The latest News and Information on DevOps, CI/CD, Automation and related technologies.
In a previous post, we talked about the increasing adoption of Platform Engineering teams. The post covered topics such as defining Platform Engineering and the roles and responsibilities of the team. When building an internal platform, a clear goal that many teams want to achieve is: Even though this is key to a successful platform team, this responsibility increases complexity, costs, support time, and more. Not to mention that this can be a long, very long journey.
The link between DevOps and artificial intelligence for operations (AIOps) has only started to become clear within the last few years. Monitoring and alerting has evolved from a "black box approach," where you don't actually know what's happening, into observability, where you have access to data that provides everything you possibly need to know about your IT systems. How does AIOps come into play? AIOps is the practice of applying artificial intelligence, machine learning, and advanced analytics to automate and improve IT operations. Since it entered as a formal discipline with Gartner in 2016, IT teams have been trying to figure out how to employ it to make their lives easier.
Late last year, SUSE completed their acquisition of Rancher Labs, and in doing so, has had to make some decisions on their product roadmap and ongoing support commitments. SUSE Enterprise Storage, SUSE’s software-defined storage product based on Ceph, doesn’t appear to have made the cut. According to their support pages, it is scheduled for End of Life with milestones in January 2021 and 2022.
It seems that virtually every day, another threat to cybersecurity presents itself. In response to this ongoing concern, the Australian Cyber Security Centre has developed prioritized mitigation strategies, in the form of the Strategies to Mitigate Cyber Security Incidents, to help organizations protect themselves against various cyber threats.
Not all colors look good. Let me rephrase: not all colors look good on everything. This is even more applicable when it comes to websites. When put next to each other, it is important for colors to look good, have the right contrast and be readable. Thankfully there are ways to generate such colors - attractive, readable and complementary - using code. I started looking into generating attractive and complementary colors when we were working on a feature involving tags.