Perfecto Mobile announced its new MobileCloud Developer Toolkit.
The MobileCloud Developer Toolkit extends leading software development tools to mobile and provides mobile app developers with the test automation and collaboration capabilities required to support agile development.
By supporting familiar open source tools, including Eclipse, Selenium, and Jenkins, this toolkit defines an easy path for developers going mobile, allowing them to leverage their existing tools and workflows, enable continuous integration and support faster delivery.
Today, many mobile developers are working around limitations from tools originally designed for interacting and testing web apps to test mobile applications across multiple devices. Integrating the MobileCloud Developer Toolkit into the mobile application development lifecycle helps overcome these challenges by transforming these existing development tools into a mobile-ready toolset necessary for achieving the goal of building better apps faster.
“Mobile is agile by nature and thus forces developers to simultaneously contend with faster release cycles and an ever-changing mobile device feature set. Testing on real devices in real-life conditions earlier in the development process is key to delivering higher quality applications.” said Yoram Mizrachi, CTO, Perfecto Mobile. “With the new MobileCloud Developer Toolkit, we are providing new designed-for-mobile capabilities which DevOps teams can execute using familiar tools and skillsets, all designed to support rather than change existing workflows.”
With the MobileCloud Developer Toolkit, developers are able to extend the environment, tools and languages they know into mobile and embed real devices connected to real carriers throughout the development process. These solutions combine the strengths of device-as-a-service, leveraging leading mobile test frameworks and the rapid feedback of continuous integration. Following are the different integrations available in the Mobile Developer Toolkit:
- MobileCloud for Eclipse – An Eclipse add-on that delivers full support for automated mobile application testing using real devices from within the Eclipse UI. The add-on provides record, playback and debugging abilities, full object support regardless of application style, complete device under test data including logs, vitals and step-by-step execution reporting.
- MobileCloud WebDriver (Selenium) – A mobile-ready Selenium-based testing solution moving beyond browser-only applications to native and hybrid mobile applications on real cloud-based devices. MobileCloud WebDriver adds additional capabilities including device vital information, visual and object analysis from within the app by using robust checkpoints.
- MobileCloud Jenkins Plugin – The MobileCloud for Jenkins Plugin enables developers to automate build acceptance testing as part of each build and supports continuous integration. The MobileCloud plugin enables broader testing on real cloud-based devices resulting in earlier defect identification. Adding real device testing to the Jenkins nightly build can be accomplished in minutes and test results delivered automatically.
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 ...