Operations | Monitoring | ITSM | DevOps | Cloud

Our first SIGNL4 release tin 2020 includes some great new features. Have a look. For all those who still need to work with pager devices in addition to their smartphone, it is now possible to include this device in the alarm workflow. This might be the case to secure alert delivery even in areas with poor cell coverage. Legcy pager support is provided through a new app we have added to the SIGNL4 app gallery. This apps sends an email to a paging gateway.

The potential for disrupting business is much greater when you decommission a data center than if you’re constructing one. The process involves a lot more than just shutting down servers, turning off switches, and dismantling storage racks. In this article, we’ll consider some of the specifics and best practices required to achieve a smooth decommissioning process.

Do you own or manage a business? Managing a company involves many steps. These steps begin right from the genesis of an idea through its execution. They also involve choosing a development procedure and managing risks. Most software companies these days are adopting the latest project methodologies, like DevOps and agile.

Today we’re excited to announce the general availability of InfluxDB Cloud for Google Cloud. With this new service, GCP users can now use our leading time series data platform on Google infrastructure. This lets you address a wide range of use cases: server monitoring, IoT sensor data tracking, real-time customer analytics, application performance metrics, network monitoring, security threat detection, and financial market analysis.

SAN FRANCISCO — February 4, 2020 — InfluxData, creator of the time series database InfluxDB, today announced the availability of InfluxDB Cloud on Google Cloud. The strategic collaboration, originally announced in April 2019, is part of a major Google Cloud initiative to make the most powerful open source technologies more accessible to its customer base.

In the first part of this blog series, we presented a use case on how machine learning can help to improve police operations. The use case demonstrates how operational planning can be optimized by means of machine learning techniques using a crime dataset of Chicago. However, this isn’t the only way to predict and prevent crime. Our next example takes us to London to have a look at what NCCGroup’s Paul McDonough and Shashank Raina have worked on.