The latest News and Information on DevOps, CI/CD, Automation and related technologies.
We’re on the verge of something here, people. A growing number of companies are shipping software in minutes. Yeah, you read that right. Minutes. Not hours, not weeks, months, or longer. Minutes. Often, teams struggle to ship software into the customer’s hands due to lack of consistency and excessive manual labor. Continuous integration (CI) and continuous delivery (CD) deliver software to a production environment with speed, safety, and reliability.
It’s here at last: StackStorm 3.0. This is a big release for us: Orquesta is GA, and Workflow Designer has a great new look & feel, massively improving usability. We’ve added Microsoft Teams support, Inquiries also goes GA, and more. Here’s all the details.
Moving your WordPress Site to Cycle is incredibly fast and easy. Let’s take a look at what we’ll need to follow along with this tutorial. If you don’t have that set up, take a moment now to do that so you can follow along. For assistance reach out to us directly on our public slack channel, or visit the Cycle documentation.
Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week, we explore DevSecOps and why it’s vital for businesses to integrate security into their DevOps workflow.
Connection tracking (“conntrack”) is a core feature of the Linux kernel’s networking stack. It allows the kernel to keep track of all logical network connections or flows, and thereby identify all of the packets which make up each flow so they can be handled consistently together.
You probably use many tools to get you through the day. Do you ever wonder what tools get other people through their days? In our Tools This Engineer Uses series, we explore the routines, systems, and tools your peers rely on to solve problems and accomplish goals.
As industries shift to a microservices approach of deploying applications using containers, data scientists can reap the benefits. Data Scientists use specific frameworks and operating systems that can often conflict with the requirements of a production system. This has led to many clashes between IT and R&D departments. IT is not going to change the OS to meet the needs of a model that needs a specific framework that won’t run on RHEL 7.2.
