hmcts/ARIAMigration-Databrick
Apr 2025 – Apr 2026
13 Months active
Languages Used
BashBinaryPythonSQLShellYAMLCSSHTML
Technical Skills
ADLSApache SparkAuthenticationAzureAzure DatabricksAzure DevOps
AndrewMcDevittHMCTS
PROFILE
Andrewmcdevitthmcts
Andrew McDevitt engineered and maintained complex data processing and migration pipelines for the hmcts/ARIAMigration-Databrick repository, focusing on appeals workflows, payment processing, and robust deployment automation. He leveraged Python, Apache Spark, and Azure Databricks to deliver end-to-end ETL solutions, integrating CI/CD pipelines and infrastructure-as-code for reliable multi-environment deployments. Andrew’s work included parameterized Azure Functions, notebook-driven analytics, and secure secret management, addressing data integrity, auditability, and operational resilience. Through iterative enhancements and targeted bug fixes, he improved data quality, observability, and system stability, enabling faster, safer releases and supporting business-critical decision-making across the appeals migration landscape.
Overall Statistics
Feature vs Bugs
57%Features
Repository Contributions
785Total
Bugs
170
Commits
785
Features
227
Lines of code
374,455
Activity Months13
Your Network
231 peopleShared Repositories
16
Asaleem-hmctsMember
AndrewHMCTSMember
AndrewHMCTSMember
AraIHMCTSMember
AraIHMCTSMember
Avi SinghMember
gburnside-hmctsMember
misbahulislam2Member
NaveenSriramAddagarlaMember
Work History
April 2026
8 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for hmcts/ARIAMigration-Databrick focused on delivering end-to-end improvements to the appeals processing and data pipelines, while strengthening data quality and storage reliability. Core features and fixes delivered across the month improved accuracy, auditability, and operational resilience, directly supporting faster, more reliable decision-making in production.
8 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for hmcts/ARIAMigration-Databrick focused on delivering end-to-end improvements to the appeals processing and data pipelines, while strengthening data quality and storage reliability. Core features and fixes delivered across the month improved accuracy, auditability, and operational resilience, directly supporting faster, more reliable decision-making in production.
April 2026
March 2026
24 Commits • 1 Features
Mar 1, 2026March 2026 (2026-03) monthly summary for hmcts/ARIAMigration-Databrick. Delivered a focused set of enhancements to segmentation cloning and a comprehensive bug-fix sweep across ARIADM tickets, resulting in improved migration fidelity, data integrity, and system stability for UTA/FTA/FPA flows. Code quality improvements and cleanup reduced technical debt and security risk while enabling faster deployment of fixes and features.
March 2026
24 Commits • 1 Features
Mar 1, 2026March 2026 (2026-03) monthly summary for hmcts/ARIAMigration-Databrick. Delivered a focused set of enhancements to segmentation cloning and a comprehensive bug-fix sweep across ARIADM tickets, resulting in improved migration fidelity, data integrity, and system stability for UTA/FTA/FPA flows. Code quality improvements and cleanup reduced technical debt and security risk while enabling faster deployment of fixes and features.
February 2026
54 Commits • 11 Features
Feb 1, 2026February 2026 monthly summary for hmcts/ARIAMigration-Databrick focusing on observability, data quality, UI accuracy, bail/adjournment data integrity, and pipeline readiness. Delivered measurable improvements across logging, HTML views, and DQ rules, enabling faster troubleshooting and higher data trust.
54 Commits • 11 Features
Feb 1, 2026February 2026 monthly summary for hmcts/ARIAMigration-Databrick focusing on observability, data quality, UI accuracy, bail/adjournment data integrity, and pipeline readiness. Delivered measurable improvements across logging, HTML views, and DQ rules, enabling faster troubleshooting and higher data trust.
February 2026
January 2026
22 Commits • 5 Features
Jan 1, 2026January 2026 performance summary for hmcts/ARIAMigration-Databrick. The month delivered significant data processing improvements, deployment readiness, and robustness across the migration pipeline. Business value was derived from accurate retention and state handling, automated notebook publishing, and reliable dashboards that support safe state replays and auditable data. Key achievements focused on: data integrity, deployment readiness, and automation of reporting and auditing.
