Juniper Yakazara Stack Input, Maximum Output
USER GUIDE
Full Stack Input, Maximum Output:
Maitiro Ekuita Yakanyanya yeAI muNetworking
Kushandisa simba remhando yepamusoro-ye-yemhando yakazara networking stack kuendesa yakasarudzika zviitiko
Kufunga patsva campisu nebazi networking yenguva yeAI
MaCEO pasi rese akapa zvirevo zvemakambani kuti atumire artificial intelligence (AI) mubhizinesi rese. Vanovavarira kushandura mashandiro uye kupinda mumari yakavanzika. Uye vatengesi muzvikamu zvese, kusanganisira IT networking, vane shungu dzekushandisa mukana uyu.
Kune vatungamiri venetworking vanobata zvakaoma uye zvinodhura campisu uye nharaunda dzebazi, mibvunzo yakakosha yabuda:
• Mangani advantagAI inogona kunyatso kuburitsa?
• Ndeipi yakakodzera kushivirira njodzi?
• Ndeipi nzira yakanakisa yekumberi yekuwedzera zvinobuda?
Nezvakawanda sarudzo dziripo dzekutumirwa, izvo chaizvo zvinounzwa nemutengesi kufanoona, kugona, uye hunyanzvi zvakanyanya kukosha kupfuura nakare kose. Uye vatengesi vari kutevera AI vane nharo dzakapatsanurwa muzvikamu zvishoma zvakakura, kusanganisira:
- Siloed, niche vatengesi vane akasiyana AI masimba avo vasingakwanise kuendesa yakazara stack c.ampisu nekubatanidzwa kwebazi
- Vatengesi vane akasiyana bhoti-paAI mhinduro dzinogadzira fungidziro yeakazara stack kushanda zvakanaka.
- Vatengesi vane akapupurirwa akazara stack zvivakwa zvakagadzirirwa kubva pasi kusvika kune kushandisa AI yakazara kugona.
Dzidza zvakawanda nezveJuniper's AI-Native uye gore-yekuzvarwa yakazara stack mhinduro portfolio.
Dzidza zvakawanda →
Iyo yekupedzisira inomiririra shanduko yakakosha munetwork:
Kubatanidzwa kwakasimba pakati pezvakanakisa-zve-kubereka network network zvikamu uye zvitsva zveAI-Native maficha ari kutungamira kune ari nani mushandisi uye ruzivo rwevashandisi-kutsanangura patsva zvinorehwa nezwi rekuti "full stack" mune yemazuvano network network.
Juniper anotenda kuti mazuva ano anotungamira-kumucheto akazara stack network anofanirwa kuve ane simba uye ane scalable mukutsigira kubuda kwezvido zvebhizinesi. Uye ivo vanofanirwa kusanganisira AI uye otomatiki masimba ayo anorerutsa manejimendi uye slash mutengo uchivandudza nekuchengetedza ruzivo rwevashandisi kubva pakutanga kusvika pakupedzisira.
Iyi ebook inovhara nyaya irikubuda. Inoongorora basa re data muAI networking uye kukosha kwekuvharira bhizinesi-kirasi, yakazara-stack mhinduro. Iyo zvakare inoongorora kukosha kwemhando ye data yekuisa kuti ive nechokwadi chekubuda kwakanyanya kweAI mhinduro muIT networking.
Ngatitangei
max·i·mum out·put [zita]
Kubudirira kwekuita kwepamusoro-soro uye kugona mukushanda kwetiweki, kunoratidzwa nekuunza zvakasarudzika uye zvakachengeteka zviitiko zvemushandisi muLAN neWAN network. Izvi zvinosanganisira shanduko chiyero uye agility, kuita zviri nani, mashandiro ari nyore, uye kuwana yakaderera TCO uye OpEx.
Key takaways
Kuburikidza nehunyanzvi hwakaita sekufungidzira analytics uye kugadzirisa, otomatiki, uye nehungwaru network yekutarisa, AI yakabuda sesimba rinoshandura munetwork. Muna campisu uye akagovera nharaunda yebazi, iyo chaiyo "full stack" nzira inogona kuwedzera kuderedza kuoma uye mutengo.
