Search Results for "apache monitor"

Apache Airflow is a community-created platform for programmatically authoring, scheduling, and monitoring workflows. It’s much easier to do all these things when workloads are defined as code. They become more versionable, testable, maintainable and collaborative. With Airflow you can author workflows as directed acyclic graphs (DAGs) of tasks. This means that your tasks are executed on an array of workers while following the specified dependencies. And with rich command line utilities in...

Open-source data pipeline tool for transforming and integrating data. The modern replacement for Airflow. Effortlessly integrate and synchronize data from 3rd party sources. Build real-time and batch pipelines to transform data using Python, SQL, and R. Run, monitor, and orchestrate thousands of pipelines without losing sleep. Have you met anyone who said they loved developing in Airflow? That’s why we designed an easy developer experience that you’ll enjoy. Each step in your pipeline is a...

Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust...

Elementary is an open-source data observability solution for data & analytics engineers. Monitor your dbt project and data in minutes, and be the first to know of data issues. Gain immediate visibility, detect data issues, send actionable alerts, and understand the impact and root cause. Generate a data observability report, host it or share with your team. Monitoring of data quality metrics, freshness, volume and schema changes, including anomaly detection. Elementary data monitors are...

BPYTOP is a feature-rich, terminal-based resource monitor written in Python 3 that provides a highly visual overview of system performance. It displays real-time usage and statistics for CPU, memory, disks, network, and processes, with colorful graphs and widgets that update at configurable intervals. Users can drill into a process list, sort by various metrics, view tree hierarchies, and quickly spot heavy resource consumers. The tool is highly configurable through both an in-app options...