feat(metrics): create the metrics kafka ingest chain via migration by jzhu13 · Pull Request #89631 · PostHog/posthog

jzhu13 · 2026-08-26T18:14:11Z

Problem

OTLP metrics sent to a dev or multinode stack never reached the Metrics product — they stopped at the clickhouse_metrics Kafka topic because no ClickHouse consumer table existed outside the cloud logs cluster. Anyone developing against Metrics locally saw only hand-seeded rows.

The metrics ingest objects (kafka_metrics_avro + its materialized views) were provisioned only via the cloud HCL layer. And metrics1 (the raw table those views write to) had no creating migration at all — cloud provisions it out of band, dev laptops via the schema-sync path — so it is absent wherever only migrations run (the multinode CI smoke, a from-migrations dev stack).

Before

flowchart LR
    A[otel collector / capture-logs] --> B[(metrics_ingestion)]
    B --> C[ingestion-metrics consumer]
    C --> D[(clickhouse_metrics)]
    D -.->|no consumer table| X[nothing]
    classDef phBlue fill:#1d4aff,stroke:#1d4aff,color:#fff;
    classDef phGray fill:#e5e7eb,stroke:#c7ccd1,color:#000;
    classDef phRed fill:#f54e00,stroke:#f54e00,color:#fff;
    class A,C phBlue;
    class B,D phGray;
    class X phRed;

After

flowchart LR
    A[otel collector / capture-logs] --> B[(metrics_ingestion)]
    B --> C[ingestion-metrics consumer]
    C --> D[(clickhouse_metrics)]
    D --> E[kafka_metrics_avro]
    E --> F[(metrics1 / metric_samples1 / metric_series1 / metrics_kafka_metrics)]
    classDef phBlue fill:#1d4aff,stroke:#1d4aff,color:#fff;
    classDef phGray fill:#e5e7eb,stroke:#c7ccd1,color:#000;
    classDef phYellow fill:#f9bd2b,stroke:#f9bd2b,color:#000;
    class A,C,E phBlue;
    class B,D phGray;
    class F phYellow;

Changes

OTLP metrics sent to a dev stack now land in ClickHouse and show in the Metrics UI (chart, samples, and trace-exemplar dots) after migrate_clickhouse, instead of only hand-seeded data.
Migration 0305_metrics_kafka_ingest creates the ingest chain on NodeRole.LOGS: metrics1 + its distributed reader, metrics_kafka_metrics, kafka_metrics_avro, and the four materialized views. All IF NOT EXISTS, so it is a no-op where the objects already exist (cloud, seeded laptops).
Creating metrics1 in a migration closes the gap that made the multinode smoke fail — 0283 created metric_samples1/metric_series1 this way but omitted metrics1.
The ingest objects are now modeled in an all-env HCL layer (roles/logs/metrics, moved out of the cloud-only roles/logs/{shared,cloud}), composed by every logs env including local-multi and local-single. The convergence gate therefore checks the migration-created objects instead of excluding them, so a future migration that drifts from the HCL fails the smoke.
The layer declares the local shape (noshard ZK paths, posthog_single_shard reader). The cloud envs restore their logs-cluster paths via patches in roles/logs/shared, the same way metric_samples/metric_series are modeled. The cloud logs goldens are byte-identical before and after the move.
Local mirrors prod's value/count codecs on metrics1 via patches in roles/logs/local; the other explicit codecs are stripped from the Django SQL, so the created tables converge with the codec-free base declaration (dev stays codec-free by design, and ZSTD(1) is the server default).
New posthog/clickhouse/metrics/kafka_metrics.py holds the SQL, matching the HCL definitions.
The hand-run bin/clickhouse-metrics.sql init script (and its hogli clickhouse:metrics:init command) is deleted — metrics was the last product provisioning ClickHouse objects that way; the migration replaces it. 0305 therefore also creates metric_attributes and its two feeder views, which only the script covered before.
Mechanical: warpstream_metrics named collection added to the dev and multinode ClickHouse configs so the Kafka table resolves its broker list; schema snapshot regenerated for the codec change.

How did you test this code?

Offline HCL guard (bash posthog/clickhouse/hcl/check.sh) passes: duplicates baseline unchanged, all envs validate, no golden drift, generated SQL fresh.
The regenerated dev/prod-us/prod-eu logs goldens are byte-identical to the committed ones, so the layer move changes nothing on cloud.
pytest posthog/clickhouse/test/test_schema.py passes (370 tests) after the codec change.
Applied the same object definitions to a running dev stack earlier: the clickhouse-metrics-avro consumer group went Dead → Stable and drained the backlog into metrics1/metric_samples1/metric_series1, with exemplar trace ids resolving against trace_spans.
Not run locally (no full multinode stack in the working clone): the multinode migration smoke — CI is the authority for live convergence of the migration-created objects against the new local goldens.

Automatic notifications

Publish to changelog?

Docs update

None — dev-environment schema only. posthog/clickhouse/hcl/README.md updated for the layer move.

🤖 Agent context

Autonomy: Human-driven (agent-assisted)

Authored with PostHog Code (Claude). Skills invoked: /clickhouse-migrations, /writing-pr-descriptions.
First attempt modeled the ingest objects in a new all-env HCL layer; CI surfaced two blockers — the multinode smoke failed because metrics1 is created by no migration, and the HCL guard rejected the layer (duplicate declarations vs the cloud shared/cloud layers, plus metrics1 referenced but undeclared in the local compositions).
An intermediate revision fixed the runtime bug via migration but excluded the objects from the local convergence gate. Review feedback asked for extending the HCL instead of excluding, so this revision moves the declarations into an all-env layer with per-env patches — the exclusions are gone.

Created with PostHog Code

trunk-io · 2026-08-26T18:14:15Z

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github-actions · 2026-08-26T18:18:12Z

🤖 CI report

🚨 Trunk lane — universal lane

This PR is assigned to the universal lane. It cannot merge in parallel with other PRs, so it can take longer to merge. Ask dev-ex if you think this is wrong.