1. Chokwadi yakazara stack inopfuura "marchitecture"
Zano razvino rinoshandisa yakabatana Hardware uye software nzira (kusanganisira yeAI), inotsigirwa ne100% yakavhurika API yekuvaka kufambisa mashandiro uye kugadzirisa zviitiko.
2. AI mune networking ndeyepamusoro-inokanganisa, njodzi yakaderera
AI munetworking inomira pachena nekugona kwayo kuendesa nekukurumidza, kunoenderana, uye kwakakosha maitiro kune vashandisi neIT.
3. Best-of-breed, full stack input inowedzera kubuda
Kuunganidza nekushandisa zvinopinda kubva kuLAN, WAN, chengetedzo, uye nemhiri kweAI inopa mikana isati yamboitika.
4. Kufanoona uye kukura zvine basa
Izvo zvakakosha kuti uise akakura uye uchienderera-kudzidza data sainzi algorithms kune yakanyatsogadziriswa data seti.
5. Sangano rinozivisa kuenderera mberi kwekuimba
Kupfuura matekinoroji matekinoroji, kurongeka kwakaringana uye kurongeka mukati mezvikwata zvevatengesi kwakakosha.
6. AI-Native yakazara stack outperforms
Juniper inopa iyo indasitiri chete AI-Native uye cloudnative yakazara stack mhinduro inogona kushandura networking mikana.
Zvipingamupinyi zvakakura zvekubudirira kweNetOps zvinosanganisira shortage yevashandi vane hunyanzvi, akawandisa manejimendi maturusi, yakashata network data mhando, uye kushomeka kwemuchinjiko-domain kuoneka, maererano neongororo yeEMA.
Vanoda kusvika makumi maviri neshanu muzana ezvikwata zvetiweki zvinoshanda zvichiri kushandisa pakati pe25-11 maturusi ekutarisa, manejimendi, uye kugadzirisa matambudziko.
30% yematambudziko etiweki anokonzerwa nezvikanganiso zvemanyorero
Chipikirwa chisingarambiki cheAI mune networking
Nhasi campisu nemanetiweki ebazi anoshanda seyese inotenderera uye tsinga masisitimu ebhizinesi.
Ivo vanofambisa kuyerera kwakakosha kwedata uye vanogonesa nekukurumidza, mhinduro dzehungwaru.
Imwe neimwe network yekubatanidza pulses ine mukana wekutyaira kugadzirwa uye hunyanzvi.
Asi kuchengetedza izvi zvakabatana web hazvina kumbooma zvakadaro.
Zvikwata zveIT zviri kunetsekana nekukurumidza kubuda kwebhizinesi zvinodiwa. Ivo vakatarisana nekuoma kwekuchengetedza nzvimbo dzekurwisa dzinogara dzichiwedzera kubva pakutyisidzira kwakaoma. Uye ivo vanofanirwa kukwikwidzana nekurwiswa kwemidziyo mitsva, mhando dzekubatanidza, uye kuwanda kwekushandisa kutyaira bandwidth zvinodiwa.
Kuenzanisa kudiwa kwekuyera kupesana nezviwanikwa uye zvipingamupinyi zvebhajeti uye kushomeka kwehunyanzvi hwehunyanzvi kunongosanganisa kuoma.
Mumamiriro ezvinhu aya, AI yakabuda sesimba rinoshandura zvechokwadi mumambure. Muchokwadi, iyo yakanyanya kukwirisa AI networking mhinduro dzatove kudzikisira zvakanyanya uye, mune dzimwe nguva, kunyange kubvisa akawanda chaiwo-epasi ekurwadziwa mapoinzi. Exampzvimwe zvinosanganisira:
- Predictive analytics uye kugadzirisa: AI-powered network manejimendi maturusi anogona kuongorora chaiyo-nguva data uye kufanotaura zvingangoitika zvinhu zvisati zvaitika. Izvi zvinogonesa proactive kugadzirisa uye kuderedza downtime. Inosanganisira kuona zvinogona kutyisidzira kuchengetedza, kuona anomalies, uye optimize network kuita.
