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cloud saas
Running Spark on Kubernetes with Dataproc
Google announced general availability of Dataproc on Google Kubernetes Engine (GKE), enabling Apache Spark workloads to run on self-managed Kubernetes clusters with native container job submission and GKE's autoscaling capabilities. The offering allows multiple independent Spark jobs, different Spark versions, and multiple Dataproc clusters to share the same infrastructure for cost optimization and simplified cluster management.
Why it matters: Data engineering teams standardizing on Kubernetes can now consolidate Spark workloads on shared GKE infrastructure, reducing operational overhead and infrastructure costs while gaining access to advanced resource sharing and job isolation features.
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- First seen by Cybersecurity Tracker
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cloud saas
Running Spark on Kubernetes with Dataproc
Google announced general availability of Dataproc on Google Kubernetes Engine (GKE), enabling Apache Spark workloads to run on self-managed Kubernetes clusters with native container job submission and GKE's autoscaling capabilities. The offering allows multiple independent Spark jobs, different Spark versions, and multiple Dataproc clusters to share the same infrastructure for cost optimization and simplified cluster management.
Why it matters: Data engineering teams standardizing on Kubernetes can now consolidate Spark workloads on shared GKE infrastructure, reducing operational overhead and infrastructure costs while gaining access to advanced resource sharing and job isolation features.
- Source published
- First seen by Cybersecurity Tracker