Operations | Monitoring | ITSM | DevOps | Cloud

You may be using your log data in a completely wrong way. Today, your business produces more data than ever before, and log data is at the center of all this because it contains the signals of what caused a problem. If your teams have to search for these signals in an ad-hoc manner, then they are wasting their precious time. Nearly every company in existence is dealing with this challenge because it may not have the tools to filter these signals from the noise.

Look out for these Kubernetes monitoring best practices when evaluating a Kubernetes monitoring solution. It will be easier to make sense of them if your tools are Kubernetes native. Let’s face it. Running containers in Kubernetes brings a number of advantages in terms of automation, segmentation, and efficiency. However, the ability to monitor performance and availability in an ever-changing infrastructure like Kubernetes can be a challenge.

dbaddon.mp4 - Google Drive Sign in Most modern web applications are heavily reliant on persisting data with relational databases, and so it’s no surprise that a large part of application performance monitoring relates to keeping an eye on database performance to ensure that our SQL queries are as efficient as possible. With this in mind, Scout features a Database Add-on module, and in this video, we are going to take a closer look at what it has to offer.

These release notes describe new features, improvements and fixed issues in Pandora FMS NG 748. They also provide information about upgrades and describe some workarounds for known issues.

Markley Group is a Boston-based data center leader that provides co-location and private cloud services through a three-million square foot data center portfolio. The company was founded in 1991, when there was no such thing as the cloud. Today, many of its customers are experimenting in public cloud but often have workload requirements which are better suited or more affordable running on private infrastructure, according to Patrick Houston, Director of Engineering at Markley Group.

The OpenTelemetry Collector is a new, vendor-agnostic agent that can receive and send metrics and traces of many formats. It is a powerful tool in a cloud-native observability stack, especially when you have apps using multiple distributed tracing formats, like Zipkin and Jaeger; or, you want to send data to multiple backends like an in-house solution and a vendor. This article will walk you through configuring and deploying the OpenTelemetry Collector for such scenarios.

Keeping track of what’s going on in Kubernetes isn’t easy. It’s an environment where things move quickly, individual containers come and go, and a large number of independent processes involving separate users may all be happening at the same time. Container-based systems are by their nature optimized for rapid, efficient response to a heavy load of requests from multiple users in a highly abstracted environment and not for high-visibility, real-time monitoring.

If you’re here, it means that your application is a hit, coming through a long way of development and deployments. Your application is finally in a stage where you or your team need to set up more servers than you can handle manually, and you have to provision them fast. There’s also the need to make sure that all of them have the same configuration, packages, and versions in order for your application to have the same behavior in all of them.

Increasing online traffic is the goal for any website managers, developers, or e-commerce website builders. More traffic equals more customers and, therefore, sales. However, it can be too much of a good thing. If you don't take steps to address website or app performance during traffic peaks, it can cause those assets to slow down and ultimately crash. Making you a victim of your own success! Website crashes are a catastrophe for e-commerce stores.