- Automation uye orchestration: AI-inokwidziridzwa otomatiki inogonesa network kuzvirapa, kuzvigadzirisa, uye kuzvigadzirisa. Izvo zvese zvinotungamira kukudzikisira kupindira kwemanyorero uye kuwedzera kwese kunyatsoshanda uku uchisimudza mushandisi uye mushandisi zviitiko. AI-powered orchestration maturusi anogona zvakare kuita otomatiki maitiro akaomarara, akadai setiweki kupa uye shanduko manejimendi.
- Hungwaru network yekutarisa uye ruzivo: AI-powered yekutarisa maturusi anopa chaiyo-nguva kuoneka mukuita kwetiweki uye inogona kupa maitiro ekuona uye kugonesa kuita sarudzo inotungamirwa nedata.
AI-inotyairwa analytics inogona kuona mafambiro, kuona mapatani, uye kupa kurudziro ye optimization, chengetedzo, uye kuronga kugona.
Nepo aya marudzi ekugona aripo nhasi, ndiwo akasarudzika uye kwete akajairwa. Mazhinji mhinduro haana kubatanidzwa uye data inodiwa kushandura zvakanyanya mashandiro ezuva nezuva.
"Kana iwe uchida kuita otomatiki tier 2/tier 3 kwaunonyura mukati metiweki stack uye edza kufunga kuti dambudziko re [network] riri papi uye kuti rinogadziriswa sei-yakawanda chinangwa chakajairika, domain-agnostic AIOps mapuratifomu haaiti. ita izvozvo; havasi nyanzvi dzenzvimbo.”
Shamus McGillicuddy, Mutevedzeri weMutungamiriri weOngororo, EMA
04. Input nyaya
Maximum inobuda inotanga neyakakwana yekuisa data
Kana zvasvika pakubvisa kukosha kwakazara kubva kuAI uye muchina kudzidza (ML) munetwork, vhoriyamu, kusvika, mhando, nguva, uye kugadzirisa- uye zviwanikwa zvekuongorora nekuita iyo data-yakakosha. Mushure mezvose, zviito zvinogonesa zveAI zvinotsamira pakunzwisisa kwakadzama kwemamiriro ezvinhu aripo.
Kuziva chaizvo zviri kuitika, zviri kuitika, uye kuti sei zvichiitika kwakakosha pakuzivisa mhinduro dzakakodzera nenguva. Uye data yemhando ndiyo ibwe rekona rezvese.
Sezvinongoita maitiro ekugadzira waini yakasarudzika zvinoenderana nezvakasiyana siyana, chizvarwa chemhando yedata yeAI mukushanda kwemambure kunoitawo. Zvakafanana nekuti waini inoda sei mazambiringa akakodzera, ivhu, uye nguva yekuchembera, hunyanzvi hwetiweki, kushanda nesimba, uye moyo murefu zvese zvakakosha mukurera maseti edata akasiyana ane ruzivo rwakanyatsonyorwa uye rwakanyatsochengetedzwa.
Chero ani zvake anogona kuunganidza yekutanga data pane network hutano uye kuidyisa muAI injini. Nekudaro, kusimudzira inonyatso kanganisa AI inokwanisa kugonesa yakasarudzika mushandisi ruzivo uye kudzikisira manyepo enhema kunosanganisira kufunga kwakawanda. Kuti uwane izvi zvinangwa, vatengesi vanofanirwa kufunga nezve zvese kubva kuhurongwa hwesangano kusvika kune hardware / software kuvandudza, data spectrum, uye seti yezvishandiso. Zvakare, zvakakosha kushandisa vanhu vakuru uye nekuenderera mberi nekudzidza data sainzi maalgorithms kune akanyatso curated data seti.
