As the complexity of Kubernetes environments grow, costs can quickly spiral out of control if an effective strategy for optimization is not in place. We’ve compiled expert recommendations and best practices for running cost-optimized Kubernetes workloads on AWS, Microsoft Azure, and Google Cloud (GCP).

When each quarter’s financial report lands on the desks of a company’s C-Suite executives, those execs are essentially looking at a black box of spending and revenue. They can see the total numbers and the growth or shrinkage of certain categories, but they ultimately have very little context into why each number is as high or low as it is. Without this context, it’s all too easy to feel sticker shock over a seemingly outrageous cloud bill and demand that costs be cut at once.

AWS Cost Explorer is one of the core pillars of AWS cloud financial management. It helps collect resource consumption data and associated cost information across multiple AWS services. Cost Explorer then helps visualize all of this data in one dashboard to ease cost management. You can then analyze, understand, and share cloud cost data with various parties. Cost Explorer is also ideal for companies that have simple cloud billing — and it's free with an AWS subscription.

Early on in our journey as a company, CloudZero split with legacy data architecture, migrating to Snowflake and opening up a world of resource flexibility. With the centralized, limitless processing power that Snowflake provided, our team could focus more energy on value-added work, less on managing inefficiencies. With a rapidly expanding customer base, Snowflake allowed us to maintain peak velocity, scaling without running into storage-based slowdowns.

The FinOps position, for most SaaS companies, is a relatively recent addition to the team. FinOps acts as a liaison between the Finance and Engineering teams, with the goal of getting everyone on the same page (and speaking the same language) when it comes to setting, optimizing, and sticking to budgets. FinOps and engineering have a special relationship, because engineers are the ones who ultimately make major infrastructure, development, and design choices that impact the cloud bill.

There are few organizations left today without some of their business operating in the cloud. A recent IDG Cloud Computing Study found that 92% of businesses globally moved to the cloud. According to Gartner, cloud adoption spending will surge to about $482 billion by the end of 2022. Most companies make the move to take advantage of the speed, innovation, and flexibility offered by cloud computing solutions. Operating in the cloud can also provide cost savings and improved productivity.

Cloud computing offers nearly limitless capacity on-demand, but left unmanaged, that flexibility can lead to surprisingly high monthly cloud bills. To be fair, rising cloud costs aren't always a bad thing; they could be a signal of growth. For example, you’ll incur higher costs as you gain more customers. Your costs of goods sold (COGS) may also increase. These scenarios are often a good thing unless your margins on COGS are thinning out.

Containers are one of the most popular ways for businesses to deploy applications. They provide an easy method of packaging applications into self-sufficient units that can be used, moved around, and re-used in any number of ways without breaking the overall functionality of your software. With the possible exception of serverless architecture, containerization is perhaps the best way to achieve smooth, seamless application deployment and minimal hassle with updates and application maintenance.

What separates an engineer fresh out of university from one who has been working in the field for several years? While specialized coding knowledge certainly plays a part, it’s the softer, more business-oriented skills that often set engineers apart from the pack. If an employee doesn’t take the time to develop skills for business in the engineering field, it could hinder their career growth over the long term.

Regulatory compliance and data privacy requirements require financial institutions (FIs) to consider carefully where their applications are running and where the customer data is stored. The data protection and data sovereignty laws in most countries require an enterprise to keep data in certain geographic locations. PCI Data Security Standard, for example, regulates the way the customer and financial transactions data is stored and transmitted.