It’s been a great month for exciting insights about the role that engineering must play in driving profitable innovation.

Businesses are increasingly interested in the economics of cloud computing. For instance, what are the financial implications of moving to the cloud versus staying on-premises? And what’s the best strategy for optimizing cloud consumption to get the best value from cloud resources? This article takes a look at some of the key concepts of cloud economics, and how your business can leverage cloud cost intelligence to maximize the value of your investment.

Big data analytics help organizations use data to explore both new and improvement opportunities. Whichever cloud data platform you choose, there are two data storage technologies you will want to understand. Data warehouses and data lakes are the two dominant data solutions commonly used for defining how an organization stores, queries, analyzes, and reports on big data. This post will define what a data warehouse and data lake are, how they work, and their differences.

AWS tags are a bit like flossing your teeth every day — or getting eight hours of sleep a night. Everyone agrees they’re good habits that will make life easier down the road. But sometimes life gets in the way, and those habits fall a little short. Most teams set out with the intention to tag their infrastructure, but in our experience, it’s rare that companies have a perfect, thorough AWS tagging strategy.

To make sure your company’s cloud-based resources remain continuously available, you need a way to monitor all your applications and quickly detect when something goes wrong — especially if you are running multiple instances and using a variety of products. Amazon’s inbuilt tool, CloudWatch, allows you to do just this. In this article, we’ll cover exactly what AWS CloudWatch is, how it works, and how much it costs to use.

Data is a key business intelligence tool. Successful businesses rely on data to make decisions. And every business needs a secure destination for storing collected data for later analysis. Cloud-based data warehouses are increasingly becoming the go-to destination. Redshift and Snowflake are two of the big names in this space and they provide similar services. They are big data analytics databases that can read and analyze huge amounts of data.