"Developer enablement" tools increased productivity, but they present challenges relating to upskilling and retraining developers to use these tools, according to The next generation of developer productivity, a report authored by Mike Loukides, VP of Emerging Tech Content at O'Reilly Media ...
By 2025, more than half of all software engineering leader role descriptions will explicitly require oversight of generative artificial intelligence (AI), according to Gartner ...
In Episode 13 of the Cybersecurity Awesomeness Podcast, Chris Steffen and Ken Buckler from EMA discuss security uses of AI ...
There's no buzzier technology right now than ChatGPT and for good reason. Because while the hype over how blockchain was going to transform trust, financial systems and even the business of selling art has yet to materialize, ChatGPT and, more broadly, generative AI are already delivering real value. In fact, ChatGPT is already so powerful, there are many who worry that generative AI will ultimately replace creative and information workers ...
The emergence of artificial intelligence (AI) continues to transform the technological landscape. Its application in several facets of software development continues to grow. One of the areas of software development where the adoption of AI can advance is software testing ...
An increased demand for highly skilled developers is creating a talent gap within the software industry. Automation can help solve the developer gap across the board ...
Today, DevOps teams and organizations are increasingly looking to implement tools that can streamline various processes to run more efficiently with less error. Of these tools rising in popularity, artificial intelligence (AI) and automation are two that continue to see implementation ... By implementing these tools into existing DevOps features, DevOps teams and organizations can effectively achieve more while operating with less ...
The future of DevOps is bright and the opportunities to utilize cutting edge artificial intelligence (AI) and machine learning (ML) applications of these technologies will only further enhance its adoption ...
As digitalization continues pushing applications and services to the cloud, many companies discover that traditional security, compliance and observability approaches do not transfer directly to cloud-native architectures. This is the primary takeaway from Tigera's recent The State of Cloud-Native Security report ...
Looking at the world of emerging technologies, artificial intelligence (AI) appears to be the next technology on the cusp of breaking into the mainstream, thanks to the development and growing proliferation of no-code AI. A code-free technology that enables non-AI experts to implement and test their ideas without any need for a data scientist, no-code AI will prove to be a democratizing force within the AI industry enabling greater accessibility and use by businesses outside of the Fortune 100 ...
Machine learning operations (MLOps), combining ML and software engineering, are becoming more mainstream and intend to improve the quality and speed of delivering ML models to production. Business leaders are missing out on many opportunities without proper MLOps platforms in place. So, how can companies get started? ...
The first learning from big tech is: Most large companies — wanting to adopt AI — hire teams to build internal platforms for ML practitioners. But these data scientists or ML engineers are often not familiar with enterprise software engineering. Expecting them to learn is feasible but inefficient, which is where MLOps platforms come in ...
As DevOps transformations move enterprise organizations to the cloud, Cloud AI Developer Services help elevate and advance the software development lifecycle. By definition, Cloud AI developer Services (CAIDS) are "cloud-hosted services/models that allow development teams to leverage AI models via APIs. Some of the ways that CAIDS provide support to engineering teams include ...
Leading organizations around the world are adopting cloud native technologies to build next- generation products and achieve the agility that they need to stay ahead of their competition. Although cloud native and Kubernetes are very disruptive technologies, there is another technology that is probably the most disruptive technology of our generation — artificial intelligence (AI) and its subset, machine learning (ML) ...
Over the past few decades, artificial intelligence (AI) has gone from a sci-fi concept to an everyday reality. But just how valuable and useful has AI been when it comes to customer service? Applause recently conducted a survey on the topic, which looked into the use of AI for voice applications, such as chatbots, interactive voice response (IVR), and other conversational AI-assistants. Here's what we uncovered ...
This year and every year come down to how we can raise the bar with and for developers. In software development, there are many areas that are working well and some that have room for improvement. Let's dive right into predictions for DevOps in 2022 (and beyond) ...
Each year, O'Reilly Media analyzes annual trends in technology usage to help the developer community stay abreast of emerging technology areas — whether it's learning about software architecture for the cloud, mastering new languages to support cryptocurrency or productizing artificial intelligence (AI). By evaluating the top search terms, targeted questions and content usage on our learning platform, we're able to share insights into the top trends influencing software development — insights that empower software developers, data scientists and other practitioners to begin the hard work of taking emerging technologies and deploying them as real-world solutions ...
The Holiday Season means it is time for DEVOPSdigest's annual list of DevOps predictions. Industry experts — from analysts and consultants to users and the top vendors — offer thoughtful, insightful, and often controversial predictions on how DevOps and related technologies will evolve and impact business in 2022 ...
Transformative technologies like Artificial Intelligence (AI) and Machine Learning (ML) have changed the way we perceive DevOps. They have transformed the DevOps environment in such a way that execution of processes like data analysis and management has not only become simpler but also faster. Not to mention, these next-level solutions help users speed up their software development cycle, thus ensuring faster time-to-value ...
From facial recognition to self-driving cars, Artificial Intelligence (AI) and machine learning (ML) have become commonplace for many industries in recent years. In parallel, the software development industry has undergone a transformation of its own ...
In 2020, while a pandemic raged and teams everywhere learned how to work remotely, something rather unexpected happened to DevOps: it grew up. Teams stopped talking about DevOps and simply started doing DevOps, bringing in "big guns" technologies, new ways of thinking, and making huge breakthroughs in everything from release times to automation, new technology adoption and code quality ...
Agile philosophy always puts people over the processes, thus more and more companies nowadays want to hire specialists with strong soft skills, because they are much harder to develop than closing some technical gaps that come with the experience. So here we go with the top 5 soft skills that are critical for a developer working in Agile environments ...
2020 was one of the most transformative years for software testing to date. Teams were forced to adapt to completely new work environments and learn to develop, test and innovate at warp speed. At Perfecto by Perforce, we were intrigued by the rollercoaster that was 2020 and wanted to glean more insights into the unique testing trends and challenges that surfaced as a result. As such, we surveyed more than 700 DevOps professionals for our 2021 State of Test Automation Report ...
There are several forces that are going to impact this field that we'll see in 2021. Let's get a peek into DevOps' future with an eye on some trends that have already shown up ...
Developers today are faced with the hard reality that modernizing systems is more than simply moving technology to a new location. Rather, they are expected to be intimately familiar with a host of new-generation technologies while simultaneously managing existing legacy systems as they migrate to an infrastructure that is more responsive, predictive, and scalable. Looking ahead to 2021, let's review the trends surrounding the most challenging, yet promising, topics in infrastructure and operations: Kubernetes, site reliability engineering, security, and more ...
