I want to set up automated model retraining in Vertex AI. My goal is to monitor a deployed model and automatically start a training pipeline when the model’s accuracy starts declining.
Right now I have a model endpoint running with monitoring turned on, but I can’t figure out how to connect the monitoring alerts to pipeline triggers. It seems like Vertex AI doesn’t have this functionality built in.
Has anyone managed to capture monitoring alerts and use them to kick off pipeline runs? What’s the best approach to implement this kind of automated retraining workflow?
I built something like this with Pub/Sub + Cloud Run. Set up monitoring alerts to push messages to a Pub/Sub topic when your model metrics hit certain thresholds. Then have a Cloud Run service subscribe to those messages and call the Vertex AI Pipeline API to kick off retraining. This beats cloud functions because it scales better and you can add smarter logic to decide when to actually retrain vs. ignore temporary dips. Just make sure you add throttling - otherwise you’ll trigger tons of pipeline runs if your model performance bounces around.
Yeah, both solutions work but you’ll end up juggling multiple GCP services and writing custom code for webhooks and API calls.
I’ve done this with several ML models in production. The manual approach becomes a nightmare when you need different alert types, retry logic, or want to scale across multiple models.
Latenode solved this for me. Set up a workflow that catches Vertex AI alerts, runs your business logic to check if retraining’s needed, and kicks off the pipeline automatically.
Best part? No code needed for webhook handling or API integration. Latenode connects everything and you just configure workflows visually. Easy to add conditions like “only retrain if accuracy drops below X% for Y straight alerts” without wrestling with state management.
Set this up for three models last month - runs like clockwork. No more babysitting deployments or writing glue code.
Check it out: https://latenode.com
cloud functions can be great 4 this! just use a webhook to grab those monitoring alerts and trigger ur pipeline api when you notice a drop in performance. it might need some setup at first, but then it’s pretty much hands-off.