Migrating From Open Source Application Servers To IBM WAS Liberty
View IBM's privacy policy here
View IBM's privacy policy here
The pace of business is accelerating. Mobile and social trends have influenced client engagement models, driving customers to expect new and better application services delivered faster. IBM cloud technology is helping businesses respond to these drivers by changing the status quo, enabling business leaders to fast-track innovation and advance key priorities.
To achieve these results, organizations need to rapidly exploit cloud capabilities across a hybrid environment that includes both on-premises and off-premises options. The IBM PureApplication solution portfolio helps deliver these capabilities quickly and easily.
View IBM's privacy policy here
Today’s leading enterprises are undergoing a digital transformation. They are diving into the API economy, in which businesses provide services—and the services of partners—when and where customers want them. They are connecting existing enterprise applications, data and services to new channels of personalized customer engagement. These transformations are driven by:
View IBM's privacy policy here
In this IBM limited-edition Dummies book, you’ll learn what operational decision management (ODM) is and how it can benefit your organization by helping to:
This IBM limited edition e-book helps you learn the basics of application programming interfaces (APIs), including:
For years, application performance management (APM) played an important but largely background role. With the evolution of a digital world where innovation and customer engagement rule, APM is now firmly in the spotlight.
View the IBM webcast featuring Cameron Haight from Gartner, Inc., to learn how APM has evolved alongside DevOps and agile practices.
You’ll also hear from Arun Biligiri, IBM's APM leader, as he discusses how IBM is leveraging its leadership in hybrid cloud and cognitive capabilities to deliver a DevOps-centric APM solution.
View IBM's privacy policy here
In the domain of data science, solving problems and answering questions through data analysis is standard practice. Often, data scientists construct a model to predict outcomes or discover underlying patterns, with the goal of gaining insights. Organizations can then use these insights to take actions that ideally influence future outcomes for the better. The flow of IBM's data science methodology ensures that as data scientists learn more about the data and the modeling, they can return to a previous stage to make adjustments, iterate quickly and provide continuous value to the organization.
View IBM's privacy policy here