As a student, developing your software engineering skills is about continuous learning and practice. When building software in the real-world, developers are expected to be proficient with a variety of tools and stacks. Internships, class and personal projects provide great opportunities for students to gain the experience needed to become more effective.
Announcing Graylog v3.1 Today we are officially releasing Graylog v3.1. This release brings a whole new alerting and event system that provides more flexible alert conditions and event correlation based on the new search APIs that also power the views. In addition, some extended search capabilities introduced in Graylog Enterprise v3.0 are now available in the open source edition in preparation for unifying the various search features.
Logs need to be stored. In some cases, for a long period of time. Whether you’re using your own infrastructure or a cloud-based solution, this means that at some stage you’ll be getting a worried email from your CFO or CPO asking you to take a close look at your logging architecture. This, in turn, will push you to limit some data pipelines and maybe even totally shut off others. Maybe we don’t need those debug logs after all, right? Wrong.
Throughout the past few months, I had the opportunity to work with and serve hundreds of Coralogix’s customers, the challenges in performing efficient Log Analytics are numerous, from collecting, searching, visualizing, and alerting. What I have come to learn is that at the heart of each and every one of these challenges laid the challenge of data parsing. JSON structured logs are easier to read, easier to search, alert, and visualize.
In this blog series, we will cover how Amazon Redshift and Sumo Logic deliver best-in-class data storage, processing, analytics, and monitoring. In this first post, we will discuss how Amazon Redshift works and why it is the fastest growing cloud data warehouse in the market, used by over 15,000 customers around the world. When an organization gains traction, the size of data that needs to be stored, monitored, and analyzed expands exponentially.
