<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Resharding on Tarragon</title><link>https://tarrragon.github.io/blog/tags/resharding/</link><description>Recent content in Resharding on Tarragon</description><generator>Hugo -- gohugo.io</generator><language>zh-TW</language><copyright>Tarragon (CC BY 4.0)</copyright><lastBuildDate>Tue, 19 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://tarrragon.github.io/blog/tags/resharding/index.xml" rel="self" type="application/rss+xml"/><item><title>Redis Cluster Re-sharding：source = target，但 topology 重劃的 5 段流程</title><link>https://tarrragon.github.io/blog/backend/02-cache-redis/vendors/redis/cluster-resharding/</link><pubDate>Tue, 19 May 2026 00:00:00 +0000</pubDate><guid>https://tarrragon.github.io/blog/backend/02-cache-redis/vendors/redis/cluster-resharding/</guid><description>&lt;blockquote>
&lt;p>本文是 &lt;a href="https://tarrragon.github.io/blog/backend/02-cache-redis/vendors/redis/" data-link-title="Redis" data-link-desc="OSS in-memory data structure store、cache 主流">Redis&lt;/a> overview 的 implementation-layer deep article。本文是 &lt;a href="https://tarrragon.github.io/blog/posts/migration-playbook-%E6%96%B9%E6%B3%95%E8%AB%96%E7%9A%84%E6%BC%94%E5%8C%96%E7%B4%80%E9%8C%84stage-0-variant-%E8%A6%8F%E5%8A%83%E6%8A%8A-collapse-%E7%8E%87%E5%BE%9E-60-%E9%99%8D%E5%88%B0-0/" data-link-title="Migration Playbook 方法論的演化紀錄：Stage 0 variant 規劃把 collapse 率從 60% 降到 0%" data-link-desc="跨 vendor migration playbook 需要獨立寫作方法論的依據，以及這套方法論從三輪 batch dogfood 中演化出來的驗證證據。">Migration playbook methodology&lt;/a> 「何時不該套」段的第 3 項實證（容量重新規劃 / re-sharding）— source / target 同 vendor 同 cluster、但 &lt;em>data topology 重劃&lt;/em>、不在 5 type 內。&lt;/p>&lt;/blockquote>
&lt;h2 id="source--target但-topology-重劃">Source = Target，但 topology 重劃&lt;/h2>
&lt;p>Migration 通常假設 &lt;em>source 跟 target 是不同 cluster / vendor&lt;/em>；re-sharding 是 &lt;em>同 cluster 內的 slot 重分配&lt;/em>、source 跟 target 是 &lt;em>同一個 Redis Cluster 的不同 state&lt;/em>：&lt;/p>





&lt;div class="highlight">&lt;pre tabindex="0" class="chroma">&lt;code class="language-text" data-lang="text">&lt;span class="line">&lt;span class="ln">1&lt;/span>&lt;span class="cl">Before re-shard:
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="ln">2&lt;/span>&lt;span class="cl"> Cluster A: [node1: slots 0-5460] [node2: slots 5461-10921] [node3: slots 10922-16383]
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="ln">3&lt;/span>&lt;span class="cl"> ~ 33% load ~ 50% load ~ 17% load (heavy imbalance)
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="ln">4&lt;/span>&lt;span class="cl">
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="ln">5&lt;/span>&lt;span class="cl">After re-shard:
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="ln">6&lt;/span>&lt;span class="cl"> Cluster A: [node1: slots 0-4095] [node2: slots 4096-8191] [node3: slots 8192-12287] [node4: slots 12288-16383]
&lt;/span>&lt;/span>&lt;span class="line">&lt;span class="ln">7&lt;/span>&lt;span class="cl"> ~ 25% load ~ 25% load ~ 25% load ~ 25% load&lt;/span>&lt;/span>&lt;/code>&lt;/pre>&lt;/div>&lt;p>source 跟 target 是 &lt;em>同 cluster&lt;/em>、區別在 &lt;em>slot 對 node 的 mapping&lt;/em>。Application connection string 不變、cluster API 不變、data model 不變。但 &lt;em>slot migration 期間&lt;/em> application 行為跟 &lt;em>normal operation&lt;/em> 差很多 — 這是 re-sharding 主要工作。&lt;/p>
