opensearch-project/data-prepper
Nov 2024 – Oct 2025
12 Months active
Languages Used
GroovyJavaMarkdownGradleYAML
Technical Skills
AWS LambdaBuild ConfigurationDead Letter Queue (DLQ)Error HandlingIntegration TestingJava
Krishna Kondaka
PROFILE
Krishna Kondaka
Krishna Krishnan developed and enhanced data pipeline features for the opensearch-project/data-prepper repository over a year, focusing on reliability, observability, and cloud integration. He engineered robust AWS Lambda, SQS, and CloudWatch Logs sinks with Dead Letter Queue support, advanced error handling, and configurable resource management. Leveraging Java and the AWS SDK, Krishna introduced OpenTelemetry-compliant event modeling, automatic data format detection, and extensible plugin frameworks. His work included optimizing CSV and JSON parsing, implementing caching, and refining configuration flows to reduce failures and improve performance. Through comprehensive integration testing and modular refactoring, he delivered scalable, maintainable solutions for complex distributed data processing.
Overall Statistics
Feature vs Bugs
82%Features
Repository Contributions
47Total
Bugs
6
Commits
47
Features
27
Lines of code
30,361
Activity Months12
Your Network
1413 people
Work History
October 2025
5 Commits • 2 Features
Oct 1, 2025October 2025 highlights for opensearch-project/data-prepper: Implemented Dead Letter Queue (DLQ) support and enhanced error handling for sinks, enabling failed events to be routed to DLQ pipelines or files across OpenSearch and CloudWatch Logs, with negative integration tests for credential-missing scenarios. Introduced SinkForwardConfig to forward successful sink records to downstream pipelines, enabling conditional routing and greater pipeline flexibility. Fixed aggregate processor to gracefully handle empty groups, preventing null pointer exceptions. These changes improve reliability, observability, and operational resilience, reducing data loss and enabling more robust data pipelines. Key commits covered: 41773e6029ea58ce63f0d483c620aad389dfd6d1; 5ad48850a38b40458b2f20b2e9edad498d4db873; 13def65f5563686e54f729e9663943aebb0ca291; 3e7190264cb311aec385a3a75a348078925e03ae; 4071ed0dc465336694a091b7ae375618002ab3b5.
5 Commits • 2 Features
Oct 1, 2025October 2025 highlights for opensearch-project/data-prepper: Implemented Dead Letter Queue (DLQ) support and enhanced error handling for sinks, enabling failed events to be routed to DLQ pipelines or files across OpenSearch and CloudWatch Logs, with negative integration tests for credential-missing scenarios. Introduced SinkForwardConfig to forward successful sink records to downstream pipelines, enabling conditional routing and greater pipeline flexibility. Fixed aggregate processor to gracefully handle empty groups, preventing null pointer exceptions. These changes improve reliability, observability, and operational resilience, reducing data loss and enabling more robust data pipelines. Key commits covered: 41773e6029ea58ce63f0d483c620aad389dfd6d1; 5ad48850a38b40458b2f20b2e9edad498d4db873; 13def65f5563686e54f729e9663943aebb0ca291; 3e7190264cb311aec385a3a75a348078925e03ae; 4071ed0dc465336694a091b7ae375618002ab3b5.
October 2025
September 2025
1 Commits
Sep 1, 2025September 2025 monthly summary for opensearch-project/data-prepper: Focused on reliability and resource management improvements for the CloudWatch Logs sink through enhanced integration tests and verification of event handle lifecycle. No new user-facing features delivered this month; primary effort centered on test coverage and stability of the sink integration.
September 2025
1 Commits
Sep 1, 2025September 2025 monthly summary for opensearch-project/data-prepper: Focused on reliability and resource management improvements for the CloudWatch Logs sink through enhanced integration tests and verification of event handle lifecycle. No new user-facing features delivered this month; primary effort centered on test coverage and stability of the sink integration.
August 2025
3 Commits • 3 Features
Aug 1, 2025August 2025: Focused on reliability, efficiency, and performance improvements in opensearch-project/data-prepper. Delivered three core features: Dead Letter Queue for Pipeline Failures to gracefully reroute failed events; JSON Serialization for DefaultTraceGroupFields to reduce data size in transit and storage; and Caching for the AWS Lambda Processor to boost throughput by reusing results. Also completed test fixes and enhancements to raise code coverage, and refactored batch/cache key handling to support scalable processing. Results: reduced failure impact, improved data handling, and faster event processing in production.