Uyezve, kuwedzera kuburitsa kubva kuAI munetwork kunoenderana nenhamba uye hupamhi hwekupinza data. Uye apa ndipo chaipo panowanikwa mhinduro zhinji dzeAI networking. Parizvino, mamwe maIT networking mhinduro anogona kuunganidza data kubva kuLAN, vamwe kubva kuWAN. Asi mhinduro shoma dzinogona kuunganidza uye kushandisa data kubva kuLAN neWAN (nekupfuura) zvinobudirira - yatinodaidza kuti "full stack." Izvi zvinosimbisa kukosha kwakakosha kwekuona kwemutengesi mukuona kubatanidzwa nekudyidzana.
Basa rekuisa vs kubuda kweAI networking kuvandudzwa
| LAN yakanaka kana WAN | Zvirinani LAN uye WAN | Yakakura LAN, WAN, chengetedzo, nzvimbo, uye nezvimwe zvine AI-Native kugona |
| Inopa yakakamurwa view ye networking performance uye chengetedzo | Inotanga kupa zvakawanda zvakakwana view yekushanda kwetiweki, ichigonesa maAI masisitimu kuita sarudzo dzine ruzivo | Inoendesa yakazara data seti uye inopa panoramic view iyo inogonesa AI masisitimu kuti awane kugona kwavo kuzere |
| Benefits snapshot: Iyo yakaganhurirwa chiyero inodzora zvinogoneka mabhenefiti, goho kusimudzira kwekutanga mukubudirira uye kutyisidzira kutariswa. | Benefits snapshot: Inotsigira kuvandudzwa kuri pakati nepakati mukutonga kwetiweki, kudzikisira nguva uye kuona nyaya yakaoma. | Benefits snapshot: • Inopa simba AI kuti inyatso kukwenenzvera mashandiro etiweki • Inowedzera kuchengeteka nekufungidzira kutyisidzira kuongororwa • Inopa ruzivo rwemunhu wega |
Kufamba kupfuura echinyakare uye achangoburwa AI networking modhi yevazhinji vatengesi, Juniper's AI-Native yakazara stack nzira inomiririra unotevera muganho mune network innovation.
05. Kuvandudza zvinobuda
Iyo AI-Native yakazara stack nzira inosimudzira network
Parizvino, takaona kuti nei data remhando riri iro ropa reAI uye nei yakanyanya kuburitsa munetwork ichitora data remhando kubva kunetiweki yese. Mubvunzo muhombe unotevera ndewekuti: Ndeipi nzira yakanakisa yekuwana nekushandisa yemhando data pamatanho ese ekuvandudza mabudiro etiweki?
Iyo yakanakisa zano inoshandisa yakabatana nzira kuburikidza neindasitiri-inotungamira Hardware uye software stacks-yakazara stack-inogadzirisa mashandiro, kufambisa mashandiro, nekuvandudza ruzivo rwevashandisi uye chengetedzo. Inotsigirwa ne microservices gore uye 100% yakavhurika API architecture kuti iwedzere kune mamwe anotungamira mhinduro mumadomasi, akadai se5G, ITSM, mapuratifomu ekutaurirana, cybersecurity, uye kufamba.
Juniper iri kushandura chinyakare networking data collection nekubata networking madivayiri sema sensors, kutora yakazara data data kubva mhiri kweLAN neWAN, pamwe nekubatanidza chengetedzo uye nzvimbo-yakavakirwa mapeji. For exampuye, zvinhu zvakakosha zvemaitiro edu zvinosanganisira (ona peji 12 yemufananidzo muhombe):
- Yakavandudzwa yekupedzisira-kusvika-kumagumo telemetry: Kuyera 150+ chaiyo-nguva isina waya mushandisi inotaura kuburikidza nekushambadzira telemetry kubva kune marouters, switch, uye firewall, inosimudzirwa neMist AI ™ yekufungidzira analytics.
