Lapho abantu abaningi bezwa “ubuhlakani bokwenziwa,” bathwebula amanethi e-neural, ama-algorithms amnandi, noma mhlawumbe lawo marobhothi angaziwa kancane. Okungavamile ukuthi kukhulunywe ngakho ngaphambili yilokhu: I-AI idla isitoreji cishe ngendlela exakile njengoba yenza ukubala . Futhi akukhona nje noma yisiphi isitoreji sento ehlala ngokuthula ngemuva, senza umsebenzi ongathandeki kodwa obaluleke kakhulu wokuphakela amamodeli idatha ayidingayo.
Ake sihlukanise ukuthi yini eyenza ukugcinwa kwezinto kubaluleke kakhulu ku-AI, ukuthi yehluke kanjani “kunogada omdala” wezinhlelo zokugcina, nokuthi kungani igcina isingesinye sezici ezibalulekile zokukala nokusebenza.
Izindatshana ongathanda ukuzifunda ngemva kwalesi:
🔗 Yibuphi ubuchwepheshe okufanele bube khona ukuze kusetshenziswe i-AI yokukhiqiza enkulu yebhizinisi
Ubuchwepheshe obubalulekile amabhizinisi abudingayo ukukala i-AI ekhiqizayo ngempumelelo.
🔗 Ukuphathwa kwedatha yamathuluzi e-AI okufanele ukubheke
Imikhuba ehamba phambili yokuphatha idatha ukuze kuthuthukiswe ukusebenza kwe-AI.
🔗 Imithelela yobuhlakani bokwenziwa yesu lebhizinisi
I-AI iwathinta kanjani amasu ebhizinisi kanye nokwenziwa kwezinqumo zesikhathi eside.
Yini Eyenza Umaka Wesitoreji Sento ye-AI? 🌟
Umbono omkhulu: ukugcinwa kwento akukhathazi ngamafolda noma izakhiwo eziqinile zamabhulokhi. Ihlukanisa idatha ibe "izinto," ngayinye efakwe imethadatha. Leyo metadata ingaba izinto zezinga lesistimu (usayizi, izitembu zesikhathi, isigaba sokulondoloza) kanye nokhiye ochazwe umsebenzisi:amathegi amanani [1]. Kucabange njengawo wonke amafayela aphethe isitaki samanothi anamathelayo akutshela kahle ukuthi siyini, sadalwa kanjani, nokuthi singena kuphi epayipini lakho.
Emaqenjini e-AI, lokho kuvumelana nezimo kuyawushintsha umdlalo:
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I-Scale without migraines - Amachibi edatha anwebeka abe ama-petabytes, futhi izitolo zezinto zikuphatha kalula. Zenzelwe ukukhula okucishe kukhawulelwe kanye nokuqina kwe-AZ eningi (i-Amazon S3 izishaya isifuba “ngama-11 nines” kanye nokuphindaphindwa kwezindawo eziphambene ngokuzenzakalela) [2].
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Ukunotha kwemethadatha - Ukusesha okusheshayo, izihlungi ezihlanzekile, namapayipi ahlakaniphile njengoba umongo uhamba nento ngayinye [1].
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I-Cloud-native - Idatha ingena nge-HTTP(S), okusho ukuthi ungakwazi ukufanisa ukudonsa futhi ugcine ukuqeqeshwa okusabalalisiwe kuhemuza.
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Ukuqina kubhakiwe - Uma uziqeqesha izinsuku, awukwazi ukubeka engcupheni inkathi yokubulawa kweshadi eyonakele engu-12. Ukugcinwa kwento kugwema lokho ngokuklama [2].
Empeleni ubhaka ongenamkhawulo: mhlawumbe ungcolile ngaphakathi, kodwa yonke into isabuyiseka uma uyifinyelela.