✅ Bundle size — no change

Uncompressed size of every built .js bundle, compared against the base branch.

Total: 68.04 MiB · no change

No file changed by more than 1000 B.

_{Posted automatically by build-bundle-size-report · uncompressed bytes from dist-report}

✅ Eager graph — within budget

How much code each root ships on the eager path — downloaded and parsed before the surface is interactive. Measured from the esbuild output chunks (post-tree-shake, static imports only); lazy import() / React.lazy chunks are not counted.

Root	Eager (shipped)	Δ vs base	Budget
entry (logged-out pages, app bootstrap) `src/index.tsx`	1.37 MiB · 22 files	no change	`███░░░░░░░` 30.3% of 4.51 MiB
authenticated shell (every logged-in page) `src/scenes/AuthenticatedShell.tsx`	8.81 MiB · 3,245 files	no change	`█████████░` 90.7% of 9.71 MiB

🟢 node_modules/monaco-editor/ stays out of src/index.tsx
🟢 src/lib/components/ActivityLog/describers stays out of src/index.tsx
🟢 [object Object] stays out of src/index.tsx
🟢 [object Object] stays out of src/index.tsx
🟢 node_modules/monaco-editor/ stays out of src/scenes/AuthenticatedShell.tsx
🟢 src/lib/components/ActivityLog/describers stays out of src/scenes/AuthenticatedShell.tsx
🟢 [object Object] stays out of src/scenes/AuthenticatedShell.tsx
🟢 [object Object] stays out of src/scenes/AuthenticatedShell.tsx

Largest files eagerly shipped from src/index.tsx

Size	File
126.8 KiB	`../node_modules/.pnpm/react-dom@18.3.1_react@18.3.1/node_modules/react-dom/cjs/react-dom.production.min.js`
24.6 KiB	`../node_modules/.pnpm/buffer@6.0.3/node_modules/buffer/index.js`
6.3 KiB	`../node_modules/.pnpm/react@18.3.1/node_modules/react/cjs/react.production.min.js`
4.5 KiB	`../node_modules/.pnpm/@jspm+core@2.1.0/node_modules/@jspm/core/nodelibs/browser/process.js`
3.9 KiB	`../node_modules/.pnpm/scheduler@0.23.2/node_modules/scheduler/cjs/scheduler.production.min.js`
1.4 KiB	`../node_modules/.pnpm/base64-js@1.5.1/node_modules/base64-js/index.js`
1.3 KiB	`src/RootErrorBoundary.tsx`
912 B	`../node_modules/.pnpm/ieee754@1.2.1/node_modules/ieee754/index.js`
789 B	`src/scenes/ChunkLoadErrorBoundary.tsx`
762 B	`src/index.tsx`

Largest files eagerly shipped from src/scenes/AuthenticatedShell.tsx

Size	File
306.9 KiB	`../node_modules/.pnpm/posthog-js@1.420.0_@types+react@18.3.27_react@18.3.1/node_modules/posthog-js/dist/rrweb.js`
267.7 KiB	`../node_modules/.pnpm/@posthog+icons@0.38.0_react-dom@18.3.1_react@18.3.1__react@18.3.1/node_modules/@posthog/icons/dist/posthog-icons.es.js`
260.9 KiB	`../node_modules/.pnpm/posthog-js@1.420.0_@types+react@18.3.27_react@18.3.1/node_modules/posthog-js/dist/module.js`
252.5 KiB	`src/taxonomy/core-filter-definitions-by-group.json`
154.2 KiB	`../node_modules/.pnpm/re2js@0.4.1/node_modules/re2js/build/index.esm.js`
126.8 KiB	`../node_modules/.pnpm/react-dom@18.3.1_react@18.3.1/node_modules/react-dom/cjs/react-dom.production.min.js`
104.7 KiB	`src/lib/api.ts`
95.2 KiB	`../packages/quill/packages/quill/dist/index.js`
93.3 KiB	`../node_modules/.pnpm/prosemirror-view@1.40.1/node_modules/prosemirror-view/dist/index.js`
90.6 KiB	`../node_modules/.pnpm/@tiptap+core@3.20.6_@tiptap+pm@3.20.6/node_modules/@tiptap/core/dist/index.js`

_{Posted automatically by check-eager-graph · sizes are eager output bytes (shipped, post-tree-shake) from the esbuild metafile · part of #32479}

✅ Toolbar bundle — eager 2.25 MiB within budget

What the toolbar ships to customer pages, measured from the esbuild output (minified, post-tree-shake). The eager set is the entry plus everything statically imported from it — fetched before any feature runs; deferred chunks load lazily. The eager guardrail is 5.72 MiB. Each output file must also stay below 10 MB, where CloudFront stops compressing it. The module boundary is enforced separately by check-toolbar-graph.

Metric	Size	Δ vs base	Budget
Eager (shipped) entry + static imports	2.25 MiB · 18 files	no change	`████░░░░░░` 39.4% of 5.72 MiB
Deferred (lazy)	2.11 MiB · 45 files	no change	n/a — loads on demand
Loader `dist/toolbar.js`	1.1 KiB	no change	`█░░░░░░░░░` 5.8% of 19.5 KiB

Largest eagerly-shipped chunks

Size	File
748.8 KiB	`dist/toolbar/toolbar-app-XYGAYFW6.css`
585.4 KiB	`dist/toolbar/chunk-chunk-WAAZXMI4.js`
484.7 KiB	`dist/toolbar/chunk-chunk-QMGLBVDO.js`
133.8 KiB	`dist/toolbar/chunk-chunk-WIGPXHXA.js`
131.8 KiB	`dist/toolbar/chunk-chunk-FDH2IBXT.js`
71.3 KiB	`dist/toolbar/toolbar-app-IO2JX2X2.js`
69.0 KiB	`dist/toolbar/chunk-chunk-TSAL54PB.js`
35.6 KiB	`dist/toolbar/chunk-chunk-ENVYWGUI.js`
20.9 KiB	`dist/toolbar/chunk-chunk-HEUIHINI.js`
6.8 KiB	`dist/toolbar/chunk-chunk-DV7IWQNF.js`

_{Posted automatically by check-toolbar-size · sizes are toolbar output bytes (shipped, post-tree-shake) from the esbuild metafile}

✅ Dist folder size — no change

Total size of the built frontend/dist folder (all assets), compared against the base branch.

