SRE-1003: Let a deploy catalog entry choose its ECR architecture by TimDiekmann · Pull Request #9540 · hashintel/hash

TimDiekmann · 2026-09-04T13:07:18Z

🌟 What is the purpose of this PR?

ECR holds one architecture per repository, because Amazon Inspector does not scan manifest lists. Until now that architecture was hard-wired to arm64 for every service, and publishing to GHCR implied building both architectures. The upcoming atlas-fit image (GPU fit job on x86 instances) is amd64-only and goes to ECR and GHCR, so the deploy catalog gains two optional fields.

🔍 What does this change?

.github/workflows/deploy.yml: an optional arches per catalog entry (default: both for GHCR services, arm64 otherwise) and an optional ecr_arch (default: the only arch when a service builds one, else arm64). The build matrix expands arches; the ECR push compares against ecr_arch instead of a literal arm64; the pull-request-time amd64 skip no longer drops a service whose only architecture is amd64. The setup step fails loudly when ecr_arch is not among arches, since the ECR push would otherwise silently never happen.
No catalog entry changes. Every existing service resolves to the same build matrix and tags as before; the atlas-fit entry follows with its Dockerfile (H-6806).

Pre-Merge Checklist 🚀

🚢 Has this modified a publishable library?

This PR:

does not modify any publishable blocks or libraries, or modifications do not need publishing

📜 Does this require a change to the docs?

The changes in this PR:

are internal and do not require a docs change

🕸️ Does this require a change to the Turbo Graph?

The changes in this PR:

do not affect the execution graph

🛡 What tests cover this?

The resolve and build-matrix jq programs run against a sample catalog (graph ECR+GHCR, kratos ECR-only, atlas-fit ECR+GHCR with arches: ["amd64"], a multi-arch entry with ecr_arch: "amd64") in push and pull-request mode: existing services keep their matrix, atlas-fit builds amd64 only in both modes.
The consistency check flags an entry whose ecr_arch is outside its arches and passes GHCR-only entries.
actionlint reports the same findings as on main; the workflow parses.

ECR holds one architecture per repository because Inspector does not scan manifest lists. Until now that architecture was arm64 for every service. A catalog entry can now set `ecr_arch`; ECR-only services build just that arch, GHCR services keep building both for their multi-arch manifest, and the PR-time amd64 skip no longer drops a service whose only arch is amd64. Defaults leave every existing service unchanged.

vercel · 2026-09-04T13:07:22Z

The latest updates on your projects. Learn more about Vercel for GitHub.

Project	Deployment	Actions	Updated
hash	Ready	Preview	Sep 4, 2026 1:29pm UTC
hashdotdesign-tokens	Ready	Preview	Sep 4, 2026 1:29pm UTC
petrinaut	Ready	Preview	Sep 4, 2026 1:29pm UTC
petrinaut-docs	Ready	Preview	Sep 4, 2026 1:29pm UTC

codecov · 2026-09-04T13:11:38Z

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 60.89%. Comparing base (eea4e1f) to head (57fbb92).
⚠️ Report is 7 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #9540   +/-   ##
=======================================
  Coverage   60.89%   60.89%           
=======================================
  Files        1461     1461           
  Lines      146725   146725           
  Branches     6744     6744           
=======================================
  Hits        89343    89343           
  Misses      56264    56264           
  Partials     1118     1118

