OVERVIEW:
Apache Airflow is an open-source platform designed to programmatically author, schedule, and monitor workflows. Developed under the Apache Software Foundation, it enables users to orchestrate complex computational workflows, data processing jobs, and ETL (Extract, Transform, Load) processes through simple to complex DAGs (Directed Acyclic Graphs). Airflow's Python-based platform offers flexibility and a rich set of operators for integrating with numerous third-party services, databases, and infrastructure layers.
One of Airflow's core principles is the idea of "configuration as code." This approach allows data engineers and scientists to define their workflows in code, which promotes version control, collaboration, and reuse across the organization. Airflow's scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command-line utilities make it easy to visualize workflows, monitor progress, and troubleshoot issues directly.
Airflow's extensive plugin system and a large number of available integrations mean it can connect with almost any system in your data ecosystem, from cloud providers like AWS and GCP to databases such as PostgreSQL and MySQL, to messaging systems like Apache Kafka. This extensibility, combined with a strong community and a focus on scalability, makes Apache Airflow a powerful tool for automating and optimizing complex data workflows and processing pipelines in modern data platforms.
Here are some features of Whisper-Tiny Sentiment:
GET STARTED:
To open the console, follow the below instructions
Step 1. Allow ports in the security group:
Allow the Ports 8080, 8786,8787,22.
Step 2. Open the server:
Open the Public IP of the instance on port 8080. Wait for 1 minute for the Airflow interface.
Step 3. Fill the fields:
Now you will see the below dashboard where the admin is your default username and InstanceID is your password. Now press the sign-in button.
Now you will see the Dags dashboard. You can add your dags by doing SSH in the instance.
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