3 Commits • 3 Features
Aug 1, 2025August 2025: Focused on reliability, efficiency, and performance improvements in opensearch-project/data-prepper. Delivered three core features: Dead Letter Queue for Pipeline Failures to gracefully reroute failed events; JSON Serialization for DefaultTraceGroupFields to reduce data size in transit and storage; and Caching for the AWS Lambda Processor to boost throughput by reusing results. Also completed test fixes and enhancements to raise code coverage, and refactored batch/cache key handling to support scalable processing. Results: reduced failure impact, improved data handling, and faster event processing in production.
August 2025
July 2025
4 Commits • 3 Features
Jul 1, 2025July 2025 highlights for opensearch-project/data-prepper. Key features delivered: Event Key Normalization across CSV, Key-Value, and JSON parsers via a normalize_keys config to replace invalid characters in event keys, improving data consistency and reducing parsing errors. Architectural work included an AWS Common module refactor (introduce and revert) to improve modularity, with reintegration back into aws-plugin. Additionally, an extensibility improvement changed createStsClient from private to protected to enable subclass overrides. Business value: more reliable data processing, clearer module boundaries, and easier customization for downstream deployments. No major bugs fixed this month based on the provided scope.
July 2025
4 Commits • 3 Features
Jul 1, 2025July 2025 highlights for opensearch-project/data-prepper. Key features delivered: Event Key Normalization across CSV, Key-Value, and JSON parsers via a normalize_keys config to replace invalid characters in event keys, improving data consistency and reducing parsing errors. Architectural work included an AWS Common module refactor (introduce and revert) to improve modularity, with reintegration back into aws-plugin. Additionally, an extensibility improvement changed createStsClient from private to protected to enable subclass overrides. Business value: more reliable data processing, clearer module boundaries, and easier customization for downstream deployments. No major bugs fixed this month based on the provided scope.
June 2025
7 Commits • 7 Features
Jun 1, 2025June 2025 Monthly Summary for opensearch-project/data-prepper: Delivered a set of feature enhancements that improve integration flexibility, performance, and data processing capabilities. Highlights include AWS Glue Schema Registry endpoint override for Kafka sources, CloudWatch Logs sink fixed thread pool with configurable workers, DetectFormatProcessor for automatic data format detection, CSV processor multi-line support, and ConvertType processor auto conversion for booleans, numbers, and timestamps. Major bugs fixed: no critical bug fixes reported this month. Overall impact: enables connections to multiple Glue Registry instances, more predictable resource usage, and richer, more reliable data processing pipelines with clearer pipeline instrumentation. Technologies/skills demonstrated: Java-based plugin framework improvements, extension loading optimizations, multi-threading, and advanced data parsing and type coercion.
7 Commits • 7 Features
Jun 1, 2025June 2025 Monthly Summary for opensearch-project/data-prepper: Delivered a set of feature enhancements that improve integration flexibility, performance, and data processing capabilities. Highlights include AWS Glue Schema Registry endpoint override for Kafka sources, CloudWatch Logs sink fixed thread pool with configurable workers, DetectFormatProcessor for automatic data format detection, CSV processor multi-line support, and ConvertType processor auto conversion for booleans, numbers, and timestamps. Major bugs fixed: no critical bug fixes reported this month. Overall impact: enables connections to multiple Glue Registry instances, more predictable resource usage, and richer, more reliable data processing pipelines with clearer pipeline instrumentation. Technologies/skills demonstrated: Java-based plugin framework improvements, extension loading optimizations, multi-threading, and advanced data parsing and type coercion.
June 2025
May 2025
2 Commits • 1 Features
May 1, 2025May 2025: Focused on reliability, observability, and correctness of the SQS sink integration in opensearch-project/data-prepper. Implemented increased test coverage, introduced latency and payload-size metrics, and refactored configuration flow. Renamed log_send_interval to flush_interval and tightened validation to prevent misconfig. Addressed Jakarta annotation issues to improve correctness. Also aligned related configuration for CloudWatch Logs to reduce runtime errors. These changes reduce ingestion failures, improve operational visibility, and enable safer deployments.
May 2025
2 Commits • 1 Features
May 1, 2025May 2025: Focused on reliability, observability, and correctness of the SQS sink integration in opensearch-project/data-prepper. Implemented increased test coverage, introduced latency and payload-size metrics, and refactored configuration flow. Renamed log_send_interval to flush_interval and tightened validation to prevent misconfig. Addressed Jakarta annotation issues to improve correctness. Also aligned related configuration for CloudWatch Logs to reduce runtime errors. These changes reduce ingestion failures, improve operational visibility, and enable safer deployments.
