By now you've heard that Atlassian is deprecating its server products. For Jira users who cannot or do not want to move to the Cloud, this is troubling news. Data Center is an option, but it's quite an expensive alternative if you do not need its minimum 500 users. Then again, it's quite disruptive to migrate to a new tool, isn't it? No one wants to interrupt their workflow by changing tools — especially one that is so central to daily operations. But it does not have to be so scary.

The purpose of a DevSecOps checklist is not to list every single action and practice you should take to ensure that DevSecOps pipeline is effective. Rather, the purpose is to help you establish the right sort of DevSecOps mindset. DevSecOps is more than a collection of best practices, it’s a shared mindset that security is the responsibility of everyone on your team.

One of Xplenty's most rewarding features is its ability to enact low-code and no-code digital transformation. Even with no experience in ETL or data integration, non-technical users can take advantage of Xplenty’s intuitive drag-and-drop interface to build robust, complex data pipelines to a data warehouse or data lake in the cloud.

Before we get specifically to microapp solutions, imagine you’re an IT director at a Fortune 500 company. It’s 6 p.m. on a Thursday after your meeting with an executive went late.

As technology invades nearly every facet of our lives, businesses need to keep up. Digital transformation is a new normal for today’s business strategy, but you’ll need a solid foundation to work with. The solution to that is a solid application programming interface – or API for short. Did you know you can create an API in minutes without writing a line of code? Let DreamFactory show you how. Our 14-day free trial comes with a guided tour. Sign up today!

The velocity of change is accelerating. The rate of change businesses are experiencing is just astounding. As many organizations have experienced during the pandemic, especially in their supply chain, the need for the data environment to be able to deliver faster is now mission-critical for all! We need better data—but at a rate that’s much faster than before. Businesses need their data teams to become more responsive to changing data demands. That means they need agility.

For many businesses in 2020, the increased use of cloud providers and online services has been essential to keeping the lights on in virtual environments. This has prompted companies to overcome the inertia and red tape surrounding SaaS, PaaS and other “aaS” products.

Ep. 11: Jeannie Hawrysz, leader of API Programs at SAS Joining us is Jeannie Hawrysz, the Lead API Architect at SAS, a 22,000 person business analytics company. Before that she was an 18-year veteran at IBM and was the Technical Development Manager for IBM’s API Connect Micro Gateway. In our podcast she shares how to successfully launch API programs in non API-first companies.

Synchronous and asynchronous, also known as sync and async, are two types of programming models. At an abstract level, programming models define how software is designed and executed. The basic programming models are synchronous, but asynchronous models are critical for performance reasons and to more efficiently use computing resources. Programming languages usually have built-in primitives to deal with asynchronous programming.

Python is one of the best programming resources available for designing machine learning systems. With a variety of technical abilities and potentially time-saving loops and processes, it can be an invaluable tool. However, it’s these capabilities that also make Python difficult to use. In many cases, Python may seem sluggish as it tries to navigate intricate, complicated strings of code.