With　the　surge　of　bandwidth　demand　for　cloud　applications　and　the　exponential　growth　of　data,　data　center　networks　(DCNs)　are　expanding　rapidly,　followed　by　the　daily　increasing　likelihood　of　failures.　Such　failures,　whether　due　to　device　or　link　issues,　are　inevitable　and　often　lead　to　packet　loss,　transmission　delays,　and　even　system　downtime.　Thus,　it　is　crucial　to　assess　the　fault-tolerant　capabilities　of　data　center　networks　using　appropriate　reliability　metrics　when　failures　occur.　BCube　is　a　well-known　server-centric　data　center　network　with　many　advantages,　such　as　rich　low-diameter　paths,　high　throughput,　and　excellent　expandability.　Not　only　do　the　recently　proposed　matroidal　connectivity　and　conditional　matroidal　connectivity　have　reasonable　fault　assumptions　that　align　well　with　the　structural　characteristics　of　data　center　networks,　but　they　also　significantly　enhance　the　fault　tolerance　performance　of　DCNs.　This　paper　determines　the　matroidal　connectivity　and　conditional　matroidal　connectivity　of　BCube,　which　is　the　first　study　to　apply　the　two　reliability　metrics　in　DCNs.　Then,　we　extend　the　conclusions　about　(conditional)　matroidal　connectivity　to　analyze　the　fault　tolerance　of　BCube　in　the　occurrence　of　switch　failures.　In　addition,　we　develop　an　efficient　algorithm　to　identify　the　structural　features　of　minimum　faulty　edge　sets,　where　the　cardinality　of　these　edge　sets　corresponds　to　the　conditional　matroidal　connectivity　of　BCube.　Finally,　we　experimentally　evaluate　the　effects　of　both　link　and　switch　failures　on　BCube＇s　performance　under　the　matroidal　restriction.　The　experimental　analyses　reveal　that　BCube　DCNs　exhibit　high　fault　tolerance　under　matroidal　constraints,　with　the　ability　to　withstand　both　link　and　switch　failures.