Overview
Kubeflow ndeye yakavhurika-sosi yekushandisa iyo inomhanyisa muchina wekudzidza workflows paKubernetes, ichishandura modhi yekudzidziswa uye kuendesa kune inogadzirwazve, ine midziyo mapaipi. Izvo zvine basa nekuti zvinoita kuti zvikwata zviyere ML nenzira imwechete yavanoyera yemazuva ano gore software.
Kubeflow uye ML Pipeline Orchestration chivakwa chekuvaka chinobata mhando yemhando, mutengo wezvivakwa, latency, uye kuvimbika pachiyero.
Deep Dive
Kubeflow yakatanga pa Google senzira yekumhanyisa TensorFlow paKubernetes, ndokuzokura kuita chikuva chakakura. Pfungwa yaro yepakati nderekuti nhanho yega yega yeML yekufambisa senge data prep, kudzidziswa, kuongorora, uye kushumira inomhanya sechinhu chakaiswa mukati meKubernetes pod. Kubeflow Pipelines (KFP) inoita kuti utaure nhanho idzi seyakatungamirwa acyclic graph (DAG): node yega yega mudziyo unozvimiririra, uye mipendero inotsanangura zvinoenderana nedata. Nekuti Kubernetes inobata kuronga, kuyera, uye kugovera zviwanikwa, pombi inogona kukumbira maGPU ekudzidziswa uye oasunungura mushure. Zvimwe zvikamu zvinosanganisira Katib ye hyperparameter tuning, KServe yekusevha modhi, uye maseva ekunyorera. Mubairo ndeyekuberekana, kutakurika mumakore, uye kugona kuyera nhanho dzemunhu wakazvimirira.
Technical Insight
Iyo Kubeflow pombi inounganidza Python DSL muArgo Workflows YAML spec. Chikamu chega chega chinova mudziyo unoverenga zvinopinda uye unonyora zvinobuda sezvigadzirwa, zvakapfuudzwa pakati pematanho kuburikidza nechitoro chechinhu chakagovaniswa seMiniO kana S3. Kubernetes inoronga podhi yega yega, ichibatanidza GPU kana CPU zviwanikwa pachikumbiro chechikamu. Iyo ndege yekudzora inochengetedza nhanho zvinobuda, saka nhanho dzisina kuchinjika dzinosvetuka pakudzokorora, kuchengetedza komputa uye kugadzira maDAG makuru anoshanda.
Mastering Kubeflow uye ML Pipeline Orchestration
Kubeflow ndeye yakavhurika-sosi yekushandisa iyo inomhanyisa muchina wekudzidza workflows paKubernetes, ichishandura modhi yekudzidziswa uye kuendesa kune inogadzirwazve, ine midziyo mapaipi. Izvo zvine basa nekuti zvinoita kuti zvikwata zviyere ML nenzira imwechete yavanoyera yemazuva ano gore software. Kubeflow uye ML Pipeline Orchestration chivakwa chekuvaka chinobata mhando yemhando, mutengo wezvivakwa, latency, uye kuvimbika pachiyero. Kuvaka kunzwisisa kwakadzama, bata Kubeflow uye ML Pipeline Orchestration semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodikanwa, kujekesa fungidziro, uye patsanura izvo system inogona kuita nekuvimbika kubva kune ichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Kubeflow uye ML Pipeline Orchestration inokwidziridza zvivakwa, data, uye sarudzo dzezvivakwa zvinopesana nekuvimbika uye mutengo. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore. Panguva imwecheteyo, Kukwirisa imwe bhenji kunogona kuvanza yakafara system kushaya simba. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore.
Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Dzidzo yehunyanzvi inobatsira zvikwata kusarudza murwi wakakodzera, kwete iwo mutsva chete.
Dzidzo yehunyanzvi inobatsira zvikwata kusarudza murwi wakakodzera, kwete iwo mutsva chete. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Sarudzo dzeinjiniya dziri nani dzinoderedza zviitiko zvekuvimbika mukugadzira.
