The Moment the Entrypoint Vanished: Discovering Vast.ai's SSH Launch Mode Behavior

Introduction

In the complex dance of deploying a distributed proving system on Vast.ai's GPU marketplace, few moments are as decisive as the one captured in message 922 of this opencode session. The assistant had just SSH'd into a freshly created instance—a 2x RTX 3090 machine in British Columbia, Canada—expecting to find the carefully crafted Docker entrypoint running through its lifecycle of tunnel setup, manager registration, and benchmark execution. Instead, it found something else entirely: Vast.ai's own init script sitting at PID 1, and the entrypoint nowhere to be seen.

This message represents a classic inflection point in infrastructure engineering: the moment when an assumption collides with reality, and the entire deployment strategy must be re-evaluated. What makes it particularly instructive is not just the discovery itself, but the structured reasoning that follows—a three-option analysis that transforms a frustrating blocker into a clear set of actionable paths forward.

The Discovery: What the Assistant Found

The message opens with a moment of recognition: "There it is—the SSH launch mode replaced our entrypoint with its own init script (/.launch)." The assistant had run ps aux on the remote instance and observed that PID 1 was running:

/bin/sh -c while [ ! -e /.launch ]; do sleep 1; done; bash /.launch

This was not the Docker ENTRYPOINT. The entrypoint.sh script—painstakingly built over multiple rounds to handle parameter fetching, portavailc tunnel setup, vast-manager registration, benchmark execution, and log shipping—was simply not executing. The container was alive, SSH was accessible, but the automated worker lifecycle was dead on arrival.

The assistant then read the /.launch script itself, revealing Vast.ai's initialization machinery. The script set VAST_CONTAINERLABEL=C.32710414, configured bashrc with port ranges, and proceeded to install SSH server, set up password authentication, and configure the environment for interactive SSH sessions. This was Vast.ai's standard SSH onboarding script, designed to make instances accessible to users—not to run custom application workloads.

The Core Insight: SSH Mode Replaces ENTRYPOINT

The critical realization here is that Vast.ai's --ssh launch mode does not layer SSH on top of the existing Docker entrypoint. It replaces the entrypoint entirely. As the assistant correctly notes, this is documented behavior: "The SSH and Jupyter launch modes inject setup scripts into your existing Docker image, which means your image's original entrypoint is replaced."

This distinction is subtle but crucial. Many container platforms allow you to run SSH alongside your application—you set up an SSH daemon as a sidecar or background process while the main application runs as the entrypoint. Vast.ai takes a different approach: when you request SSH access, it swaps in its own init system (/.launch) which handles SSH setup, user configuration, and environment preparation. Your application then becomes something you must launch manually from within that SSH session, rather than something that runs automatically at container start.

For the assistant's architecture, this was a fundamental problem. The entire design depended on the entrypoint running automatically: it would start the portavailc tunnel (establishing connectivity back to the controller host), register the instance with the vast-manager service, download Filecoin proof parameters, run the benchmark, and then transition to the proving worker. Without the entrypoint executing, none of this happened. The instance would sit idle, registered in the Vast.ai dashboard but invisible to the manager, consuming GPU resources without doing any useful work.

The Three-Option Analysis

The assistant's response to this discovery is a model of structured problem-solving. Rather than panicking or trying ad-hoc fixes, it lays out three distinct approaches:

Option 1: Use --entrypoint launch mode instead of --ssh. This would preserve the Docker ENTRYPOINT, allowing entrypoint.sh to run as designed. However, it would lose the convenience of SSH access for debugging and manual intervention—a significant drawback when deploying to remote, untrusted hardware.

Option 2: Put startup logic in an onstart script. Vast.ai supports an --onstart parameter that runs a script after the container starts, regardless of launch mode. This could be used to launch the entrypoint in the background while still allowing SSH access. This option preserves both automated lifecycle and debugging capability.

Option 3: Not use --ssh and configure SSH ourselves. The Docker image could include its own SSH server setup in the entrypoint, making the instance accessible without relying on Vast.ai's SSH mode. This gives full control but requires more complexity in the Docker image itself.

Each option represents a different trade-off between convenience, control, and complexity. The assistant doesn't immediately commit to one—instead, it reads the /.launch script to understand exactly what Vast.ai's SSH mode provides, gathering information before deciding.

