To stay competitive, companies who want to run an agile business need log analysis to navigate the complex world of Big Data in search of actionable insight. However, scouring through the apparently boundless data lakes to find meaningful info means treading troubled waters when appropriate tools are not employed. Best case scenario, data amounts to terabytes (hence the name “Big Data”), if not petabytes.

Stan Lee believed in the power of strength in numbers, that a group working together can create a force so powerful it’s unstoppable; from “X-Men” to “Avengers”, these teams had a pioneering spirit, heroic work ethics, and group thinking that surpasses individual brainpower almost every time. Today marks that day when the LogDNA superhero team becomes even stronger. I’m excited to announce that we have closed our Series B round of financing.

Data science and machine learning have gotten a lot of attention recently, and the ecosystem around these topics is moving fast. One significant trend has been the rise of data science notebooks (including our own here at Sumo Logic): interactive computing environments that allow individuals to rapidly explore, analyze, and prototype against datasets.

One of the biggest KPIs in the DevOps space is monitoring. There are so many tools to help any organization to complete their monitoring picture, but no tool does everything and most organizations use many tools to help complete their monitoring solution. Mashing tools together often creates a problem of its own — the tool sprawl problem.

Sematext provides a single pane of glass and machine learning powered alerts for logs, metrics, traces and digital user experience data. The new Sematext agent is fully Docker Engine and Kubernetes-aware. (Re)written in Go, it has a minimal memory and CPU footprint. It also collects Kubernetes metrics in the most optimal fashion possible.

To gain a better understanding of the adoption and usage of machine data in Europe, Sumo Logic commissioned 451 Research to survey 250 executives across the UK, Sweden, the Netherlands and Germany, and to compare this data with a previous survey of U.S. respondents that were asked the same questions. The research set out to answer a number of questions, including: Is machine data in fact an important source of fuel in the analytics economy?

Sematext provides a single pane of glass and machine learning powered alerts for logs, metrics, traces and user experience data. Sematext Cloud provides advanced monitoring, logging and tracing for all Docker platforms such as Docker EE, Kubernetes, GKE, AWS ECS, and IBM Cloud. Sematext’s new monitoring agent leverages the powerful eBPF Linux kernel observability functionality and uses the Kubernetes API to enrich the container and cluster level metrics.

Logagent is a modern, open-source, light-weight data shipper with out of the box and extensible log parsing, on-disk buffering, secure transport and bulk indexing to Elasticsearch and Sematext Cloud. Its low memory footprint and low CPU overhead make it suitable for deploying on edge nodes and devices, while its ability to parse and structure logs makes it a great Logstash alternative.