April 2025
9 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for opensearch-project/data-prepper focusing on feature delivery, bug fixes, and technical milestones that drive reliability, scalability, and cloud integration.
9 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for opensearch-project/data-prepper focusing on feature delivery, bug fixes, and technical milestones that drive reliability, scalability, and cloud integration.
April 2025
March 2025
4 Commits • 2 Features
Mar 1, 2025Month: 2025-03 | opensearch-project/data-prepper Concise monthly summary focusing on key accomplishments, business value, and technical achievements: Key features delivered: - OpenTelemetry integration: Introduced OTEL standard classes for Logs, Traces, and Metrics and added OTEL-conformant event generation via a new output format. This alignment of identifiers (instrumentationScope) across metric/span classes enhances OTEL-compliant telemetry modeling and improves observability data pipelines. - Notable commits: 04dc226be36f6d22d22f6e1f237bdf9819a68453; f136f48335cae5551a2220f44a17efa95800cf4e - S3 source plugin: metadata_only scans via data_selection option: Added data_selection='metadata_only' to scan only object metadata, reducing data transfer and latency; includes new integration tests validating performance benefits and behavior. - Notable commit: f32d12e5dc5500f0c148688e05be979f96cef81f Major bugs fixed: - S3 source plugin: robust handling of multiple data selections per prefix: Fixed mapping of data_selection to prefixes in the ScanObjectWorker to improve reliability in complex, multi-prefix configurations; integration tests updated accordingly. - Notable commit: 7c721888e9710477c134236d1e1d1433a070c10c Overall impact and accomplishments: - Business value: Improved observability readiness with OTEL-aligned telemetry, reduced data transfer costs and latency for S3 scans, and increased reliability in complex bucket configurations, enabling more efficient data pipelines and faster insights. - Operational efficiency: Added integration tests to cover new features and scenarios, boosting confidence in deployments and reducing regression risk. Technologies/skills demonstrated: - OpenTelemetry standards and OTEL-conformant event generation, instrumentationScope alignment - S3 source plugin development and robust data_selection handling - Test automation and integration testing to validate behavior and performance This month’s work positions Data Prepper for scalable telemetry pipelines and more cost-efficient data ingestion from S3 sources.
March 2025
4 Commits • 2 Features
Mar 1, 2025Month: 2025-03 | opensearch-project/data-prepper Concise monthly summary focusing on key accomplishments, business value, and technical achievements: Key features delivered: - OpenTelemetry integration: Introduced OTEL standard classes for Logs, Traces, and Metrics and added OTEL-conformant event generation via a new output format. This alignment of identifiers (instrumentationScope) across metric/span classes enhances OTEL-compliant telemetry modeling and improves observability data pipelines. - Notable commits: 04dc226be36f6d22d22f6e1f237bdf9819a68453; f136f48335cae5551a2220f44a17efa95800cf4e - S3 source plugin: metadata_only scans via data_selection option: Added data_selection='metadata_only' to scan only object metadata, reducing data transfer and latency; includes new integration tests validating performance benefits and behavior. - Notable commit: f32d12e5dc5500f0c148688e05be979f96cef81f Major bugs fixed: - S3 source plugin: robust handling of multiple data selections per prefix: Fixed mapping of data_selection to prefixes in the ScanObjectWorker to improve reliability in complex, multi-prefix configurations; integration tests updated accordingly. - Notable commit: 7c721888e9710477c134236d1e1d1433a070c10c Overall impact and accomplishments: - Business value: Improved observability readiness with OTEL-aligned telemetry, reduced data transfer costs and latency for S3 scans, and increased reliability in complex bucket configurations, enabling more efficient data pipelines and faster insights. - Operational efficiency: Added integration tests to cover new features and scenarios, boosting confidence in deployments and reducing regression risk. Technologies/skills demonstrated: - OpenTelemetry standards and OTEL-conformant event generation, instrumentationScope alignment - S3 source plugin development and robust data_selection handling - Test automation and integration testing to validate behavior and performance This month’s work positions Data Prepper for scalable telemetry pipelines and more cost-efficient data ingestion from S3 sources.
