Machine learning affects nearly every aspect of our daily lives. To understand how this technology works and how you can use machine learning, it’s necessary to know the difference between unsupervised and supervised machine learning. The following are essential points regarding the different aspects of unsupervised and supervised machine learning.

OpenShift is a platform that allows developers and operations engineers, or even DevOps professionals, to run containerized applications and workloads. Under the hood, it’s powered by Kubernetes, but there’s an additional architectural layer that makes life simpler for DevOps teams. OpenShift is from enterprise software specialist Red Hat and provides a range of automation options and lifecycle management, regardless of where you choose to run your applications.

In December 2022, the latest version of HAProxy, 2.7.0, was released. This open-source software is both a proxy and a load balancer, and is immensely popular due to the sheer volume of features it provides to help reduce or even avoid downtime and manage web traffic. Website or application downtime is disastrous for businesses. You want to serve as many users as possible, but if you have nothing in place to manage traffic, then your web applications can quickly become overwhelmed and fail.

In modern application development and architecture, there has been a big push from monolithic, large applications that can do everything a product would need, to many smaller services that have a specific purpose. This onset has brought on the age of microservice frameworks (micro-frameworks), with the goal of making it easier to prototype, build, and design applications in this paradigm.

As a site reliability engineer (SRE), you juggle a lot of moving targets. You keep tabs on your operational environment’s health and maximize service levels, all while trying to scale your business and exceed client expectations. To hold it all together, you’ve likely implemented a hybrid cloud strategy to keep a watchful eye over everything: your on-premises infrastructure, containers, and numerous cloud deployments.

A new year means a new set of goals. In 2022, we set some lofty goals to help our customers achieve clarity across their modern IT infrastructure. We set out to do this by improving our log collection and analysis within LM Envision, our unified observability platform, which was announced at LogicMonitor’s Elevate user conference this summer. At the conference, we gathered feedback to understand the various ways our customers access and review log data.

The Cisco Networking portfolio is an essential part of your IT support services. These networks can provide your company with the necessary efficiency, security, and productivity, so you can securely connect your team, customers, and assets.

As you explore IT event management and IT incident management, they may look and even sound similar, but it’s essential to understand how they differ. Your IT management team needs to know what to look for, both in an event and an incident, so they can resolve any red-flag issues and return your system to normalcy. But why is it so important to recognize the difference?

At LogicMonitor, ingesting and processing time series metric data is arguably the most critical portion of our unified observability platform. In order to fully prepare for growth, scale, and fault-tolerance, we have evolved what we refer to as our Metrics Processing Pipeline from a monolith to a microservice-driven architecture.

Finding service relationships and diagnosing bottlenecks within an application can be incredibly difficult to accomplish, especially if your applications are spread across multiple services, with both internal and external service calls. Although users could get granular visibility into individual traces using our Distributed Tracing features, they couldn’t see how their services were connected across different traces.