January 2026
22 Commits • 5 Features
Jan 1, 2026January 2026 performance summary for hmcts/ARIAMigration-Databrick. The month delivered significant data processing improvements, deployment readiness, and robustness across the migration pipeline. Business value was derived from accurate retention and state handling, automated notebook publishing, and reliable dashboards that support safe state replays and auditable data. Key achievements focused on: data integrity, deployment readiness, and automation of reporting and auditing.
December 2025
17 Commits • 6 Features
Dec 1, 2025December 2025 performance summary for hmcts/ARIAMigration-Databrick: Delivered a cohesive set of data-processing enhancements and analytics readiness improvements across the Databricks migration project. Key features include Azure Log Analytics Notebook Integration with refined DQRules fee handling; dashboard notebooks maintenance for Case Execution Tracking; sponsor data quality improvements with sponsor authorization validation; bail data processing enhancements with robust HTML output and reconciliation; and the Response Dashboard branding with RunID lifecycle and enhanced logging. Major bugs fixed included resolving data integrity issues in sponsor handling (hasSponsor), bail/archive reconciliation, removal of outdated journeyType logic, and robust deletion/error handling to prevent job failures. The work improved data integrity, auditability, and production readiness, enabling faster analytics, safer data deletion, and more reliable appeals processing. Technologies demonstrated include Databricks notebooks, Azure Log Analytics API, Python-based data quality rules, code cleanup and refactoring, logging and RunID lifecycle management, and end-to-end audit-ready data workflows.
17 Commits • 6 Features
Dec 1, 2025December 2025 performance summary for hmcts/ARIAMigration-Databrick: Delivered a cohesive set of data-processing enhancements and analytics readiness improvements across the Databricks migration project. Key features include Azure Log Analytics Notebook Integration with refined DQRules fee handling; dashboard notebooks maintenance for Case Execution Tracking; sponsor data quality improvements with sponsor authorization validation; bail data processing enhancements with robust HTML output and reconciliation; and the Response Dashboard branding with RunID lifecycle and enhanced logging. Major bugs fixed included resolving data integrity issues in sponsor handling (hasSponsor), bail/archive reconciliation, removal of outdated journeyType logic, and robust deletion/error handling to prevent job failures. The work improved data integrity, auditability, and production readiness, enabling faster analytics, safer data deletion, and more reliable appeals processing. Technologies demonstrated include Databricks notebooks, Azure Log Analytics API, Python-based data quality rules, code cleanup and refactoring, logging and RunID lifecycle management, and end-to-end audit-ready data workflows.
December 2025
November 2025
1 Commits
Nov 1, 2025Monthly work summary for 2025-11 focusing on delivering robustness improvements and a critical bug fix for the ARIAMigration-Databrick project. Emphasizes business value by increasing reliability of data processing and reducing failure handling overhead.
November 2025
1 Commits
Nov 1, 2025Monthly work summary for 2025-11 focusing on delivering robustness improvements and a critical bug fix for the ARIAMigration-Databrick project. Emphasizes business value by increasing reliability of data processing and reducing failure handling overhead.
October 2025
56 Commits • 18 Features
Oct 1, 2025October 2025 — hmcts/ARIAMigration-Databrick: Focused on stabilizing and modernizing the build+deploy pipeline, migrating packaging tooling to UV and adopting PyPI wheels, and accelerating delivery with CI/CD improvements. Delivered packaging/tooling modernization, reliable wheel-based deployments, and runtime/runtime-data access optimizations that reduce operational risk and enable faster iterations.
56 Commits • 18 Features
Oct 1, 2025October 2025 — hmcts/ARIAMigration-Databrick: Focused on stabilizing and modernizing the build+deploy pipeline, migrating packaging tooling to UV and adopting PyPI wheels, and accelerating delivery with CI/CD improvements. Delivered packaging/tooling modernization, reliable wheel-based deployments, and runtime/runtime-data access optimizations that reduce operational risk and enable faster iterations.
October 2025
September 2025
15 Commits • 3 Features
Sep 1, 2025September 2025 monthly summary for hmcts/ARIAMigration-Databrick. Delivered end-to-end payment-pending data processing pipelines and workflows on Databricks, including active appeals data pipelines, queues, task orchestration, and publishing to Event Hubs. Added active data transformation and CCD call results configurations to support robust data processing workflows. Ingested reference data asset for Scottish bail cases (Scottish_Bailsfile.csv) to enable accurate reference data processing. Implemented targeted bug fixes in active data transformation workflows to correct typos, parameter naming, dependencies, and full_refresh behavior. Improved deployment/config hygiene with YAML-based naming conventions and dependency management for maintainable pipelines.
