DOC-1288 Remove limitation on reducing core count#1093
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📝 WalkthroughWalkthroughThe changes are limited to documentation updates in the Kubernetes Redpanda scaling guide. The revisions focus on improving clarity, consistency, and readability of the instructions for scaling Redpanda clusters. Terminology was updated for precision, explanations were reworded for better understanding, and some cautionary language was softened. The outdated limitation on reducing CPU cores in a running cluster was removed. No code or functional logic was altered. Changes
Sequence Diagram(s)No sequence diagram generated as the changes are documentation-only and do not affect control flow or introduce new features. Assessment against linked issues
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🧹 Nitpick comments (4)
modules/manage/pages/kubernetes/k-scale-redpanda.adoc (4)
7-7: Enhance parallel phrasing
For improved readability and to clearly delineate vertical vs. horizontal scaling, consider using parentheses instead of commas.- You can scale a cluster both vertically, by increasing or decreasing the resources available to existing brokers, and horizontally, by adding or removing brokers from the cluster. + You can scale a cluster both vertically (by increasing or decreasing the resources available to existing brokers) and horizontally (by adding or removing brokers from the cluster).
11-11: Condense resource definition
The phrase “amount of hardware available to Redpanda brokers” is a bit wordy. Consider tightening it to “hardware resources” for conciseness:- Resources include the amount of hardware available to Redpanda brokers, such as CPU cores, memory, and storage. + Resources include hardware resources such as CPU cores, memory, and storage.
30-30: Use imperative voice for caution
Switching to an imperative mood strengthens the warning. For example:- CAUTION: Redpanda does not support Kubernetes autoscalers. Autoscalers rely on CPU and memory metrics for scaling decisions, which do not fully capture the complexities involved in scaling Redpanda clusters. You should always manually scale your Redpanda clusters as described in this topic. + CAUTION: Redpanda does not support Kubernetes autoscalers. Autoscalers rely on CPU and memory metrics for scaling decisions, which do not fully capture Redpanda’s complexities. Always manually scale your Redpanda clusters as described in this topic.
34-34: Break up lengthy caution sentence
The current sentence is quite long. Splitting it improves readability:- While you should not rely on Kubernetes autoscalers to scale your Redpanda brokers, you can prevent infrastructure-level autoscalers, such as Karpenter, from terminating nodes that run Redpanda Pods. + Do not rely on Kubernetes autoscalers to scale your Redpanda brokers. Instead, prevent infrastructure-level autoscalers—such as Karpenter—from terminating nodes that host Redpanda Pods.
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🔇 Additional comments (2)
modules/manage/pages/kubernetes/k-scale-redpanda.adoc (2)
18-18: Approve consistent gerund usage
The change from “Deleting each worker node one by one” to “Deleting each worker node individually” maintains the gerund style used throughout the list and reads clearly.
45-45: Approve expanded scaling out description
The revised text clearly outlines the benefits of scaling out (throughput, availability, fault tolerance) and emphasizes large datasets. This enhances reader understanding without altering intent.
JakeSCahill
changed the title
JakeSCahill
requested review from
chrisseto
and removed request for
travisdowns
|
@michael-redpanda this falls in your area on the core side: can you maybe find someone to take a peek at this docs update? |
@travisdowns I think you meant @mmaslankaprv ? |
Oops yes sorry. |
6 participants
Description
Resolves https://redpandadata.atlassian.net/browse/DOC-1288
Review deadline: April 29
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