Sarudzo dzeinjiniya dziri nani dzinoderedza zviitiko zvekuvimbika mukugadzira. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Mutengesi anoronga pombi yehusiku yeKubeflow iyo inopinza data rekutengesa, inodzokorodza yekuda-yekufanotaura modhi, uye oisundira kuKServe kuti iite fungidziro.
Lab yekutsvagisa inoshandisa Katib kumhanya mazana eyakafanana hyperparameter miedzo paGPU cluster, otomatiki kusarudza iyo yakanyanya kurongeka.
Bhangi rinovaka pombi yekuona hutsotsi hunogona kudzokororwa uko kwega kwega odhisheni yekuteerera inogona kudzokorodza nhanho dzekudzidzira kubva kune zvakachengetwa.
Kutanga kunoshandisa maseva enotibhuku paKubeflow saka data masayendisiti prototype modhi dzinopedza zvakananga mumapaipi ekugadzira pasina kunyorazve kodhi.
Maitiro Ekuita
Kubeflow uye ML Pipeline Orchestration mukuita
Mutengesi anoronga pombi yehusiku yeKubeflow iyo inopinza data rekutengesa, inodzokorodza yekuda-yekufanotaura modhi, uye oisundira kuKServe kuti iite fungidziro.
Mutengesi anoronga pombi yehusiku yeKubeflow inopinza data rekutengesa, inodzoreredza modhi yekufanotaura, uye inoisundira kuKServe yekufungidzira Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura maburi emhando kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Kubeflow uye ML Pipeline Orchestration mukuita
Lab yekutsvagisa inoshandisa Katib kumhanya mazana eyakafanana hyperparameter miedzo paGPU cluster, otomatiki kusarudza iyo yakanyanya kurongeka.
Labhu yekutsvagisa inoshandisa Katib kumhanyisa mazana eyakafanana hyperparameter miedzo pachikwata cheGPU, ichisarudza otomatiki iyo yakanakisa yekumisikidza Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvekubereka uye kukanganisa mutengo nekufamba kwenguva.
Kubeflow uye ML Pipeline Orchestration mukuita
Bhangi rinovaka pombi yekuona hutsotsi hunogona kudzokororwa uko kwega kwega odhisheni yekuteerera inogona kudzokorodza nhanho dzekudzidzira kubva kune zvakachengetwa.
Bhangi rinovaka pombi inodzokororwa yekubiridzira-yekuona pombi uko kwega kwega ongororo yekutevedzera inogona kudzokorodza nhanho dzekudzidzira kubva kune zvakavharirwa zvigadzirwa Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Kubeflow uye ML Pipeline Orchestration mukuita
Kutanga kunoshandisa maseva enotibhuku paKubeflow saka data masayendisiti prototype modhi dzinopedza zvakananga mumapaipi ekugadzira pasina kunyorazve kodhi.
Kutanga kunoshandisa maseva enotibhuku paKubeflow saka masayendisiti edatha prototype modhi anopedza zvakananga mumapombi ekugadzira asina kunyorazve kodhi kodhi Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese kubudirira kwekubudirira uye kukanganisa mutengo nekufamba kwenguva.
Njodzi & Guardrails
Kugadzirisa imwe bhenji kunogona kuvanza yakafara system kushaya simba.
Infrastructure uye mari yekugadzirisa inowanzotarisirwa pasi.
Chengetedzo uye kucherechedzwa mapundu anogona kukura sezvo masisitimu anowedzera kuoma.
Implementation Roadmap
Tsanangura latency, mhando, uye mutengo zvinangwa usati waitwa.
Tsanangura latency, mhando, uye mutengo zvinangwa usati waitwa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Benchmark pasi pechokwadi mutoro uye data mamiriro.
Benchmark pasi pechokwadi mutoro uye data mamiriro. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Chishandiso chekutarisa zvikanganiso, kudonha, uye mushandisi maitiro.
Chishandiso chekutarisa zvikanganiso, kudonha, uye mushandisi maitiro. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Gadzirira nzira dzekudzosera kumashure uye dzezviitiko usati wawedzera.
Gadzirira nzira dzekudzosera kumashure uye dzezviitiko usati wawedzera. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.