The latest News and Information on DevOps, CI/CD, Automation and related technologies.
Dear StackStorm. You have grown up. The time has come for us to part ways. You will continue the life of mature, established open-source project, with growing community. I will step aside, watch with pride your successes, and be always here to help when you need me.
This is the first of a two-part blog series. In this post we’ll use Stackery to configure and deploy a serverless data processing architecture that utilizes AWS Step Functions to coordinate multiple steps within a workflow. In the next post we’ll expand this architecture with additional workflow logic to highlight techniques for increasing resiliency and reliability.
ITOps vs. DevOps: where does one end and the other begin? These two terms are commonly confused even within the IT industry, which is understandable since neither is set in stone and they often overlap, especially when talking about infrastructure. What does each role encompass and how can you tell the difference between them?
There are a few, simple things in life I really, truly enjoy: a full breath of air, watching my kids learn and grow, and playing the piano immediately come to mind. I was reminded of another one after spending an hour with CameronB from DevOpsChat — full understanding of a complex problem. For me, it’s not finding a fix that works, I have to continue until I understand the underlying issues, but then it’s bliss.
Updating information held on container volumes, debugging a running instance, backing up files locally, or just making sure everything is where you expect it to be… remote access is an integral part of any system.
XDP or Express Data Path arises due to the pressing need for high-performance packet processing in the Linux kernel. Several kernel bypass techniques (DPDK being the most prominent one) aim to accelerate network operations by moving packet processing to user space.
Kafka is an open source real-time streaming messaging system and protocol built around the publish-subscribe system. In this system, producers publish data to feeds for which consumers are subscribed to. With Kafka, clients within a system can exchange information with higher performance and lower risk of serious failure. Instead of establishing direct connections between subsystems, clients communicate via a server which brokers the information between producers and consumers.