&lt;p>跑 &lt;a href="https://tarrragon.github.io/blog/report/content-structure-by-max-diff-dimension/" data-link-title="Process content 結構由最大差異維度決定、不是 universal phased" data-link-desc="跨 X process content（migration / upgrade / rollout / playbook）的結構由 source / target 之間 *差異維度組合* 決定、不存在 universal phased 模板；6 種 migration / process type 實證（schema 差 / drop-in / operational / multi-tool / paradigm / topology re-layout）跑出 6 種不同結構；寫作前必須做 *6 維 diff dimension audit* 才能決定結構、跳過會套錯模板">diff dimension audit&lt;/a> 對 Redis cluster re-sharding：&lt;/p></description><content:encoded><![CDATA[<blockquote>
<p>本文是 <a href="/blog/backend/02-cache-redis/vendors/redis/" data-link-title="Redis" data-link-desc="OSS in-memory data structure store、cache 主流">Redis</a> overview 的 implementation-layer deep article。本文是 <a href="/blog/posts/migration-playbook-%E6%96%B9%E6%B3%95%E8%AB%96%E7%9A%84%E6%BC%94%E5%8C%96%E7%B4%80%E9%8C%84stage-0-variant-%E8%A6%8F%E5%8A%83%E6%8A%8A-collapse-%E7%8E%87%E5%BE%9E-60-%E9%99%8D%E5%88%B0-0/" data-link-title="Migration Playbook 方法論的演化紀錄：Stage 0 variant 規劃把 collapse 率從 60% 降到 0%" data-link-desc="跨 vendor migration playbook 需要獨立寫作方法論的依據，以及這套方法論從三輪 batch dogfood 中演化出來的驗證證據。">Migration playbook methodology</a> 「何時不該套」段的第 3 項實證（容量重新規劃 / re-sharding）— source / target 同 vendor 同 cluster、但 <em>data topology 重劃</em>、不在 5 type 內。</p></blockquote>
<h2 id="source--target但-topology-重劃">Source = Target，但 topology 重劃</h2>
<p>Migration 通常假設 <em>source 跟 target 是不同 cluster / vendor</em>；re-sharding 是 <em>同 cluster 內的 slot 重分配</em>、source 跟 target 是 <em>同一個 Redis Cluster 的不同 state</em>：</p>





<div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="ln">1</span><span class="cl">Before re-shard:
</span></span><span class="line"><span class="ln">2</span><span class="cl">  Cluster A: [node1: slots 0-5460] [node2: slots 5461-10921] [node3: slots 10922-16383]
</span></span><span class="line"><span class="ln">3</span><span class="cl">              ~ 33% load           ~ 50% load              ~ 17% load (heavy imbalance)
</span></span><span class="line"><span class="ln">4</span><span class="cl">
</span></span><span class="line"><span class="ln">5</span><span class="cl">After re-shard:
</span></span><span class="line"><span class="ln">6</span><span class="cl">  Cluster A: [node1: slots 0-4095] [node2: slots 4096-8191] [node3: slots 8192-12287] [node4: slots 12288-16383]
</span></span><span class="line"><span class="ln">7</span><span class="cl">              ~ 25% load           ~ 25% load              ~ 25% load              ~ 25% load</span></span></code></pre></div><p>source 跟 target 是 <em>同 cluster</em>、區別在 <em>slot 對 node 的 mapping</em>。Application connection string 不變、cluster API 不變、data model 不變。但 <em>slot migration 期間</em> application 行為跟 <em>normal operation</em> 差很多 — 這是 re-sharding 主要工作。</p>
