clean run before changing application code.
What is safe to include when sharing microVM logs?
Include timestamps, phase names, exit codes, error classes, image identifiers, and whether required variables were present. Remove token values, cookies, private keys, authorization headers, full credential files, and response bodies that may contain user data.
When should I ask the platform provider for help?
Escalate after you can provide a minimized case and a pass/fail comparison showing the first divergent phase. Include the guest and host architectures, image or template digest, startup response, sanitized logs, workspace and network settings, resource limits, and whether a fresh run reproduces the issue.
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