Using Java and Marqeta, we’ll build out a fully functioning card payment system your users can use for payments anywhere that a debit or credit card is accepted.

Make the most of your backpacking adventure by creating customized weather alerts using Tomorrow.io weather API. Stay safe with critical alerts tailored to your needs.

Learn how to avoid traps with Java Optional and how to use it efficiently by taking the best of this API to make a readable code.

DevOps pipelines automate software development workflow for continuous integration, delivery, and deployment.

So, Android Studio exists. While there are a number of fixes for the less-than-graceful aspects of Android development in Eclipse - Genymotion, right? - some are moving to Android Studio for a more stream-lined approach. This recent post from MeetMe's engineering blog details Bill Donahue's switch from Eclipse to Android Studio, and he has some pretty strong feelings about it. He says - and this is his own emphasis - the following: I will never go back to Eclipse Donahue then explains the key differences as he sees them. First he makes a list of complaints about Eclipse - constant refreshing, awkward UI building, hogging RAM, and so on - followed by a list of the improvements found in Android Studio, such as full-program themes, new UI tools, better stability and performance, and more. He does point to a couple of hiccups, such as the switch to a Gradle build, but it's more of a thing you're going to have to learn than an issue with Android Studio. Check out Donahue's full post for more details on the switch and the little things Android Studio does to make it more comfortable.

One crucial aspect of ensuring a secure Kubernetes infrastructure is the effective management of secrets, such as API keys, passwords, and tokens.

Explore how flexibility in ACE allows the progression of independent unit testing, without needing to wait for a larger organization to move to containers.

In this interview, learn more about what kind of data Foursquare deals with, what it does with that data, and how using a knowledge graph is going to help.

The article outlines two methods for connecting Snowflake and BigQuery: the Snowflake connector and various third-party ETL tools.

In this blog, I would like to share a few best practices for creating High Available (HA) Applications in Mule 4 from an infrastructure perspective.

Several of us might be familiar with the clear () API in the Java collections framework. In this post, let’s discuss what is the purpose of this clear() API?

Where to start when it comes to extracting and integrating enterprise applications data for data insights and being a truly data-driven enterprise.

This article discusses the importance of detecting threatening IP addresses in various forms and provides two API solutions to help detect those threats.

Message broker vs. data streaming — trade-offs, integration, and migration scenarios from JMS, IBM MQ, TIBCO, or ActiveMQ to Apache Kafka.

Testcontainers allows us to create a production-like environment for integration testing. Review the most popular case: testing an application’s services and data access layer.

In this blog post, we'll take a deep dive into the world of integration testing and explore its benefits. Join us on this journey of discovery.

This article outlines basic Kubernetes scheduling concepts, including node selector, node affinity and anti-affinity, and pod affinity and anti-affinity.

Implementing these effective methods will ensure that the testing of your software application or project is executed smoothly, leading to favorable outcomes.

This article provides an in-depth analysis and comparison of both approaches and helps you make an informed decision for your project.

In this blog post, I will demonstrate how to use OceanBase in a Python project. We will create a REST API that serves as the backend of a headless e-commerce app.