Alerting: Add compressed periodic save for alert instances (#111803)

What is this feature?

This PR implements compressed periodic save for alert state storage, providing a more efficient alternative to regular periodic saves by grouping alert instances by rule UID and storing them using protobuf and snappy compression. When enabled via the state_compressed_periodic_save_enabled configuration option, the system groups alert instances by their alert rule, compresses each group using protobuf serialization and snappy compression, and processes all rules within a single database transaction at specified intervals instead of syncing after every alert evaluation cycle.

Why do we need this feature?

During discussions in PR #111357, we identified the need for a compressed approach to periodic alert state storage that could further reduce database load beyond the jitter mechanism. While the jitter feature distributes database operations over time, this compressed periodic save approach reduces the frequency of database operations by batching alert state updates at explicitly declared intervals rather than syncing after every alert evaluation cycle.
This approach provides several key benefits:

- Reduced Database Frequency: Instead of frequent sync operations tied to alert evaluation cycles, updates occur only at configured intervals
- Storage Efficiency: Rule-based grouping with protobuf and snappy compression significantly reduces storage requirements

The compressed periodic save complements the existing jitter mechanism by providing an alternative strategy focused on reducing overall database interaction frequency while maintaining data integrity through compression and batching.

Who is this feature for?

- Platform/Infrastructure teams managing large-scale Grafana deployments with high alert cardinality
- Organizations looking to optimize storage costs and database performance for alerting workloads
- Production environments with 1000+ alert rules where database write frequency is a concern

docs/sources/alerting/set-up/performance-limitations/index.md

@@ -68,7 +68,21 @@ You can change this behavior by disabling the `alertingSaveStateCompressed` feat
 
 You can also reduce database load by writing states periodically instead of after every evaluation.
 
-To save state periodically:
+There are two approaches for periodic state saving:
+
+#### Compressed periodic saves
+
+You can combine compressed alert state storage with periodic saves by enabling both `alertingSaveStateCompressed` and `alertingSaveStatePeriodic` feature toggles together.
+
+This approach groups all alert instances by rule UID and compresses them together for efficient storage.
+
+When both feature toggles are enabled, Grafana will save compressed alert states at the interval specified by `state_periodic_save_interval`. Note that in compressed mode, the `state_periodic_save_batch_size` setting is ignored as the system groups instances by rule UID rather than by batch size.
+
+#### Batch-based periodic saves
+
+Alternatively, you can use batch-based periodic saves without compression:
+
+This approach processes individual alert instances in batches of a specified size.
 
 1. Enable the `alertingSaveStatePeriodic` feature toggle.
 1. Disable the `alertingSaveStateCompressed` feature toggle.
@@ -77,7 +91,7 @@ By default, it saves the states every 5 minutes to the database and on each shut
 can also be configured using the `state_periodic_save_interval` configuration flag. During this process, Grafana deletes all existing alert instances from the database and then writes the entire current set of instances back in batches in a single transaction.
 Configure the size of each batch using the `state_periodic_save_batch_size` configuration option.
 
-#### Jitter for periodic saves
+##### Jitter for batch-based periodic saves
 
 To further distribute database load, you can enable jitter for periodic state saves by setting `state_periodic_save_jitter_enabled = true`. When jitter is enabled, instead of saving all batches simultaneously, Grafana spreads the batch writes across a calculated time window of 85% of the save interval.