Azure/Azure-Sentinel
Nov 2024 – Nov 2024
1 Month active
Languages Used
Python
Technical Skills
API IntegrationAzure FunctionsCloud IntegrationCloud StorageData ConnectorData Engineering
shashank-shah1719
PROFILE
Shashank-shah1719
Worked on hardening and expanding the Armis Azure Sentinel Connector within the Azure/Azure-Sentinel repository, focusing on improving the reliability of data ingestion pipelines. Refactored the connector to use Azure Table Storage for checkpoint management, which enhanced startup reliability and ingestion stability. Implemented robust timeout and error handling logic using Python and Azure Functions, streamlining the connector’s initialization and reducing downtime from failed ingestions. Enhanced code quality and maintainability through updates to Flake8 and SonarQube, and refreshed packaging for easier code reviews. These improvements led to more stable system integration, better observability, and reduced operational overhead for incident detection workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
1,013
Activity Months1
Your Network
223 peopleSame Organization
@crestdata.ai29
Shared Repositories
194
Work History
November 2024
3 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for Azure/Azure-Sentinel: Hardened and expanded the Armis Azure Sentinel Connector with robust checkpointing, timeout handling, and improved error management to ensure reliable data ingestion and faster recovery. Implemented checkpoint storage in Azure Table Storage, simplified timeout logic, and strengthened initialization, resulting in a more stable ingestion pipeline and improved observability.
3 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for Azure/Azure-Sentinel: Hardened and expanded the Armis Azure Sentinel Connector with robust checkpointing, timeout handling, and improved error management to ensure reliable data ingestion and faster recovery. Implemented checkpoint storage in Azure Table Storage, simplified timeout logic, and strengthened initialization, resulting in a more stable ingestion pipeline and improved observability.
November 2024
Activity
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Quality Metrics
Correctness83.4%
Maintainability80.0%
Architecture76.6%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
API IntegrationAzure FunctionsCloud IntegrationCloud StorageData ConnectorData EngineeringError HandlingException HandlingLoggingSystem Integration
Repositories Contributed To
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