assets bundle

seefoods — Tue, 17 Jun 2025 15:37:23 GMT

Hello Guys,

I am working on assets bundle. So i want to make it generic for all team like ( analytics, data engineering), Someone could you share a best practice for this purpose ?

Cordially,

Re: assets bundle

lingareddy_Alva — Tue, 17 Jun 2025 16:17:56 GMT

Hi @seefoods

Creating a generic asset bundle that works across different teams requires careful design around modularity, configurability, and clear interfaces.

Here are key best practices:
1. Structure and Organization
Modular Architecture: Design your bundle with separate modules for common functionality (logging, configuration, data connectors) and team-specific components.
Use a plugin-style architecture where teams can extend base functionality without modifying core components.
Clear Separation of Concerns: Separate infrastructure code, business logic, and configuration. This allows teams to customize what they need while inheriting stable, tested infrastructure components.

2. Configuration Management
Parameterized Templates: Use configuration files or environment variables for team-specific settings like database connections, API endpoints, storage paths, and processing parameters. Avoid hardcoding these values.
Environment-Specific Configs: Support different configurations for development, staging, and production environments that teams can customize independently.
Schema Validation: Define clear schemas for configuration to catch errors early and provide documentation for teams on what parameters are available.

3. Standardization with Flexibility
Common Interfaces: Define standard interfaces for data ingestion, transformation, and output that all teams must implement, but allow flexibility in the underlying implementation.
Shared Libraries: Create common utility libraries for tasks like data validation, error handling, monitoring, and authentication that teams can leverage consistently.
Naming Conventions: Establish consistent naming patterns for resources, variables, and outputs across teams.

4. Documentation and Onboarding
Comprehensive Documentation: Include setup guides, API references, examples, and troubleshooting guides. Document both the common components and how to extend them.
Example Implementations: Provide working examples for typical use cases that each team encounters.
Migration Guides: If updating existing bundles, provide clear migration paths and backward compatibility strategies.

5. Testing and Quality
Automated Testing: Include unit tests for common components and integration test templates that teams can adapt for their specific use cases.
CI/CD Integration: Provide pipeline templates that teams can customize while maintaining consistent deployment practices.

6. Governance and Maintenance
Version Management: Use semantic versioning and maintain clear changelogs. Consider having LTS versions for stability-focused teams.
Feedback Mechanisms: Establish channels for teams to request features, report issues, and contribute improvements back to the common bundle.
Regular Reviews: Schedule periodic reviews with stakeholder teams to assess what's working and what needs adjustment

Re: assets bundle

Michał — Wed, 03 Sep 2025 13:55:35 GMT

Hi seefoods,

Were you able to achieve that generic asset bundle setup? I've been working on something, potentially, similar, and I'd be happy to discuss it, hoping to share experiences.

While what I have works for a few teams, it is focused on declarative pipeline development only. Also, it appears to make it work I've been going against Databricks advice, or at least against their examples. What was your experience?

topic assets bundle in Data Engineering

assets bundle

Re: assets bundle

Re: assets bundle