Morning Star EngineeringMorning Star Engineering

Technology

The Stack We Work In

We choose tools based on fit, not familiarity or vendor incentives. Below is the technology we work with day-to-day - from the plant floor to the lakehouse.

OT & Historian

Where operational data originates. We extract, contextualize, and move it to where it can be used.

OSI PIAspen IP.21Seeq

Streaming & Orchestration

Moving data reliably from source to destination - whether in real time or on a schedule.

Apache KafkaApache FlinkApache Airflow

Processing & Transformation

Turning raw operational data into clean, structured, analytics-ready tables.

Apache SparkdbtDelta Live Tables

Lakehouse & Storage

The platform layer where data lands, is governed, and is made available for analysis.

DatabricksDelta LakeApache IcebergMinIO

Formats

Open, interoperable formats that avoid lock-in and work across the entire stack.

ParquetAvroDelta

Governance & Quality

Knowing what data you have, who can access it, and whether it can be trusted.

Unity CatalogGreat ExpectationsDataHub

Observability

Pipeline health, model performance, and infrastructure metrics that are visible before they become operational problems.

GrafanaPrometheusMLflow

Machine Learning & Analytics

Statistical analysis, predictive analytics, and production machine-learning systems built around a defined decision or operational response.

PyTorchscikit-learnstatsmodelsSeeq

Languages

The primary languages we write production code in.

PythonSQLSpark / Scala

Infrastructure

Reproducible, version-controlled infrastructure that doesn't become a maintenance burden.

KubernetesTerraformDocker

Cloud

We work across all three major clouds. Platform decisions are driven by your requirements, not our preferences.

AWSAzureGCP