Ithebula lokuqhathanisa elisheshayo le-AI Object Storage 🗂️
| Ithuluzi / Isevisi | Ilungele (Izethameli) | Ibanga lentengo | Kungani Isebenza (Amanothi Emaphethelweni) |
|---|---|---|---|
| I-Amazon S3 | Amabhizinisi + Amaqembu e-Cloud-first | Khokha njengoba uhamba | Ihlala isikhathi eside ngokwedlulele, iqinile ngokwesifunda [2] |
| I-Google Cloud Storage | Ososayensi bedatha nama-ML devs | Izigaba eziguquguqukayo | Ukuhlanganiswa kwe-ML okuqinile, okomdabu wamafu ngokugcwele |
| Isitoreji se-Azure Blob | Izitolo ze-Microsoft-ezisindayo | I-Tiered (kuyashisa/kubanda) | Ingenamthungo ngedatha ye-Azure + ithuluzi le-ML |
| I-MiniIO | Umthombo ovulekile / ukusetha kwe-DIY | Mahhala/self-host | Ihambisana ne-S3, ilula, sebenzisa noma yikuphi 🚀 |
| Wasabi Hot Cloud | Ama-orgs azwela izindleko | Izinga eliphansi liphansi $ | Azikho izimali zesicelo se-egress noma ze-API (ngenqubomgomo ngayinye) [3] |
| I-IBM Cloud Object Storage | Amabhizinisi amakhulu | Iyahlukahluka | Isitaki esikhulile esinezinketho eziqinile zokuphepha zebhizinisi |
Hlala ubheka amanani entengo ngokumelene nokusetshenziswa kwakho komhlaba wangempela-ikakhulukazi ukuphuma, ivolumu yokucela, kanye nengxube yezinga lesitoreji.
Kungani Ukuqeqeshwa kwe-AI Kuthanda Isitoreji Sento 🧠
Ukuqeqesha akuwona “idlanzana lamafayela.” Izigidi ngezigidi zamarekhodi aphihlizwe ngokuhambisana. Amasistimu wamafayela e-hierarchical ayabophela ngaphansi kwesivumelwano esinzima. Isitoreji sento siphambene nalokho esinezikhala zamagama eziyisicaba kanye nama-API ahlanzekile. Yonke into inokhiye oyingqayizivele; abasebenzi baphephetha futhi balande ngokuhambisana. Amasethi edatha abiwe + parallel I/O = Ama-GPU ahlala ematasa esikhundleni sokulinda.
Ithiphu evela emiseleni: gcina ama-shards ashisayo eduze kweqoqo lekhompiyutha (isifunda noma indawo efanayo), bese ugcina inqolobane ngokunamandla ku-SSD. Uma udinga okuphakelayo okuseduze kuma-GPU, i-NVIDIA GPUDirect Storage kufanelekile ukuyibheka-inquma amabhafa we-CPU, inciphisa ukubambezeleka, futhi ikhuphule umkhawulokudonsa iqonde kuma-accelerator [4].
Imethadatha: Amandla Anamandla Angalinganiselwe 🪄
Lapha kulapho ukugcinwa kwezinto kukhanya khona ngezindlela ezingacacile. Lapho ulayisha, unganamathisela imethadatha yangokwezifiso (njenge -x-amz-meta-… ye-S3). Isethi yedatha yombono, ngokwesibonelo, ingamaka izithombe ngokukhanya =phansi noma ukufiphala=phezulu . Lokho kuvumela amaphayiphi ukuthi ahlunge, alinganise, noma ahlukaniseke ngaphandle kokuskena kabusha amafayela aluhlaza [1].
Bese kuba nenguqulo . Izitolo eziningi zento zigcina izinguqulo eziningi zento zihlangene-ziphelele ekuhloleni okungakhiqizeka kabusha noma izinqubomgomo zokubusa ezidinga ukuhlehliswa [5].
Into vs Vimba vs Isitoreji Sefayela ⚔️
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Vimba Isitoreji : Kuhle kusizindalwazi sokwenziwe-ngokushesha nokunembayo-kodwa kubiza kakhulu kudatha engakhiwanga yesikali se-petabyte.
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Isitoreji Sefayela : Ijwayelekile, i-POSIX-friendly, kodwa izinkomba ziminyanisa ngaphansi kwemithwalo ehambisana kakhulu.
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Isitoreji Sento : Idizayinelwe kusuka phansi kuya esikalini, ukufana, nokufinyelela okushayelwa imethadatha [1].
Uma ufuna isingathekiso esixakile: ukugcinwa kwebhulokhi yikhabhinethi yokufayila, ukugcinwa kwamafayela kuyifolda yedeskithophu, futhi ukugcinwa kwento…umgodi ongenamkhawulo onamanothi anamathelayo awenza asebenziseke ngandlela thize.