<p>跑 <a href="/blog/report/content-structure-by-max-diff-dimension/" data-link-title="Process content 結構由最大差異維度決定、不是 universal phased" data-link-desc="跨 X process content（migration / upgrade / rollout / playbook）的結構由 source / target 之間 *差異維度組合* 決定、不存在 universal phased 模板；6 種 migration / process type 實證（schema 差 / drop-in / operational / multi-tool / paradigm / topology re-layout）跑出 6 種不同結構；寫作前必須做 *6 維 diff dimension audit* 才能決定結構、跳過會套錯模板">diff dimension audit</a> 對 Redis cluster re-sharding：</p>
<table>
  <thead>
      <tr>
          <th>維度</th>
          <th>評估</th>
          <th>等級</th>
      </tr>
  </thead>
  <tbody>
      <tr>
          <td>Schema / API</td>
          <td>同 Redis、無變</td>
          <td>Low</td>
      </tr>
      <tr>
          <td>Operational model</td>
          <td>同 Redis Cluster、operational 不變</td>
          <td>Low</td>
      </tr>
      <tr>
          <td>Abstraction / paradigm</td>
          <td>同 Redis Cluster、無 paradigm 差</td>
          <td>Low</td>
      </tr>
      <tr>
          <td>Number of components</td>
          <td>同 1 個（cluster）</td>
          <td>Low</td>
      </tr>
      <tr>
          <td>Application change</td>
          <td>多數不改、client cluster mode 自處理</td>
          <td>Low</td>
      </tr>
      <tr>
          <td><strong>Data topology</strong></td>
          <td><strong>重劃</strong> — slot mapping 跟 node 數</td>
          <td><strong>New axis</strong></td>
      </tr>
  </tbody>
</table>
<p>5 維皆 Low、對映 Type B drop-in；但 <em>data topology</em> 是 5 type 沒有的 <em>第 6 維度</em>。本文採用 <em>re-sharding-specific 結構</em>、不是 5 type 任一個。</p>
<h2 id="4-種-re-sharding-driver">4 種 re-sharding driver</h2>
<p>不同 driver 對應不同 re-sharding 策略：</p>
<table>
  <thead>
      <tr>
          <th>Driver</th>
          <th>觸發場景</th>
          <th>對應 re-sharding 操作</th>
      </tr>
  </thead>
  <tbody>
      <tr>
          <td>Slot imbalance</td>
          <td>業務熱點打到部分 slot、單 node CPU / memory 80%+</td>
          <td>Rebalance（slot 重分配、不加 node）</td>
      </tr>
      <tr>
          <td>Capacity expansion</td>
          <td>整 cluster memory / throughput 上限快到、要加 node</td>
          <td>Add node + slot migration（從現有 node 搬部分 slot 過去）</td>
      </tr>
      <tr>
          <td>Node decommission</td>
          <td>老 node 硬體淘汰 / cloud instance 換代</td>
          <td>Drain（該 node 的 slot 全搬走）+ remove</td>
      </tr>
      <tr>
          <td>Hash tag refactor</td>
          <td>業務 access pattern 變、需要 co-located key 群重分組</td>
          <td>Application-side migration（不是 cluster-level）</td>
      </tr>
  </tbody>
</table>
<p>前 3 種是 cluster-internal、用 <code>redis-cli --cluster</code> 工具完成；第 4 種需要 application 端 dual-write + migration、本文不展開。</p>
<h2 id="slot-migration-機制">Slot migration 機制</h2>
<p>Redis Cluster 16384 個 slot、每個 key 經 <code>CRC16(key) % 16384</code> 對應 slot。Slot migration 過程：</p>





<div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="ln"> 1</span><span class="cl">Source node:     [slot N: MIGRATING to dest]
</span></span><span class="line"><span class="ln"> 2</span><span class="cl">Dest node:       [slot N: IMPORTING from source]
</span></span><span class="line"><span class="ln"> 3</span><span class="cl">                 ↓
</span></span><span class="line"><span class="ln"> 4</span><span class="cl">Source node:     SCAN slot N → for each key:
</span></span><span class="line"><span class="ln"> 5</span><span class="cl">                 1. DUMP key (serialize value)
