Kubernetes is a powerful platform that has shifted the way modern software operates and scales over the past five years. It’s got a strong open source community and benefits from innovation from the collective. Also, some of its current shortcomings are: difficulties in installation, complexity, and customization. In many ways, Kubernetes is like the Linux kernel: it provides a framework for running software, but none of the tools. This is where Kubernetes distributions (or distros) come in.

What if I told you that it took me just under 10 minutes, 8 commands and 6 mouse clicks to create this bar chart informing me — big surprise — that I have too many open tabs in Chrome on my Mac? That might sound like a lot to some readers, but if you’re not a stranger to ELK you’ll know that installing the stack, even for testing and development purposes, usually involves a whole lot more than that. ELK can be installed on almost any system and in any environment.

To keep you up-to-date with what’s going on in anomaly detection, we keep an ongoing list of the biggest glitches happening in the business world. Here is what made waves in June. June 25, 2019 When Dutch telco KPN suffered a major outage on the evening of Tuesday, June 25, the 112 emergency number was also knocked out across the country. “We have no reason to think it was (a hack) and we monitor our systems 24/7,” the company spokesperson told Reuters.

Companies invest in anomaly detection in order to proactively identify risks, such as revenue loss, customer churn and operational performance issues. Anomaly detection essentially enhances traditional BI and visualization tools, venturing beyond a summary view of your data. It constantly scans every metric, at a granular level, to find abnormalities. But in order for this technology to have an impact, you must be able to trust it.

Machine Learning (ML) algorithms are designed to automatically build mathematical models using sample data to make decisions. Rather than use specific instructions, they rely on patterns and inference instead. And the business applications abound. In recent years, companies such Google and Facebook have found ways to use ML to utilize the massive amounts of data they have for more profit.

he Graylog community is what makes the product so exciting. It is awesome to see our community members take the time to help everyone over on our community forums, twitter, reddit or on their own private channels. I wanted to take some time to highlight a blog post by Community member BlueTeamNinja (aka Big Abe) who, after tackling a Graylog deployment shared lessons learned from a non-Linux/non-Elk person.

Logging your Kubernetes clusters to LogDNA is already a breeze, and now the LogDNA Kubernetes agent Helm chart makes it even easier. Helm is the official package manager for Kubernetes. With Helm, deploying and managing Kubernetes applications is as simple as typing a single command. This makes deploying the LogDNA agent across your cluster absolutely effortless.

Cloud is driving the way modern software is being built and deployed. At the forefront of this revolution is AWS, holding a whopping 33% of the cloud services market in Q1 2019. Considering AWS had a seven-year head start before its main competitors, Microsoft and Google, this dominance is not surprising. AWS offers, by far, the widest array of fully evolved cloud services, helping engineers to develop, deploy and run applications at cloud scale.