Operations | Monitoring | ITSM | DevOps | Cloud

A lot has changed in the past few weeks. And the percentage of us working from home (WFH) has increased tremendously. With increased WFH, we rely more on email communication, and this increases the opportunities for abuse by others. One thing that has stayed constant: bad people want to do bad things. As we have seen in the past, when one avenue of attack is restricted, the fraudsters redouble their efforts in other areas, and online fraud attempts are already increasing during our new normal.

All you telecom engineers out there must have already heard of fault management, right? Well, those of you who haven’t yet heard of it and need to understand what it’s about, worry no more! I’ll help you. Let’s start by defining the term.

In February, we announced the general availability of InfluxDB on Google Cloud, as well as a rich set of integrations that allow you to use our time series data platform to monitor your Google Cloud services, store sensor data from Google IoT core, and send your time series data to Pub/Sub for analysis on Google AI Platform.

From the very beginning, the Elastic Stack — Elasticsearch, Kibana, Beats, and Logstash — has been free and open. Our approach is not only to make our technology stack available for free, but to make it open — housed in public repositories and developed through a transparent approach with direct involvement from the community. Two simple principles — free and open — broke down barriers and enabled many amazing things.

Even though search is the primary function of Elasticsearch, getting search right can be tough — and sometimes even confusing. To retrieve your data in the most efficient way from Elasticsearch, sometimes you’ll need to overcome some Lucene’s obstacles. While you need to familiarize yourself with Lucene Query Syntax for advanced Kibana use, Lucene’s implementation within Elasticsearch still has some challenges.

We’re excited to announce that Zendesk is now available as a pre-built content source, along with a host of others, as part of the Workplace Search application. With more than 130,000 customers in 30 countries, Zendesk has become one of the de facto customer service platforms in the world. Each day, millions of users interact with support agents via the cloud-based tool regardless of the support channel they choose.

With Elasticsearch machine learning one can build regression and classification models for data analysis and inference. Accurate prediction models are often too complex to understand simply by looking at their definition. Using feature importance, introduced in Elastic Stack 7.6, we can now interpret and validate such models.

In these times of remote teamwork, the pressure on IT teams is at its peak. So how can you ensure teams function well and conditions are good when working remotely? How do you ensure that the IT Ops teams can support the business as per usual? VPN, office suite, critical applications, videoconference, etc. The list of priorities change, new business apps need to be added while your kids and their endless energy become your face to face office colleagues. :)