September 2025
15 Commits • 3 Features
Sep 1, 2025September 2025 monthly summary for hmcts/ARIAMigration-Databrick. Delivered end-to-end payment-pending data processing pipelines and workflows on Databricks, including active appeals data pipelines, queues, task orchestration, and publishing to Event Hubs. Added active data transformation and CCD call results configurations to support robust data processing workflows. Ingested reference data asset for Scottish bail cases (Scottish_Bailsfile.csv) to enable accurate reference data processing. Implemented targeted bug fixes in active data transformation workflows to correct typos, parameter naming, dependencies, and full_refresh behavior. Improved deployment/config hygiene with YAML-based naming conventions and dependency management for maintainable pipelines.
August 2025
4 Commits • 1 Features
Aug 1, 2025August 2025 performance summary for hmcts/ARIAMigration-Databrick highlighting delivery of a critical environment alignment feature, targeted bug fixes in the GOLD_PAYMENT_PENDING_JSON workflow, and restoration of notebooks/metadata to maintain stable migration operations. These actions improved data integrity, workflow reliability, and deployment consistency across DBFS environments.
4 Commits • 1 Features
Aug 1, 2025August 2025 performance summary for hmcts/ARIAMigration-Databrick highlighting delivery of a critical environment alignment feature, targeted bug fixes in the GOLD_PAYMENT_PENDING_JSON workflow, and restoration of notebooks/metadata to maintain stable migration operations. These actions improved data integrity, workflow reliability, and deployment consistency across DBFS environments.
August 2025
July 2025
21 Commits • 12 Features
Jul 1, 2025Month: 2025-07. Key outcomes across hmcts/ARIAMigration-Databrick include delivery of end-to-end deployment automation for staging and sandbox environments, enhanced pipeline resilience, and targeted fixes that improve multi-env reliability. Delivered deployment pipeline re-run capability to accelerate recovery from failures and enable safer rollbacks. Implemented Deploy to staging and staging deployment execution workflows to ensure consistent updates in staging. Expanded sandbox coverage by deploying to sbox and sbox00, enabling early validation. Fixed critical issues: incorrect DAB stg00 host corrected with re-deploy validation; removed tenant_url from multi-env pipelines to avoid cross-env leakage; stg_aria parameters were commented out to restrict to staging only; minor typo fix. Updated CI/CD configuration for main/master and PR triggers to standardize naming and reduce unintended runs. Performed code cleanup and deployment/config tweaks to simplify deployments by removing legacy flags. These changes deliver business value by faster releases, reduced downtime, better environment parity, and improved governance for deployment pipelines.
July 2025
21 Commits • 12 Features
Jul 1, 2025Month: 2025-07. Key outcomes across hmcts/ARIAMigration-Databrick include delivery of end-to-end deployment automation for staging and sandbox environments, enhanced pipeline resilience, and targeted fixes that improve multi-env reliability. Delivered deployment pipeline re-run capability to accelerate recovery from failures and enable safer rollbacks. Implemented Deploy to staging and staging deployment execution workflows to ensure consistent updates in staging. Expanded sandbox coverage by deploying to sbox and sbox00, enabling early validation. Fixed critical issues: incorrect DAB stg00 host corrected with re-deploy validation; removed tenant_url from multi-env pipelines to avoid cross-env leakage; stg_aria parameters were commented out to restrict to staging only; minor typo fix. Updated CI/CD configuration for main/master and PR triggers to standardize naming and reduce unintended runs. Performed code cleanup and deployment/config tweaks to simplify deployments by removing legacy flags. These changes deliver business value by faster releases, reduced downtime, better environment parity, and improved governance for deployment pipelines.
