diff --git a/microsite/blog/2023-01-31-incremental-entity-provider.md b/microsite/blog/2023-01-31-incremental-entity-provider.md
index 991ac4db4a..cffe118deb 100644
--- a/microsite/blog/2023-01-31-incremental-entity-provider.md
+++ b/microsite/blog/2023-01-31-incremental-entity-provider.md
@@ -25,10 +25,10 @@ A mutation can be either a full mutation or a delta mutation. A full mutation re
 
 A large organization typically deals with massive datasets. Until recently, ingesting large datasets with entity providers has been problematic because performing a full ingestion resulted in out-of-memory errors, and many data sources don’t provide webhooks or other events-based APIs. At the same time, the datasets were too large to efficiently manage through targeted delta mutations.
 
-This is a problem that [DevEx team at HP](http://hp.com) faced when building their software catalog with Backstage. [Damon Kaswell](https://github.com/dekoding), Senior Application Developer on the DevEx team at HP, shared their experience at [BackstageCon 2022](https://www.youtube.com/watch?v=5qHyZntKXRU&list=PLj6h78yzYM2OKySsTuiip3BqmdYZQRnSf&index=13), detailing the problem and the solution that Frontside created in collaboration with developers on HP’s DevEx team.
+This is a problem that [DevEx team at HP](http://hp.com) faced when building their software catalog with Backstage. [Damon Kaswell](https://github.com/dekoding), Senior Application Developer on the DevEx team at HP, shared their experience at [BackstageCon 2022](https://www.youtube.com/watch?v=5qHyZntKXRU&list=PLj6h78yzYM2OKySsTuiip3BqmdYZQRnSf&index=13), detailing the problem and the solution that [Frontside](https://frontside.com/) created in collaboration with developers on HP’s DevEx team.
 
  
-The solution HP and Frontside arrived at was to implement an incremental entity provider. An incremental entity provider effectively performs a full mutation using a series of delta mutations combined with a mark and sweep mechanism. It paginates through the dataset, tracking entities retrieved from each page and the cursor of the next page, pausing ingestion every few minutes to give the processing loop time to process existing entities. Once it reaches the end of the dataset, it determines which entities were not ingested during this ingestion cycle and emits a delta mutation to delete unmarked entities.
+The solution HP and [Frontside](https://frontside.com/) arrived at was to implement an incremental entity provider. An incremental entity provider effectively performs a full mutation using a series of delta mutations combined with a mark and sweep mechanism. It paginates through the dataset, tracking entities retrieved from each page and the cursor of the next page, pausing ingestion every few minutes to give the processing loop time to process existing entities. Once it reaches the end of the dataset, it determines which entities were not ingested during this ingestion cycle and emits a delta mutation to delete unmarked entities.
 
 Simply by adding a few new tables to the database schema, the incremental ingestion entity provider converts any existing entity provider into an incremental entity provider. These tables allow the incremental entity provider to be long-lived and keep track of its current location in the dataset by persisting a cursor that it uses to page through any large dataset. The larger the dataset, the more pages of data or bursts of work the incremental entity provider will ingest—but there will be no out-of-memory errors, effectively removing scalability problems. 
 
@@ -37,7 +37,7 @@ The results speak for themselves. Migrating from regular entity providers to inc
 
 ## Go forth and ingest!
 
-Backstage provides a robust framework for ingesting data from external sources, but HP needed to scale it beyond its design. The Backstage framework allowed Frontside and HP’s developers to extend it with a plugin to support HP’s scaling requirements.
+Backstage provides a robust framework for ingesting data from external sources, but HP needed to scale it beyond its design. The Backstage framework allowed [Frontside](https://frontside.com/) and HP’s developers to extend it with a plugin to support HP’s scaling requirements.
 
 We're delighted to share that as of [this PR](https://github.com/backstage/backstage/pull/14356), the incremental ingestion backend is available for anyone to use with Backstage. The solution was released open source as [@backstage/plugin-catalog-backend-module-incremental-ingestion](https://github.com/backstage/backstage/tree/master/plugins/catalog-backend-module-incremental-ingestion#backstageplugin-catalog-backend-module-incremental-ingestion) and contains a package for creating incremental entity providers. The plugin's [repository README](https://github.com/backstage/backstage/tree/master/plugins/catalog-backend-module-incremental-ingestion) has detailed configuration and usage outlined.