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.

You need a robust platform to speed up your read/write operations per second if you provide services such as live streaming, social media networking, and analytics. By storing frequently accessed objects in faster memory (RAM or in-memory data stores instead of slower disk-based storage), caching reduces latency. Amazon ElastiCache is a managed, in-memory data store and caching service in one.

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.

Databricks has emerged as one of the most powerful solutions for organizations to sort and normalize the data they ingest. But like all cloud providers — from the big three to more specialized infrastructure vendors — it adds complexity to customers’ IT spend. This week, we announced support for Databricks on the CloudZero Platform.

We see it often. Too many companies struggle to optimize their cloud costs — whichever platform they use, from Microsoft Azure to Amazon Web Services (AWS) and Google Cloud Platform (GCP). So, in this guide, we are sharing over 20 Azure cost optimization best practices you can apply right away — all in a calorie-free, snackable guide you can read in less than a coffee break.

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.

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.

Like any business, management service provider firms are always looking for ways to reduce MSP costs and improve profits. MSPs provide critical services to their clients, so finding ways to cut costs without cutting corners is essential. You’ve probably heard all the standard advice on cutting costs: review your pricing, renegotiate contracts, cut unnecessary expenses, and so on. But what about MSPs who are already doing all those things and are still looking for ways to save?

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.