Operations | Monitoring | ITSM | DevOps | Cloud

Do you want to know how to measure the full impact of third-party scripts and page contents on your website? In this article, we step you through the process as we analyze the performance impact third-party elements have on a popular content marketing site. We go beyond looking at how a single third-party supplier affects page performance and show you how to measure how the different types of third-party content affect page performance.

As time goes by, I’m looking for solutions that require as little maintenance as possible. One of those is deploying our client web app and our homepage directly on the CDN edge, with GitHub Actions. Not only we don’t need a server to host the app, but the deployment script is also serverless and maintenance-less. This allows me to focus on important tasks, knowing that deployment and serving of the app is always blazing fast.

Making sense out of logs is not an easy task. Log management solutions, such as Sematext Cloud, gather and accept data from multiple sources. Those sources can have different log events structures, providing a different granularity. They may not follow common, logging good practices and be hard to get some meaning from. Because of that, it is important that the application we develop and follow best practices. One of those is keeping meaningful log levels.

A key topic of conversation that comes up again and again with our customers is the challenge of collaboration in a remote work environment. Too many channels of communication or documentation are ineffective, and IT professionals are starting to feel fatigued by never feeling quite “in the know” with business decisions that are happening in real-time. When separated from colleagues, teams can feel distant and unmotivated or find it hard to stay focused.

Your monitoring system provides a comprehensive overview of any infrastructure. To effectively monitor your infrastructure and systems, you’ll need to get all of your data into one place - regardless if you have 1 node or 10 nodes. This centralization of data inevitably creates a vulnerable point that attackers can potentially target and exploit. In this article, we look at how to design your infrastructure in a secure way, as well as focus in on how to secure your nodes.

Helm charts are great. They combine high quality, ready-made runtime configurations for a huge number of applications with an incredible getting-started experience. There is literally no faster way to install a production-ready Grafana or Loki on Kubernetes than using helm install. Unfortunately, Helm charts can also be incredibly inflexible.

This community meetup took a deeper look into how the Civo marketplace can improve your Kubernetes workflows. Featuring some cool apps to try out, and how you can easily get involved with contributing, growing, and ultimately improving the marketplace. As well as talks from Civo's very own Saiyam Pathak and Kai Hoffman, we were also joined by community members Steve Miller and Jürgen Etzlstorfer.

HashiCorp Terraform is an open source Infrastructure as Code (IaC) tool that is widely used to deploy cloud infrastructure in the public cloud, such as AWS and Azure, along with on-premises VMware vSphere environments. One of the challenges is developing a method for bootstrapping the instances with configuration management agents such as the Puppet Enterprise agent.

In this guide, we are going to see what a Docker health check is and how to configure it for your Docker containers. A Health Check means to check the health of any resource to determine whether that resource is operating normally. Here, it is about checking the health of Docker containers. If you’ve been using docker containers in production, you might have noticed that docker checks the status of a container by using the status of the process (PID) launched from the Docker file command.

Any application built today is expected to be highly responsive, highly available, and required to adapt to enormous changes in real-time at peak business hours, store ever-increasing volumes of data, and make that stored data available for users a fraction of seconds. To achieve such low latency and high availability, you need to deploy these applications’ Instances in data centers that are close to their users.