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Businesses are rapidly transitioning to the cloud, making effective cloud cost management vital. This article discusses best practices that you can use to help reduce cloud costs.

As many companies shift from traditional IT infrastructure to cloud computing, they are also rethinking how they handle cloud costs — from accounting to tax reporting. Computing costs are predictable and relatively fixed in traditional IT environments. An organization purchases computing capacity upfront and uses it over time. The total cost of ownership is fairly easier to calculate with this setup. By contrast, cloud computing operates on a pay-as-you-go basis, with no upfront payments.

Amazon’s Relational Database Service (Amazon RDS) offers a variety of database instances, which can be confusing at first. In this guide, we'll clarify what each RDS instance class, family, type, and size means in under 15 minutes. Let's start at the beginning.

Pepperdata’s ability to halve cloud costs at top enterprises may seem radical and new, but it’s absolutely not. Pepperdata has been hardened and battle tested since 2012, and our software is currently deployed on about 100,000 instances and nodes across some of the largest and most complex cloud deployments in the world. We’re an AWS ISV Accelerate partner focused on helping customers save money running Spark on Amazon EMR and Spark and microservices on Amazon EKS.

Cloud computing is among the roles occupied by 9.1 million people in the tech industry. With “tech jobs” appearing in 255,000 Google monthly searches and tech job listings increasing by 25% in the U.S., which are the best cities to pursue a career in tech?

The latest cloud cost news is primarily good news: Each of the major cloud providers released changes that could improve your bottom line: Dive into the details below.

According to Statista, the mass volume of data created, stored, copied, and consumed in 2020 was over 64 zettabytes (ZB), or about 64 trillion gigabytes (GB). This is expected to rise to 181 ZB by the year 2025. A large portion of this data is likely to be significant to your business. It can provide you with new insights that help you improve your product, communicate with consumers, and perform risk analysis. However, you’ll need the right tools to extract, sort, process, and analyze it.

The most successful brands are data-driven. Whether it's Google, Amazon, or TikTok, they all use data to inform their next moves. But here's the thing. It's easy to collect a lot of data. Making sense of all that data is often the most challenging part. You can do that in three ways. Scripting is one option. Here, your developers code custom data integration tools in Python and Java alongside technologies like Hadoop and Spark.