Netdata completed a new round of financing totaling $14.2M led by Bessemer Venture Partners, with participation from existing investors Bain Capital Ventures and Uncorrelated Ventures, bringing its total raised in Series A to $31M.
The investment will be used to accelerate research and development in support of Netdata’s open, interoperable, and extensible monitoring and troubleshooting platform.
The funding extends Netdata’s Series A round and builds on an exceptional year punctuated by the growing adoption of the open-source Netdata Agent and the introduction of the new Netdata Cloud software-as-a-service offering, a cloud-based console for infrastructure-wide monitoring, enabling teams to collaborate and work in parallel to streamline troubleshooting workflows, driving down incident response times.
Key features and benefits of the Netdata platform include:
- Visualizes unlimited, highly granular, real-time metrics optimized for anomaly detection
- Deploys easily with no preplanning and zero configuration, with autodetection of hundreds of turnkey integrations, enabling monitoring and troubleshooting of web servers, file systems, databases, containers, and more
- Runs seamlessly on physical or virtual servers, containers and IoT devices to collect per-second or per-event metrics with no limits on scalability thanks to its distributed data architecture
- Works autonomously to collect, store, visualize, check, stream, and archive data, or can be easily integrated into existing monitoring tool chains
Both open-source Netdata Agent and closed-source Netdata Cloud are offered free of charge.
“Netdata has experienced exponential growth by filling an unmet need: giving SREs, DevOps engineers, sysadmins, and developers a way to gain visibility into their infrastructure in minutes, with zero configuration, thousands of metrics, and milliseconds from data collection to visualization,” said Costa Tsaousis, founder and CEO of Netdata. “With nearly a million new Docker pulls every day, Netdata has proven to be the most useful tool in the troubleshooting arsenal of IT professionals who are often challenged by the cost, complexity, and limitations of existing monitoring solutions. This new investment will further our vision by enabling us to build upon our community momentum to deliver innovative solutions in both our open source project and future commercial products.”
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 ...