The data center is a remarkably complex structure. However, they are crucial to the everyday running of even the smallest businesses and enterprises. Whether in-house, cloud, or hybrid, the average data center management requires specialist knowledge and meticulous oversight for max efficiency. That is one reason, at least, why machine learning is emerging as an ideal partner for centers of the future.
It’s on the agenda of almost every CIO, COO and CFO, and sounds like a great idea in general: tool rationalization, often trying to standardize on top of a single vendor. It can reduce costs and provide a streamlined IT Ops process through data consistency, a single pane of glass and a single source of action.
Last week my colleague, Clay Ryder, and I presented a webinar, titled No! The cloud is not someone else’s data center, in which we examined how companies can reduce the complexity of a cloud migration and accelerate the benefits of digital transformation. It’s an important topic, so as a follow-up to the session, I’ve summarized five key things you need to understand to be successful in the cloud. If you missed the session, you can listen to the full discussion at the link above.
It’s finally happened. After months of whispers, JFrog have announced the sunsetting date for Bintray - their distribution add-on to their long-standing on-premises Artifactory product. It’s officially shutting down on May 1, 2021. Cloudsmith is a direct replacement for Bintray. And Artifactory. And their X-Ray product. Don’t get us wrong - JFrog has achieved a lot over the years and we would never publicly speak out against them.
Facter is a cross platform system profiling tool. It gathers nuggets of information about a system such as its hostname, IP address and operating system. We call these nuggets of information facts and they are used by other Puppet products like Puppet, Puppet Server and Bolt to make decisions in their automation process. You can extend Facter by writing custom facts or external facts and use them in Puppet manifests.
StatsD is an industry-standard technology stack for monitoring applications and instrumenting any piece of software to deliver custom metrics. The StatsD architecture is based on delivering the metrics via UDP packets from any application to a central statsD server. Although the original StatsD server was written in Node.js, there are many implementations today, with Netdata being one of them.
One of the reasons we selected Sierra Ventures as one of our seed investors is because of their CXO Advisory Board. They have dozens of knowledgeable advisors across a wide variety of verticals: Healthcare, Consumer, Retail, Finance, Technology, Media and Telecom. Each year they conduct a broad survey of major trends. This kind of survey data is gold for Enterprise-focused startups.
The monitoring and incident management process is often chaotic and time-consuming for organizations. However, there is a better way to approach IT incidents and make your existing process function better. Topology and relationship-based observability solutions take the incident management process from chaotic to structured. Let’s look into how StackState’s solution improves and speeds up the incident resolution process.
