DevOps teams rely on Artifactory as the bread and butter tool of universal binary repo managers, but observing its operations can be challenging. With multiple high availability nodes and unification with Xray as the JFrog DevOps Platform, that operations data is spread out across logs for each service in the JFrog Platform deployment. Operations teams need a view into valuable data insights that can only be gained through real time data mining and observation of the platform.

It’s a mystery why the film community felt an iconic movie like “Grease” needed a reprise. But alas, “Grease 2” hit the big screen and ushered in new teen angst themes around bowling and the talent show.

Throughout the history of software development, one statement has remained true: no application is perfect. Due to that fact, development organizations must work with all resources at their disposal to limit the impact that application problems have on the end-user. Server log files represent an important resource that should be referred to during the process for troubleshooting any application issue.

The first thing we tell Graylog users is, “Monitor your disk space.” The core set of metrics discussed below should always be in acceptable parameters and never grow over extended periods without going back to normal levels. This is why it is critical to monitor metrics that come directly from the hosts running your Graylog infrastructure.

We’re pleased to introduce you to the latest Elastic Cloud features and functionality. Grab a cup of your favorite beverage and five minutes, and let’s dive in.

If I asked you to describe Splunk, you’d likely reply with something about it being really good (the best!) at gathering and searching logs. You’re right! But while that’s true, you may not know Splunk is also tops at gathering and analyzing metrics. Putting the two together is very powerful; logs (events, more generically) and metrics go together like cookies and milk!

Over the past few years, we’ve seen an almost obsession with developing and adopting CI/CD tools throughout the DevOps community. There are thousands of “how-to’s”, “top x tools”, and “tool x vs tool y” type articles, and it has gotten to the point where it’s quite difficult to figure out how and which one to pick as your own.

Like everyone else, my life for the last few months has become a never-ending stream of video calls. With Zoom calls, and the occasional Skype, Google Meet, or Microsoft Teams, becoming the norm I’ve noticed that the fans on my Macbook have been kicking in and sounding like a tiny jet trying to take off.

As networks become more distributed and complex, it’s becoming ever more challenging for IT professionals to track all the events happening on their networks. Still, it’s vitally important to do so—logging activity on an agency’s network is critical to determining who’s on the network, what applications they’re using, and whether those applications can compromise the network and user data.

Isn’t all logging pretty much the same? Logs appear by default, like magic, without any further intervention by teams other than simply starting a system… right? While logging may seem like simple magic, there’s a lot to consider. Logs don’t just automatically appear for all levels of your architecture, and any logs that do automatically appear probably don’t have all of the details that you need to successfully understand what a system is doing.