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Artsiom Mishuta

PROFILE

Artsiom Mishuta

Artsiom Mishuta focused on enhancing the reliability and accuracy of the scylladbbot/scylla-cluster-tests repository by addressing core issues in SLA verification and test stability. He applied targeted bug fixes in Python, refining error handling and monitoring logic to reduce flaky test outcomes and align test metrics with real ScyllaDB resource usage. His work included correcting resource verification metrics, improving memtable flush period logic, and consolidating error reporting in SLA and aggregation pipelines. By removing unreliable metric checks and standardizing exception handling, Artsiom delivered more consistent performance validation and clearer failure states, demonstrating depth in configuration, database management, and system testing.

Overall Statistics

Feature vs Bugs

0%Features

Repository Contributions

6Total
Bugs
4
Commits
6
Features
0
Lines of code
632
Activity Months3

Work History

June 2025

1 Commits

Jun 1, 2025

June 2025 monthly performance summary for scylla-cluster-tests. Focused on stabilizing test outcomes and reducing flakiness in performance validation to deliver consistent, business-relevant results. The primary deliverable was removing a flaky metric check from a throughput test to ensure test results reflect core read stability rather than ancillary metrics.

January 2025

3 Commits

Jan 1, 2025

January 2025: Delivered targeted bug fixes to harden error handling in SLA testing and the FullScan aggregation pipeline within the scylla-cluster-tests repository. Consolidated error handling, standardized exception raises, and refined severity logic to improve observability and reduce false alarms, resulting in clearer failure states and faster debugging.

November 2024

2 Commits

Nov 1, 2024

Month: 2024-11. Focused on reliability and accuracy improvements in the scylladbbot/scylla-cluster-tests suite. Implemented targeted fixes to SLA verification metrics and test property logic, reducing flaky results and aligning test behavior with real resource usage and upstream ScyllaDB semantics. This enables better capacity planning and more trustworthy performance insights for multi-tenant deployments.

Activity

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Quality Metrics

Correctness85.0%
Maintainability86.6%
Architecture80.0%
Performance73.4%
AI Usage20.0%

Skills & Technologies

Programming Languages

Python

Technical Skills

ConfigurationDatabase ManagementError HandlingMonitoringPerformance TestingPrometheusSLA ManagementScyllaDBSystem MonitoringSystem TestingTesting

Repositories Contributed To

2 repos

Overview of all repositories you've contributed to across your timeline

scylladb/scylla-cluster-tests

Jan 2025 Jun 2025
2 Months active

Languages Used

Python

Technical Skills

Error HandlingSystem MonitoringTestingPerformance TestingPrometheusScyllaDB

scylladbbot/scylla-cluster-tests

Nov 2024 Nov 2024
1 Month active

Languages Used

Python

Technical Skills

ConfigurationDatabase ManagementMonitoringPerformance TestingPrometheusSLA Management

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