Finance and engineering both thrive on efficiency. So when companies realize they’re wasting cloud spend, but aren’t sure where or how, both teams become frustrated. It’s remarkable how common this scenario is, particularly in the past five years. Before the pandemic, Gartner reported companies wasted over $14 billion in 2019 on cloud services. During the height of the pandemic and cloud adoption spurt in 2020, IDG reported that 70% of US businesses overspent by as much as 62%.

Establishing a Cloud Center of Excellence (CCOE) is an important milestone in every company’s cloud computing journey. While it is usually not the first milestone — which is focused on delivering value to customers — this milestone is reached as the company grows and scales. Turning ad-hoc cloud initiatives into a company-wide strategy, the CCOE helps the business to manage the cloud process and adopt best practices.

Rolled out in 2011, AWS ElastiCache has grown to become one of the most prominent Amazon services among developers. So much so that in the 2020 Stack Overflow Developer Survey, one of its fully-managed engines was voted by developers as the most loved database. On the flip side, however, AWS ElastiCache happens to be infamous for its high costs. Although it offers a flexible pricing system that charges you only for what you use, the usage bill can get pretty high for some users.

As a cloud cost intelligence platform, we spend nearly every day talking to companies about their cloud cost — and there’s something we’ve noticed — people don’t generally have the warm and fuzzies for their cloud cost management tools. You know, the ones that have been around for a while, that you use to build reports about your cloud spend? We won’t refer to them by name. These popular tools have really given the whole category a bit of a bad rap.

Automation does not only eliminate the mundaneness of performing repetitive tasks, it can also help reduce errors and mistakes. Good cloud infrastructure encourages cloud automation. That should be one of the main motivators of implementing it. As ubiquitous as the idea of cloud computing has become in the last decade, there is still a lot of demystification to be done. People still don't fully understand its potential. Yes, it can save you money and time but how?

One of the biggest benefits of the cloud is that it gives engineering teams the freedom to deploy and iterate applications quickly. Unlike traditional IT environments where engineers require a series of approvals before embarking on projects, in the cloud, engineers can choose from several managed services and deploy them at the click of a button. This means your team can innovate faster and respond quickly to market demands.

Whether you've recently migrated to the cloud, or you've been operating there for awhile now, you've likely realized how challenging it can be to understand exactly where your cloud spend goes and what drives your costs. Using a cloud service provider can offer many benefits, like the ability to easily scale up and down based on need, but unless you're using the right services and tools, your costs can quickly spiral out of control.

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.

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.