As cloud computing continues to grow in popularity, so does the need for accurate cloud cost forecasting. With cloud costs being variable and unpredictable, it can be difficult to know how much you’re going to spend each month, a problem that can lead to budget overruns and financial problems. This makes cloud cost forecasting a necessary step in owning and managing your cloud efficiently. In simple terms, cloud cost forecasting is the process of predicting future cloud costs.

Kubeapps is one of the open source projects that the Bitnami team at VMware contributes to, and it is among the 100+ pre-packaged open source images present in Bitnami Application Catalog and VMware Tanzu Application Catalog (the enterprise edition of Bitnami Application Catalog). This blog presents an overview of Kubeapps and how you can use it to simplify your Kubernetes application deployments.

Kubernetes has emerged as a transformative force, reshaping the way organizations develop, deploy, and manage applications. Adoption of containers and Kubernetes has ballooned in the past years, as heralded by everyone from the Cloud Native Computing Foundation (CNCF) itself, to the vendors offering their Kubernetes wares, to the research firms that track trends in enterprise technology adoption.

As companies continue to invest, adopt, and grow into cloud, as well as manage a strong public and hybrid cloud environment, it is very important to understand what are the common pain points of their sub-organizations.

Setting and tracking appropriate target metrics are an important part of a product manager’s job. Goals must be defined, not just as inspiring vision statements, but also as quantifiable targets that can be objectively measured. Metrics can be deployed in different contexts and for purposes; however, useful metrics in one scenario can be misleading in regards to another. The problem comes when you’re not clear about what kind of metric you’re trying to set.

This blog was co-written by Howard Twine and Gregory Green. A few years ago, a colleague of ours wrote an informative post to help readers understand when to use RabbitMQ and when to use Apache Kafka. While the two solutions take very different approaches architecturally and can solve different problems, many people find themselves comparing them for situations where there is overlap.

A couple of weeks ago, I wrote about The Art of True Chargebacks and how VMware Tanzu CloudHealth makes simple work of the cost reallocation of cloud expenses. In addition to being a refresher on cost reallocation with Tanzu CloudHealth, it was also shared as a kickoff of our newly released cutting-edge Cost Reallocation API. This officially available API revolutionizes the seamless automation of chargeback reallocation across diverse geographies, brands, business units (BUs), and product lines.

KuppingerCole AG published its report assessing Cloud Security Posture Management (CSPM) solutions in the market for 2023. Their leadership compass helps cloud users find an appropriate solution to meet CSPM needs of an organization to monitor, assess, and manage risks associated with the use of cloud services. Fifteen vendors were assessed based on responses to a questionnaire, strategy briefing, and demo.

Cloud computing and AI/machine learning (ML) are two powerful technologies that are even more impactful when used together. Cloud computing provides the infrastructure and resources needed to support AI/ML applications; while AI/ML enhances cloud computing by providing intelligent automation and decision-making capabilities.

Many organizations struggle with managing thousands of services and applications. A typical environment consists of a combination of modern cloud applications, on-premises workloads, and workloads that are in the process of being moved to the cloud. IT and operations teams can easily be overwhelmed by the large volume of data and activity that is generated across these systems.