ML Workflow Automation
Manual ML workflows don't scale. Retraining models by hand, manually validating data, and deploying via SSH are bottlenecks that slow down iteration. We automate your entire ML lifecycle — data ingestion triggers, scheduled retraining, automated validation, and hands-free deployment — so your team focuses on model improvement, not operations.
Need this done for your project?
We implement, you ship. Async, documented, done in days.
Event-Driven Triggers
New data arrival triggers validation and preprocessing pipelines. Data drift detection triggers retraining. Model registry promotions trigger deployment. Alert thresholds trigger rollback. Each trigger connects to the appropriate pipeline via Argo Events, Airflow sensors, or cloud-native event bridges. No cron jobs that run whether needed or not — workflows execute in response to actual events.
Scheduled Retraining
For models that need regular updates (recommendation engines, fraud detection), we configure scheduled retraining pipelines. Each run: pulls latest data, validates it, trains the model, evaluates against baselines, and promotes if improved. The schedule is configurable — daily, weekly, or triggered by data volume thresholds. Failed runs retry with exponential backoff and alert on persistent failure.
Self-Healing Automation
Stale model endpoints get automatically replaced. Failed pipeline steps retry with exponential backoff. OOM-killed training jobs restart with reduced batch size. Unhealthy serving pods get replaced by Kubernetes liveness probes. We build automation that handles the 90% of operational issues that follow predictable patterns — your on-call engineer handles the remaining 10%.
Orchestration & Observability
All automated workflows are observable: DAG visualizations show pipeline state, execution logs capture every step, and metrics track end-to-end pipeline duration. SLA monitoring alerts when pipelines exceed expected runtime. You get a dashboard showing all active workflows, their status, and historical success rates. Automation you can't observe is automation you can't trust.
Why Anubiz Engineering
Ready to get started?
Skip the research. Tell us what you need, and we'll scope it, implement it, and hand it back — fully documented and production-ready.