June 2025
143 Commits • 51 Features
Jun 1, 2025June 2025 performance summary for hmcts/ARIAMigration-Databrick. Key features and improvements delivered: - Parameterized Azure Function and bail logic to improve configurability and maintainability. Commits: 1d3a4ebcd4f63a43414caab2cf2232a57cf756d3; 66a749cff97c3b2e22d0ecc171f11b1c8fe1a735. - Storage reference updates: ABFS to ABFSS, local storage usage, and HTML storage account naming fixes to improve reliability. Commits: 69b781022f2cd4929df3d97360ab56928ec88727; 64eac8074af37300178554d21aa38e51c3871b8c; 461e410f9f07acc440d1e50da554269a812b0f9e. - Pipeline automation and cleanup: automatic pipeline triggering on changes and removal of legacy code paths to accelerate delivery. Commits: 870d45c6f3bf475b3e4a2824cd305c8e665f6d5b; 9fb9f792c5f5b8b9cc348f8d8c48d20517fe301c. - SAS token and secret management enhancements: SAS token usage, CLI-based secret creation, pulling secrets from KV, and deployment debugging support. Commits: 3e5cbbf39e5dd7df75c3c662743c9c764c69cd78; 5ded093cc37ab64ec4c7ffd6ddaa5e04d9c07d36; b289e51b0c2c83f20c853d461ced42ac2b1e2ecc; d904cf8f7fdba1ae752edeff7fe90ba9d97a3eeb; a9b01ff5a29dc8045962614ce697d9180b4ea71d. - Observability and testing: added logging steps, FP segmentation refinements, and expanded ARM path end-to-end tests and test curation coverage. Commits: c06c14285a1ff6ece83f195311a23ba4c2e8637b; 20b866fedeeb07746d867954b6ade0b48f3f55e4; 5a09b9567d875e4ee3a1b46ab062b4238b52e44d; 615a1e39a095b82941ad0b2801b7ba9717190fe9; a2c52ede895d60cf167ff40f006d165d5016784a; c0e8e3c084a7784f47e1bb1fb82aa1eb74e7cd0e. Major bugs fixed: - Reverted Python wheel to 0.0.1 due to compatibility issues, avoiding downstream breakages. Commit: 503492a5856bca4ee251cbbe79feab475440bd05. - Audit path and table naming fixes to prevent data overwrites and ensure correct EH Audit data paths. Commits: dfa5feed2a6fea0990820b7a02dcb227cad249ee; d564bd61cc106624330875fc7a7f9b87a977ef6c; b7c935e8120d801e8bc7e1dfbf06959f7d894e7e. - Azure Function fixes and subdir handling with added logging to verify subdir paths, reducing deployment and runtime failures. Commits: ae5be299a44bb1e45197c2b2e5185b44637f4b63; e48c93bb43c80cdd97a86ebf20a2a4f9e209defb; 022cf110a8d1b20fdbfd33d7609ff3cc80ac5ae9. - Closing bracket and autoloader path issues mitigated by fixes to syntax and filepath handling; removal of stale code paths. Commits: 882f5f546e0b8cdb310f03331243f7f28508556e; e7df64c9ef821b0d4440caa615a7f49825c39fb3. - General code quality and typo fixes across the pipeline and dashboards to stabilize releases. Commits: 317454381dfa2220acea90efd9fa9aad23a2ce6e; 665656f9da0ce2ba527417e107f44ee3a3cd1786. Overall impact and accomplishments: - Strengthened release stability, security posture, and governance across the ARIA Migration Databrick workflow. - Improved configurability, data-path reliability, and automated CI/CD, enabling faster delivery with fewer manual interventions. - Enhanced observability and testing coverage, supporting quicker incident diagnosis and higher confidence in production runs. Technologies/skills demonstrated: - Azure Functions configuration and bail logic parametrization; ABFSS storage integration; KV-backed secret management and SAS token workflows. - Data engineering pipeline governance: automated triggers, pipeline cleanup, and environment-aware TD/FTA/ARM flows; autoloader and dashboard integration. - Observability, testing, and debugging: added logging, FP segmentation refinements, E2E ARM tests, and test curation.