Total: 1449.72 MiB · no change

✅ Playwright — all passed

All tests passed.

View test results →

ℹ️ ClickHouse migration SQL — 2 migration(s)

ClickHouse migration SQL per cloud environment

unset

all

ALTER TABLE posthog_test.metric_series1
    ADD COLUMN IF NOT EXISTS `aggregation_temporality` LowCardinality(String) AFTER unit,
    ADD COLUMN IF NOT EXISTS `is_monotonic` Bool DEFAULT false AFTER aggregation_temporality

ALTER TABLE posthog_test.metric_series1
    MODIFY TTL toDateTime(last_seen) + INTERVAL 90 DAY DELETE

ALTER TABLE posthog_test.metric_samples1
    ADD COLUMN IF NOT EXISTS `count` UInt64 DEFAULT 1 AFTER value,
    ADD COLUMN IF NOT EXISTS `histogram_bounds` Array(Float64) AFTER count,
    ADD COLUMN IF NOT EXISTS `histogram_counts` Array(UInt64) AFTER histogram_bounds

ALTER TABLE posthog_test.metric_series
    ADD COLUMN IF NOT EXISTS `aggregation_temporality` LowCardinality(String) AFTER unit,
    ADD COLUMN IF NOT EXISTS `is_monotonic` Bool DEFAULT false AFTER aggregation_temporality

ALTER TABLE posthog_test.metric_samples
    ADD COLUMN IF NOT EXISTS `count` UInt64 DEFAULT 1 AFTER value,
    ADD COLUMN IF NOT EXISTS `histogram_bounds` Array(Float64) AFTER count,
    ADD COLUMN IF NOT EXISTS `histogram_counts` Array(UInt64) AFTER histogram_bounds

CREATE TABLE IF NOT EXISTS posthog_test.metrics1
(
    `time_bucket` DateTime MATERIALIZED toStartOfDay(timestamp),
    `uuid` String,
    `team_id` Int32,
    `trace_id` String,
    `span_id` String,
    `trace_flags` Int32,
    `timestamp` DateTime64(6),
    `observed_timestamp` DateTime64(6),
    `created_at` DateTime64(6) MATERIALIZED now(),
    `service_name` LowCardinality(String),
    `metric_name` LowCardinality(String),
    `metric_type` LowCardinality(String),
    `value` Float64 CODEC(Gorilla),
    `count` UInt64 DEFAULT 1 CODEC(T64),
    `histogram_bounds` Array(Float64),
    `histogram_counts` Array(UInt64),
    `unit` LowCardinality(String),
    `aggregation_temporality` LowCardinality(String),
    `is_monotonic` Bool DEFAULT false,
    `resource_attributes` Map(LowCardinality(String), String),
    `resource_fingerprint` UInt64 MATERIALIZED cityHash64(resource_attributes),
    `instrumentation_scope` String,
    `attributes_map_str` Map(LowCardinality(String), String),
    `attributes_map_float` Map(LowCardinality(String), Float64),
    `time_minute` DateTime ALIAS toStartOfMinute(timestamp),
    `attributes` Map(String, String) ALIAS mapApply((k, v) -> (left(k, -5), v), attributes_map_str),
    INDEX idx_metric_name_set metric_name TYPE set(100) GRANULARITY 1,
    INDEX idx_metric_type_set metric_type TYPE set(10) GRANULARITY 1,
    INDEX idx_attributes_str_keys mapKeys(attributes_map_str) TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_attributes_str_values mapValues(attributes_map_str) TYPE bloom_filter(0.001) GRANULARITY 1,
    INDEX idx_observed_minmax observed_timestamp TYPE minmax GRANULARITY 1,
    PROJECTION projection_aggregate_counts
    (
        SELECT
            team_id,
            time_bucket,
            toStartOfMinute(timestamp),
            service_name,
            metric_name,
            metric_type,
            resource_fingerprint,
            count() AS event_count,
            sum(value) AS total_value,
            min(value) AS min_value,
            max(value) AS max_value
        GROUP BY
            team_id,
            time_bucket,
            toStartOfMinute(timestamp),
            service_name,
            metric_name,
            metric_type,
            resource_fingerprint
    )
)
ENGINE = ReplicatedMergeTree('/clickhouse/tables/noshard/posthog.metrics1', '{replica}-{shard}')
PARTITION BY toDate(timestamp)
PRIMARY KEY (team_id, time_bucket, service_name, metric_name, resource_fingerprint, timestamp)
ORDER BY (team_id, time_bucket, service_name, metric_name, resource_fingerprint, timestamp)
SETTINGS
    index_granularity_bytes = 104857600,
    index_granularity = 8192,
    ttl_only_drop_parts = 1

CREATE TABLE IF NOT EXISTS posthog_test.metrics AS posthog_test.metrics1 ENGINE = Distributed('posthog_single_shard', 'posthog_test', 'metrics1')

CREATE TABLE IF NOT EXISTS posthog_test.metric_attributes
(
    `team_id` Int32,
    `time_bucket` DateTime64(0),
    `service_name` LowCardinality(String),
    `resource_fingerprint` UInt64 DEFAULT 0,
    `attribute_key` LowCardinality(String),
    `attribute_value` String,
    `attribute_count` SimpleAggregateFunction(sum, UInt64),
    `attribute_type` LowCardinality(String),
    INDEX idx_attribute_key attribute_key TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_attribute_value attribute_value TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_attribute_key_n3 attribute_key TYPE ngrambf_v1(3, 32768, 3, 0) GRANULARITY 1,
    INDEX idx_attribute_value_n3 attribute_value TYPE ngrambf_v1(3, 32768, 3, 0) GRANULARITY 1
)
ENGINE = ReplicatedAggregatingMergeTree('/clickhouse/tables/noshard/posthog.metric_attributes', '{replica}-{shard}')
PARTITION BY toDate(time_bucket)
ORDER BY (team_id, attribute_type, time_bucket, resource_fingerprint, attribute_key, attribute_value)
SETTINGS
    deduplicate_merge_projection_mode = 'drop',
    index_granularity = 8192

