groundcover raised $35 Million in Series B funding led by Zeev Ventures with follow-up participation from Angular Ventures, Heavybit, and Jibe Ventures.
This brings the company's total funding to $60 Million USD, which will be used to aggressively expand in the USA.
"Our platform offers much better coverage and value than the legacy application monitoring solutions that have been around for over a decade," said Shahar Azulay, CEO and Co-Founder of groundcover. "We are the only solution built with eBPF at the forefront from day one, and we are now pioneering the 'bring your own cloud' approach to observability that enables organizations to keep their data on premise while maintaining all of the benefits of the SaaS experience."
groundcover is a "Bring Your Own Cloud" (BYOC) observability solution, redefining the architecture of a modern observability platform by enabling customers to host their observability data on-prem, while still being fully managed by groundcover. This approach is the X-factor behind groundcover's velocity, maximizing the security and privacy needs of customers, while unlocking coverage tradeoffs with unlimited data, and providing a full observability suite with a simple, predictable pricing model. groundcover also utilizes eBPF to collect observability data straight from the Linux kernel, providing engineers with super-granular visibility into their entire environment including traces, application-level metrics, infrastructure performance and application logs.
"groundcover is fundamentally reshaping the observability landscape. With its eBPF-driven platform and 'Bring Your Own Cloud' approach, it's setting a new standard for depth of observability, cost efficiency, and security," said Oren Zev, Founder of Zeev Ventures. "As the industry continues to shift to richer experiences, such as AI, around observability data, groundcover with its unique and modern architecture is positioned to outpace legacy solutions and dominate the space."
The Latest
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...
A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...
IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...
A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...
According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...
2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...
Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...