Operations | Monitoring | ITSM | DevOps | Cloud

With 34% of cloud developers facing difficulties when calculating how much their cloud provider is going to charge them each month, it is essential to prioritize cloud cost management. This concept surrounds the process of monitoring, controlling, and optimizing an organization’s cloud service spend. By having the correct cloud cost management strategies in place, organizations are able to eliminate unnecessary expenses through optimizing resource allocation and cost-saving strategies.

As companies start their Kubernetes and cloud-native journey, cloud infrastructures and services grow at a rapid pace. This happens all too often as organizations shift left without thorough controls, which can lead to overallocating and overspending on their Kubernetes environments. Organizations running workloads in the cloud can put budgets at risk when they lack information about key facts.

Repatriation in cloud computing refers to moving workloads from the public cloud to on-premise infrastructure. Sarah Wang and Martin Casado from Andreessen Horowitz have written one of the most popular articles about repatriation: they explain the motivation with the significant cost savings possible. For software-based businesses, public cloud spend can rise to 50% of the cost of revenue (COR). Reducing these costs has the potential for significant margin increases.

Most customers running Kubernetes clusters Amazon EKS are regularly looking for ways to better understand and control their costs. While EKS simplifies Kubernetes operations tasks, customers also want to understand the cost drivers for containerized applications running on EKS and best practices for controlling costs. Anodot has collaborated with Amazon Web Services (AWS) to address these needs and share best practices on optimizing Amazon EKS costs.

In the realm of big data, Hive is a big deal. Well-written and well-designed Hive queries accelerate data retrieval from datasets. Hive is much better than SQL as the former works with complicated data more effectively. In addition, Hive queries help bring down processing costs. This is why it’s critical to write and optimize Hive queries correctly for big data analytics users and developers.

MongoDB has evolved into the database solution of choice for developers looking to build efficient, scalable applications in the cloud. But, as when using any cloud-based infrastructure, using MongoDB introduces an additional layer of complexity to customers’ IT spend. This week, we announced support for MongoDB on the CloudZero Platform.

In the early days of SaaS companies, most engineering and cloud operations teams weren’t tasked with monitoring or optimizing cloud costs. In fact, it would have been unlikely for these teams to care about cloud cost optimization at all, let alone take measures to fix issues and look for opportunities. Today, SaaS companies that want to secure a competitive foothold and ensure long-term success have to care about cloud costs.

Amazon’s Elastic Compute Cloud (EC2) service provides a variety of virtual machines (instances) for compute workloads. Among those, Amazon EC2 M5 instances are among the most versatile. In addition, there are different types of M5 instances available. Each of these has its own best use case. In this guide, we share an in-depth look at M5 instance types, sizes, and when to use them.

For IT and EUC teams, reducing costs is easier said than done. You can’t just blindly reduce headcount, delay transformation projects, or extend hardware lifecycles in the hopes of appeasing your CFO’s demands for short-term cost reduction. The reality is, rushed cost-cutting will put your service desk under pressure. In turn, such self-inflicted inefficiencies will only result in performance degradations, additional tickets, and escalations.