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.metrics1_to_metric_attributes TO posthog_test.metric_attributes
(
    `team_id` Int32,
    `time_bucket` DateTime64(0),
    `service_name` LowCardinality(String),
    `resource_fingerprint` UInt64,
    `attribute_key` LowCardinality(String),
    `attribute_value` String,
    `attribute_type` LowCardinality(String),
    `attribute_count` SimpleAggregateFunction(sum, UInt64)
)
AS SELECT
    team_id,
    time_bucket,
    service_name,
    resource_fingerprint,
    attribute_key,
    attribute_value,
    attribute_type,
    attribute_count
FROM
(
    SELECT
        team_id AS team_id,
        toStartOfInterval(timestamp, toIntervalMinute(10)) AS time_bucket,
        service_name AS service_name,
        resource_fingerprint,
        mapFilter((k, v) -> ((length(k) < 256) AND (length(v) < 256)), attributes) AS attributes,
        arrayJoin(attributes) AS attribute,
        'metric' AS attribute_type,
        attribute.1 AS attribute_key,
        attribute.2 AS attribute_value,
        sumSimpleState(1) AS attribute_count
    FROM posthog_test.metrics1
    GROUP BY
        team_id,
        time_bucket,
        service_name,
        resource_fingerprint,
        attributes
)

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.metrics1_to_resource_attributes TO posthog_test.metric_attributes
(
    `team_id` Int32,
    `time_bucket` DateTime64(0),
    `service_name` LowCardinality(String),
    `resource_fingerprint` UInt64,
    `attribute_key` LowCardinality(String),
    `attribute_value` String,
    `attribute_type` LowCardinality(String),
    `attribute_count` SimpleAggregateFunction(sum, UInt64)
)
AS SELECT
    team_id,
    time_bucket,
    service_name,
    resource_fingerprint,
    attribute_key,
    attribute_value,
    attribute_type,
    attribute_count
FROM
(
    SELECT
        team_id AS team_id,
        toStartOfInterval(timestamp, toIntervalMinute(10)) AS time_bucket,
        service_name AS service_name,
        resource_fingerprint,
        arrayJoin(resource_attributes) AS attribute,
        'resource' AS attribute_type,
        attribute.1 AS attribute_key,
        attribute.2 AS attribute_value,
        sumSimpleState(1) AS attribute_count
    FROM posthog_test.metrics1
    GROUP BY
        team_id,
        time_bucket,
        service_name,
        resource_fingerprint,
        resource_attributes
)

CREATE TABLE IF NOT EXISTS posthog_test.metrics_kafka_metrics
(
    `_partition` UInt32,
    `_topic` String,
    `max_offset` SimpleAggregateFunction(max, UInt64),
    `max_observed_timestamp` SimpleAggregateFunction(max, DateTime64(9)),
    `max_timestamp` SimpleAggregateFunction(max, DateTime64(9)),
    `max_created_at` SimpleAggregateFunction(max, DateTime64(9)),
    `max_lag` SimpleAggregateFunction(max, UInt64)
)
ENGINE = ReplicatedAggregatingMergeTree('/clickhouse/tables/noshard/posthog.metrics_kafka_metrics', '{replica}-{shard}')
ORDER BY (_topic, _partition)
SETTINGS
    index_granularity = 8192

CREATE TABLE IF NOT EXISTS posthog_test.kafka_metrics_avro
(
    `uuid` String,
    `trace_id` String,
    `span_id` String,
    `trace_flags` Nullable(Int32),
    `timestamp` DateTime64(6),
    `observed_timestamp` DateTime64(6),
    `service_name` Nullable(String),
    `metric_name` Nullable(String),
    `metric_type` Nullable(String),
    `value` Nullable(Float64),
    `count` Nullable(Int64),
    `histogram_bounds` Array(Float64),
    `histogram_counts` Array(Int64),
    `unit` Nullable(String),
    `aggregation_temporality` Nullable(String),
    `is_monotonic` Nullable(UInt8),
    `resource_attributes` Map(String, String),
    `instrumentation_scope` Nullable(String),
    `attributes` Map(String, String),
    `series_fingerprint` Nullable(Int64)
)
ENGINE = Kafka(warpstream_metrics, kafka_topic_list = 'clickhouse_metrics', kafka_group_name = 'clickhouse-metrics-avro-new', kafka_format = 'Avro')
SETTINGS
    kafka_skip_broken_messages = 100,
    kafka_thread_per_consumer = 1,
    kafka_num_consumers = 8,
    kafka_poll_timeout_ms = 3000,
    kafka_poll_max_batch_size = 1000

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.kafka_metrics_avro_mv TO posthog_test.metrics1
AS SELECT
    uuid,
    trace_id,
    span_id,
    ifNull(trace_flags, 0) AS trace_flags,
    timestamp,
    observed_timestamp,
    ifNull(service_name, '') AS service_name,
    ifNull(metric_name, '') AS metric_name,
    ifNull(metric_type, '') AS metric_type,
    ifNull(value, 0) AS value,
    toUInt64(ifNull(count, 1)) AS count,
    histogram_bounds,
    arrayMap(x -> toUInt64(x), histogram_counts) AS histogram_counts,
    ifNull(unit, '') AS unit,
    ifNull(aggregation_temporality, '') AS aggregation_temporality,
    ifNull(is_monotonic, 0) AS is_monotonic,
    mapSort(mapApply((k, v) -> (k, JSONExtractString(v)), resource_attributes)) AS resource_attributes,
    ifNull(instrumentation_scope, '') AS instrumentation_scope,
    mapSort(mapApply((k, v) -> (concat(k, '__str'), JSONExtractString(v)), attributes)) AS attributes_map_str,
    mapSort(mapFilter((k, v) -> isNotNull(v), mapApply((k, v) -> (concat(k, '__float'), toFloat64OrNull(JSONExtract(v, 'String'))), attributes))) AS attributes_map_float,
    toInt32OrZero(_headers.value[indexOf(_headers.name, 'team_id')]) AS team_id
FROM posthog_test.kafka_metrics_avro
SETTINGS
    min_insert_block_size_rows = 0,
    min_insert_block_size_bytes = 0

