索引生命周期管理（ILM）
掌握 Index Lifecycle Management，自动化执行索引滚动更新、冷热架构和数据保留，让日志索引保持高性能并控制存储使用。
索引生命周期管理（ILM） 是 CoddyKit 上的免费 System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) 课时。 这是第 4 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) 课程共包含 4 节课。
本课时的部分内容尚未翻译，以英文显示。
Why Manage Index Lifecycle?
Time-series data like logs grows endlessly. Index Lifecycle Management (ILM) automates moving, shrinking, and deleting indices so old data does not crush your cluster.
Rollover
Rollover creates a new index when the current one hits a size, age, or document count threshold. Writes always go to a single alias.
rollover:
max_size: 50gb
max_age: 1d
max_docs: 100000000Write Aliases
Apps write to an alias such as logs-write. ILM swaps which physical index the alias points to on rollover, invisible to the writer.
POST logs-write/_doc
{ "message": "..." }The Phases
ILM defines lifecycle phases a data ages through.
- Hot: actively written and queried
- Warm: read-only, queried less
- Cold: rarely queried, cheap storage
- Delete: removed
Hot Phase
The hot phase lives on the fastest nodes with the most resources, handling all writes and recent queries.
phases:
hot:
actions:
rollover: { max_age: 1d }Warm Phase
In warm, indices become read-only and may move to cheaper nodes. You can shrink shards and force-merge segments to save space.
warm:
min_age: 7d
actions:
forcemerge: { max_num_segments: 1 }
shrink: { number_of_shards: 1 }Cold and Frozen
Cold data moves to the cheapest disks; frozen can be searched directly from object storage. Both trade query speed for cost.
cold:
min_age: 30d
actions:
allocate: { require: { data: cold } }Delete Phase
The delete phase enforces retention by removing indices past a chosen age, the simplest way to cap storage growth.
delete:
min_age: 90d
actions:
delete: {}Attaching a Policy
An index template binds new indices to an ILM policy and the write alias automatically.
PUT _index_template/logs
{ "template": { "settings": {
"index.lifecycle.name": "logs-policy" } } }Node Roles
Hot-warm-cold relies on node attributes so allocation actions can route shards to the right hardware tier.
node.attr.data: hot # on fast nodes
node.attr.data: cold # on cheap nodesPutting It Together
A typical logging policy: roll over daily in hot, move to warm and force-merge after a week, go cold after a month, and delete after ninety days.
Quick Check
Pick the phase that enforces retention.
Recap
You learned how ILM automates index management: rollover starts fresh indices behind a write alias, and the hot-warm-cold-delete phases move data to cheaper tiers as it ages and finally remove it. Index templates bind policies automatically, keeping clusters fast and storage bounded.
常见问题解答
「索引生命周期管理（ILM）」课时是免费的吗？
是的 — 「索引生命周期管理（ILM）」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) 课程的其余内容，请升级到 CoddyKit PRO。 System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) 课程共包含 4 节课。
「索引生命周期管理（ILM）」这节课中我会学到什么？
掌握 Index Lifecycle Management，自动化执行索引滚动更新、冷热架构和数据保留，让日志索引保持高性能并控制存储使用。 你通过在浏览器中直接运行的动手代码来练习 System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry)，全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) 需要有经验吗？
无需任何先前经验。CoddyKit 上的 System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 4 节课，共 4 节。
「索引生命周期管理（ILM）」课时需要多长时间？
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。
我能在这节 System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) 课中编写并运行代码吗？
能。每节 System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。