</span></span><span class="line"><span class="ln"> 6</span><span class="cl">                 2. send to dest via MIGRATE command
</span></span><span class="line"><span class="ln"> 7</span><span class="cl">                 3. dest RESTORE key
</span></span><span class="line"><span class="ln"> 8</span><span class="cl">                 4. source DEL key
</span></span><span class="line"><span class="ln"> 9</span><span class="cl">                 ↓
</span></span><span class="line"><span class="ln">10</span><span class="cl">Source node:     [slot N: OWNED by dest]
</span></span><span class="line"><span class="ln">11</span><span class="cl">Dest node:       [slot N: OWNED]
</span></span><span class="line"><span class="ln">12</span><span class="cl">                 ↓
</span></span><span class="line"><span class="ln">13</span><span class="cl">跨 cluster broadcast: slot N 屬於 dest</span></span></code></pre></div><p>期間 client 行為：</p>
<ul>
<li>Key 在 source 端（未 migrate）：source 直接 serve</li>
<li>Key 在 dest 端（已 migrate）：source 回 <code>-ASK</code> redirect、client 重發到 dest</li>
<li>寫入 MIGRATING slot 的新 key：source serve、之後也會 migrate</li>
<li>Application 不需要改 code、cluster-aware client 自動處理 <code>-ASK</code> redirect</li>
</ul>
<h2 id="redis-cli-cluster-工具">redis-cli &ndash;cluster 工具</h2>
<p>production 用 official tool、不要手寫 slot migration：</p>





<div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="ln"> 1</span><span class="cl"><span class="c1"># 1. Rebalance（slot 重分配、適合 imbalance）</span>
</span></span><span class="line"><span class="ln"> 2</span><span class="cl">redis-cli --cluster rebalance 10.0.0.1:6379 <span class="se">\
</span></span></span><span class="line"><span class="ln"> 3</span><span class="cl"><span class="se"></span>  --cluster-use-empty-masters <span class="se">\
</span></span></span><span class="line"><span class="ln"> 4</span><span class="cl"><span class="se"></span>  --cluster-threshold <span class="m">5</span>
</span></span><span class="line"><span class="ln"> 5</span><span class="cl">
</span></span><span class="line"><span class="ln"> 6</span><span class="cl"><span class="c1"># 2. Reshard（指定來源 → 目標、適合 capacity expansion）</span>
</span></span><span class="line"><span class="ln"> 7</span><span class="cl">redis-cli --cluster reshard 10.0.0.1:6379 <span class="se">\
</span></span></span><span class="line"><span class="ln"> 8</span><span class="cl"><span class="se"></span>  --cluster-from &lt;source-node-id&gt; <span class="se">\
</span></span></span><span class="line"><span class="ln"> 9</span><span class="cl"><span class="se"></span>  --cluster-to &lt;dest-node-id&gt; <span class="se">\
</span></span></span><span class="line"><span class="ln">10</span><span class="cl"><span class="se"></span>  --cluster-slots <span class="m">4096</span> <span class="se">\
</span></span></span><span class="line"><span class="ln">11</span><span class="cl"><span class="se"></span>  --cluster-yes
</span></span><span class="line"><span class="ln">12</span><span class="cl">
</span></span><span class="line"><span class="ln">13</span><span class="cl"><span class="c1"># 3. Add-node（加新 node 進 cluster）</span>
