Operations | Monitoring | ITSM | DevOps | Cloud

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 It can be caused by outdated architecture, a change in requirements, or the result of choosing an easier solution instead of a better, but more difficult one.

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.

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.

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.

As companies are increasingly built in the cloud, cost management has become a major issue for many engineering teams. While cloud providers like AWS offer flexibility and easy scaling, cloud costs can be opaque and difficult to track. As a result, many companies that rely on the cloud are adopting cloud cost management strategies to understand and manage the charges associated with their cloud-based technology, and maximize cloud usage and efficiency.

For developers and programmers, Amazon Web Services (AWS) offers many benefits. It gives you access to the computing and DevOps tools you need at the press of a button — which helps you get products out the door fast. However, it can be challenging to control your costs and identify waste. In this comprehensive guide, we will examine some practical steps you can take for AWS cost optimization.

One of the many aspects of CloudZero’s cloud cost intelligence is anomaly detection. Unlike solutions which require you to set budgets or thresholds, CloudZero uses machine learning to automatically detect and alert on anomalies, then send them directly to dev team Slack channels where the responsible engineers can view and take action. Here are just a few examples of real customer anomalies, what caused them, and the action the customer took.

Earlier this year, Gartner published a report called “How to Manage and Optimize Costs of Public Cloud IaaS and PaaS.” Overall, we agreed with the piece and wrote a blog post about what they get right (and where they miss). However, one thing that stood out to us is how many aspects of optimization Gartner described as very difficult — which CloudZero can help make easier.

Earlier this year, Gartner published “How to Manage and Optimize Costs of Public Cloud IaaS and PaaS,” by analysts Marco Meinardi and Traverse Clayton. As a company that is focused on enabling engineering teams with cloud cost intelligence, we were of course curious what they had to say. Now, if you are familiar with Gartner, you know they have a reputation for serving enterprise clients, so they can sometimes be — well, enterprisey.