Datadog acquired CoScreen, the collaboration platform for technical teams.
This acquisition will bring new capabilities to the Datadog platform that help engineers share their screens and work together during incident and security response, pair programming, prototyping, debugging and other activities in an integrated, joint workspace.
Engineers often collaborate with each other over code, commands in terminal windows and data on dashboards. CoScreen is built specifically for the daily workflows of engineers and enables active collaboration by allowing many users to simultaneously share and control apps with their team.
“Bringing teams together has always been Datadog’s core mission,” said Ilan Rabinovitch, SVP of Product and Community at Datadog. “Adding CoScreen’s real-time communication capabilities helps our customers bring distributed teams closer together and move forward with in-product collaboration. The end result is higher developer productivity, faster incident response and reduced mean time to resolution.”
“Engineering and agile teams are most effective when they have a shared sense of belonging and context—this is true whether team members are colocated in an office or working remotely hundreds of miles apart,” said Till Pieper, CEO of CoScreen. “Our goal with CoScreen has been to create a frictionless and engaging collaboration environment. We couldn’t think of a better partner than Datadog to further this goal and create even deeper and more effective workflows among distributed teams.”
The Latest
In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability...
While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...
Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...
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 ...