With the vast number of innovations in the DevOps space—and more arriving all the time—it's hard for businesses to know which DevOps developments warrant their attention and which can be forgotten. Here's how to tell the difference.

Yalla DevOps made a grand entrance! and for those of you who didn’t make it this time, or those of you who just want a recap, here are the highlights from the event. From an expert panel to a live broadcast by Alan Shimel (Founder, CEO & Editor-In-Chief of DevOps.com), there was a lot going on. The main themes across keynotes and talks were centered around the community, all about introducing change, shifting left and the importance of enhancing people processes.

Modern businesses are evolving rapidly with the advent of cloud, CI/CD and microservices. However, there still exists an extensive and obvious divide between principle business stakeholders and developmental teams. Development teams are often unaware of the challenges faced by operations teams and vice-versa. This is where a need for adoption of DevOps principles comes into the picture. DevOps which came into existence as the natural successor to Agile practices in software development.

In our previous blog post, we discussed how organizations deploy new hyperconverged resources into their environments without disrupting existing platforms in place by tracking interdependencies as they integrate hyperconverged infrastructure (HCI) into standard IT monitoring processes. Developing digitally native capabilities while managing ongoing IT operations can be challenging, but with industry wide adoption of HCI, a few key benefits have emerged that are shaping our modern businesses today.

Redshift is a fast, managed, data warehouse solution that's part of AWS. Although it is traditional SQL and meant for BI (Business Intelligence), it is designed for scalability and can support many workloads typically reserved for Big Data tools. It is protocol-compatible with PostgreSQL and is available through JDBC/ODBC, opening it up to a huge range of existing SQL tools.

Imagine you’re driving a car, but there’s no windshield. You can’t see in front of you. On top of that, your car is full of friends looking out the side windows and yelling various things to you: “We should turn left!” “No, we should turn right!” “I’m pretty sure the next turn is in two miles.” In this scenario, how likely are you to reach your destination instead of ending up in a ditch or careening off a bridge?

With Sumo Logic, we can put all of these pieces together to build end-to-end Observability in Kubernetes.

As your infrastructure grows more complex, storing long-term metrics becomes difficult and costly to retain. Your team stars to limit the amount of historical data they archive, causing gaps in coverage. Anomalies start to slip through the cracks. Version 1.18 of Netdata aims to solve the monitoring metrics storage problem once and for all. Aside from 5 new collectors, 16 bug fixes, 27 improvements, and 20 documentation updates, here’s what you need to know.