</span></span><span class="line"><span class="ln">14</span><span class="cl">redis-cli --cluster add-node 10.0.0.4:6379 10.0.0.1:6379 <span class="se">\
</span></span></span><span class="line"><span class="ln">15</span><span class="cl"><span class="se"></span>  --cluster-master-id &lt;existing-master-id&gt;
</span></span><span class="line"><span class="ln">16</span><span class="cl">
</span></span><span class="line"><span class="ln">17</span><span class="cl"><span class="c1"># 4. Del-node（移除 node、需先 drain slot）</span>
</span></span><span class="line"><span class="ln">18</span><span class="cl">redis-cli --cluster del-node 10.0.0.1:6379 &lt;node-to-remove&gt;</span></span></code></pre></div><p>關鍵：</p>
<ul>
<li><code>--cluster-threshold 5</code>：load 差異超過 5% 才 rebalance、避免反覆觸發</li>
<li><code>--cluster-slots</code>：一次 migrate 多少 slot；太大 lock 久、太小步驟多</li>
<li>Rebalance / reshard 過程 cluster 仍 serve traffic、但 <em>latency 升高</em>（migration overhead）</li>
</ul>
<h2 id="5-段執行流程">5 段執行流程</h2>





<div class="highlight"><pre tabindex="0" class="chroma"><code class="language-text" data-lang="text"><span class="line"><span class="ln"> 1</span><span class="cl">1. Pre-resharding analysis
</span></span><span class="line"><span class="ln"> 2</span><span class="cl">   - 當前 slot 分佈跟 load
</span></span><span class="line"><span class="ln"> 3</span><span class="cl">   - Hot key 識別（CLUSTER COUNTKEYSINSLOT）
</span></span><span class="line"><span class="ln"> 4</span><span class="cl">   - 預估 migration 時間
</span></span><span class="line"><span class="ln"> 5</span><span class="cl">
</span></span><span class="line"><span class="ln"> 6</span><span class="cl">2. Backup checkpoint
</span></span><span class="line"><span class="ln"> 7</span><span class="cl">   - BGSAVE on all master
</span></span><span class="line"><span class="ln"> 8</span><span class="cl">   - 確認 replica 跟得上（replication offset diff &lt; 10MB）
</span></span><span class="line"><span class="ln"> 9</span><span class="cl">
</span></span><span class="line"><span class="ln">10</span><span class="cl">3. Execute re-sharding
</span></span><span class="line"><span class="ln">11</span><span class="cl">   - 用 redis-cli --cluster 工具
</span></span><span class="line"><span class="ln">12</span><span class="cl">   - Monitor cluster health（CLUSTER INFO + CLUSTER NODES）
</span></span><span class="line"><span class="ln">13</span><span class="cl">   - Migration 期間 application 端 latency baseline 比對
</span></span><span class="line"><span class="ln">14</span><span class="cl">
</span></span><span class="line"><span class="ln">15</span><span class="cl">4. Verify
</span></span><span class="line"><span class="ln">16</span><span class="cl">   - Slot distribution 對 expected mapping
</span></span><span class="line"><span class="ln">17</span><span class="cl">   - Application traffic pattern 對 baseline
</span></span><span class="line"><span class="ln">18</span><span class="cl">   - 跑 cross-node sanity check
</span></span><span class="line"><span class="ln">19</span><span class="cl">
</span></span><span class="line"><span class="ln">20</span><span class="cl">5. Cleanup
</span></span><span class="line"><span class="ln">21</span><span class="cl">   - 舊 node（若 decommission）reset / 釋放