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.kafka_metrics_avro_to_metric_samples TO posthog_test.metric_samples1
AS SELECT
    toInt32OrZero(_headers.value[indexOf(_headers.name, 'team_id')]) AS team_id,
    ifNull(metric_name, '') AS metric_name,
    reinterpretAsUInt64(assumeNotNull(series_fingerprint)) AS series_fingerprint,
    timestamp,
    ifNull(value, 0) AS value,
    toUInt64(ifNull(count, 1)) AS count,
    histogram_bounds,
    arrayMap(x -> toUInt64(x), histogram_counts) AS histogram_counts,
    trace_id,
    span_id,
    ifNull(trace_flags, 0) AS trace_flags
FROM posthog_test.kafka_metrics_avro
WHERE kafka_metrics_avro.series_fingerprint IS NOT NULL
SETTINGS
    min_insert_block_size_rows = 0,
    min_insert_block_size_bytes = 0

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.kafka_metrics_avro_to_metric_series TO posthog_test.metric_series1
AS SELECT
    toInt32OrZero(_headers.value[indexOf(_headers.name, 'team_id')]) AS team_id,
    ifNull(metric_name, '') AS metric_name,
    reinterpretAsUInt64(assumeNotNull(series_fingerprint)) AS series_fingerprint,
    ifNull(metric_type, '') AS metric_type,
    ifNull(unit, '') AS unit,
    ifNull(aggregation_temporality, '') AS aggregation_temporality,
    ifNull(is_monotonic, 0) AS is_monotonic,
    ifNull(service_name, '') AS service_name,
    mapSort(mapApply((k, v) -> (k, JSONExtractString(v)), resource_attributes)) AS resource_attributes,
    mapSort(mapApply((k, v) -> (k, JSONExtractString(v)), attributes)) AS attributes,
    timestamp AS last_seen
FROM posthog_test.kafka_metrics_avro
WHERE kafka_metrics_avro.series_fingerprint IS NOT NULL
SETTINGS
    min_insert_block_size_rows = 0,
    min_insert_block_size_bytes = 0

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.kafka_metrics_avro_kafka_metrics_mv TO posthog_test.metrics_kafka_metrics
AS SELECT
    _partition,
    _topic,
    maxSimpleState(_offset) AS max_offset,
    maxSimpleState(observed_timestamp) AS max_observed_timestamp,
    maxSimpleState(timestamp) AS max_timestamp,
    maxSimpleState(now()) AS max_created_at,
    maxSimpleState(now() - observed_timestamp) AS max_lag
FROM posthog_test.kafka_metrics_avro
GROUP BY _partition, _topic

US, EU, DEV

logs

ALTER TABLE posthog_test.metric_series1
    ADD COLUMN IF NOT EXISTS `aggregation_temporality` LowCardinality(String) AFTER unit,
    ADD COLUMN IF NOT EXISTS `is_monotonic` Bool DEFAULT false AFTER aggregation_temporality

ALTER TABLE posthog_test.metric_series1
    MODIFY TTL toDateTime(last_seen) + INTERVAL 90 DAY DELETE

ALTER TABLE posthog_test.metric_samples1
    ADD COLUMN IF NOT EXISTS `count` UInt64 DEFAULT 1 AFTER value,
    ADD COLUMN IF NOT EXISTS `histogram_bounds` Array(Float64) AFTER count,
    ADD COLUMN IF NOT EXISTS `histogram_counts` Array(UInt64) AFTER histogram_bounds

ALTER TABLE posthog_test.metric_series
    ADD COLUMN IF NOT EXISTS `aggregation_temporality` LowCardinality(String) AFTER unit,
    ADD COLUMN IF NOT EXISTS `is_monotonic` Bool DEFAULT false AFTER aggregation_temporality

ALTER TABLE posthog_test.metric_samples
    ADD COLUMN IF NOT EXISTS `count` UInt64 DEFAULT 1 AFTER value,
    ADD COLUMN IF NOT EXISTS `histogram_bounds` Array(Float64) AFTER count,
    ADD COLUMN IF NOT EXISTS `histogram_counts` Array(UInt64) AFTER histogram_bounds

CREATE TABLE IF NOT EXISTS posthog_test.metrics1
(
    `time_bucket` DateTime MATERIALIZED toStartOfDay(timestamp),
    `uuid` String,
    `team_id` Int32,
    `trace_id` String,
    `span_id` String,
    `trace_flags` Int32,
    `timestamp` DateTime64(6),
    `observed_timestamp` DateTime64(6),
    `created_at` DateTime64(6) MATERIALIZED now(),
    `service_name` LowCardinality(String),
    `metric_name` LowCardinality(String),
    `metric_type` LowCardinality(String),
    `value` Float64 CODEC(Gorilla),
    `count` UInt64 DEFAULT 1 CODEC(T64),
    `histogram_bounds` Array(Float64),
    `histogram_counts` Array(UInt64),
    `unit` LowCardinality(String),
    `aggregation_temporality` LowCardinality(String),
    `is_monotonic` Bool DEFAULT false,
    `resource_attributes` Map(LowCardinality(String), String),
    `resource_fingerprint` UInt64 MATERIALIZED cityHash64(resource_attributes),
    `instrumentation_scope` String,
    `attributes_map_str` Map(LowCardinality(String), String),
    `attributes_map_float` Map(LowCardinality(String), Float64),
    `time_minute` DateTime ALIAS toStartOfMinute(timestamp),
    `attributes` Map(String, String) ALIAS mapApply((k, v) -> (left(k, -5), v), attributes_map_str),
    INDEX idx_metric_name_set metric_name TYPE set(100) GRANULARITY 1,
    INDEX idx_metric_type_set metric_type TYPE set(10) GRANULARITY 1,
    INDEX idx_attributes_str_keys mapKeys(attributes_map_str) TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_attributes_str_values mapValues(attributes_map_str) TYPE bloom_filter(0.001) GRANULARITY 1,
    INDEX idx_observed_minmax observed_timestamp TYPE minmax GRANULARITY 1,
    PROJECTION projection_aggregate_counts
    (
        SELECT
            team_id,
            time_bucket,
            toStartOfMinute(timestamp),
            service_name,
            metric_name,
            metric_type,
            resource_fingerprint,
            count() AS event_count,
            sum(value) AS total_value,
            min(value) AS min_value,
            max(value) AS max_value
        GROUP BY
            team_id,
            time_bucket,
            toStartOfMinute(timestamp),
            service_name,
            metric_name,
            metric_type,
            resource_fingerprint
    )
)
ENGINE = ReplicatedMergeTree('/clickhouse/tables/noshard/posthog.metrics1', '{replica}-{shard}')
PARTITION BY toDate(timestamp)
PRIMARY KEY (team_id, time_bucket, service_name, metric_name, resource_fingerprint, timestamp)
ORDER BY (team_id, time_bucket, service_name, metric_name, resource_fingerprint, timestamp)
SETTINGS
    index_granularity_bytes = 104857600,
    index_granularity = 8192,
    ttl_only_drop_parts = 1

