As the complexity of modern cloud

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DevOps and Platform Engineering
As more organizations adopt cloud-native architectures and technologies, DevOps and platform engineering for public clouds are experiencing rapid growth and innovation. Leading industry hyperscalers offer a range of tools and services to support them, such as continuous integration (CI) and continuous development (CD) pipelines, automation, and infrastructure as code. These tools enable enterprises to improve the speed and efficiency of software development processes, as well as the reliability and scalability of applications.

applications continues to grow, the importance of DevOps and platform engineering becomes even greater. By implementing best practices in these areas, organizations can reduce the risk of downtime, increase their ability to respond to changing market conditions, and ultimately achieve greater business success by delivering value to their customers faster and more efficiently than ever before.

Cloud solutions are fundamentally changing the way businesses “manage IT.” With the right strategies, the cloud can be a helper, not a hindrance, to future success.

Leaders embarking on this journey don’t have to go it alone. Leveraging strategic partnerships and relying on colleagues with cloud migration experience can help quickly correct or even circumvent any pitfalls along the path to the cloud.
How Predictive Analytics Helps Developers Anticipate User Needs
30.05.2023
Predictive analytics helps developers make informed el salvador mobile database about future software changes to ensure a painless customer experience, writes Polina Tibets, head of business operations at Pangea.ai, on the InformationWeek portal.

Users are four times more likely to switch apps after a bad experience with a program, such as persistent problems, frequent crashes or errors, or an unintuitive user interface. To meet the ever-changing needs of users, developers can use predictive analytics, which involves using historical user data, statistical modeling, and machine learning to forecast or influence future decisions. However, according to ResearchAndMarkets’ “Global Predictive Analytics Markets Report 2022,” only 23% of companies currently use predictive analytics to anticipate customer needs.