BlazeMeter, a provider of the Apache JMeter based load testing cloud, released a module for the open-source Drupal software.
Drupal developers can now launch high volume load tests and optimize Drupal websites in minutes, using next generation cloud testing tools.
BlazeMeter’s new Drupal module allows users to consume cloud testing services to optimize the performance of their Drupal sites using BlazeMeter’s self-service load testing cloud.
“Until now load and performance testing was time consuming, expensive, and required expertise in performance. BlazeMeter now steps in to do all the legwork, allowing developers to focus on their web applications,” said Alon Girmonsky, Founder & CEO of BlazeMeter.
“The BlazeMeter module, having an insight into the specific Drupal installation, automatically creates the test script and builds a dedicated testing environment in the cloud, ready to run on-demand."
The BlazeMeter module supports Drupal 6 and 7 and will support Drupal 8 upon its release. The BlazeMeter module will create a load script that will simulate both anonymous users and authenticated users visiting the Drupal website. During a load test, a dedicated cluster of load engines is launched from a preconfigured geographic location. These servers generate traffic according to a load script generated by the BlazeMeter module according to the parameters set by the user. During the load, real time measurements of KPIs present themselves on the report dashboard, where users can easily evaluate system performance and run numerous iterations, allowing users to locate bugs and bottlenecks, fix and re-test time and time again.
BlazeMeter Partners with Acquia
BlazeMeter has also partnered with Acquia as an Acquia Network Partner. The combined forces of Acquia and BlazeMeter create a new standard in the world of load and performance testing. Acquia is a commercial open source software company providing products, services, and technical support for the open source Drupal content management system and BlazeMeter provides developers ways to quickly and seamlessly create comprehensive load tests on its load testing cloud.
Acquia Network customers can now load test their Drupal installations and fine-tune them before going to production. They can use BlazeMeter to simulate realistic traffic that originates from the cloud, allowing users to test the load their website or app can handle, locate and resolve bugs and retest as needed.
“Partnering with Acquia was an obvious step in BlazeMeter’s evolution,” Said Alon Girmonsky, Founder & CEO of BlazeMeter. “Acquia is the world leader for enterprise level Drupal deployment. Together, we provide the most comprehensive combination of tools for the development and testing of Drupal based sites representing a significant leap forward and reinforces BlazeMeter’s position in the vanguard of performance and load testing.”
Peter Guagenti, Acquia’s Vice President of Products, agrees, “Acquia continues to build great relationships with organizations that provide amazing software and tools for Drupal. BlazeMeter’s load testing service will be tremendously valuable to our customers as they work to ensure their site is performing at its peak.”
Getting started with BlazeMeter is simple. Acquia Managed Cloud customers will have BlazeMeter provisioned for them automatically. Customers hosting their own sites on the Acquia Network should log into the Acquia Network, select BlazeMeter from the Services page and follow the on-screen instructions. Time to test is less than 5 minutes.
Acquia offers free Drupal distributions, commercial support, and a cloud-based hosting platform for one stop Drupal infrastructure support. Acquia’s portfolio of Drupal products and services, along with the Acquia Network of support experts and management tools, combine to create an unparalleled enterprise Drupal solution. BlazeMeter is integrated with the Acquia Network subscription service.
Acquia customers are eligible to run 40 tests on BlazeMeter’s load testing cloud for one month, free of charge.
The Latest
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...