Flag	Coverage Δ
apps.hash-ai-worker-ts	`1.99% <ø> (ø)`
apps.hash-api	`15.41% <ø> (ø)`
apps.hash-graph	`13.32% <ø> (ø)`
blockprotocol.type-system	`38.15% <ø> (ø)`
local.claude-hooks	`0.00% <ø> (ø)`
local.harpc-client	`51.49% <ø> (ø)`
local.hash-backend-utils	`3.27% <ø> (ø)`
local.hash-graph-sdk	`10.02% <ø> (ø)`
local.hash-isomorphic-utils	`12.22% <ø> (ø)`
rust.antsi	`2.36% <ø> (ø)`
rust.error-stack	`90.81% <ø> (ø)`
rust.harpc-codec	`84.70% <ø> (ø)`
rust.harpc-net	`96.21% <ø> (ø)`
rust.harpc-tower	`67.03% <ø> (ø)`
rust.harpc-types	`0.00% <ø> (ø)`
rust.harpc-wire-protocol	`92.23% <ø> (ø)`
rust.hash-codec	`72.76% <ø> (ø)`
rust.hash-config	`74.74% <ø> (ø)`
rust.hash-graph-api	`19.71% <ø> (ø)`
rust.hash-graph-authentication	`96.02% <ø> (ø)`
rust.hash-graph-authorization	`63.14% <ø> (ø)`
rust.hash-graph-embeddings	`91.88% <ø> (ø)`
rust.hash-graph-postgres-store	`32.15% <ø> (ø)`
rust.hash-graph-store	`48.41% <ø> (ø)`
rust.hash-graph-temporal-versioning	`50.18% <ø> (ø)`
rust.hash-graph-types	`0.00% <ø> (ø)`
rust.hash-graph-validation	`84.71% <ø> (ø)`
rust.hash-middleware	`90.92% <ø> (ø)`
rust.hashql-ast	`89.63% <ø> (ø)`
rust.hashql-compiletest	`28.39% <ø> (ø)`
rust.hashql-core	`78.95% <ø> (ø)`
rust.hashql-diagnostics	`72.51% <ø> (ø)`
rust.hashql-eval	`79.82% <ø> (ø)`
rust.hashql-hir	`89.09% <ø> (ø)`
rust.hashql-mir	`87.92% <ø> (ø)`
rust.hashql-syntax-jexpr	`94.04% <ø> (ø)`

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Publishing to GHCR no longer implies building both architectures: `arches` names what a service builds, and the ECR architecture follows from it when there is only one. The setup step fails when `ecr_arch` is not among the arches built, since the ECR push would otherwise silently never happen.

codspeed-hq · 2026-09-04T13:15:57Z

Merging this PR will not alter performance

✅ 98 untouched benchmarks

_{Comparing t/sre-1003-ecr-architecture-per-service (57fbb92) with main (4854d5f)¹}

No successful run was found on main (9371f71) during the generation of this report, so 4854d5f was used instead as the comparison base. There might be some changes unrelated to this pull request in this report. ↩