</span></span><span class="line"><span class="ln">22</span><span class="cl">   - Monitoring dashboard 更新 (Prometheus target / Grafana panel)
</span></span><span class="line"><span class="ln">23</span><span class="cl">   - Document new topology</span></span></code></pre></div><p>整體 1-7 天、依 cluster 大小（10GB ~ 1 小時、TB 級 1-3 天）。</p>
<h2 id="production-故障演練">Production 故障演練</h2>
<h3 id="case-1cluster-busy-期間-application-timeout">Case 1：Cluster busy 期間 application timeout</h3>
<p><strong>徵兆</strong>：re-sharding 跑到一半、application 端開始大量 <code>CLUSTER BUSY</code> error / <code>OOM</code> warning / latency p99 從 5ms 跳到 200-2000ms；某些 batch operation 完全失敗。</p>
<p><strong>根因</strong>：MIGRATE command 對單 key 是 <em>blocking</em>（DUMP + send + RESTORE + DEL atomic）— 大 value（HASH / SORTED SET / LIST 含 100K+ entry）migration 可能 lock node 數秒；同期間其他 query 阻塞。</p>
<p><strong>修法</strong>：</p>
<ol>
<li><strong>Pre-resharding audit</strong>：<code>MEMORY USAGE</code> 跑 sample key、找 &gt; 1MB 的 <em>fat key</em>、列出單獨處理</li>
<li><strong>MIGRATE timeout 調</strong>：<code>redis.conf</code> 設 <code>cluster-migration-timeout 10000</code>（10s）、避免單 key migration 卡爆 cluster</li>
<li><strong>降低並行</strong>：<code>--cluster-pipeline 1</code> 一次只搬一個 slot（預設 10）、減少 CPU 壓力</li>
<li><strong>Fat key refactor</strong>：production 不該有 1M+ entry 的 collection、refactor 拆分</li>
</ol>
<h3 id="case-2replica-lag-during-re-sharding">Case 2：Replica lag during re-sharding</h3>
<p><strong>徵兆</strong>：reshard 完成後、replica 顯示 stale data 數分鐘、application 端 read from replica 拿到舊值。</p>
<p><strong>根因</strong>：master 端 slot migration 產生大量 <code>DEL</code> + <code>RESTORE</code> 命令、replication stream 量爆、replica 跟不上、accumulated lag。</p>
<p><strong>修法</strong>：</p>
<ol>
<li><strong>Pre-resharding 確認 replica lag &lt; 5MB</strong>、否則先 fix replica issue 再開始</li>
<li><strong>Throttle migration</strong>：用 <code>--cluster-replace</code> + lower pipeline、放慢 master 寫入速度</li>
<li><strong>Application 端 read-write split policy</strong>：reshard 期間強制 read from master、暫時放棄 replica read</li>
<li><strong>預備計畫</strong>：若 lag &gt; 30s 撐了 5+ 分鐘、考慮暫停 reshard、wait replica catch up</li>
</ol>
<h3 id="case-3client-side-topology-cache-stale">Case 3：Client-side topology cache stale</h3>
<p><strong>徵兆</strong>：reshard 完、application 端持續報 <code>MOVED &lt;slot&gt; &lt;new-node&gt;</code> redirect、但隔 30s 又 redirect 一次；某些 client 直接 connection refused（連到已 decommission node）。</p>
<p><strong>根因</strong>：cluster-aware client（lettuce / Jedis cluster mode）有 <em>topology cache</em>、reshard 後不主動 refresh；遇 MOVED 後 refresh 一次、但 cache TTL 內可能繼續用舊 mapping。</p>
<p><strong>修法</strong>：</p>
<ol>
<li><strong>Client config</strong>：lettuce <code>clusterTopologyRefreshOptions(...)</code> 設較短 refresh interval（60s）+ <code>enablePeriodicRefresh()</code></li>
<li><strong>Reshard 完後 trigger refresh</strong>：application 端可主動發 <code>CLUSTER NODES</code> 拿最新 topology、不依賴 client lib 自動 refresh</li>
<li><strong>Graceful client shutdown / restart</strong>：對 latency-sensitive 服務、reshard 完 rolling restart application pod、避免 stale cache</li>
<li><strong>Decommissioned node 保留 5 分鐘</strong>：不立刻 stop node、給 stale client 自然 retry 機會</li>
</ol>
