opensearch-project/data-prepper
Jul 2025 – Nov 2025
3 Months active
Languages Used
Java
Technical Skills
AWS SDKConcurrencyDistributed SystemsJavaRefactoringTesting
Jonah Calvo
PROFILE
Jonah Calvo
Worked on the opensearch-project/data-prepper repository, delivering features and fixes to enhance streaming data ingestion and reliability. Built per-shard checkpointing for DynamoDB stream sources by introducing a ShardAcknowledgementManager, refactoring core components to decouple acknowledgment logic and improve fault tolerance. Addressed critical bugs by ensuring reliable finalization of DynamoDB Streams shard processing and normalizing null messages in the Dead Letter Queue to prevent errors. Added OpenSearch Data Streams support with automatic action selection and data stream detection, reducing manual configuration. Leveraged Java, AWS SDK, and distributed systems expertise, with a focus on robust error handling, testing, and maintainable backend development.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
4Total
Bugs
2
Commits
4
Features
2
Lines of code
1,832
Activity Months3
Your Network
1669 peopleShared Repositories
59
Work History
November 2025
1 Commits • 1 Features
Nov 1, 2025Month 2025-11: Delivered OpenSearch Data Streams support with automatic action selection in opensearch-project/data-prepper. Implemented data stream detection and data-stream-specific configuration handling, and added tests to validate behavior across data stream scenarios. This work improves ingestion reliability, reduces manual configuration, and enhances OpenSearch compatibility for streaming workloads. All changes are traceable to commit 23eb0d9ddd8a8379ee1424f650ca54fda13cfaf2 (Signed-off-by: Jonah Calvo).
1 Commits • 1 Features
Nov 1, 2025Month 2025-11: Delivered OpenSearch Data Streams support with automatic action selection in opensearch-project/data-prepper. Implemented data stream detection and data-stream-specific configuration handling, and added tests to validate behavior across data stream scenarios. This work improves ingestion reliability, reduces manual configuration, and enhances OpenSearch compatibility for streaming workloads. All changes are traceable to commit 23eb0d9ddd8a8379ee1424f650ca54fda13cfaf2 (Signed-off-by: Jonah Calvo).
November 2025
August 2025
2 Commits
Aug 1, 2025Month: 2025-08 — Focused on reliability and data integrity for streaming ingestion in opensearch-project/data-prepper. Delivered two critical bug fixes: DynamoDB Streams shard finalization to prevent partial processing and DLQ null-message normalization to avoid NPE, with tests added for DLQ handling. These changes reduce data loss risk, improve resiliency, and demonstrate proficiency in streaming architectures, Java, and test coverage.
August 2025
2 Commits
Aug 1, 2025Month: 2025-08 — Focused on reliability and data integrity for streaming ingestion in opensearch-project/data-prepper. Delivered two critical bug fixes: DynamoDB Streams shard finalization to prevent partial processing and DLQ null-message normalization to avoid NPE, with tests added for DLQ handling. These changes reduce data loss risk, improve resiliency, and demonstrate proficiency in streaming architectures, Java, and test coverage.
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for opensearch-project/data-prepper: Delivered per-shard checkpointing for the DynamoDB stream source via ShardAcknowledgementManager, integrating it with ShardConsumer and StreamScheduler. This refactor decouples acknowledgment logic from core processing, improving reliability, fault tolerance, and operational visibility for DynamoDB streaming. The change reduces risk during shard rebalances and restarts and lays the groundwork for future resilience enhancements. Business value includes more predictable ingestion, easier troubleshooting, and smoother scaling of DynamoDB-based data ingestion.
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for opensearch-project/data-prepper: Delivered per-shard checkpointing for the DynamoDB stream source via ShardAcknowledgementManager, integrating it with ShardConsumer and StreamScheduler. This refactor decouples acknowledgment logic from core processing, improving reliability, fault tolerance, and operational visibility for DynamoDB streaming. The change reduces risk during shard rebalances and restarts and lays the groundwork for future resilience enhancements. Business value includes more predictable ingestion, easier troubleshooting, and smoother scaling of DynamoDB-based data ingestion.
July 2025
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Quality Metrics
Correctness97.6%
Maintainability87.6%
Architecture92.6%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
AWS SDKBackend DevelopmentConcurrencyData ProcessingDistributed SystemsDynamoDB StreamsError HandlingJavaOpenSearchRefactoringTesting
Repositories Contributed To
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