The December 2021 report from the CNCF showed that 5.6 million developers use Kubernetes today. We adopted Kubernetes a little over three years ago and felt this is a good time to reflect on what we thought we were getting into and what we have actually experienced. Here are five areas where the prevailing wisdom did not match our expectations.

If an organization is to be productive, it needs to work with the right data at the right times exactly where it needs them, across the whole structure and in each of its departments.

What should you measure in Semrush to do the best job for your agency clients? Learn the top 12 Semrush metrics to track.

Given the array of ongoing challenges businesses face, including those posed by hybrid work and COVID-19, business automation is more important than ever. In large organizations, many business units have long been using robotic process automation (RPA) to automate simple manual tasks such as copying and pasting data. While RPA can address local needs quickly and easily, it can’t scale to deliver the complete end-to-end automation, also called hyperautomation, that modern companies need.

In the age of transformation, agility is critical for companies to remain competitive. Continuous integration/continuous deployment (CI/CD) is an automated software delivery process that empowers development teams to respond to market demands quickly. The process helps companies deploy new features as often as every few hours. This is ideal for teams using APIs to modernize legacy systems as a part of their digital transformation strategy.

The benefits of moving your on-prem Spark Hadoop environment to Databricks are undeniable. A recent Forrester Total Economic Impact (TEI) study reveals that deploying Databricks can pay for itself in less than six months, with a 417% ROI from cost savings and increased revenue & productivity over three years. But without the right methodology and tools, such modernization/migration can be a daunting task.

The 5 best tools for visualizing e-commerce data are: Whenever you encounter a thorny business problem, data is your secret weapon. By deploying tools for business intelligence and data analytics, you can crunch very large datasets and get real-time insights to assist your decision-making process.

Here are seven key differences between data lakes vs data warehouses: A lot of terms get thrown around in the big data space that every business should understand. Many of these terms are easily confused with each other. This is the case with data lakes vs data warehouses. What are some of the most important differences between them, and how can your business use them most effectively for data analytics and data management? Read on to learn the differences between data lakes and data warehouses.

Five differences between using an ETL platform vs. writing your own code: The ETL (extract, transform, load) process is one of the most critical, and one of the most challenging, parts of enterprise data integration. But what if we told you there was a low-code ETL solution to your problems?

Functional testing is one of the final steps before a software application goes live, and it’s designed to ensure critical user paths are operating correctly. It’s a kind of black box testing that doesn’t evaluate the underlying code of the application, but instead tests whether a specific input leads to an expected output in the user interface (UI).