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If you lead an IT, DevOps, or business operations team, youre probably working on a digital transformation and cloud migration strategy. Youre also likely doing it with scarce resources under the strain of shifting market needs and accelerated customer demands.

Your organizations success hinges on delivering differentiated, high-value digital experiences to customers and internal users. The applications and services that enable these experiences are built on multicloud environments that promise faster innovation and better business outcomes. But these dynamic environments also bring a scale, complexity, and frequency of change that have grown beyond humans capacity to manage.

The common approaches to monitoring these environments to build applications, optimize performance, and run operations are no longer effective. Just capturing data to display on a dashboard without providing automatic root-cause analysis or prioritizing discoveries by business impact just creates more noise than value.

Likewise, traditional tools and approaches are unable to automatically discover all services, processes, and interdependencies within a modern IT environment in real time, which results in blind spots. They also require manual configuration and instrumentation. Manual configurations may have worked in the era of on-premises data centers, but in the multicloud era, when applications and microservices come and go in seconds, manual efforts simply dont scale and instead steal time from innovation.

To manage these complex, cloud-native environments and to save time and resources for developing new innovations that deliver business impact, teams need solutions that rely on artificial intelligence (AI) and continuous automation to provide precise and intelligent answers.

A recent global survey of CIOs from large enterprises details why observability and AI for IT operations (AIOps) have become essential to managing modern IT environments:

According to the same survey, 70% of CIOs said their teams spend too much time doing manual tasks that could be automated, yet only 19% of all repeatable IT processes have been automated. CIOs view AI assistance as a solution93% said AI will be critical to their teams ability to cope with increasing workloads and deliver maximum value to the business.

To make the leap forward, companies are embracing AIOps. One example is ERT, a developer of the software and devices used by medical researchers in 75% of Food and Drug Administration-approved clinical trials in 2019. As the company adopted a cloud-native architecture running on Kubernetes, the IT team realized it needed to automate its software development processes.

ERTs teams now use one observability solution to monitor and automate DevOps processes and application delivery pipelines and to continuously watch for errors and degradation. Their AIOps solution automatically prioritizes any issues based on impact, saving developers time and ensuring they can find, understand, and resolve issues before they impact clinical trials. These processes have reduced from six to four weeks the time it takes ERT to deliver new applications, which means the company can help researchers get new, potentially lifesaving treatments out of the laboratory and into hospitals and pharmacies faster.

To understand the impact of IT on business outcomesincluding the significance of an outage, the value of a software update, or the level of customer engagement with a new feature or releaseIT, DevOps, and business operations teams need a single source of intelligence that provides precise answers prioritized by business impact and with root-cause determination.

As the pace of transformation accelerates, theres no time for silos, guessing, or finger-pointing, says Steve Tack, SVP product management at software intelligence company Dynatrace. Imagine having all teams in your organization on the same page all the time, with everyone using a common language, collaborating across teams, and speeding toward better business outcomes. This is possible with a platform that provides automatic and intelligent observability.

Tack pointed to footwear retailer Rack Room Shoes as one example of a company that transformed how its teams work by using a single source of software intelligence. As the company increased its investments in improving user experiences, its teams realized they needed to improve their understanding of how the performance of their new digital services impacted business key performance indicators, including e-commerce conversion rates and revenue. Their IT, developer, and business teams now rely on a single software intelligence platform to tie together data about their customers behavior with the applications they use and the cloud infrastructure on. As a result, the teams collaborate more effectively and optimize user experience more quickly, leaving 30% more time to focus on innovation, which has driven up their e-commerce conversions by 25%.

Regardless of your industry, success depends on accelerating digital transformation to drive new revenue streams, manage customer relationships, and keep employees productive. To achieve this, organizations are investing in multicloud platforms and cloud-native technologies. To maximize the benefits of these investments and to eliminate silos separating teams, organizations are increasingly looking to observability, automation, and AI-powered insights to automate IT operations so they can innovate faster and deliver better results.

Click here to learn how Dynatrace simplifies cloud complexity and accelerates digital transformation.

Read more from the original source:
Observability and Artificial Intelligence Have Become Essential to Managing Modern IT Environments - SPONSOR CONTENT FROM DYNATRACE - Harvard Business...