CREATE TABLE IF NOT EXISTS posthog_test.metrics AS posthog_test.metrics1 ENGINE = Distributed('posthog_single_shard', 'posthog_test', 'metrics1')

CREATE TABLE IF NOT EXISTS posthog_test.metric_attributes
(
    `team_id` Int32,
    `time_bucket` DateTime64(0),
    `service_name` LowCardinality(String),
    `resource_fingerprint` UInt64 DEFAULT 0,
    `attribute_key` LowCardinality(String),
    `attribute_value` String,
    `attribute_count` SimpleAggregateFunction(sum, UInt64),
    `attribute_type` LowCardinality(String),
    INDEX idx_attribute_key attribute_key TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_attribute_value attribute_value TYPE bloom_filter(0.01) GRANULARITY 1,
    INDEX idx_attribute_key_n3 attribute_key TYPE ngrambf_v1(3, 32768, 3, 0) GRANULARITY 1,
    INDEX idx_attribute_value_n3 attribute_value TYPE ngrambf_v1(3, 32768, 3, 0) GRANULARITY 1
)
ENGINE = ReplicatedAggregatingMergeTree('/clickhouse/tables/noshard/posthog.metric_attributes', '{replica}-{shard}')
PARTITION BY toDate(time_bucket)
ORDER BY (team_id, attribute_type, time_bucket, resource_fingerprint, attribute_key, attribute_value)
SETTINGS
    deduplicate_merge_projection_mode = 'drop',
    index_granularity = 8192

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.metrics1_to_metric_attributes TO posthog_test.metric_attributes
(
    `team_id` Int32,
    `time_bucket` DateTime64(0),
    `service_name` LowCardinality(String),
    `resource_fingerprint` UInt64,
    `attribute_key` LowCardinality(String),
    `attribute_value` String,
    `attribute_type` LowCardinality(String),
    `attribute_count` SimpleAggregateFunction(sum, UInt64)
)
AS SELECT
    team_id,
    time_bucket,
    service_name,
    resource_fingerprint,
    attribute_key,
    attribute_value,
    attribute_type,
    attribute_count
FROM
(
    SELECT
        team_id AS team_id,
        toStartOfInterval(timestamp, toIntervalMinute(10)) AS time_bucket,
        service_name AS service_name,
        resource_fingerprint,
        mapFilter((k, v) -> ((length(k) < 256) AND (length(v) < 256)), attributes) AS attributes,
        arrayJoin(attributes) AS attribute,
        'metric' AS attribute_type,
        attribute.1 AS attribute_key,
        attribute.2 AS attribute_value,
        sumSimpleState(1) AS attribute_count
    FROM posthog_test.metrics1
    GROUP BY
        team_id,
        time_bucket,
        service_name,
        resource_fingerprint,
        attributes
)

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.metrics1_to_resource_attributes TO posthog_test.metric_attributes
(
    `team_id` Int32,
    `time_bucket` DateTime64(0),
    `service_name` LowCardinality(String),
    `resource_fingerprint` UInt64,
    `attribute_key` LowCardinality(String),
    `attribute_value` String,
    `attribute_type` LowCardinality(String),
    `attribute_count` SimpleAggregateFunction(sum, UInt64)
)
AS SELECT
    team_id,
    time_bucket,
    service_name,
    resource_fingerprint,
    attribute_key,
    attribute_value,
    attribute_type,
    attribute_count
FROM
(
    SELECT
        team_id AS team_id,
        toStartOfInterval(timestamp, toIntervalMinute(10)) AS time_bucket,
        service_name AS service_name,
        resource_fingerprint,
        arrayJoin(resource_attributes) AS attribute,
        'resource' AS attribute_type,
        attribute.1 AS attribute_key,
        attribute.2 AS attribute_value,
        sumSimpleState(1) AS attribute_count
    FROM posthog_test.metrics1
    GROUP BY
        team_id,
        time_bucket,
        service_name,
        resource_fingerprint,
        resource_attributes
)

CREATE TABLE IF NOT EXISTS posthog_test.metrics_kafka_metrics
(
    `_partition` UInt32,
    `_topic` String,
    `max_offset` SimpleAggregateFunction(max, UInt64),
    `max_observed_timestamp` SimpleAggregateFunction(max, DateTime64(9)),
    `max_timestamp` SimpleAggregateFunction(max, DateTime64(9)),
    `max_created_at` SimpleAggregateFunction(max, DateTime64(9)),
    `max_lag` SimpleAggregateFunction(max, UInt64)
)
ENGINE = ReplicatedAggregatingMergeTree('/clickhouse/tables/noshard/posthog.metrics_kafka_metrics', '{replica}-{shard}')
ORDER BY (_topic, _partition)
SETTINGS
    index_granularity = 8192