- Cloud-native, microservices architecture: Kutsigira iyo chaiyo-nguva kugadzirisa kweAI data uye kugonesa kuwedzera scalable, kusimba, uye kushanda kwakanaka kwetiweki manejimendi masisitimu.
- Yakajairwa AI injini: Kubatanidza network yekuongorora data uye maitiro ekuita sarudzo pasi peimwe chete, yakangwara sisitimu inofambiswa neMist AI inofambisa mashandiro akakwenenzverwa, kufembera kugadzirisa matambudziko, uye kudzidzira kudzidzira mukati metiweki yese ecosystem.
Kuburikidza nekuenderera mberi kweruzivo rwemushandisi kudzidza kwakavakirwa pane yakadzama telemetry data, Juniper inobatanidza application data pamwe netiweki data. Izvi zvinoita kuti iyo AI sisitimu idzidze nezve maapplication ari kushandiswa uye kufanotaura zvingangokanganisa pachiitiko chemushandisi chekushandisa zvichibva pane akashata network mamiriro.
Pamusoro pezvo, kupayona kwedu AI-Native Virtual Network Assistant, Marvis™, inorerutsa manejimendi uye kugadzirisa matambudziko. Marvis inoratidzira yekukurukurirana interface yekugadzirisa dambudziko rekugadzirisa uye otomatiki chiito chimiro, ichityaira inoenderera mberi nekuvandudza network. Marvis zvakare inoratidzira Marvis Minis, iyo indasitiri yekutanga yedhijitari ruzivo mapatya. Maminisi anotarisisa nyaya dzekubatanidza dzisati dzaitika, zvichiwedzera kudzivirira vashandisi kubva kune zvinoshungurudza network zviitiko.
Mukuru campisu uye yakagovaniswa nharaunda yebazi, iyi musanganiswa wekugona ndeyekuchinja kwemutambo. Iyo inobvisa zvinobudirira kuburitsa, kugadzirisa matambudziko, uye kugadzirisa zvinonetsa zvinokwidza mitengo, kutambanudza zvikwata zveIT kusvika pamiganho yavo, inobvisa ruzivo rwevashandisi, uye inomisa scalability uye agility. Pamwe chete, ivo vanosanganisira shanduko yechokwadi mune yebhizinesi networking nzira iyo inongoramba ichivandudza nekufamba kwenguva.
Kuona mufananidzo mukuru
Nheyo yemazuva ano yakazara-stack network yakakosha kune yayo ine simba hunhu uye inogonesa kusanganisa isina mutsetse mune itsva networking domains-uye mberi. Kuwedzera kuchinjika kuchave mucherechedzo wenguva nyowani muIT network, kukanganisa echinyakare TCO modhi yeakasimbiswa matekinoroji uye kushandura ruzivo rwetiweki kune vese vashandisi nevashandisi. Heano mashoma anosarudza exampmashoma ekugona anoratidza kuti Juniper iri kufungidzira sei yakazara stack mashandiro:
MUFANANIDZO 1
Tsigiro yeAI-Native inoramba ichiwedzera nekufamba kwenguva: iyo muzana yevatengi IT network matikiti anogadziriswa neAI mukati memakore akati wandei.
Integrated nzvimbo masevhisi
Wireless yekuwana nzvimbo (APs) iyo inokwirisa 16-element Bluetooth® antenna array yeotomatiki AP yekuisa / kutaridzika uye chaiyo asset kuoneka uye vBLE yechokwadi uye scalable nzvimbo masevhisi anogona kuwedzera mushandisi kubatikana uye kuwedzera mafambiro ebasa mumaindasitiri ese.
Yepamusoro-inoita SD-WAN
Iyo mugero-isina, musangano-yakavakirwa SD-WAN uchishandisa Session Smart Networking yekuvandudza bandwidth mashandisirwo uye nekukasira kukundikana zvichibva pane chaiyo-nguva network mamiriro.
Chengetedza AI-Native Edge
Chengetedzo, WAN, LAN, uye NAC (Network Access Control) mune imwechete yekushanda portal, inopa kuvharika kwepamusoro kwekutyisidzira pawaya-kumhanya, uye nhanho yakakosha kumberi kweAI-Native uZTNA uye.
