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Answer: Implement batch processing to reduce the number of container launches.
Implementing batch processing can significantly reduce the number of container launches, thereby reducing the overhead associated with container creation and termination. This approach can help in managing the workload more efficiently and reducing latency and CPU usage.
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You are tasked with optimizing the performance of a data processing pipeline that uses Amazon EKS for container orchestration. The current setup involves a large number of small, short-lived containers that process data from a JDBC-connected SQL database. The pipeline frequently experiences latency issues and high CPU usage. What strategy would you employ to improve the performance of this pipeline?
A
Increase the number of worker nodes in the EKS cluster.
B
Use larger container instances with more CPU and memory resources.
C
Implement batch processing to reduce the number of container launches.
D
Switch to using Amazon ECS instead of Amazon EKS.
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