![]() Initially, we created Léargas with the purpose of filling a gap in the converged security space: multi-contextual, multi-dimensional network forensics, enriched with leaked data, physical security control logs, and breach artifacts. Léargas transports pre- and post-processed data into Elasticsearch clusters using Beats lightweight data shippers. Behavioral analytics for network security monitoring and intrusion detection services proves invaluable for these companies. The Léargas platform, built on the open source Elastic Stack, helps reduce the high cost of entry that has traditionally prevented many small- and mid-sized companies from gaining effective visibility into their environments. The Léargas platform, visualized in Kibana, provides a workspace with correlated indicators of compromise with associated sentiment analysis. Our company carries the concept of actionable, converged data even further with natural language processing and correlation of dark web, social media, TOR, chan, and additional sources in near real time to expose indicators of compromise and threats against customers and partner organizations. The deal is expected to close in the latter half of 2020, subject to customary closing conditions and regulatory reviews.Léargas Security (Léargas is Gaelic for “insight”) provides clients with actionable insights into anomalous or abstract behaviors through the correlation of data gathered from converged security controls: cyber and physical. And so what’s happening on one instance is not as interesting as what’s happening across the collection of instances since performance matters across an entire service.” “Today’s architectures are more and more distributed - you have VMs, you have containers, you have distributed architectures and distributed databases that might be running on tens or hundreds of nodes. There’s a lot of monitoring that you can do locally to understand if instances fail,” Rau told The New Stack in a 2018 podcast interview. ![]() “In a traditional enterprise architecture, you have a monolith and it’s running on a single server. These technologies, in Splunk’s view, present new challenges for IT professionals and developers, in terms of ensuring high availability and seamless operations. IT analyst firm Garter has predicted that by 2022, more than 75% of organizations will be running containerized applications in production. The purchase is in direct response to the rapidly growing ecosystem of Docker, Kubernetes, serverless and other cloud native technologies. “As the world continues to move towards complex, cloud-first architectures, Splunk and SignalFx is the new approach needed to monitor and observe cloud native infrastructure and applications in real-time, whether via logs, metrics or tracing,” added Karthik Rau, SignalFX Founder and CEO, in a statement. ![]() A combined Splunk and SignalFx data platform would offer a single interface to monitor and observe all the data these systems produce in real-time, according to Splunk. “Data fuels the modern business, and the acquisition of SignalFx squarely puts Splunk in position as a leader in monitoring and observability at massive scale,” said Doug Merritt, Splunk president and CEO, in a statement. ![]() Splunk started off offering a popular appliance for searching logs for performance issues, though expanded into a full range of APM services, including those for AIOps and IT Operations Management (ITOM). SignalFx offers a hosted service that provides real-time monitoring and metrics that can be applied to the emerging markets of cloud infrastructure and microservices, as well as for regular applications. Looking to expand into the difficult field of microservices observability, application performance management (APM) software provider Splunk is acquiring SignalFX, for approximately $1.05 billion, according to both companies.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |