The rise in AI integration and embedded analytics adoption signals a transformative era for software developers. Embracing AI holds the promise to enhance productivity and help resolve the developer shortage. However, it comes with risks, including security and privacy concerns ...
Analytics has come a very long way in recent years, with transformational developments widening its impact beyond internal stakeholders and into the hands of external users. This brings with it a range of challenges, and when building analytics applications for customers ...
Industry experts offer thoughtful, insightful, and often controversial predictions on how DevOps and related technologies will evolve and impact business in 2021. Part 3 covers DevOps tools and automation ...
DEVOPSdigest posed the following question to the development community: How should DevOps and development adapt to the new normal? In response, DevOps industry experts offered their best recommendations for how development teams can adapt to this new remote work environment. Part 3 covers visibility and alignment ...
Artificial intelligence (AI) has revolutionized almost every industry and few areas of life remain untouched by the technology. It has begun to shape the software development process and software developers can now use AI to write and review code, test software and detect bugs. Let's take a dive into just a few of the many areas of software development that have all been impacted by AI, such as DevOps, tooling and algorithms ...
Advances in GPU/TPU technology, and the development of new platforms and frameworks have enabled an explosion in AI and Machine Learning, while new platforms from Amazon, Microsoft and others have put pre-built frameworks firmly in the grasp of developers. Despite all this movement, however, we are still definitely very early in the transition to using AI to transform software development — commonly referred to as Software 2.0, or AIOps ...
In 2020, DevOps teams will face heightened expectations for higher speed and frequency of code delivery, which means their IT environments will become even more modular, ephemeral and dynamic — and significantly more complicated to monitor. As a result, AIOps will further cement its position as the most effective technology that DevOps teams can use to see and control what's going on with their applications and their underlying infrastructure, so that they can prevent outages. Here I outline five key trends to watch related to how AIOps will impact DevOps in 2020 and beyond ...
Industry experts offer predictions on how DevOps and related technologies will evolve and impact business in 2020. Part 4 covers AI, analytics and automation ...
DEVOPSdigest asked DevOps experts for their predictions on how DevOps and related technologies will evolve and impact business in 2019. Part 6, covers DevOps Analytics, including AI and Machine Learning ...
DEVOPSdigest asked experts from across the IT industry for their opinions on the top tools to support DevSecOps. Part 3 covers security and monitoring ...
Organizations are focusing investments on security and analytics, while actively researching emerging technologies such as machine learning and artificial intelligence, according to the 2018 CIO Tech Poll: Tech Priorities survey ...
LogiGear predicts that the following trends will be worth keeping an eye on in 2018: Blockchain technology has the potential to be disruptive and is going to be in high demand as this becomes more popular ...
DevOps experts offer predictions on how DevOps and related technologies will evolve and impact business in 2018. Part 6 covers analytics and data ...
Managing application performance today requires analytics. IT Operations Analytics (ITOA) is often used to augment or built into Application Performance Management solutions to process the massive amounts of metrics coming out of today's IT environment. But today ITOA stands at a crossroads as revolutionary technologies and capabilities are emerging to push it into new realms. So where is ITOA going next? With this question in mind, DEVOPSdigest partner site APMdigest asked experts across the industry for their opinions on the next steps for ITOA ...
As trends like cloud computing and DevOps become the de facto standard, organizations are increasingly looking for next-generation analytics tools and services that provide continuous intelligence to help them build, run and secure modern applications, and accelerate their journey to the cloud, according to a new study with UBM Technology titled The New Normal: Cloud, DevOps and SaaS Analytics Tools Reign in the Modern App Era ...
An overwhelming majority of developers (93 percent) indicate that web technologies are critical to their strategy for desktop and mobile, and the demand for new applications and updates to existing applications isn’t going away, according to The State of the Modern Web, a survey of web development professionals ...
The reason Gartner brought the idea of bimodal IT to light was to create breathing space so that organizations could transform and innovate without crashing and burning. The reason that Agile was created, for instance, was to enable a faster, more responsive process than waterfall practices can offer. However, switching to continuous delivery and integration mode too quickly could prove disastrous for certain systems, as some change carries more inherent risk than other changes. Following are key elements to consider when transitioning to ensure that applications continue to run at optimal levels ...
After many science fiction plots and decades of research, Artificial Intelligence (AI) is being applied across industries for a wide variety of purposes. AI, Big Data and human domain knowledge are converging to create possibilities formerly only dreamed of. The time is ripe for IT operations to incorporate AI into its processes ...
To optimize application performance, IT teams need to proactively ensure the optimized performance of every underlying infrastructure component, including physical and virtual servers, networks, storage devices, databases, end-user services and cloud and big data environments. It is imperative that they not only identify and resolve issues quickly, but also pre-empt potential issue before there's an adverse impact on the user experience. Below are six key requirements that can help you achieve these objectives ...
At this moment there are over two million apps available for download, and as many as 60,000 new apps added per month. But with countless new additions and tremendous growth expected over the years, thousands of applications are also being removed to never return – entering the app graveyard ...
Data science and machine learning algorithms have become pervasive throughout the modern consumer world. There are many successful applications of machine learning in consumer products that we use on a daily basis. But, when we look at the Ops world, we find that there is no breakthrough product that incorporates these same machine learning innovations ...
Log Analytics is a process of investigating logs and hoping to derive actionable information that might be useful to the business. Many log analytics tools are used to gain visibility into web traffic, security, application behavior, etc. But how valuable and practical is log analytics in reality? ...
Improving end-user customer experience is one of the key objectives of an application performance management solution in a production environment. By leveraging the application performance data earlier in the development cycle, DevOps teams can ensure readiness for exceptional customer experience before deploying any application in production. Finally, harnessing the business data in application transactions and logs and correlating them with operational data can provide actionable business insights. In this blog, I will discuss five steps to DevOps success leveraging an application performance management solution in production ...
Over the last few years I've tried to represent a clear and growing trend that I've come to call "Advanced IT Analytics" or AIA, in contrast with other industry terms such as "IT Operations Analytics" and "Big Data". My issue with the former is that AIA isn't restricted to operations, but can reach out across all of IT, including executives, service desk and ITSM teams, development and even non-IT business stakeholders. It is multi-use case and multi-stakeholder in value, as the same data mosaic may serve performance, security, change management, and DevOps requirements, while also supporting business stakeholders in areas such as customer experience and market planning ...
With agile and lean influencing our thinking, it’s perhaps no surprise that the impetus behind DevOps has come from development. That’s great for the speed side of the equation, but success requires that IT operations also modify their practices. This means ensuring that Application Performance Management (APM) tools and processes are not only supporting the resilience and service goals of production systems, but that they exhibit the functionality needed to help improve customer experience – even as applications are developed, tested, released and deployed. APM can accelerate the benefits of DevOps, but where do you start and what tools do you use? The tech landscape is littered with many products and services all claiming to be the secret sauce that’s going to support a DevOps-like culture. But don’t be fooled, modern APM can only accelerate DevOps when it exhibits four fundamental characteristics. Quite simply it has to be "EPIC" ...