IHybrid AI Workflows 🔀
Akuhlali kungamafu kuphela. Ingxube evamile ibonakala kanje:
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Isitoreji sento e-on-prem (i-MinIO, i-Dell ECS) yedatha ebucayi noma elawulwayo.
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Isitoreji sento yamafu sokuqhuma komsebenzi, ukuhlola, noma ukuhlanganyela.
Le bhalansi ifinyelela izindleko, ukuthobela, nokuba bukhali. Ngibone amaqembu elahla ngokoqobo ama-terabyte ngobusuku ebhakedeni le-S3 ukuze nje akhanyise iqoqo lesikhashana le-GPU-bese eyinuke yonke lapho i-sprint isonga. Ngezabelomali eziqinile, imodeli ye-Wasabi ye-flat-rate/no-egress [3] yenza ukuphila kube lula ukubikezela.
Ingxenye Akekho Ozishaya Ngayo 😅
Ukuhlola iqiniso: akunasici.
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Ukubambezeleka - Beka ikhompuyutha nesitoreji kude kakhulu futhi ama-GPU akho ayacaca. I-GDS iyasiza, kodwa izakhiwo zisabalulekile [4].
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Izindleko ezimangazayo - Izindleko ze-Egress kanye nezicelo ze-API zingena ngesinyenyela kubantu. Abanye abahlinzeki bayekela (u-Wasabi uyakwenza; abanye abakwenzi) [3].
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Isiphithiphithi semethadatha esikalini - Ubani ochaza “iqiniso” kumathegi nezinguqulo? Uzodinga izinkontileka, izinqubomgomo, kanye nemisipha ethile yokuphatha [5].
Isitoreji sento amapayipi engqalasizinda: abalulekile, kodwa awanabukhazikhazi.
Lapho ibheke khona 🚀
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Isitoreji esihlakaniphile, esiqaphela i-AI esimaka ngokuzenzakalelayo futhi siveze idatha kusetshenziswa izendlalelo zombuzo ezifana ne-SQL [1].
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Ukuhlanganiswa kwezingxenyekazi zekhompuyutha eziseduze (izindlela ze-DMA, ukulayishwa kwe-NIC) ukuze ama-GPU angabulawa yindlala ye-I/O [4].
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Intengo esobala, ebikezelwayo (amamodeli enziwe lula, izinkokhelo zokuphuma eziyekiwe) [3].
Abantu bakhuluma ngekhompyutha njengekusasa le-AI. Kodwa ngokweqiniso? Ibhodlela imayelana nokuphakela idatha kumamodeli ngokushesha ngaphandle kokushaya ibhajethi . Yingakho indima yokugcinwa kwezinto ikhula kuphela.
Ukugoqa 📝
Ukugcinwa kwento akuyona into ekhanyayo, kodwa iyisisekelo. Ngaphandle kwe-scalable, i-metadata-ware, isitoreji esiqinile, ukuqeqesha amamodeli amakhulu kuzwakala njengokugijima ibanga elide ngezimbadada.
Ngakho-ke yebo-GPUs ibalulekile, izinhlaka zibalulekile. Kodwa uma uzimisele nge-AI, ungazibi lapho kuhlala khona idatha yakho . Okungenzeka ukuthi, indawo yokugcina into isivele ibambe wonke umsebenzi ngokuthula.
Izithenjwa
[1] AWS S3 – Imethadatha yento - isistimu nemethadatha yangokwezifiso
https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingMetadata.html
[2] I-AWS S3 – Amakilasi esitoreji - ukuqina (“11 nines”) + ukuqina
https://aws.amazon.com/s3/storage-classes/
[3] Ifu Le-Wasabi Elishisayo - Intengo - izinga eliphansi, akukho zindleko ze-egress/API
https://wasabi.com/pricing
[4] I-NVIDIA GPUDirect Storage – Amadokhumenti - Izindlela ze-DMA eziya kuma-GPU
https://docs.nvidia.com/gpudirect-storage/
[5] I-AWS S3 – Inguqulo - izinguqulo eziningi zokubusa/ukukhiqiza kabusha
https://docs.aws.amazon.com/AmazonS3/latest/userguide/Versioning.html