
Catchpoint announced the expansion of the WebPageTest platform, an open-source web performance testing suite.
It allows web developers, SEO managers and performance teams to run instant tests from various locations and receive a detailed performance audit of their web pages and web applications.
WebPageTest’s new Opportunities and Experiments features help these teams code with confidence, instantly providing actionable insights and automated experiments for implementing best practices and building quick, usable and resilient websites. WebPageTest Opportunities and Experiments allows performance teams to code with confidence by automatically generating and testing performance tweaks to eliminate blocking scripts, optimize image rendering, and minimize layout shifts with zero code changes.
WebPageTest Opportunities allows users access to unique and actionable insights generated by test results. IT teams receive suggested best practices, such as deferred or async JavaScript, right-sized images, and security fundamentals. Built by leading performance experts with decades of experience, WebPageTest Opportunities guides teams to implement best practices and create lightning-fast websites that delight and convert more users.
WebPageTest Experiments gives users access to custom and automatically generated optimization tests that show how their websites could benefit from specific, actionable improvements with zero changes to the codebase. By making on-the-fly changes to the site’s HTML, JS, and CSS without actually changing any deployed code and comparing it to a control test, developers can instantly gauge the potential for success of their performance tuning. This will prove to be an essential piece of any developers’ or site owners’ toolbox, improving the pace of development and increasing their ability to code with confidence.
“For devs and businesses alike, WebPageTest is continuing to evolve as the gold-standard of performance testing,” says Mehdi Daoudi, CEO at Catchpoint. “Teams will save countless hours of triage by accelerating performance prototyping for both production and in-prod sites. The ability to test and tweak major performance improvements without changing any production code will help to remove red tape and improve the org-wide adoption of performance as a culture.”
In addition to Opportunities and Experiments, WebPageTest is also substantially enhancing the platform experience with access to Private Tests, Bulk Tests, and Priority Testing. As of today, all existing API users of WebPageTest will be also be able to access all new features.
WebPageTest will be hosting a series of livestreams, events, and competitions over the coming month to help users experience, explore, and test out these incredible new features. For more information, please visit our events page.
The Latest
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
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.