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Load Testing Blog

Install OctoPerf in your company

Article Summary

Installing OctoPerf on-premise has become straightforward and flexible, even in highly constrained enterprise environments.
The platform runs entirely on containers and supports Docker, Kubernetes, and Rancher deployments.
SSO integration, fine-grained administration, and workspace isolation make it compatible with strict security policies.
Load generators can be managed on-premise or provisioned dynamically via cloud providers.
The setup scales from small teams to large organizations while keeping full control over data and infrastructure.

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Troubleshoot your tests

Article Summary

Reliable load tests require solid preparation, controlled smoke testing, and structured error analysis.
Validation and smoke tests help detect script issues early and establish trustworthy baseline response times.
The guide explains how to identify common problems such as missing agents, premature test stops, and overloaded load generators.
It details how to distinguish script errors from server-side failures using response codes, error rates, and logs.
Clear troubleshooting patterns make it easier to isolate root causes and avoid misleading performance conclusions.

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OctoPerf 11.9 - Azure on demand, new JMeter, setup/teardown threadgroups and more

Article Summary

OctoPerf 11.9 expands load-testing capabilities with Azure on-demand load generators and broader cloud coverage.
The release updates JMeter to version 5.3 and adds native support for setup and teardown thread groups.
Improved agent monitoring introduces load-average tracking to better detect performance bottlenecks.
Runtime properties can now be shared easily across load generators for coordinated test behavior.
Reporting is enhanced with a redesigned Top chart highlighting the slowest transactions.

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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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