CREATE TABLE IF NOT EXISTS posthog_test.kafka_metrics_avro
(
    `uuid` String,
    `trace_id` String,
    `span_id` String,
    `trace_flags` Nullable(Int32),
    `timestamp` DateTime64(6),
    `observed_timestamp` DateTime64(6),
    `service_name` Nullable(String),
    `metric_name` Nullable(String),
    `metric_type` Nullable(String),
    `value` Nullable(Float64),
    `count` Nullable(Int64),
    `histogram_bounds` Array(Float64),
    `histogram_counts` Array(Int64),
    `unit` Nullable(String),
    `aggregation_temporality` Nullable(String),
    `is_monotonic` Nullable(UInt8),
    `resource_attributes` Map(String, String),
    `instrumentation_scope` Nullable(String),
    `attributes` Map(String, String),
    `series_fingerprint` Nullable(Int64)
)
ENGINE = Kafka(warpstream_metrics, kafka_topic_list = 'clickhouse_metrics', kafka_group_name = 'clickhouse-metrics-avro-new', kafka_format = 'Avro')
SETTINGS
    kafka_skip_broken_messages = 100,
    kafka_thread_per_consumer = 1,
    kafka_num_consumers = 8,
    kafka_poll_timeout_ms = 3000,
    kafka_poll_max_batch_size = 1000

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.kafka_metrics_avro_mv TO posthog_test.metrics1
AS SELECT
    uuid,
    trace_id,
    span_id,
    ifNull(trace_flags, 0) AS trace_flags,
    timestamp,
    observed_timestamp,
    ifNull(service_name, '') AS service_name,
    ifNull(metric_name, '') AS metric_name,
    ifNull(metric_type, '') AS metric_type,
    ifNull(value, 0) AS value,
    toUInt64(ifNull(count, 1)) AS count,
    histogram_bounds,
    arrayMap(x -> toUInt64(x), histogram_counts) AS histogram_counts,
    ifNull(unit, '') AS unit,
    ifNull(aggregation_temporality, '') AS aggregation_temporality,
    ifNull(is_monotonic, 0) AS is_monotonic,
    mapSort(mapApply((k, v) -> (k, JSONExtractString(v)), resource_attributes)) AS resource_attributes,
    ifNull(instrumentation_scope, '') AS instrumentation_scope,
    mapSort(mapApply((k, v) -> (concat(k, '__str'), JSONExtractString(v)), attributes)) AS attributes_map_str,
    mapSort(mapFilter((k, v) -> isNotNull(v), mapApply((k, v) -> (concat(k, '__float'), toFloat64OrNull(JSONExtract(v, 'String'))), attributes))) AS attributes_map_float,
    toInt32OrZero(_headers.value[indexOf(_headers.name, 'team_id')]) AS team_id
FROM posthog_test.kafka_metrics_avro
SETTINGS
    min_insert_block_size_rows = 0,
    min_insert_block_size_bytes = 0

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.kafka_metrics_avro_to_metric_samples TO posthog_test.metric_samples1
AS SELECT
    toInt32OrZero(_headers.value[indexOf(_headers.name, 'team_id')]) AS team_id,
    ifNull(metric_name, '') AS metric_name,
    reinterpretAsUInt64(assumeNotNull(series_fingerprint)) AS series_fingerprint,
    timestamp,
    ifNull(value, 0) AS value,
    toUInt64(ifNull(count, 1)) AS count,
    histogram_bounds,
    arrayMap(x -> toUInt64(x), histogram_counts) AS histogram_counts,
    trace_id,
    span_id,
    ifNull(trace_flags, 0) AS trace_flags
FROM posthog_test.kafka_metrics_avro
WHERE kafka_metrics_avro.series_fingerprint IS NOT NULL
SETTINGS
    min_insert_block_size_rows = 0,
    min_insert_block_size_bytes = 0

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.kafka_metrics_avro_to_metric_series TO posthog_test.metric_series1
AS SELECT
    toInt32OrZero(_headers.value[indexOf(_headers.name, 'team_id')]) AS team_id,
    ifNull(metric_name, '') AS metric_name,
    reinterpretAsUInt64(assumeNotNull(series_fingerprint)) AS series_fingerprint,
    ifNull(metric_type, '') AS metric_type,
    ifNull(unit, '') AS unit,
    ifNull(aggregation_temporality, '') AS aggregation_temporality,
    ifNull(is_monotonic, 0) AS is_monotonic,
    ifNull(service_name, '') AS service_name,
    mapSort(mapApply((k, v) -> (k, JSONExtractString(v)), resource_attributes)) AS resource_attributes,
    mapSort(mapApply((k, v) -> (k, JSONExtractString(v)), attributes)) AS attributes,
    timestamp AS last_seen
FROM posthog_test.kafka_metrics_avro
WHERE kafka_metrics_avro.series_fingerprint IS NOT NULL
SETTINGS
    min_insert_block_size_rows = 0,
    min_insert_block_size_bytes = 0

CREATE MATERIALIZED VIEW IF NOT EXISTS posthog_test.kafka_metrics_avro_kafka_metrics_mv TO posthog_test.metrics_kafka_metrics
AS SELECT
    _partition,
    _topic,
    maxSimpleState(_offset) AS max_offset,
    maxSimpleState(observed_timestamp) AS max_observed_timestamp,
    maxSimpleState(timestamp) AS max_timestamp,
    maxSimpleState(now()) AS max_created_at,
    maxSimpleState(now() - observed_timestamp) AS max_lag
FROM posthog_test.kafka_metrics_avro
GROUP BY _partition, _topic

✅ Hobby preview — passed

Hobby deployment smoke test passed successfully.

_{Run 33106283498}

trunk-io · 2026-08-26T18:43:08Z

_{View Full Report ↗︎ ⋅ Docs}

stamphog · 2026-08-26T20:20:09Z

Gates denied this PR (new ClickHouse migration hit the migrations deny-list, and size/scope classified it T2-never); it's a cross-team schema change with no reviews or approvals, so it needs human sign-off rather than automated approval.

