Doc updates

src/concepts/history.md

@@ -136,8 +136,7 @@ documentation.
 
 ## Firefox Desktop Telemetry: The Next Generation
 
-The next step for Firefox Desktop Telemetry is to prototype an implementation
-using [Glean](glean/glean.md).
-
-This effort is known as "Firefox on Glean" or FOG. This effort is expected to
-begin in late 2019 / early 2020.
+The next step for Firefox Desktop Telemetry was to reimplement it on top of
+[Glean](glean/glean.md). That effort, known as "Firefox on Glean" or FOG, began in
+late 2019 / early 2020 and has since shipped — Glean is now the standard instrumentation
+path for Firefox Desktop, and legacy Telemetry is being wound down rather than extended.

src/concepts/pipeline/data_pipeline_detail.md

@@ -1,5 +1,15 @@
 # A Detailed Look at the Data Platform
 
+> **Status: describes the legacy AWS-era platform.** Much of the architecture below —
+> Redshift, the Heka and Parquet data lakes, Hindsight streaming, Landfill — has been
+> decommissioned and replaced by the GCP pipeline that lands data in BigQuery. Treat this
+> page as historical background on how the platform was structured, not as a description
+> of how data flows today. For the current pipeline see the
+> [Pipeline Overview](data_pipeline.md).
+>
+> <!-- This banner is a stopgap: the page needs either a rewrite against the current
+> GCP architecture or an explicit move under an archive/ section. -->
+
 For a more gentle introduction to the data platform, please read the [Pipeline Overview](data_pipeline.md) article.
 
 This article goes into more depth about the architecture and flow of data in the platform.

src/datasets/obsolete/activity-stream/reference.md

@@ -1,5 +1,8 @@
 # Activity Stream Datasets
 
+> This dataset is obsolete and is no longer maintained. It is kept for historical
+> reference; do not use it for new analyses.
+
 This article describes the various BigQuery tables Mozilla uses to store Activity Stream data, along with some examples of how to access them.
 
 ## Table of Contents

src/datasets/search/search_revenue_levers/reference.md

@@ -21,13 +21,18 @@ In practice, Mozillians focused on search-only analyses may prefer the other exi
 
 The differences between the aggregation structures are summarized as follows:
 
-| Column Name     | `search_revenue_levers_daily`  | `search_revenue_levers_monthly` |
-| --------------- | ------------------------------ | ------------------------------- |
-| device          | `desktop`, `mobile`            | `desktop`, `mobile`             |
-| partner         | `Google`, `Bing`, `DuckDuckGo` | `Google`, `Bing`, `DuckDuckGo`  |
-| channel         | `NULL`, `personal`, `ESR`      | column does not exist           |
-| country         | `US`, `DE`, `FR`, ...          | All partners: `US`, `ROW`       |
-| submission_date | minimum aggregation: daily     | minimum aggregation: monthly    |
+Note that the two tables do not use the same column names for the search partner or for
+the aggregation date — `search_revenue_levers_monthly` uses `partner_name` and
+`submission_month`, so a query written against the daily table will not run unchanged
+against the monthly one.
+
+| Concept          | `search_revenue_levers_daily`                    | `search_revenue_levers_monthly`                     |
+| ---------------- | ------------------------------------------------ | --------------------------------------------------- |
+| device           | `device`: `desktop`, `mobile`                     | `device`: `desktop`, `mobile`                        |
+| search partner   | `partner`: `Google`, `Bing`, `DuckDuckGo`         | `partner_name`: `Google`, `Bing`, `DuckDuckGo`       |
+| channel          | `channel`: `NULL`, `personal`, `ESR`              | column does not exist                                |
+| country          | `country`: `US`, `DE`, `FR`, ...                  | `country`: all partners `US`, `ROW`                  |
+| aggregation date | `submission_date`: minimum aggregation daily      | `submission_month`: minimum aggregation monthly      |
 
 There are 14 possible revenue levers measures available: