Logs Streams

### Value proposition:

Observability, security, and platform engineers need a simple, consistent, and scalable way to manage their log data. Today, this often requires manually configuring and maintaining complex index templates, ingest pipelines, and retention policies across many disparate data sources, which is error-prone and time-consuming.

Logs Streams provide an opinionated, managed, and hierarchical system for all logs. This allows users to easily organize data (e.g., `logs` $\to$ `logs.production` $\to$ `logs.production.api`), with settings like processing, schema, and retention being automatically inherited by sub-streams. This dramatically simplifies configuration, ensures consistency, and provides a single, queryable entity for all your log data.

### Expected behaviors:

* **Hierarchical Organization:** Organize all logs under a single, high-level `logs` stream and create "Ingest Sub Streams" (e.g., `logs.production.api`) to partition data.
* **Setting Inheritance:** Define ingest processing, mappings, and retention policies on a parent stream (e.g., `logs.production`), and all its sub-streams will automatically inherit these settings.
* **Automatic Normalization:** Incoming log data is automatically processed and normalized to an OTel-like shape, ensuring consistent field names and types out-of-the-box.
* **Centralized Management:** Manage the full lifecycle of your logs. From ingest processing to schema and retention, in one place.