Digitalization, as we’re talking about in this article, refers to the strategic use of digital technologies and analytics to shift customer interactions from physical locations to digital platforms like apps and online services.

Storing information in a relational database and sharing it via a RESTful API is a very common scenario these days. Depending on your RDBMS (relational database management system), this may take a lot of development effort. One solution that attempts to simplify the process is the PostgREST web server add-on for PostgreSQL. If your organization uses the PostgreSQL database, PostgREST quickly adds basic CRUD (create, read, update, delete) functions in an easy-to-use RESTful HTTP interface.

Hey, you! Yeah, you! The puzzled-looking Spring Boot developer, scouring the web for a guide on integrating your microservices with Apache Kafka on Confluent Cloud with Stream Governance. Admit it, you’ve been Googling nonstop for the past hour and all you’ve found are examples using StringSerializer/StringDeserializer with not even the slightest mention of "schema registry-aware" serialization methods. And I bet the examples you found are implemented in Java.

Check out Ken Ahrens and Scott Moore as they discuss some blockers of developer productivity when building in Kubernetes, and how removing environment and data challenges can reduce toil and frustration! You can catch the full podcast on Scott’s page here: Scott Moore: Hey everybody out there in internet meme land. It’s time to hide your kids and hide your wife because it’s time for the SMC Journal podcast. Some of you will get that joke. Others will not.

Smooth and effective data migration helps organizations move data across systems efficiently to maintain their competitive advantage. Still, Gartner reports that only 17% of initiatives involving data migration are completed within their budgets or set timelines. Understanding these data migration challenges is the first step toward overcoming them. In this blog, we’ll explore data migration and its different types, challenges, and strategies for dealing with them.

In 24.2, we introduced our enterprise copilot. Enterprise copilot allows you to upload business documents and collect them in knowledge sets. From there, you can ask questions about information in these documents and receive answers quickly. For instance, an organization with a heavy regulatory burden could upload legislative and operational documents. Then, these employees could get insights from Appian AI Copilot to ensure they adhere to compliance requirements.

Organizations today are accumulating data more than ever. Traditional data management approaches, such as centralized data warehouses and siloed data marts, are struggling to keep pace with the ever-increasing volume, velocity, and variety of information. The complexity of modern data environments is outpacing the capabilities of these legacy systems and demands a more agile and distributed solution.

Imagine launching your software with confidence, knowing that every button click, data transfer, and user interaction works perfectly—no surprises, no last-minute bugs. This level of assurance doesn't happen by chance; it’s the result of accurate End-to-End (E2E) Testing. But what exactly does end-to-end testing mean? How does it ensure that your application not only works but grows under real-world conditions?

Smoke testing and regression testing play crucial roles in ensuring the functionality and reliability of software applications. Although both test software’s functionality, their purposes differ, and they occur at different stages of development. Understanding the differences between these two testing types can help effectively manage and maintain software quality.