github-actions · 2026-09-04T14:20:25Z

Benchmark results

@rust/hash-graph-benches – Integrations

policy_resolution_large

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2002	$$20.3 \mathrm{ms} \pm 114 \mathrm{μs}\left({\color{gray}0.843 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.66 \mathrm{ms} \pm 14.4 \mathrm{μs}\left({\color{gray}1.04 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1002	$$9.95 \mathrm{ms} \pm 78.5 \mathrm{μs}\left({\color{gray}3.13 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$34.0 \mathrm{ms} \pm 268 \mathrm{μs}\left({\color{gray}1.91 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$11.2 \mathrm{ms} \pm 79.5 \mathrm{μs}\left({\color{gray}-0.127 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1527	$$19.1 \mathrm{ms} \pm 148 \mathrm{μs}\left({\color{gray}2.15 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$21.0 \mathrm{ms} \pm 200 \mathrm{μs}\left({\color{gray}0.362 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.90 \mathrm{ms} \pm 17.8 \mathrm{μs}\left({\color{gray}-1.655 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$10.9 \mathrm{ms} \pm 76.1 \mathrm{μs}\left({\color{gray}1.48 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$2.91 \mathrm{ms} \pm 16.9 \mathrm{μs}\left({\color{gray}0.007 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.35 \mathrm{ms} \pm 12.7 \mathrm{μs}\left({\color{gray}-0.754 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 52	$$2.60 \mathrm{ms} \pm 13.9 \mathrm{μs}\left({\color{gray}-0.974 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$3.99 \mathrm{ms} \pm 24.6 \mathrm{μs}\left({\color{gray}-0.270 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$2.77 \mathrm{ms} \pm 14.5 \mathrm{μs}\left({\color{gray}-1.029 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 108	$$3.24 \mathrm{ms} \pm 20.0 \mathrm{μs}\left({\color{gray}0.675 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$3.43 \mathrm{ms} \pm 16.4 \mathrm{μs}\left({\color{gray}0.053 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.68 \mathrm{ms} \pm 13.4 \mathrm{μs}\left({\color{gray}-1.667 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$3.24 \mathrm{ms} \pm 23.0 \mathrm{μs}\left({\color{gray}2.03 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.14 \mathrm{ms} \pm 11.0 \mathrm{μs}\left({\color{gray}0.125 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.09 \mathrm{ms} \pm 11.8 \mathrm{μs}\left({\color{gray}0.665 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 2	$$2.21 \mathrm{ms} \pm 12.4 \mathrm{μs}\left({\color{gray}1.01 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$2.38 \mathrm{ms} \pm 11.7 \mathrm{μs}\left({\color{gray}-0.630 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.24 \mathrm{ms} \pm 10.4 \mathrm{μs}\left({\color{gray}-0.525 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$2.47 \mathrm{ms} \pm 14.6 \mathrm{μs}\left({\color{gray}0.039 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$2.38 \mathrm{ms} \pm 12.4 \mathrm{μs}\left({\color{gray}0.031 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.17 \mathrm{ms} \pm 14.6 \mathrm{μs}\left({\color{gray}0.160 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 26	$$2.31 \mathrm{ms} \pm 16.6 \mathrm{μs}\left({\color{gray}1.14 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$2.70 \mathrm{ms} \pm 14.0 \mathrm{μs}\left({\color{gray}-0.229 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$2.38 \mathrm{ms} \pm 10.3 \mathrm{μs}\left({\color{gray}-1.357 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 27	$$2.54 \mathrm{ms} \pm 11.0 \mathrm{μs}\left({\color{gray}-1.737 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$2.65 \mathrm{ms} \pm 12.9 \mathrm{μs}\left({\color{gray}0.238 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.36 \mathrm{ms} \pm 12.4 \mathrm{μs}\left({\color{gray}-1.809 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$2.59 \mathrm{ms} \pm 13.2 \mathrm{μs}\left({\color{gray}-1.064 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$24.7 \mathrm{ms} \pm 117 \mathrm{μs}\left({\color{gray}1.45 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$54.2 \mathrm{ms} \pm 351 \mathrm{μs}\left({\color{gray}3.10 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$27.8 \mathrm{ms} \pm 162 \mathrm{μs}\left({\color{gray}1.81 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$30.2 \mathrm{ms} \pm 206 \mathrm{μs}\left({\color{gray}3.43 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$34.1 \mathrm{ms} \pm 196 \mathrm{μs}\left({\color{red}5.16 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$25.6 \mathrm{ms} \pm 147 \mathrm{μs}\left({\color{gray}-0.547 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$315 \mathrm{ms} \pm 949 \mathrm{μs}\left({\color{gray}4.48 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$71.1 \mathrm{ms} \pm 417 \mathrm{μs}\left({\color{red}5.76 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$55.0 \mathrm{ms} \pm 351 \mathrm{μs}\left({\color{gray}1.16 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$237 \mathrm{ms} \pm 736 \mathrm{μs}\left({\color{red}13.8 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$8.37 \mathrm{ms} \pm 62.9 \mathrm{μs}\left({\color{gray}3.72 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$8.41 \mathrm{ms} \pm 56.3 \mathrm{μs}\left({\color{gray}2.23 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$8.51 \mathrm{ms} \pm 69.2 \mathrm{μs}\left({\color{gray}1.75 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$8.63 \mathrm{ms} \pm 60.7 \mathrm{μs}\left({\color{red}7.06 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$8.74 \mathrm{ms} \pm 71.6 \mathrm{μs}\left({\color{red}5.45 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$8.22 \mathrm{ms} \pm 54.4 \mathrm{μs}\left({\color{gray}2.28 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$8.44 \mathrm{ms} \pm 56.0 \mathrm{μs}\left({\color{red}5.59 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$8.38 \mathrm{ms} \pm 55.7 \mathrm{μs}\left({\color{gray}3.77 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$8.33 \mathrm{ms} \pm 68.3 \mathrm{μs}\left({\color{gray}1.02 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$8.68 \mathrm{ms} \pm 62.9 \mathrm{μs}\left({\color{gray}1.30 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity

