The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.
If you’ve been around the observability world for the past few years, you’ve probably heard a few stats around data growth. Worldwide, data is increasing at a 23% compound annual growth rate (CAGR), per IDC. That means in five years, organizations will be dealing with nearly three times the amount of data they have today – generated by diverse and emerging sources, from data centers to cloud sources to edge computing.
How is your organization handling Kubernetes observability? What tools are you using to monitor Kubernetes? Is it a time-consuming, manual process to collect, store and visualize your logging, metrics and tracing data? And, what are you actually getting out of all that investment? At Logz.io we’re trying to make this process easier for customers who are serious about Kubernetes observability. We’ve made significant investments in this area for Kubernetes use cases.
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.
Five worthy reads is a regular column on five noteworthy items we have discovered while researching trending and timeless topics. This week, we explore the impending impact of the metaverse on the future (or now) of work and productivity. Illustration by Akshaya Maheswaran Imagine a world where you can work from anywhere, collaborate with colleagues from around the globe, and attend meetings in virtual reality (VR) conference rooms.
This article is the third of a four-part series of articles about Elasticsearch monitoring. In the first article, we put together an Elasticsearch guide, covering how Elasticsearch works and why the setup and tuning of Elasticsearch requires a good knowledge of configuration options and performance metrics.
