The Health Insurance Portability and Accountability Act, or HIPAA for short, is a set of laws around handling health-related data in information systems. It defines safeguards, which are rules you have to follow when handling health data for your customers. There are three safeguard categories: All three categories have to be handled correctly if you want your API to be HIPAA compliant. In a companion article we covered those key requirements and how to build HIPAA complaint API platforms.

This article explores Socket.IO v4, assessing some of the more important updates compared with v3 – the improvements they offer, and how to migrate.

We are thrilled to announce that Google has been named a Leader in The Forrester Wave™: Cloud Data Warehouse, Q1 2021 report. For more than a decade, BigQuery, our petabyte-scale cloud data warehouse, has been in a class of its own. We're excited to share this recognition and we want to thank our strong community of customers and partners for voicing their opinion. We believe this report validates the alignment of our strategy with our customers’ analytics needs.

As stakeholders in more organizations look toward digital transformation strategies, they need to take a closer look at how to modernize their software. An overhaul of an IT system can be expensive and risky, even if the results pay off. What is not often examined however is the role of APIs in supporting enterprise IT transformation initiatives.

One of the most effective ways to improve performance and minimize cost in database systems today is by avoiding unnecessary work, such as data reads from the storage layer (e.g., disks, remote storage), transfers over the network, or even data materialization during query execution. Since its early days, Apache Hive improves distributed query execution by pushing down column filter predicates to storage handlers like HBase or columnar data format readers such as Apache ORC.

The global pandemic continues to impact our world in so many ways. But it has also served as a catalyst for technological change—a forcing function that is accelerating cloud migration. Every company wants to create better products or services, differentiate offerings, price strategically, grab more market share, retain customers, and grow in a sustainable manner.

We don’t even need a moment to gather which operating system is the most used one. Android development is a booming business because of the number of users it has. It is open source and its development can be ported across devices with relative ease. Plus, it has good backwards compatibility across versions. And, precisely due to this diversity, the need for testing on many devices is paramount.

Have you heard of the misconception that agile is about velocity: i.e. delivering more, at a faster rate? Although this statement is true, it is ultimately meaningless if you don’t deliver value and the customer is not satisfied.

Whether you're breaking up a monolith or building a green-field application, you may consider using a microservice architecture. Like all app architectures, this model brings opportunities and challenges that a developer must be aware of in order to make the most of this app design. One such challenge is ensuring communication between your microservices.

In today’s post, we’ll dive into how we, at AppSignal, solved a daunting engineering challenge. Giving you a look into the kitchen, this post will show you how we tested a new database in production without having to worry about errors/downtime. Alright, let’s get cooking!