Operations | Monitoring | ITSM | DevOps | Cloud

In part one of this series, I introduced you to Kubeflow, a machine learning platform for teams that need to build machine learning pipelines. In this section, we will learn how to take an existing machine learning project and turn it into a Kubeflow machine learning pipeline, which in turn can be deployed onto Kubernetes. As you are going through this exercise, think about how you can convert your existing machine learning projects into a Kubeflow one.

Today, monolithic applications evolve to be too large to deal with as all the functionalities are placed in a single unit. Many enterprises are tasked with breaking them down into microservices architecture. At LogicMonitor we have a few legacy monolithic services. As business rapidly grew we had to scale up these services, as scaleout was not an option.

There are many challenges that engineering teams face when attempting to incorporate a multi-cloud approach into their infrastructure goals. Kubernetes does a good job of addressing some of these issues, but managing the communication of clusters that span multiple cloud providers in multiple regions can become a daunting task for teams. Often this requires complex VPNs and special firewall rules to multi-cloud cluster communication.

In this video, we are going to take a look at what memory bloat is, and how you can use Scout to eliminate it from your applications. Memory related performance issues have the potential to bring your entire application down, and yet, most APMs completely ignore this fact and fail to provide any useful way of monitoring memory usage at all.

Many Mattermost DevOps teams work in “Microsoft Shops”—organizations that use Office 365 apps with the Microsoft 365 business plan—and want to tightly integrate with Microsoft tools to more easily collaborate with the rest of the company. Mattermost E20 was architected from the ground up to be highly flexible. As such, integrating with other platforms including Microsoft is easy. Here’s how.

The SolarWinds® Pingdom® Website Speed Test is one of our most popular tools. It helps countless users understand how their websites are performing and what they can do to improve their site speed. The Website Speed Test can test websites from locations around the globe, and it produces many key results to give you in-depth insight into how quickly your webpages are loading.

Most of the IT industry is floating on the cloud these days. From hosting websites to storing data, organizations have started to use the cloud for various purposes, so why not for log monitoring? In this blog, I’ll explain how cloud-based log monitoring is beneficial for you and how you can use SolarWinds® Papertrail™ for it.

Alerting systems centralize all IT alerts into one intuitive platform. IT alerting systems integrate with your tooling stack, and provide alert controls that help teams increase efficiency and reduce false positives. The main functions of an IT alerting system include activating incident response, automating alerts, providing intuitive reports, and enabling quick communication between roles. To enable these functions, alerting systems should be designed with quality in mind, rather than quantity.

The blessing and curse of cloud computing is flexibility. Now more than ever, companies leveraging the cloud are being revered for their ability to scale up usage of critical applications remotely for employees working from home, while in the same breath lambasted as IT costs sky-rocket. And in the midst of soaring usage, capacity, and cost come budget-cuts to fend off any other necessary evils during this challenging time.

How many website monitoring service providers are there, worldwide? Where are they from? What features do they offer? How much do they charge? You can learn the answers to these questions and much more from our infographic below. In May 2020, we conducted research analysing and comparing website monitoring offers from all over the world. Here is a graphical presentation of what we found out.