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Exam KCNA topic 1 question 6 discussion

Actual exam question from Linux Foundation's KCNA
Question #: 6
Topic #: 1
[All KCNA Questions]

Let's assume that an organization needs to process large amounts of data in bursts, on a cloud-based Kubernetes cluster. For instance: each Monday morning, they need to run a batch of 1000 compute jobs of 1 hour each, and these jobs must be completed by Monday night. What's going to be the most cost-effective method?

  • A. Run a group of nodes with the exact required size to complete the batch on time, and use a combination of taints, tolerations, and nodeSelectors to reserve these nodes to the batch jobs.
  • B. Leverage the Kubernetes Cluster Autoscaler to automatically start and stop nodes as they're needed.
  • C. Commit to a specific level of spending to get discounted prices (with e.g. “reserved instances” or similar mechanisms).
  • D. Use PriorityСlasses so that the weekly batch job gets priority over other workloads running on the cluster, and can be completed on time.
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Suggested Answer: B 🗳️
by nvtienanh at Aug. 28, 2023, 2:56 p.m.

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pablokoba
Highly Voted 4 months ago
The most cost-effective method would likely be option B, leveraging the Kubernetes Cluster Autoscaler to automatically start and stop nodes as they're needed. Here's why: Burst processing workloads, like the one described, benefit from the elasticity provided by cloud-based Kubernetes clusters. With Kubernetes Cluster Autoscaler, you can scale your cluster up when there's a demand for more resources (e.g., Monday mornings when the batch jobs need to run) and scale it down during periods of low demand (e.g., after the batch jobs are completed). This ensures that you're only paying for the resources you actually need, avoiding over-provisioning and reducing costs.
upvoted 7 times
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shahy0
Most Recent 1 week, 3 days ago
Selected Answer: B
Cluster Autoscaling: Utilize Kubernetes Cluster Autoscaler to automatically adjust the size of the cluster based on the current workload. This ensures that you only pay for the resources you need when you need them.
upvoted 1 times
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yoyo2424
1 month, 1 week ago
Selected Answer: B
B ...Leverage the Kubernetes Cluster Autoscaler to automatically start and stop nodes as they're needed. Explanation: When an organization needs to process large amounts of data in bursts, as described in this scenario, the most cost-effective method is to scale the infrastructure dynamically. The Kubernetes Cluster Autoscaler is specifically designed for this purpose.
upvoted 1 times
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SahandFN
2 months ago
Selected Answer: C
Reserved should be the answer
upvoted 1 times
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