Function	Value	Mean	Flame graphs
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/block/v/1`	$$8.80 \mathrm{ms} \pm 53.3 \mathrm{μs}\left({\color{gray}3.82 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/book/v/1`	$$8.45 \mathrm{ms} \pm 55.1 \mathrm{μs}\left({\color{gray}-0.871 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/building/v/1`	$$8.45 \mathrm{ms} \pm 56.2 \mathrm{μs}\left({\color{gray}-2.309 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/organization/v/1`	$$8.71 \mathrm{ms} \pm 50.7 \mathrm{μs}\left({\color{gray}1.46 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/page/v/2`	$$8.48 \mathrm{ms} \pm 44.4 \mathrm{μs}\left({\color{gray}-1.791 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/person/v/1`	$$8.56 \mathrm{ms} \pm 56.6 \mathrm{μs}\left({\color{gray}0.742 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/playlist/v/1`	$$8.59 \mathrm{ms} \pm 53.2 \mathrm{μs}\left({\color{gray}-0.287 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/song/v/1`	$$8.42 \mathrm{ms} \pm 43.0 \mathrm{μs}\left({\color{gray}0.050 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: `https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1`	$$8.52 \mathrm{ms} \pm 50.6 \mathrm{μs}\left({\color{gray}-0.010 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: `bf5a9ef5-dc3b-43cf-a291-6210c0321eba`	$$6.54 \mathrm{ms} \pm 45.4 \mathrm{μs}\left({\color{gray}4.89 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$45.1 \mathrm{ms} \pm 274 \mathrm{μs}\left({\color{gray}1.46 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$86.7 \mathrm{ms} \pm 404 \mathrm{μs}\left({\color{gray}2.83 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$51.2 \mathrm{ms} \pm 352 \mathrm{μs}\left({\color{gray}3.59 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$59.4 \mathrm{ms} \pm 329 \mathrm{μs}\left({\color{red}5.22 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$65.3 \mathrm{ms} \pm 347 \mathrm{μs}\left({\color{gray}4.91 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$69.8 \mathrm{ms} \pm 397 \mathrm{μs}\left({\color{gray}2.85 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$36.8 \mathrm{ms} \pm 177 \mathrm{μs}\left({\color{gray}4.09 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$58.3 \mathrm{ms} \pm 321 \mathrm{μs}\left({\color{gray}-0.942 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$41.9 \mathrm{ms} \pm 187 \mathrm{μs}\left({\color{gray}3.56 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$48.5 \mathrm{ms} \pm 242 \mathrm{μs}\left({\color{gray}0.940 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$50.4 \mathrm{ms} \pm 320 \mathrm{μs}\left({\color{gray}1.31 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$49.9 \mathrm{ms} \pm 337 \mathrm{μs}\left({\color{gray}-0.761 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$88.5 \mathrm{ms} \pm 431 \mathrm{μs}\left({\color{lightgreen}-9.569 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$98.7 \mathrm{ms} \pm 365 \mathrm{μs}\left({\color{lightgreen}-7.520 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$17.6 \mathrm{ms} \pm 115 \mathrm{μs}\left({\color{gray}-1.041 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$415 \mathrm{ms} \pm 1.04 \mathrm{ms}\left({\color{gray}-4.830 \mathrm{\%}}\right) $$	Flame Graph

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SRE-1003: Let a deploy catalog entry choose its ECR architecture - #9540

SRE-1003: Let a deploy catalog entry choose its ECR architecture#9540
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@rust/hash-graph-benches – Integrations

policy_resolution_large

policy_resolution_medium

policy_resolution_none

policy_resolution_small

read_scaling_complete

read_scaling_linkless

representative_read_entity

representative_read_entity_type

representative_read_multiple_entities

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🌟 What is the purpose of this PR?

🔍 What does this change?

Pre-Merge Checklist 🚀

🚢 Has this modified a publishable library?

📜 Does this require a change to the docs?

🕸️ Does this require a change to the Turbo Graph?

🛡 What tests cover this?

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Codecov Report

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Merging this PR will not alter performance

Footnotes

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github-actions Bot commented Sep 4, 2026

Benchmark results

@rust/hash-graph-benches – Integrations

policy_resolution_large

policy_resolution_medium

policy_resolution_none

policy_resolution_small

read_scaling_complete

read_scaling_linkless

representative_read_entity

representative_read_entity_type

representative_read_multiple_entities

scenarios

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Reviewers

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1 participant

TimDiekmann commented Sep 4, 2026 •

edited

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vercel Bot commented Sep 4, 2026 •

edited

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codecov Bot commented Sep 4, 2026 •

edited

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codspeed-hq Bot commented Sep 4, 2026 •

edited

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