The Kill-and-Redeploy Decision: A Pivot from In-Place Fix to Full Instance Recycling

In the high-stakes world of decentralized GPU proving infrastructure, the difference between a running cluster and a stalled one often comes down to a single missing port. Message [msg 1426] captures the exact moment when an engineer, having exhausted one repair strategy, commits to a drastic but necessary operational pivot: destroying every active proving instance to redeploy them with a corrected configuration.

The Message

The message is deceptively brief. After announcing "Image pushed," the assistant executes a bash command that queries the vast-manager dashboard API running on the controller host (10.1.2.104), filtering for all non-killed instances with valid Vast.ai identifiers:

ssh 10.1.2.104 'curl -s http://localhost:1235/api/dashboard | python3 -c "
import sys,json
d=json.load(sys.stdin)
for i in d[\"instances\"]:
    if i[\"state\"] not in (\"killed\",) and i.get(\"vast_id\",0) > 0:
        print(i[\"vast_id\"], i[\"uuid\"], i.get(\"gpu_name\",\"\"), i[\"state\"])
"'

The output enumerates eight active instances—a heterogeneous mix of RTX 5090, RTX 5060 Ti, A40, RTX 4090, RTX 5070 Ti, RTX 5000Ada, and RTX 3090 GPUs—all sitting in the params_done state. This inventory snapshot is the prelude to destruction. The assistant is taking stock before pulling the trigger.

The Road to This Decision

To understand why this message matters, one must trace the chain of events that led to it. The session had been building toward a robust, automated GPU proving farm. A sophisticated management system called vast-manager had been developed to discover, deploy, monitor, and retire Vast.ai GPU instances. The system used a portavailc/portavaild tunnel architecture to securely forward ports between worker instances and the controller, enabling the worker's curio daemon to reach the Lotus blockchain API on the controller's port 1234.

The trouble began when a newly deployed RTX PRO 4000 instance failed to start. Its logs revealed a fatal error: failed to establish connection with all chain nodes. The root cause was traced to the portavailc tunnel configuration—it forwarded ports 1235, 5433, and 9042, but critically omitted port 1234, which hosted the Lotus API. The curio daemon on the worker tried to connect to ws://127.0.0.1:1234/rpc/v1, found nothing listening, and exited.

The fix was straightforward: add -L 1234 to the portavailc command in the entrypoint.sh script. The assistant edited the file, rebuilt the Docker image, and pushed it to Docker Hub. The natural next step was to fix the already-running instances in-place by SSHing into each one and restarting portavailc with the corrected port list.

That approach failed. The assistant attempted to SSH into the instances directly from the development machine, but Vast.ai instances require the SSH key associated with the account that created them—a key that was only present on the controller host. Even tunneling through the controller didn't help, as the controller's own SSH key was not authorized on the worker instances. The in-place fix was a dead end.

The Implicit Decision

Message [msg 1426] represents the pivot. The assistant doesn't explicitly state "I've decided to kill all instances because SSH doesn't work." Instead, the decision is revealed through action: the Docker image has been pushed, and now the assistant is inventorying active instances with the clear intent to destroy them. The reasoning is implicit but unmistakable.

This is a classic engineering trade-off. The assistant could have pursued alternative paths: configuring SSH key forwarding, modifying the vast-manager to push configuration updates through its API, or writing a script that the instances themselves could pull. Each alternative would have been more elegant but slower. The instances were already stuck—curio was crash-looping, and no useful proving work was being done. Killing them and letting the vast-manager's lifecycle management spin up fresh replacements with the corrected image was the fastest path to a working cluster.

The assumption underpinning this decision is that the vast-manager's redeployment machinery is functional—that new instances will be automatically provisioned to replace the killed ones. This assumption is reasonable given the system's design: the vast-manager monitors instance counts and creates new ones to meet demand. But it's not guaranteed. The redeployment depends on offer availability, budget constraints, and the manager's scheduling logic. The assistant is betting that the automated pipeline will work.

What This Message Reveals About the System

The output of the bash command is itself revealing. Eight instances are active, all in the params_done state. This state indicates that each instance has successfully fetched its Filecoin proving parameters (a multi-gigabyte download) but has not yet completed benchmarking. The params_done state is a holding pattern—the instance has its parameters but hasn't demonstrated it can actually prove. Because of the port 1234 bug, none of these instances would ever reach the running state. They were stuck in limbo, consuming resources but producing nothing.

The diversity of hardware is striking: RTX 5090, RTX 5060 Ti (three of them), A40, RTX 4090, RTX 5070 Ti, RTX 5000Ada, and RTX 3090. This mix reflects the vast-manager's strategy of acquiring whatever cost-effective GPU capacity is available on the Vast.ai marketplace. The kill-and-redeploy approach means all of this hardware diversity will be lost and will need to be re-acquired—a potentially expensive roll of the dice if favorable offers don't reappear.

Input Knowledge Required

To fully grasp this message, a reader needs to understand several layers of context. First, the tunnel architecture: portavailc runs on each worker instance, connecting back to portavaild on the controller, forwarding local ports so that services on the worker can reach services on the controller as if they were local. Second, the instance lifecycle: instances progress through registered → params_done → running → killed, with each state representing a milestone in setup and proving. Third, the deployment workflow: the Docker image is built locally, pushed to Docker Hub, and pulled by Vast.ai instances at creation time. Fourth, the vast-manager's role: it tracks instance state in a SQLite database, monitors progress, and orchestrates the lifecycle.

Output Knowledge Created

This message produces two critical outputs. First, it confirms that the Docker image has been successfully pushed and is available for deployment. Second, it produces a precise inventory of every active instance that needs to be terminated, including its Vast.ai identifier, internal UUID, GPU model, and current state. This inventory is the kill list—it will be used in the subsequent message to actually destroy the instances via the Vast.ai API.

The Broader Significance

Message [msg 1426] exemplifies a pattern that recurs throughout infrastructure engineering: the moment when graceful recovery gives way to nuclear option. The assistant tried the surgical approach (fix the tunnel on running instances) and failed due to an access control boundary. The pragmatic response was to accept the loss of all in-progress work—parameter downloads, setup time, accumulated instance runtime—and start fresh. In cloud infrastructure, this is often the correct call. The cost of keeping broken instances alive (wasted GPU rental fees, no useful output) quickly exceeds the cost of recycling them.

The message also demonstrates the value of automated lifecycle management. Without the vast-manager, killing eight instances would mean manually provisioning eight replacements, each requiring SSH key setup, parameter downloads, and configuration. With the manager, killing is just a step in a workflow—the system will handle re-provisioning automatically. The assistant is trusting that investment in automation will pay off in this moment.

What follows [msg 1426] is the actual destruction and redeployment. The assistant will call the Vast.ai API to terminate each instance, the vast-manager will detect the gap and spin up new ones, and the corrected entrypoint will ensure port 1234 is forwarded from the start. The cluster will recover. But this message captures the hinge point—the moment of commitment to a path that destroys before it rebuilds.