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Octopipe Glossary

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Terms and Definitions

• API (Application Programming Interface): A set of protocols and tools for building software applications. In Octopipe, APIs are used to interact with external data sources and connectors.
• Connector: A module that establishes a connection to a specific data source or destination. Connectors handle the details of data extraction and loading.
• Type Safe API: An automatically generated API that enforces strict data types for all interactions. This ensures that data is handled consistently and reduces runtime errors.
• Transform Layer: The component that maps the type safe API schema to the labeled database schema. It converts data into a format that is suitable for the destination system.
• Meltano: A tool integrated within Octopipe for managing data extraction and load processes. It simplifies the integration of various data sources.
• Airflow: A workflow orchestration tool used by Octopipe to schedule and monitor pipelines. Airflow manages task dependencies and execution order.
• S3 (Simple Storage Service): A scalable storage solution provided by AWS, often used for storing intermediate data and logs.
• Kafka: A distributed event streaming platform used for real-time data pipelines and messaging. In Octopipe, Kafka helps manage streaming data.
• Spark: A unified analytics engine for large-scale data processing. Spark is used to execute transformation logic on large datasets.
• LLM (Large Language Model): An AI model used to assist in generating type safe APIs and transformation code. The LLM derives data types from API responses to ensure consistency.
• CLI (Command-Line Interface): The primary way developers interact with Octopipe. The CLI provides commands for project initialization, pipeline management, and configuration.
• Cron Expression: A string representing a schedule, used to configure when pipelines should run. Cron expressions follow a standard syntax (e.g., "0 0 * * *" for daily execution).
• Local Development: The practice of developing and testing pipelines on a local machine before deploying them to production. Octopipe supports an excellent local development experience.
• Cloud Deployment: Running Octopipe on cloud infrastructure, which may offer additional scalability and managed services.
• Configuration File: A file in JSON or YAML format that stores settings for Octopipe. Configuration files are used to maintain consistent settings across environments.
• Environment Variables: Variables set in your operating system that Octopipe can use for configuration, especially for sensitive data like API keys.
• Verbose Mode: An option that provides detailed logging output. This is useful for debugging and understanding the inner workings of commands.

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Additional Concepts

• Error Handling: Mechanisms built into Octopipe to manage and recover from errors during pipeline execution. Detailed logs help identify and fix issues.
• Scheduling: The process of setting up pipelines to run at specific intervals using cron expressions. Scheduling is handled by Airflow.
• Dependency Management: Ensuring that all parts of a pipeline (sources, transformations, destinations) are properly configured and connected before execution.

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Conclusion