143 Commits • 51 Features
Jun 1, 2025June 2025 performance summary for hmcts/ARIAMigration-Databrick. Key features and improvements delivered: - Parameterized Azure Function and bail logic to improve configurability and maintainability. Commits: 1d3a4ebcd4f63a43414caab2cf2232a57cf756d3; 66a749cff97c3b2e22d0ecc171f11b1c8fe1a735. - Storage reference updates: ABFS to ABFSS, local storage usage, and HTML storage account naming fixes to improve reliability. Commits: 69b781022f2cd4929df3d97360ab56928ec88727; 64eac8074af37300178554d21aa38e51c3871b8c; 461e410f9f07acc440d1e50da554269a812b0f9e. - Pipeline automation and cleanup: automatic pipeline triggering on changes and removal of legacy code paths to accelerate delivery. Commits: 870d45c6f3bf475b3e4a2824cd305c8e665f6d5b; 9fb9f792c5f5b8b9cc348f8d8c48d20517fe301c. - SAS token and secret management enhancements: SAS token usage, CLI-based secret creation, pulling secrets from KV, and deployment debugging support. Commits: 3e5cbbf39e5dd7df75c3c662743c9c764c69cd78; 5ded093cc37ab64ec4c7ffd6ddaa5e04d9c07d36; b289e51b0c2c83f20c853d461ced42ac2b1e2ecc; d904cf8f7fdba1ae752edeff7fe90ba9d97a3eeb; a9b01ff5a29dc8045962614ce697d9180b4ea71d. - Observability and testing: added logging steps, FP segmentation refinements, and expanded ARM path end-to-end tests and test curation coverage. Commits: c06c14285a1ff6ece83f195311a23ba4c2e8637b; 20b866fedeeb07746d867954b6ade0b48f3f55e4; 5a09b9567d875e4ee3a1b46ab062b4238b52e44d; 615a1e39a095b82941ad0b2801b7ba9717190fe9; a2c52ede895d60cf167ff40f006d165d5016784a; c0e8e3c084a7784f47e1bb1fb82aa1eb74e7cd0e. Major bugs fixed: - Reverted Python wheel to 0.0.1 due to compatibility issues, avoiding downstream breakages. Commit: 503492a5856bca4ee251cbbe79feab475440bd05. - Audit path and table naming fixes to prevent data overwrites and ensure correct EH Audit data paths. Commits: dfa5feed2a6fea0990820b7a02dcb227cad249ee; d564bd61cc106624330875fc7a7f9b87a977ef6c; b7c935e8120d801e8bc7e1dfbf06959f7d894e7e. - Azure Function fixes and subdir handling with added logging to verify subdir paths, reducing deployment and runtime failures. Commits: ae5be299a44bb1e45197c2b2e5185b44637f4b63; e48c93bb43c80cdd97a86ebf20a2a4f9e209defb; 022cf110a8d1b20fdbfd33d7609ff3cc80ac5ae9. - Closing bracket and autoloader path issues mitigated by fixes to syntax and filepath handling; removal of stale code paths. Commits: 882f5f546e0b8cdb310f03331243f7f28508556e; e7df64c9ef821b0d4440caa615a7f49825c39fb3. - General code quality and typo fixes across the pipeline and dashboards to stabilize releases. Commits: 317454381dfa2220acea90efd9fa9aad23a2ce6e; 665656f9da0ce2ba527417e107f44ee3a3cd1786. Overall impact and accomplishments: - Strengthened release stability, security posture, and governance across the ARIA Migration Databrick workflow. - Improved configurability, data-path reliability, and automated CI/CD, enabling faster delivery with fewer manual interventions. - Enhanced observability and testing coverage, supporting quicker incident diagnosis and higher confidence in production runs. Technologies/skills demonstrated: - Azure Functions configuration and bail logic parametrization; ABFSS storage integration; KV-backed secret management and SAS token workflows. - Data engineering pipeline governance: automated triggers, pipeline cleanup, and environment-aware TD/FTA/ARM flows; autoloader and dashboard integration. - Observability, testing, and debugging: added logging, FP segmentation refinements, E2E ARM tests, and test curation.
June 2025
May 2025
112 Commits • 30 Features
May 1, 2025May 2025 performance highlights for hmcts/ARIAMigration-Databrick: Key features delivered include Autoloader Notebook Enhancements and Cleanup (queryNames, checkpoint location, config cleanups), SAS Token Fix, Bails CI/CD Workflows Integration, Dashboard and Autoloader Queries Cleanup with YAML Workflow Management, JOH Deployment and Infra Test Suite, EH Data Path Update, and New HTML Template with Dynamic Creation and Validation. Additional improvements include Deployment/CI enhancements, Infrastructure Config Changes, and Packaging/Deployment workflow cleanup with ZipDeploy and ArchiveFiles. Major bugs fixed include SAS token value correction, syntax and lint fixes, loop/cyclical dependency fixes, environment detection logic fixes for sbox, naming convention fixes, dynamic host passing implementation, and environment-limited deployment constraints. Overall impact: more reliable data ingestion, secure, repeatable deployments across environments, and better observability through debugging/validation. Technologies/skills demonstrated: Databricks, Spark, Python notebooks, YAML-based CI/CD workflows, Infrastructure as Code (IaC), packaging and deployment tooling (zipDeploy, ArchiveFiles), debugging and validation tooling, and parameterization.