Adds a new ClickHouse migration (0305_metrics_kafka_ingest) creating tables/materialized views — data-model change on the deny-list
Cross-team change touching @PostHog/clickhouse and @PostHog/team-devex owned files; author is on neither team
No reviews, approvals, or discussion sign-off on the current head

Gate mechanics and policy version

Gate		Result
prerequisites	✓	all clear
deny-list	✗	matches: migrations
size	✓	744L, 20F substantive, 746L/21F incl. docs/generated/snapshots — within ceiling
tier	✗	classified as T2-never: T2-never (746L, 21F, cross-cutting, feat)
stamphog 2.0.0b4		`.stamphog/policy.yml` @ `f7d3558` · reviewed head `f7d3558`

orian · 2026-08-27T03:18:04Z

+    # Orphan: present on prod OPS but no migration or code creates it anywhere.
+    "events_team_daily_stats",
+
+    # --- metrics-overlay ingest: created by migration 0305 on LOGS, modeled in


it's better option to extend the goldens / HCL and not exclude them here, excluding them, basically removes any protection against wrong migrations in the future

It's fine to merge like this but this will have to get sorted out

@orian I'd actually rather avoid introducing anything that loosens safety/has to be undone in the future so I've attempted to go with the better option you've outlined, if you want to take another look.

gantoine

happy to unblock this but no clue what those .hcl files are doing

OTLP metrics reached the clickhouse_metrics topic but never ClickHouse outside the cloud logs cluster: no consumer table existed, so the metrics product showed only hand-seeded data on dev stacks. Migration 0305 creates the ingest chain on the LOGS role: metrics1 (raw) and its distributed reader, metrics_kafka_metrics, kafka_metrics_avro, and the materialized views into metrics1, metric_samples1, metric_series1, and metrics_kafka_metrics. metrics1 itself had no creating migration — cloud provisions it out of band and dev laptops via the schema-sync path — so 0305 creates it too (0283 did this for metric_samples1/metric_series1 but left metrics1 out). Every statement is IF NOT EXISTS, so it is a no-op where the objects already exist. Add the warpstream_metrics named collection to the dev and multinode ClickHouse configs so the Kafka table resolves its broker list. These objects are modeled in the roles/logs/shared + cloud HCL layers for dev/prod but not in the local goldens; metrics1 diverges per env (value/count codecs on local and prod, none on dev), so a single all-env HCL declaration cannot serve both yet. Skip them in the local-multi and local-single convergence dumps until that is reconciled, so the gate does not read the migration-created objects as drift. Generated-By: PostHog Code Task-Id: 6522cf9f-0db9-46ac-93ad-12a849ece06e

…igration metrics was the last product provisioning its ClickHouse objects via a hand-run script (bin/clickhouse-metrics.sql); logs and traces already moved to migrations. Delete the script and its hogli command, and extend migration 0305 to cover everything it created that no migration did: metric_attributes and its two feeder views, on top of metrics1 and the Kafka ingest chain. All IF NOT EXISTS, so environments provisioned by the script or the cloud HCL are unaffected. Generated-By: PostHog Code Task-Id: 6522cf9f-0db9-46ac-93ad-12a849ece06e

Replace the local convergence-gate exclusions with real modeling, per review feedback: the metrics ingest objects move from roles/logs/{shared,cloud} into a new all-env roles/logs/metrics layer composed by every logs env including local-multi and local-single, so the gate now checks the migration-created objects instead of skipping them. The layer declares the local shape (noshard ZK paths, posthog_single_shard reader); cloud envs restore their logs-cluster paths via patches in roles/logs/shared, mirroring how metric_samples/metric_series are modeled. Local mirrors prod's value/count codecs via patches in roles/logs/local; the remaining explicit codecs are stripped from the Django SQL so the created tables converge with the codec-free base declaration (ZSTD(1) is the server default). Cloud logs goldens are byte-identical before and after the move. Generated-By: PostHog Desktop Task-Id: 2610e715-c74a-4a86-81c0-c97289c5acdc

The rebase force-push dropped uncommitted post-rebase work: max_migration.txt still pointed at the renamed 0305 migration, the local-multi logs golden and generated SQL were missing the metrics ingest objects, and the comment references kept the old migration number. Restore all of it: max_migration now names 0308_metrics_kafka_ingest, the golden and SQL are regenerated from the manifest (check.sh passes, cloud goldens untouched), and the comments reference 0308. Generated-By: PostHog Desktop Task-Id: 2610e715-c74a-4a86-81c0-c97289c5acdc

jzhu13 self-assigned this Aug 26, 2026

jzhu13 force-pushed the posthog-code/local-metrics-clickhouse-ingest branch from 596c7b2 to 536a519 Compare August 26, 2026 19:05

jzhu13 changed the title ~~feat(metrics): wire kafka ingest into local dev clickhouse~~ feat(metrics): create the metrics kafka ingest chain via migration Aug 26, 2026

jzhu13 marked this pull request as ready for review August 26, 2026 19:09

jzhu13 requested a review from a team as a code owner August 26, 2026 19:09

jzhu13 added the stamphog Request AI approval (no full review) label Aug 26, 2026

jzhu13 force-pushed the posthog-code/local-metrics-clickhouse-ingest branch from 536a519 to 7e2756f Compare August 26, 2026 19:18

jzhu13 added stamphog Request AI approval (no full review) and removed stamphog Request AI approval (no full review) labels Aug 26, 2026

stamphog Bot removed the stamphog Request AI approval (no full review) label Aug 26, 2026

orian approved these changes Aug 27, 2026

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gantoine approved these changes Aug 27, 2026

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jzhu13 added 3 commits August 27, 2026 11:48

jzhu13 force-pushed the posthog-code/local-metrics-clickhouse-ingest branch from cf697ff to 68f27c3 Compare August 27, 2026 18:48

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feat(metrics): create the metrics kafka ingest chain via migration - #89631

feat(metrics): create the metrics kafka ingest chain via migration#89631
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