Working with Automated Ingestion CBA Practice Questions (Page 3)

Questions 11–15

1. 11expert · hard

   A team configured a custom entity provider to ingest data from an internal system. The logs show the provider is running and fetching data, but no new entities appear in the catalog. The provider's code is confirmed to be returning valid JSON. What is the most likely cause of this issue?

   • AThe catalog backend is not configured to accept new entities
   • BThe OAuth2 token used by the provider has expired
   • CThe provider's schedule is set to a very long interval
   • DThe entity data does not have a valid kind, apiVersion, and metadata.name
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2. 12expert · hard

   A team is building a custom entity provider for a source system that uses a REST API with rate limiting. The provider is successfully fetching data, but the team is concerned about hitting the rate limit and causing ingestion to fail. What is the most robust way to handle this in the provider's design?

   • AImplement retry logic with exponential backoff in the provider
   • BFetch all data in a single large request
   • CIgnore the rate limit and let the ingestion fail
   • DIncrease the ingestion schedule to run less frequently
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4. 13foundation · easy

   What happens to ingested data after it is fetched by an entity provider in Backstage?

   • AIt is processed, validated, and transformed into catalog entities
   • BIt is sent to the frontend for display before storage
   • CIt is discarded if it does not match the provider's format
   • DIt is immediately stored in the catalog database without any checks
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5. 14foundation · easy

   What is the purpose of validation in the automated ingestion process?

   • ATo encrypt the data before storage
   • BTo ensure that ingested data conforms to the Backstage entity schema
   • CTo compress the data to save storage space
   • DTo convert the data into a human-readable format
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6. 15foundation · easy

   Which of the following is a key benefit of using automated ingestion for the Backstage catalog?

   • AIt allows catalog data to be stored in any external database without configuration
   • BIt guarantees that all catalog data is always accurate and free of errors
   • CIt reduces manual effort and helps keep catalog data consistent with the source systems
   • DIt eliminates the need for any human oversight of the catalog
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