monosi
dagster
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monosi | dagster | |
---|---|---|
20 | 46 | |
320 | 10,215 | |
1.3% | 5.2% | |
0.0 | 10.0 | |
over 1 year ago | 2 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
monosi
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Open source data observability tools with UI?
I also found https://github.com/monosidev/monosi but it seems there are no activities in the repository from last year.
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Databricks monitoring/observability
I'm building an open source data observability platform - https://github.com/monosidev/monosi that visualizes metadata collected from data warehouses. Databricks is currently not supported (contributions welcome!), but it may help to take a look at how we approach the anomaly detection & visualization aspects.
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Monitor PostgreSQL for anomalies in ingested data
Building an open source tool that lets you monitor PostgreSQL instances form anomalies in data coming in - https://github.com/monosidev/monosi
- Open Source Data Observability for BigQuery
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Metadata extraction and management
It’s open source, check out the repository here - https://github.com/monosidev/monosi
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How to Monitor Supabase with Monosi
🎉 Congratulations, you've just set up and scheduled a data monitor on your Supabase instance. You can now add more monitors to other tables in your database. Find more information on how to use Monosi here.
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Setting up data monitoring for PostgreSQL
Now that you’ve worked through an example using a public PostgreSQL instance, you can further extend this to your own data store. For more information, get started here.
- Monosi v0.0.3 Released! Open source Data Observability now with a Web UI, Postgres Support, & more.
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Sunday Daily Thread: What's everyone working on this week?
Continuing to build out & stabilize Monosi (open source data observability) - https://github.com/monosidev/monosi
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Data pipeline suggestions
Observability: Monosi
dagster
- Experience with Dagster.io?
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Dagster tutorials
My recommendation is to continue on with the tutorial, then look at one of the larger example projects especially the ones named “project_”, and you should understand most of it. Of what you don't understand and you're curious about, look into the relevant concept page for the functions in the docs.
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The Dagster Master Plan
I found this example that helped me - https://github.com/dagster-io/dagster/tree/master/examples/project_fully_featured/project_fully_featured
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What are some open-source ML pipeline managers that are easy to use?
I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home
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The Why and How of Dagster User Code Deployment Automation
In Helm terms: there are 2 charts, namely the system: dagster/dagster (values.yaml), and the user code: dagster/dagster-user-deployments (values.yaml). Note that you have to set dagster-user-deployments.enabled: true in the dagster/dagster values-yaml to enable this.
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Best Orchestration Tool to run dbt projects?
Dagster seemed really cool when I looked into it as an alternative to airflow. I especially like the software defined assets and built-in lineage which I haven't seen in any other tool. However it seems it does not support RBAC which is a pretty big issue if you want a self-service type of architecture, see https://github.com/dagster-io/dagster/issues/2219. It does seem like it's available in their hosted version, but I wanted to run it myself on k8s.
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dbt Cloud Alternatives?
Dagster? https://dagster.io
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What's the best thing/library you learned this year ?
One that I haven't seen on here yet: dagster
- Anyone have an example of a project where a handful of the more popular Python tools are used? (E.g. airbyte, airflow, dbt, and pandas)
- Can we take a moment to appreciate how much of dataengineering is open source?
What are some alternatives?
datahub - The Metadata Platform for your Data Stack
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
jitsu - Jitsu is an open-source Segment alternative. Fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
castled - Castled is an open source reverse ETL solution that helps you to periodically sync the data in your db/warehouse into sales, marketing, support or custom apps without any help from engineering teams
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
soda-spark - Soda Spark is a PySpark library that helps you with testing your data in Spark Dataframes
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
soda-sql - Data profiling, testing, and monitoring for SQL accessible data.
MLflow - Open source platform for the machine learning lifecycle
great_expectations - Always know what to expect from your data.
meltano