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fix: linkchecker include filter port mismatch (#2242)

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* initial commit; fixed anchor links on internal docs pages

* add back in absolute paths for links in code comments

* fix: update linkchecker include filter to match server port 1314

PR #1629 changed the Hugo server to port 1314 but forgot to update
the --include filter, which still matched port 1313. This caused all
links to be excluded, making the checker a no-op (0 checked, 82277 excluded).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* Fix url rewrite regex so images are not impacted

* Fix links from non-documentation pages

* Fix broken links

* more broken links

* more broken links

* broken link

* Add srcset width descriptor to .lycheeignore

* Ignore URLs that contain a % character

* Anchor regex so it matches the entire URL

---------

Co-authored-by: kanungle <neil.kanungo@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Abdon Pijpelink <abdon.pijpelink@qdrant.com>
This commit is contained in:
Andrey Vasnetsov
2026-03-30 17:21:32 +02:00
committed by GitHub
co-authored by Claude Opus 4.6 kanungle Abdon Pijpelink
parent dc0080fffa
commit 1a40961d62
272 changed files with 872 additions and 879 deletions
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qdrant-landing/content/articles/dedicated-service.md
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@@ -107,7 +107,7 @@ In practice, this means that your main database becomes burdened with high memor
Fortunately, the data synchronization problem is not new and definitely not unique to vector search.
There are many well-known solutions, starting with message queues and ending with specialized ETL tools.
For example, we recently released our [integration with Airbyte](/documentation/integrations/airbyte/), allowing you to synchronize data from various sources into Qdrant incrementally.
For example, we recently released our [integration with Airbyte](/documentation/data-management/airbyte/), allowing you to synchronize data from various sources into Qdrant incrementally.
###### You have to pay for a vector service uptime and data transfer of both solutions.
@@ -115,7 +115,7 @@ In the open-source world, you pay for the resources you use, not the number of d
Resources depend more on the optimal solution for each use case.
As a result, running a dedicated vector search engine can be even cheaper, as it allows optimization specifically for vector search use cases.
For instance, Qdrant implements a number of [quantization techniques](/documentation/guides/quantization/) that can significantly reduce the memory footprint of embeddings.
For instance, Qdrant implements a number of [quantization techniques](/documentation/manage-data/quantization/) that can significantly reduce the memory footprint of embeddings.
In terms of data transfer costs, on most cloud providers, network use within a region is usually free. As long as you put the original source data and the vector store in the same region, there are no added data transfer costs.