Technical debt is an important — but often unclear — concept for engineering teams. In software development, technical debt, also called code debt or tech debt, is defined as the cost of refactoring a piece of code or system to keep it working efficiently. It can be caused by outdated architecture, a change in requirements, or the result of choosing an easier solution instead of a better, but more difficult one.

We are excited to announce the new Elastic Cloud usage analysis page. You can now explore and analyze your Elastic Cloud usage to better understand how the resources you consume contribute to your monthly bill. Your Elastic Cloud monthly bill consists of usage fees for the resources you used, including: Understanding your resource utilization allows you to make smarter decisions about your Elastic deployments as well as identify areas where you may be able to save costs.

As a cloud cost intelligence company, we often like to say “every line of code is a buying decision”. If you’re running on AWS or one of the other big cloud providers, you know that a simple decision about how to architect an application can have a significant impact on your future cost of goods sold (COGS). However, in my experience, many engineering teams don’t discuss cost — at least not until it’s already become a problem.

For those of you who aren’t familiar with AWS CodePipeline, it’s a continuous integration and continuous delivery (CI/CD) framework that enables application development teams to deliver code updates more frequently and reliably. You may have also heard it being called a CI/CD or DevOps pipeline. These pipelines have always traditionally been used to deploy the components of a certain application whenever new code in “checked-in”.

This is a follow up to a blog series where we explore DIY cloud cost management, monitoring, and optimization tools. In the first, we investigated how Lyft, Netflix, Segment, Expedia, and Slack built theirs. Check it out here. “Build versus buy” is the eternal question for every engineering and DevOps team setting out to solve a technical problem. In the cloud cost monitoring and optimization world, both options can take on many forms.

Are you suffering from overspending in Azure, lack of cost visibility and lack of context? You’re not alone; Azure cost management is a problem we hear about time and time again. That is why we created top-notch cost tiles that would allow users to build the perfect Azure cost dashboard, and help them quickly identify overspends and expensive resources in their Azure tenant.

Multi-cloud has become a hot-button topic these days, with a lot of cloud experts taking a strong stance against the practice. There are exceptions and legitimate reasons why you might choose a multi-cloud strategy (e.g., you sell to customers who restrict you from hosting their data in AWS). Extenuating circumstances aside, there are far more reasons why multi-cloud isn’t a good idea.

Here at CloudZero, we work with some of the top software-driven companies out there. Like us, they’re building their products on Amazon Web Services (AWS), along with whatever best-of-breed providers meet their needs. It’s no secret that in recent years, Snowflake has seen — well, some serious success. For many companies, including CloudZero, they're the data warehouse provider of choice — and an essential component of delivering their products.

The benefits for innovation with Kubernetes are clear: it can allow small teams to deliver more value, more rapidly. However, cost discussions around Kubernetes — and Kubernetes cost management — can be difficult. You have disposable and replaceable compute resources constantly coming and going, on a range of types of infrastructure. Yet at the end of the month, you just get a billing line item for EKS cost and a bunch of EC2 instances.

It has been nearly a year since Amazon Web Services (AWS) first rolled out its new savings plans. AWS Savings Plans were created to help manage cloud costs; however, they are best used as part of a larger strategy focused around cloud cost intelligence. (Keep reading for more on that!)