May 2025
112 Commits • 30 Features
May 1, 2025May 2025 performance highlights for hmcts/ARIAMigration-Databrick: Key features delivered include Autoloader Notebook Enhancements and Cleanup (queryNames, checkpoint location, config cleanups), SAS Token Fix, Bails CI/CD Workflows Integration, Dashboard and Autoloader Queries Cleanup with YAML Workflow Management, JOH Deployment and Infra Test Suite, EH Data Path Update, and New HTML Template with Dynamic Creation and Validation. Additional improvements include Deployment/CI enhancements, Infrastructure Config Changes, and Packaging/Deployment workflow cleanup with ZipDeploy and ArchiveFiles. Major bugs fixed include SAS token value correction, syntax and lint fixes, loop/cyclical dependency fixes, environment detection logic fixes for sbox, naming convention fixes, dynamic host passing implementation, and environment-limited deployment constraints. Overall impact: more reliable data ingestion, secure, repeatable deployments across environments, and better observability through debugging/validation. Technologies/skills demonstrated: Databricks, Spark, Python notebooks, YAML-based CI/CD workflows, Infrastructure as Code (IaC), packaging and deployment tooling (zipDeploy, ArchiveFiles), debugging and validation tooling, and parameterization.
April 2025
308 Commits • 88 Features
Apr 1, 2025April 2025 highlights: Delivered substantialDatabricks asset and CI/CD workflow improvements under hmcts/ARIAMigration-Databrick. The work focused on enabling reliable, repeatable deployment of Databricks assets, expanding deployment coverage to ingest02 workspace, and strengthening pipeline testing and observability. Key outcomes include: the Databricks Asset Bundles CICD integration (ARIA_DABs) with directory restructuring and updated bundle commands; deployment stage added with refreshed PAT variables in ADO to support re-testing; Brew-based CI changes to replace pip and persist Brew shell across steps; CI reliability and path hygiene improvements (working directory validations, notebook_paths updates, and YAML restructuring); and creation of Databricks Pipelines & Workflows with initial test scaffolding and ecosystem readiness for secret management and debugging. Effective collaboration and clear commit traceability across CI/CD, YAML, and Databricks configurations.
308 Commits • 88 Features
Apr 1, 2025April 2025 highlights: Delivered substantialDatabricks asset and CI/CD workflow improvements under hmcts/ARIAMigration-Databrick. The work focused on enabling reliable, repeatable deployment of Databricks assets, expanding deployment coverage to ingest02 workspace, and strengthening pipeline testing and observability. Key outcomes include: the Databricks Asset Bundles CICD integration (ARIA_DABs) with directory restructuring and updated bundle commands; deployment stage added with refreshed PAT variables in ADO to support re-testing; Brew-based CI changes to replace pip and persist Brew shell across steps; CI reliability and path hygiene improvements (working directory validations, notebook_paths updates, and YAML restructuring); and creation of Databricks Pipelines & Workflows with initial test scaffolding and ecosystem readiness for secret management and debugging. Effective collaboration and clear commit traceability across CI/CD, YAML, and Databricks configurations.
April 2025
Activity
Loading activity data...
Quality Metrics
Correctness84.6%
Maintainability85.0%
Architecture80.0%
Performance75.8%
AI Usage21.6%
Skills & Technologies
Programming Languages
BashBinaryCSSCSVHTMLJSONJupyter NotebookPythonSQLShell
Technical Skills
ADLSApache SparkAsync ProgrammingAsyncIOAsyncioAuthenticationAutoloaderAzureAzure Blob StorageAzure CLIAzure Data Lake StorageAzure DatabricksAzure DevOpsAzure Event HubAzure Event Hubs
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline