Understand the Kubernetes Migration Trends
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Kubernetes (K8s) has established itself as the de facto standard for orchestrating big data applications across clusters. For example, running Spark applications on Kubernetes offers numerous benefits for developers and big data analysts, such as eliminating dependency issues. However, running Spark on Kubernetes is a challenging setup.
While the market for Kubernetes monitoring tools is vast, many of these vendors don’t provide granular visibility into big data application performance or the ability to optimize resources automatically. Without the right tool to track application performance on Kubernetes, users are bound to deal with performance issues, poor resource allocation, overspending, and ineffective tuning.
“Many enterprises rely on cloud vendor solutions to monitor Kubernetes. But they end up struggling to manage their costs, optimize their resources, and meet SLAs because these tools don’t have custom functionalities for comprehensive K8s monitoring of their big data applications.“
–Matthias Parbel, Editor Heise Developer at iX
It is critical for organizations to understand the direction Kubernetes implementations are moving so they can be successful using data in the future.
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