aws / aws/sagemaker-python-sdk

Sagemaker Endpoint vanishing without traces

Abierto
#3,252 2 comentarios 0 reacciones 0 asignados Ver en GitHub
component: hosting type: bug
Lenguaje dominante
Python
Estrellas
2.3k
Forks
1.3k
Merge medio
1 d 22 h
PR fusionados (30 d)
35

Descripción

**Describe the bug**
I'm currently using Sagemaker to host a custom ML model deployed to two accounts, homolog, and production. Both endpoints have the same entry point code and were deployed the same day. The homologation version suddenly disappeared on June 28th, leaving no traces besides the last HealthCheck ping on CloudWatch. After searching CloudTrail logs to see what could have happened, there was nothing out of the ordinary: deployed the endpoint and that was it. No delete command coming from anywhere.
I thought of it as a bug and promptly redeployed the model, on June 29th, assuming it wouldn't happen again. The issue is that on July 3rd the endpoint vanished without traces again. Same thing, no delete, no update, no renaming of anything on CloudTrail, and the only proof that it was ever on running were the CloudWatch logs and the CreateEndpoint entry on CloudTrail.

**To reproduce**
Couldn't reproduce the bug willingly. I couldn't gather any evidence that could lead me to the cause of the problem.

**Expected behavior**
For it not to vanish

**Screenshots or logs**

**System information**
A description of your system. Please provide:
- **SageMaker Python SDK version**: 2.72.1
- **Framework name (eg. PyTorch) or algorithm (eg. KMeans)**: SKLearn
- **Framework version**: 0.23
- **Python version**: 3.6
- **CPU or GPU**: ml.t2.medium
- **Custom Docker image (Y/N)**: N

**Additional context**
Some more information:

- The homologation(testing) endpoint wasn't called all that often and had big gaps between calls, they would only happen when we were testing something.
- It was deployed through an AWS Sagemaker Notebook using the Sagemaker SDK for Python
- First time the delta between a request and going offline was 8 hours, and the second time the delta was 48h.

Guía de contribución

Abrir la guía de contribución

Línea de trabajo

Empieza revisando el despliegue de SageMaker Python SDK 2.72.1 desde AWS SageMaker Notebook y, a continuación, compara los registros de CloudTrail y CloudWatch del endpoint correspondientes a las desapariciones del 28 de junio y del 3 de julio. Se considera completado identificar una causa reproducible o pruebas suficientes que expliquen cómo desapareció el endpoint sin que conste ningún delete o update.

Escrito por el modelo de indexación a partir del texto del issue.

Evaluación

Stack tecnológico
aws, machine-learning, python
Área
cloud, machine-learning
Tipo de issue
Error
Dificultad
5/5
Tiempo estimado
Más de una semana
Estado de actividad
Estancado
Claridad
Necesita aclaración
Aptitud para principiantes
20/100

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