February 2025
3 Commits • 2 Features
Feb 1, 2025February 2025 performance summary for opensearch-project/data-prepper: Focused on delivering new capabilities and improving protocol compatibility, with strong emphasis on observability integrations and OTEL interoperability.
3 Commits • 2 Features
Feb 1, 2025February 2025 performance summary for opensearch-project/data-prepper: Focused on delivering new capabilities and improving protocol compatibility, with strong emphasis on observability integrations and OTEL interoperability.
February 2025
January 2025
1 Commits
Jan 1, 2025January 2025 — opensearch-project/data-prepper: Documentation quality improvements focused on Javadoc corrections across Data Prepper components. Changes fixed Javadoc errors by adding missing return type annotations and clarifying parameter descriptions, without runtime changes.
January 2025
1 Commits
Jan 1, 2025January 2025 — opensearch-project/data-prepper: Documentation quality improvements focused on Javadoc corrections across Data Prepper components. Changes fixed Javadoc errors by adding missing return type annotations and clarifying parameter descriptions, without runtime changes.
December 2024
5 Commits • 1 Features
Dec 1, 2024December 2024 (Month: 2024-12) - Key highlights for opensearch-project/data-prepper. Delivered reliability and security improvements to the Data Prepper data ingestion pipeline. Implemented aggregation acknowledgement, improved error handling in expression evaluation, and consolidated release bug fixes for 2.10.2 with security and plugin error fixes. Drove business value by reducing pipeline failures, improving observability via release notes, and strengthening OpenTelemetry source security. Documented changes and patch notes for 2.10.2/2.10.1 as part of the December release cycle.
5 Commits • 1 Features
Dec 1, 2024December 2024 (Month: 2024-12) - Key highlights for opensearch-project/data-prepper. Delivered reliability and security improvements to the Data Prepper data ingestion pipeline. Implemented aggregation acknowledgement, improved error handling in expression evaluation, and consolidated release bug fixes for 2.10.2 with security and plugin error fixes. Drove business value by reducing pipeline failures, improving observability via release notes, and strengthening OpenTelemetry source security. Documented changes and patch notes for 2.10.2/2.10.1 as part of the December release cycle.
December 2024
November 2024
3 Commits • 2 Features
Nov 1, 2024Monthly summary for 2024-11 for opensearch-project/data-prepper: Delivered two major Lambda-related initiatives that improve modularity, observability, and failure handling, with a focus on business value and reliability. Implemented a refactor of the AWS Lambda plugin to share common code between the processor and sink via a unified handler and configuration classes, updated integration tests and build configurations, and enhanced metrics, error handling, and payload size tracking for better observability and reliability of Lambda invocations. Strengthened AWS Lambda sink error handling with enhanced Dead Letter Queue (DLQ) support by refactoring DLQ handling to correctly pass configuration and AWS authentication to the DlqPushHandler and by creating/sending DlqObject instances on failures to ensure failed events are routed to the configured DLQ. These changes, along with test and build updates, improve system reliability, observability, and maintainability, driving reduced MTTR and higher confidence in Lambda-driven data flows.
November 2024
3 Commits • 2 Features
Nov 1, 2024Monthly summary for 2024-11 for opensearch-project/data-prepper: Delivered two major Lambda-related initiatives that improve modularity, observability, and failure handling, with a focus on business value and reliability. Implemented a refactor of the AWS Lambda plugin to share common code between the processor and sink via a unified handler and configuration classes, updated integration tests and build configurations, and enhanced metrics, error handling, and payload size tracking for better observability and reliability of Lambda invocations. Strengthened AWS Lambda sink error handling with enhanced Dead Letter Queue (DLQ) support by refactoring DLQ handling to correctly pass configuration and AWS authentication to the DlqPushHandler and by creating/sending DlqObject instances on failures to ensure failed events are routed to the configured DLQ. These changes, along with test and build updates, improve system reliability, observability, and maintainability, driving reduced MTTR and higher confidence in Lambda-driven data flows.
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Quality Metrics
Correctness91.2%
Maintainability87.2%
Architecture87.8%
Performance81.8%
AI Usage20.8%
Skills & Technologies
Programming Languages
GradleGroovyJavaMarkdownYAML
Technical Skills
API DevelopmentAWSAWS Glue Schema RegistryAWS LambdaAWS S3AWS SDKAcknowledgement ManagementBackend DevelopmentBuild AutomationBuild ConfigurationBuild ManagementCI/CDCSV ParsingCachingCloudWatch
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