Assumptions and Their Consequences

This message reveals several assumptions that shaped the deployment strategy up to this point:

The entrypoint-will-run assumption. The most significant assumption was that specifying --ssh would add SSH access alongside the existing entrypoint, not replace it. This is a natural assumption if you're used to Docker's standard behavior, where ENTRYPOINT and CMD always execute unless explicitly overridden. Vast.ai's deviation from this norm is documented but easy to miss when focusing on other aspects of deployment.

The environment variable assumption. Earlier in the conversation, the assistant had confirmed that VAST_CONTAINERLABEL and CONTAINER_ID were set by Vast.ai in every container. This was correct—but the assumption that these would be available to the entrypoint was only valid if the entrypoint actually ran. With the entrypoint replaced, even correctly set environment variables were irrelevant.

The "it just works" assumption about Vast.ai's platform. The assistant had been treating Vast.ai as a relatively standard Docker host with some GPU marketplace features. This discovery revealed that Vast.ai has its own container lifecycle management that differs significantly from standard Docker behavior, requiring platform-specific adaptation.

Input and Output Knowledge

To fully understand this message, the reader needs knowledge of: Docker container lifecycle (ENTRYPOINT, CMD, PID 1), Vast.ai's instance creation workflow (launch modes, --ssh, --direct, --onstart), the architecture of the proving system (entrypoint.sh, portavailc tunnel, vast-manager), and Linux process management (ps aux, PID 1, init scripts).

The message creates several important pieces of output knowledge: the concrete confirmation that --ssh mode replaces the entrypoint (not just adds SSH), the content and structure of Vast.ai's /.launch script, the three viable workaround strategies, and the understanding that VAST_CONTAINERLABEL is indeed available (visible in /.launch) but only within Vast's init context, not the original entrypoint.

The Thinking Process

What's most striking about this message is the reasoning structure. The assistant moves through a clear diagnostic sequence:

  1. Observation: ps aux shows unexpected PID 1 process
  2. Recognition: The entrypoint is not running
  3. Knowledge retrieval: Recalling documented behavior about SSH mode replacing entrypoints
  4. Information gathering: Reading /.launch to understand what Vast's init does
  5. Solution generation: Proposing three distinct approaches
  6. Deferral: Not committing to a solution until more information is available This is not just debugging—it's architectural reasoning. The assistant is treating the discovery not as a bug to be fixed but as a platform constraint to be designed around. The three options are not quick patches; they are architectural responses that each reshape the deployment strategy in different ways.

Broader Implications

This discovery ripples through the entire deployment architecture. The entrypoint was the central orchestrator of the worker lifecycle—tunnel, register, fetch params, benchmark, prove. If the entrypoint doesn't run, the worker doesn't work. But more subtly, this forces a rethinking of how the system interacts with Vast.ai's platform.

The /.launch script reveals that Vast.ai sets VAST_CONTAINERLABEL early in its init process, appending it to /root/.bashrc for SSH sessions. This validates the earlier investigation that confirmed the variable exists—but it also shows that the variable is set by Vast's init, not by Docker's ENTRYPOINT mechanism. This means the variable's availability depends on which launch mode is used and at what point in the lifecycle you check.

The assistant's response also demonstrates a mature approach to infrastructure engineering: when a platform behaves unexpectedly, the correct response is not to fight the platform but to understand its constraints and adapt. The three options all work with Vast.ai's model rather than against it, choosing different points of integration that align with the platform's actual behavior rather than assumed behavior.

Conclusion

Message 922 captures a pivotal moment in the deployment of a complex distributed system. It is the moment when a carefully constructed plan meets the messy reality of a platform with its own conventions and constraints. The assistant's response—diagnostic, structured, and solution-oriented—transforms what could have been a frustrating dead end into a clear fork in the road with three well-understood paths forward.

For anyone building infrastructure on platforms like Vast.ai, this message serves as a valuable case study in the importance of understanding container lifecycle semantics, the danger of assuming standard Docker behavior on specialized platforms, and the power of structured reasoning when things don't go as planned. The entrypoint may have vanished, but in its place emerged a much deeper understanding of the platform—and a clearer path to making the system work.