The move to cloud computing has been a no-brainer for many enterprise companies. But cloud computing is an expense that, unlike many other operating costs, is largely variable. Many companies — including the fastest-growing startups, largest enterprises, and leading government agencies — choose AWS to help them streamline fragmented processes, reduce costs, become more agile, and innovate faster.

If Netflix was a series, it would be a blockbuster. Each season would be nothing short of dramatic to the chagrin of investors. Want to crunch some numbers? The video streaming service had an $11.5 billion valuation in January 2011. It had about 26 million subscribers at the end of that year. Ten years later, Netflix reported it had about 204 million subscribers and a valuation of over $220 billion. The Los Gatos, CA, giant made a staggering $25 billion in 2020 in annual revenue.

Containers and serverless computing are two of the most popular methods for deploying applications. Both methods have their advantages and disadvantages. To choose the one that’s right for your business, you need to understand the pros and cons of managing your own containers versus using serverless services.

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.

In this enterprise cost containment series, we’ve tackled a range of topics from cloud to professional services and more. Now, I want to dive into the topic you may have expected us to cover from the start: monitoring. After all, at SolarWinds, we create monitoring software. The goal of this post is not to present or sell software, though. It’s our intention to help you have conversations with management and stakeholders—no matter the monitoring you use.

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.

The experienced IT professional is no stranger to the term “automation.” However, many don’t fully grasp the potential this word presents to IT processes, including the fast-growing realm of intelligent automation. But before you start looking to automation to help rein in costs, it’s important to develop an automation strategy that best fits the needs of your organization. This article explores the three key areas in which to start when building your automation framework.

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.