In May we released the Splunk Machine Learning Toolkit (MLTK) version 5.2. We’ve loved telling you about some of the great new features, including the most recent blog on DensityFunction. However, we know that before you can start experimenting with model-building algorithms such as DensityFunction, your data needs to be prepared for machine learning. Machine learning operates best when you provide clean data as the foundation for building your models.

Often, brands are unaware of how their website is performing or exactly when it goes down. Technical glitches are common in today’s ever-evolving cyber world and websites can become temporarily dysfunctional due to several reasons. But from a business perspective, downtime of even a few minutes can translate into huge losses for your enterprise. Your website is one of the most important elements of your business and you should be aware of its status at all times.

As the adoption of GraphQL is rising steadily, teams often come across the natural question of how to deal with errors that pass service boundaries and propagate from API endpoints to clients and consumers.

The 7.6 release of the Elastic Stack delivered the last piece required for an end-to-end machine learning pipeline. Previously, machine learning focused on unsupervised techniques with anomaly detection. However, several features have been released over the 7.x releases. In 7.2 Elasticsearch released transforms for turning raw indices into a feature index. Then 7.3, 7.4, and 7.5 released outlier detection, regression, and classification, respectively.

SAN FRANCISCO — July 22, 2020 — InfluxData, creator of the time series database InfluxDB, today announced that InfluxDB Cloud is now available on Microsoft Azure, furthering the company’s commitment to increase accessibility to developers. With this announcement, InfluxDB Cloud is now live on all three major cloud platforms — Microsoft Azure, Google Cloud and Amazon Web Services.

As companies prepare for the workforce to return to work, a myriad of decisions must be made. Return to work policies must encompass a full understanding of the needs and questions of its employees. The other top need is a true assessment of safety as it relates to COVID-19. How does the new place differ from one that is familiar? From the perspective of the employee, there may be sentiments of fear, uncertainty, and reluctance.

From smart thermostats and grocery store checkouts to public utility infrastructures and industrial manufacturing lines, the Internet of Things (IoT) is all around us—and growing larger every day. But with this rapid growth comes a number of operational challenges: IoT devices collect a large amount of data, and are often distributed across harsh, ever-changing environments.

The way we work has fundamentally changed in recent months due to the impact of the global COVID-19 pandemic. As more employees are working remotely, organizations are looking at new ways to ensure their workers can stay productive and secure. We released Splunk Remote Work Insights (RWI) to help IT and security teams have insight into the systems that their employees rely upon while working remotely.

Use of AI can be critical when developing systems to support social good, with some inspiring examples using Splunk in healthcare and higher education organisations. According to our State of Dark Data report, however, only 15% of organisations admit they are utilising AI solutions today due to lack of skills. So how can we help organisations unlock the potential of AI?