Observed Signal · May 12, 2026 · Technical Release · Source: DEV Community · Impact: 1/5 · Sentiment: Neutral
Developer Publishes Production MLOps Pipeline
Avinash Mani Tripathi published a Dev.to post on 2026-05-12 describing a finished, production-oriented MLOps pipeline (GitHub link provided). The project implements data versioning (DVC), experiment tracking (MLflow), hyperparameter tuning (Optuna), model serving (FastAPI), containerization (Docker), CI/CD via GitHub Actions with GHCR, Kubernetes deployment on Minikube, drift monitoring using PSI, and a monitoring stack based on Prometheus and Grafana. The author reports a local Prometheus scrape issue causing Grafana to show "No data" and requests community feedback on the GitHub Actions workflow, Kubernetes manifests, and the drift-monitoring implementation. A public GitHub repository URL is included for review and contributions.
Personal developer project with technical MLOps details useful to engineers but limited direct impact on the AdTech/MarTech industry at large.
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Key Takeaways & Evidence Grounding
- Author Avinash Mani Tripathi published the post on Dev.to on 2026-05-12.
- Project repository: https://github.com/avinashmnth2507-dev/mlops-house-price-predictor.git.
- Pipeline components include DVC (data versioning), MLflow (experiment tracking), Optuna (hyperparameter tuning), FastAPI (model serving), Docker (containerization), GitHub Actions → GHCR (CI/CD), and Minikube (Kubernetes deployment).
- Monitoring and observability use Prometheus and Grafana; drift monitoring implemented using Population Stability Index (PSI); FinOps cost tracking is included.
- Known issue: Grafana shows "No data" due to a Prometheus scrape problem in the local Minikube cluster; author is seeking debugging feedback on CI/CD, k8s manifests, and drift monitoring.
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