With containerization, you can write an application once and run it anywhere. Along with portability, containers are also much more resource-efficient than traditional virtual machines (VMs). However, managing containers at scale can be challenging. Besides, many teams find container orchestration platforms like Kubernetes overkill and too complex.

One of the most challenging aspects of running a SaaS business is dealing with highly variable costs. Every service you provide needs resources, and the demands for those resources fluctuate. Just when you think you’ve got this quarter’s budget nailed down, an engineer makes a restructuring decision or a new feature launch exceeds expectations (or falls flat). Suddenly, your bill looks totally different than what you were expecting.

Is your enterprise still paying the sticker price for cloud services? If so, you’re probably leaving a significant amount of money on the table. Once your company surpasses the level of “large business” and begins growing into a full-fledged enterprise, it likely qualifies for enterprise discounts offered by each of the major cloud providers. The most well-known of these would be the Enterprise Discount Program (EDP) offered by Amazon Web Services (AWS).

Building quality software is tough. Even automation requires skilled developers to make it work. Yet, good developers are in short supply. You could offer attractive packages, too. Think: hybrid working, breakfast burritos, and organic chicken wings every Wednesday. You'll still need to ask the right DevOps interview questions to find and hire qualified DevOps engineers.

At CloudZero, we advocate measuring every cloud cost metric that makes the most sense for your business. When you know your company’s unit economics inside and out, you can better inform each department, show them how to make smart decisions based on the information, and ultimately maintain control over your margins. One of the most universally useful metrics to track is cloud cost per customer.

You know this already. Regardless of your size, you must keep up with technological developments in your industry — and, increasingly, in other industries, even those that seem unrelated. Embracing disruption can enable you to increase your market share, revenue, and profit margins. Delegating some development and operations responsibilities to Site Reliability Engineering (SRE) experts allows developers to innovate and create new solutions faster.

A big part of cloud management is managing and optimizing cloud costs. CloudHealth and CloudCheckr aim to help you manage the cost, performance, security, and compliance requirements of your cloud-based services. Both offer hybrid and multi-cloud deployment capabilities. But we doubt you'll want to use them both simultaneously. So, which one do you choose? CloudCheckr or CloudHealth? In this comparison, we reveal what makes each cloud management tool unique, so you can pick the right one for your needs.

When it comes to cloud costs, engineers have a particular reputation. The executive suite and finance department often share perplexing frustration about why engineers appear not to care about budgets and costs at all. They provide hard budget limits, yet engineers frequently surpass them, citing performance and user experience as reasons for the excess spending.

Did you know that Google Search changes how it works about 12 times daily? For example, the internet search giant made about 4,500 changes to Search in 2020 alone. Those changes involved running more than 600,000 tests. Most of us can barely tell how often Google updates because the modifications are subtle. But we can tell that something keeps improving. Many other leading tech solutions do the same, from your tiniest mobile app to big ol’ Apple products.

Kubecost and Cast AI promise real-time Kubernetes cost monitoring. Both deliver this to a good extent. For example, Kubecost provides cost data from within and outside a K8s cluster. It also shares the data in a granular format, such as cost by Kubernetes concepts like namespaces, pods, and custom labels. Cast.ai offers several similar capabilities, including cost savings recommendations, and is currently available for AWS, Google Cloud, Azure, and on-prem Kubernetes.