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Load Testing Blog

OctoPerf MCP Server

Summary

The rise of MCP is reshaping how AI interacts with technical tools, and this project shows how an MCP server can let AI assistants operate OctoPerf directly.
The goal is to make performance testing more accessible: running tests, analyzing results, and generating insights through natural language.
Built as an MVP, the server demonstrates how AI can automate workflows that normally require manual navigation and correlation.
The project highlights MCP’s key concepts, the supporting Go framework, and how developers can extend the system with new tools and analyses.
A demo illustrates end-to-end usage, from listing workspaces to running tests and comparing results.
The experience confirms how MCP can bridge AI and APIs to create smarter, more productive performance-testing workflows.

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OctoPerf 11.7 - Pacing, monitoring, dynatrace and more

Article Summary

OctoPerf 11.7 focuses on more realistic load control, deeper monitoring, and stronger observability integrations.
New pacing options make it easier to model user behavior beyond simple concurrency.
Load agent monitoring now exposes JVM-level metrics to better detect bottlenecks.
Dynatrace integration has been refined for clearer correlation between load tests and APM data.
Reporting and runtime controls are improved to simplify comparisons and execution tuning.

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OctoPerf 11.6 - Automatic SLAs and other quality of life features

Article Summary

OctoPerf 11.6 focuses on usability and analysis quality with automatic SLAs applied to all default reports.
JMeter is updated to 5.2.1 with safer cache behavior enabled by default.
Correlation rules can now be reused across projects and workspaces, simplifying script maintenance.
Enterprise administration gains stronger workspace visibility and control.
Reporting improves with clearer SLA indicators and a test configuration summary for easier analysis.

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OctoPerf 11 - Modular design, tags and improved administration

Article Summary

OctoPerf 11 introduces true modular design to build reusable test components and simplify script maintenance.
Tags make it easier to organize projects, virtual users, runtimes, and results across iterations.
New percentage-based metrics improve visibility on error and success rates during test execution.
Administration is strengthened with better user management and shared providers across workspaces.
These changes lay the groundwork for more flexible design and deeper analysis in future releases.

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OctoPerf 10.6 - Microsoft Azure, Gitlab CI and Oauth2 login

Article Summary

OctoPerf 10.6 strengthens platform integrations with native Microsoft Azure support for on-demand load generators.
GitLab CI integration enables automated test execution through standard CI pipelines.
OAuth2 and OpenID Connect expand enterprise authentication options alongside existing LDAP support.
Error reporting is clearer during design, runtime, and analysis, making troubleshooting faster.
Additional reliability fixes improve test startup stability and monitoring alert visibility.

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