Amid the first bear market in over a decade, the world’s largest companies are facing intense pressure to cut back. Layoffs have made headlines, but cutting workforce is not a silver-bullet solution to surviving in a down market. True, companies tend to spend the most on personnel, but using layoffs as a first line of recession defense has myriad negative consequences for survivors, including reduced job satisfaction, reduced organizational commitment, and declining job performance.

In Part I of this two-part series, I talked about the key benefits of top-down cost allocation: It starts at the provider level, incorporates every penny of your cloud spend, and lets you break it down at as granular a level as is useful for your business.

Cloud costs can pile up quickly, and often behind the scenes. We explain how software-defined cloud interconnect (SDCI) can help your business rein in a swelling budget.

High-quality cloud cost allocation has become an existential issue for businesses. In order to get as much out of their (mounting) cloud investments as possible, business leaders need to know how much they’re spending in the cloud, what/who they’re spending it on, and whether there’s a good reason for it. In its ideal form, cost allocation answers all these questions.

Just as there are a handful of stages to describe the financial journey from startup to established company — pre-seed and seed funding, followed by series A, B, and C funding — there are also stages to the process of achieving a healthy understanding of your costs.

Almost everyone who’s used Amazon Web Services (AWS) has used Amazon simple storage service (S3). In the decade since it was first released, S3 storage has become essential to thousands of companies for file storage. While using S3 in simple ways is easy, at a larger scale it involves a lot of subtleties and potentially costly mistakes, especially when your data or team are scaling up. Here are the most important things about AWS S3 that will help you avoid costly mistakes.

Kubernetes (K8s) packs a ton of benefits as a container orchestration platform. For instance, K8s is big on automation. This includes automating workload discovery, self-healing, and scaling containerized applications. Yet, Kubernetes isn't always production-ready after a few tweaks. This guide shares crucial Kubernetes best practices you'll want to start using immediately to improve your K8s security, performance, and costs. Let’s get to it!

It’s a wrap! From October 24–28, the Pepperdata team attended KubeCon + CloudNativeCon North America 2022, which brought together top engineers and developers from communities centered around Kubernetes and cloud native. With topics ranging from container observability practices to K8s innovations, Pepperdata unveiled the latest offering of its own: Autonomous FinOps for Kubernetes.

In the last few years, the usage of databases that charge by request, query, or insert—rather than by provisioned compute infrastructure (e.g., CPU, RAM, etc.)—has grown significantly. They’re popular for a lot of the same reasons that serverless compute functions are, as the cost will scale with your usage. No one is using your site? No problem: you’re not charged.

Setting FinOps KPIs helps keep your whole organization aligned toward the same financial goals. However, it takes more than simply setting a broad, company-wide financial goal and turning every employee loose to work on that goal without more specific directions. It’s far better to come up with realistic and achievable goals tailored toward each person or team that will be responsible for them. That’s because KPIs should ideally be focused around the typical persona of each team.