Goto

Collaborating Authors

Software Engineering


Could No-Code Enable Everything Ops?

#artificialintelligence

It feels like DevOps principles are permeating every discipline, creating new buzzwords by the minute. This "JargonOps" is clearly encouraged by marketing campaigns (and bloggers, wink, wink). Yet, the phrases do depict a real trend: all industries are getting an efficiency overhaul in the wake of increased automation. As I've covered before, low-code and no-code tools lower the barrier to entry to application development, enabling field experts to construct workflows as they see fit. For tech-savvy non-engineers, this could be a huge boon to transform copy-and-paste stopgaps into efficient workflow automations.


How Microsoft plans to improve the low-code landscape

#artificialintelligence

Taking on the challenges head-on that stand in the way of their low-code platforms growing, Microsoft's series of new product announcements this week at Build 2022 gives organizations new options for achieving low-code development goals. Microsoft's series of low-code announcements made this week include Power Pages, the latest Microsoft Power Platform addition for creating integrated, scalable and secure websites. Lured by the promises of democratizing app development with visual, declarative, drag and drop interfaces often bundled with enterprise-wide platforms like Microsoft, Salesforce, ServiceNow and others, enterprises have been quick to jump in and experiment. They're learning that support for a low-code platform can get expensive fast once app development moves from small department coding projects to larger-scale, enterprise-wide apps. Low-code platforms' hidden costs include limited process workflow support that further adds to the challenge of scaling them enterprise-wide.


GitLab 15 provides replacement for do-it-yourself DevOps with The One DevOps Platform

#artificialintelligence

GitLab Inc., provider of The One DevOps Platform, announced the launch of its next major iteration, GitLab 15, starting with its first release version, 15.0, bringing forward new cutting edge DevOps capabilities in one platform. GitLab 15 helps companies develop and collaborate around business-critical code to deliver software securely and achieve desired business results through its comprehensive DevOps capabilities. Upcoming releases will enhance the platform's capabilities in solution areas including visibility and observability, continuous security and compliance, enterprise agile planning, and workflow automation and support for data science workloads. Customers using The DevOps Platform, such as Airbus, have noted tremendous improvements in efficiency. After adopting GitLab, the Airbus DevOps team was able to release feature updates in just 10 minutes – down from the full 24 hours required to set up for production, and conduct manual tests before implementing GitLab.


Start your cloud career with 47 DevOps courses for $60

ZDNet

The following content is brought to you by ZDNet partners. If you buy a product featured here, we may earn an affiliate commission or other compensation. The future of work is in the cloud. That's not just true if you work among the server stacks in highly technical fields. Social media giants, video game developers and brick and mortar businesses alike all rely on cloud computing in different ways.


Top AIOps Jobs to Apply For in April 2022! Hop on the Tech Growth

#artificialintelligence

A decade back, artificial intelligence was confined to the IT departments of the companies. As digitization became the core of business operations, brands started using technologies like data science and data analytics to get closer to their target audience. With the introduction of DevOps, things have gotten even easier for the tech ecosystem. DevOps has introduced faster release cycles better than ever before and it has also enhanced the dominance of cloud services. Teams are now able to streamline laborious jobs and use advanced tools under the acronym Artificial Intelligence for IT Operations (AIOps).


The Tricky Aftermath of Source Code Leaks

WIRED

The Lapsus$ digital extortion group is the latest to mount a high-profile data-stealing rampage against major tech companies. And among other things, the group is known for grabbing and leaking source code at every opportunity, including from Samsung, Qualcomm, and Nvidia. At the end of March, alongside revelations that they had breached an Okta subprocessor, the hackers also dropped a trove of data containing portions of the source code for Microsoft's Bing, Bing Maps, and its Cortana virtual assistant. Businesses, governments, and other institutions have been plagued by ransomware attacks, business email compromise, and an array other breaches in recent years. Researchers say, though, that while source code leaks may seem catastrophic, and certainly aren't good, they typically aren't the worst-case scenario of a criminal data breach.


When Software Engineering Meets Quantum Computing

Communications of the ACM

Shaukat Ali is a chief research scientist, research professor, and head of department at Simula Research Laboratory, Oslo, Norway. Tao Yue is an adjunct research scientist at Simula Research Laboratory, Oslo, Norway. Rui Abreu is a professor at the University of Porto, Portugal.


Command line arguments for your Python script

#artificialintelligence

Working on a machine learning project means we need to experiment. Having a way to configure your script easily will help you move faster. In Python, we have a way to adapt the code from command line. In this tutorial, we are going to see how we can leverage the command line arguments to a Python script to help you work better in your machine learning project. There are many ways to run a Python script.


Human-Centered Approach to Static-Analysis-Driven Developer Tools

Communications of the ACM

They can be too opaque, and to raise the signal of what is most important, they end up hiding too much. "The purpose of abstraction is not to be vague, but to create a new semantic level in which one can be absolutely precise."--


InfoQ Mobile and IoT Trends Report 2022

#artificialintelligence

One of the most compelling InfoQ features are our topic graphs, which synthesizes our understanding of how different topics stack up in the technology adoption curve. They are immensely useful as a guide to prioritize different and competing interests when it's time to decide what we want to cover from an editorial perspective, but we also believe that sharing them can help our readers to better understand the current and future tech landscape and help inform their decision process. Topic graphs build upon the well-known framework Geoffrey Moore developed in his book "Crossing the Chasm." Moore's framework describes five stages that describe how technology adoption evolves in time, through the "innovators", "early adopters", "early majority", "late majority", and "laggard" stages. InfoQ has a leaning towards identifying those ideas and technologies that belong to the innovators, early adopters, and early majority stages. We also strive to acknowledge topics that we consider as having already crossed into late majority. You will generally find plenty of content on InfoQ about the late majority and laggards phases, as artifacts of our previous coverage.