<h3 id="case-4cross-slot-transaction-失敗">Case 4：Cross-slot transaction 失敗</h3>
<p><strong>徵兆</strong>：application 用 <code>MULTI/EXEC</code> 跨多 key、reshard 期間部分 transaction 報 <code>MOVED</code> error、整個 transaction 失敗、business logic 不一致。</p>
<p><strong>根因</strong>：Redis Cluster transaction 要求 <em>所有 key 在同 slot</em>（用 hash tag <code>{user:123}</code>）；reshard 期間如果 transaction 內某 key migrate 到 dest、cluster topology 暫時 inconsistent、transaction 拒絕。</p>
<p><strong>修法</strong>：</p>
<ol>
<li><strong>Pre-resharding audit</strong>：grep application code 找 MULTI / pipeline 使用、確認所有都用 hash tag co-locate</li>
<li><strong>Reshard 期間 application 端加 retry</strong>：transaction failure 後 backoff retry、cluster stabilize 後成功</li>
<li><strong>架構</strong>：transaction-heavy 場景考慮不用 Redis Cluster、用 Redis Sentinel single master（無 slot 概念）</li>
</ol>
<h3 id="case-5monitor-visibility-gap-during-reshard">Case 5：Monitor visibility gap during reshard</h3>
<p><strong>徵兆</strong>：reshard 期間 Prometheus dashboard 對某 node 的 metric 突然顯示 <em>錯位</em> — load = 95% 但 slot count 顯示 6% slot；SOC 不知道 node 健康狀況。</p>
<p><strong>根因</strong>：Prometheus exporter 對 <em>slot count</em> 跟 <em>traffic load</em> 分開計算；reshard 期間 slot count 已 migrate 但流量仍打 source node（client cache stale）— metric 看似矛盾。</p>
<p><strong>修法</strong>：</p>
<ol>
<li><strong>Reshard 期間關 alert</strong>：knownmaintenance window、Prometheus silence alert</li>
<li><strong>加 reshard-aware metric</strong>：用 <code>redis_cluster_migration_slots</code> 量化 in-flight migration</li>
<li><strong>Dashboard 加註解</strong>：reshard 期間 SOC 看 dashboard 知道是 <em>normal anomaly</em></li>
</ol>
<h2 id="capacity--cost">Capacity / cost</h2>
<table>
  <thead>
      <tr>
          <th>維度</th>
          <th>估算</th>
          <th>警戒</th>
      </tr>
  </thead>
  <tbody>
      <tr>
          <td>Slot migration 速度</td>
          <td>1-10K key / sec（依 key size + network）</td>
          <td>TB 級 10K key / sec → 1 天</td>
      </tr>
      <tr>
          <td>Application latency impact</td>
          <td>p99 +50-200% during migration</td>
          <td>設 latency budget、超出暫停</td>
      </tr>
      <tr>
          <td>Memory / node</td>
          <td>不變、但 temporary 雙寫期間 +5-15%</td>
          <td>不能在 memory 90%+ 時 reshard</td>
      </tr>
      <tr>
          <td>Network bandwidth</td>
          <td>跨 node 大流量、~100-500 Mbps per migration stream</td>
          <td>跨 AZ reshard egress cost 注意</td>
      </tr>
      <tr>
          <td>Recovery time</td>
          <td>Reshard 失敗回退 = 反向 reshard（時間相同）</td>
          <td>不能在 incident 期間 reshard</td>
      </tr>
  </tbody>
</table>
<p>實務 default：</p>
<ul>
<li>跑在 <em>低流量時段</em>（夜間 / 週末）</li>
<li>Throughput 容忍度 &lt; 50% 再 reshard、不要 80%+ 時操作</li>
<li>預留 <em>回退 window</em> — reshard 卡住時能 abort + 恢復原狀</li>
</ul>
<h2 id="整合--下一步">整合 / 下一步</h2>
<h3 id="跟-redis--dragonflydb-migration-對位">跟 <a href="/blog/backend/02-cache-redis/vendors/redis/migrate-to-dragonflydb/" data-link-title="Redis → DragonflyDB：drop-in 相容下的容量躍升 &#43; 5 個踩雷" data-link-desc="DragonflyDB 號稱 Redis drop-in 替代、單機 throughput 25x、記憶體效率 30% 提升；遷移流程簡單但有 5 個 production 踩雷（RDB 版本差 / Lua 腳本不全支援 / Pub-Sub fanout 行為差異 / Cluster mode 兼容度 / Modules 不支援）、跟 Sentinel / Cluster 模式對位">Redis → DragonflyDB migration</a> 對位</h3>
