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Sentinel: Ingest Path and Log Schema Explained

Sentinel separates measurements from control events, uses message timestamps in its deduplication key, and preserves descriptor versions and native values—with explicit limits on reprocessing.
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Sentinel’s design separates incoming measurements from state-changing control events, then stores observations with versioned point descriptors so historical data can be interpreted and, within limits, reprocessed. Its ingest path is described as thirteen stages, but the available article excerpt does not name every stage; the details below focus on the documented schema choices and their consequences.

How Sentinel organizes its logs

Glitched Pixel’s September 2026 architecture article describes two linked activity records. The observation log holds incoming measurements. A separate control-event log records actions that change system state. The article describes the observation store as one hypertable per retention class, grouping observations according to the design’s retention categories.

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The article summarizes the route from message bus to database as a thirteen-stage ingest pipeline (Glitched Pixel, 2026), but the surfaced description does not enumerate all stage names or their complete ordering rules. It also gives four thousand points as an approximate design-scale example, not as a measured capacity or performance result (Glitched Pixel, 2026).

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Where ingested_at comes from

In this design, ingested_at is taken from the JetStream message timestamp, rather than assigned with processing-time now(). Glitched Pixel’s rationale is tied to its Timescale schema: the unique index must include the partitioning column, so the deduplication key includes ingested_at alongside driver instance, source epoch, and source sequence.

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If the timestamp were generated when a message was processed, a redelivery after a crash could receive a different value and avoid the intended uniqueness check. The article says the bus timestamp remains stable across redelivery, which is what makes it useful for this design’s key. This is the article’s mechanism and assumption, not a universal guarantee for every stream topology.

The rationale also assumes one observation stream assigns timestamps in stream order. If observations arrive through multiple streams, the monotonicity property is weaker, and the design decision should be reconsidered rather than applied unchanged.

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How registry versions preserve historical meaning

The registry is versioned data loaded from Git into PostgreSQL. Each load creates a registry version, while a hash identifies canonicalized descriptor content. A point descriptor links a registry version and point identifier to the relevant descriptor hash.

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This arrangement lets historical observations be interpreted against the descriptor set associated with them, or another available version. Because descriptor content is addressed by hash, a historical point description remains identifiable even as later registry versions are loaded. These are properties claimed by Glitched Pixel’s design article, not independently audited production behavior.

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Why observations keep both native and canonical values

The schema retains the device-native value and unit as well as the converted canonical value. In the article’s illustrative example, a device reports 71.6 degrees Fahrenheit; the canonical column stores 22.0 degrees Celsius while preserving the original number and unit.

Keeping both representations makes conversion correction possible. If a descriptor’s scale factor later proves wrong, the system can recompute canonical values from the retained native readings using a corrected registry version. The Fahrenheit example explains the design; it is not a reported test result.

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What reprocessing does—and does not do

According to the article, reprocessing rebuilds current state for affected points and refreshes aggregates. It is constrained by the data that remains available and by the operation’s all-or-nothing reachability check.

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  • It can only process observation rows that still exist.
  • If a request cannot reach all of the required rows, the operation is refused rather than partially applied.
  • Rules that fired on the earlier values are not rerun.

As a result, reprocessing is not a complete rewind of every downstream decision. Rebuilding current state and refreshing aggregates does not replay rules that already acted on prior values.

What this article does not specify

Glitched Pixel assigns retention policy and compaction, bounded cold-start rehydration, core runtime capacity and outage/backlog behavior, and principal/security definitions to companion documents. The ingest-path description should not be treated as a specification for those areas.

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