<p>DragonflyDB 設計上 <em>單機效能取代 cluster</em>、re-sharding 議題消失；如果 cluster re-sharding 頻繁觸發、評估直接遷 DragonflyDB 是否更便宜。</p>
<h3 id="跟-sentinel-ha-對比">跟 <a href="/blog/backend/02-cache-redis/vendors/redis/" data-link-title="Redis" data-link-desc="OSS in-memory data structure store、cache 主流">Sentinel HA</a> 對比</h3>
<p>Sentinel 模式無 slot 概念、re-sharding 不適用；但 <em>manual sharding by application</em> 場景仍可能需要類似 topology re-layout、application 端要自己處理。</p>
<h3 id="跟-redis-7-function--cluster-v2">跟 Redis 7+ Function / Cluster v2</h3>
<p>Redis 7 推 Cluster v2 跟 Functions、slot migration 機制部分升級；keyspace migration 仍是核心議題、但 API 跟 monitoring 改進。</p>
<h3 id="下一步議題">下一步議題</h3>
<ul>
<li><strong>Auto-rebalance via operator</strong>：Redis Enterprise / Aiven 等 managed Redis 提供自動 rebalance、不需手動觸發</li>
<li><strong>Cross-DC slot migration</strong>：跨 region cluster slot migration 對 latency / cost 影響大、通常用 <em>application-level sharding</em> 取代 cluster-level</li>
<li><strong>Hash tag 治理</strong>：application code grep / lint 強制 hash tag、避免 cross-slot transaction 反模式</li>
</ul>
<h2 id="相關連結">相關連結</h2>
<ul>
<li>上游 vendor 頁：<a href="/blog/backend/02-cache-redis/vendors/redis/" data-link-title="Redis" data-link-desc="OSS in-memory data structure store、cache 主流">Redis</a></li>
<li>平行 migration playbook：<a href="/blog/backend/02-cache-redis/vendors/redis/migrate-to-dragonflydb/" data-link-title="Redis → DragonflyDB：drop-in 相容下的容量躍升 &#43; 5 個踩雷" data-link-desc="DragonflyDB 號稱 Redis drop-in 替代、單機 throughput 25x、記憶體效率 30% 提升；遷移流程簡單但有 5 個 production 踩雷（RDB 版本差 / Lua 腳本不全支援 / Pub-Sub fanout 行為差異 / Cluster mode 兼容度 / Modules 不支援）、跟 Sentinel / Cluster 模式對位">Redis → DragonflyDB</a></li>
<li>對位 deep article：<a href="/blog/backend/01-database/vendors/postgresql/major-version-upgrade/" data-link-title="PostgreSQL major version upgrade (14 → 17)：為什麼這篇不套 5 type migration" data-link-desc="PostgreSQL major version upgrade 是 *5 type 漏類* 的實證 — source/target 同 vendor、5 維度都 Low 但 *upgrade-specific audit* 是核心；本文結構接近 deep article methodology 的 6-section &#43; 額外 upgrade audit 段；涵蓋 pg_upgrade / logical replication / blue-green 三方法、extension 相容性、5 production 踩雷">PostgreSQL major version upgrade</a>（另一個 5 type 漏類驗證）</li>
<li>Methodology：<a href="/blog/posts/vendor-%E6%B7%B1%E5%BA%A6%E6%8A%80%E8%A1%93%E6%96%87%E7%AB%A0%E6%96%B9%E6%B3%95%E8%AB%96%E7%9A%84%E6%BC%94%E5%8C%96%E7%B4%80%E9%8C%84%E5%90%8C-vendor-%E7%B3%BB%E5%88%97%E7%9A%84%E9%96%8B%E5%A0%B4%E8%BC%AA%E6%9B%BF%E9%A9%97%E8%AD%89/" data-link-title="Vendor 深度技術文章方法論的演化紀錄：同 vendor 系列的開場輪替驗證" data-link-desc="vendor overview 飽和後要寫單一功能深度文章、需要選題與結構依據時回來。這套方法論的驗證來源與 cadence variant 在高風險場景（同 vendor sub-tool 系列）的實證。">Vendor 深度技術文章的寫作方法論</a> / <a href="/blog/posts/migration-playbook-%E6%96%B9%E6%B3%95%E8%AB%96%E7%9A%84%E6%BC%94%E5%8C%96%E7%B4%80%E9%8C%84stage-0-variant-%E8%A6%8F%E5%8A%83%E6%8A%8A-collapse-%E7%8E%87%E5%BE%9E-60-%E9%99%8D%E5%88%B0-0/" data-link-title="Migration Playbook 方法論的演化紀錄：Stage 0 variant 規劃把 collapse 率從 60% 降到 0%" data-link-desc="跨 vendor migration playbook 需要獨立寫作方法論的依據，以及這套方法論從三輪 batch dogfood 中演化出來的驗證證據。">Migration playbook methodology</a>（本文驗證 <em>容量重劃漏類</em>）</li>
</ul>
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