SASE-based architectures
Seamless data center kubatanidzwa
Indasitiri-yekutanga Virtual Network Assistant (VNA) inopa kupera-kusvika-kumagumo kuoneka uye vimbiso kumatunhu ese emabhizinesi, kubva c.ampisu uye bazi kune data center
Advanced Routing Assurance
AI-Native otomatiki uye ruzivo rwechinyakare kumucheto routing topologies
Inotungamira-kumucheto Wi-Fi 6E uye Wi-Fi 7 hardware
APs dzakagadzirirwa kurerutsa mashandiro etiweki uku uchiwedzera chiyero uye agility. Yakakwira-simba switch yeWi-Fi 7 ine proactive centralized simba uye data manejimendi yekuvaka masisitimu
06. Kupfuura tech
Beyond tekinoroji: kukosha kwehurongwa hwehurongwa
Kuwana zvakanyanya kuburitsa kubva kune yakazara stack networking nzira haingotsamira pane tekinoroji yakaiswa; zvakare inotsamira zvakanyanya pakuumbwa kwesangano.
Kurongeka kwakaringana uye kurongeka pamatekinoroji akasiyana siyana uye mukati mezvikwata pachazvo zvakakosha pakubudirira.
PaJuniper, takagadzira nharaunda yekudyidzana uko zvikwata zvedu zvesainzi yedata uye zvikwata zvekutsigira vatengi zvinoshanda tandem. Panyama uye nekushanda zvakabatana, zvikwata zviviri izvi zvinoshandisa yedu yepamusoro AIOps chishandiso kuti chirambe chakabatana nechaiyo-nguva nyaya dzevatengi uye mhinduro.
Kudyidzana uku kunovimbisa kuti nyanzvi dzedu dzesainzi yedata uye nyanzvi dzedomasi dzinogara dzakaenderana nekuchinja kuri kuita zvinodiwa nevatengi uye kuisa pamberi pemhinduro, zvichiramba zvichifambira mberi.
Nekufamba kwenguva, mubhadharo wacho unowedzera uye nerutsigiro rwakawanda, sekubatanidza mapoinzi edata kubva kune mhinduro seZoom, Matimu, ServiceNow, Cradlepoint, uye Zebra kufembera nekushingaira mashandiro emangwana ekugadzirisa matambudziko pasi kune chimwe chinhu. Uye kufambira mberi kunongoenderera mberi.
Juniper's AIOps inomhanyisa kutumirwa, kurerutsa mashandiro, uye kuderedza TCO.
Dzidza sei.
07. Yakazara murwi ZVINO
Juniper's akasanganiswa mhinduro anovimba nemusanganiswa we telemetry, workflow otomatiki, DevOps, uye ML kugonesa inoshanduka uye inofanotaurwa network. Maitiro edu akazara kuAI mukushamwaridzana kwakatungamira kune kuwanda kwemaindasitiri ekutanga, kusanganisira:
- Kuvimbika kubatana kwevadzidzi, vatengesi, varwere, uye vashandi
- Wedzera uye zorodza Wi-Fi nekugona
- Ziva uye chengetedza nharembozha nemidziyo neNAC
Wired access
Yakavimbika uye yakachengeteka kubatana kwebhizinesi
- Kuvimbika kwekubatana kweIoT, APs, uye wired zvishandiso
- Batanidza uye chengetedza IoT uye vashandisi vane microsegmentation
- Ziva uye chengetedza zvishandiso neNAC
Indoor nzvimbo masevhisi
Ipa ruzivo-based personalized mushandisi zviitiko
- Bata nevadzidzi, vatengesi, varwere, uye vashandi
- Indoor GPS uye nzvimbo yeasset
- Nzvimbo-based analytics
Chengetedza kupinda kwebazi
Kubatana kwakachengeteka, kwakavimbika, uye kusina musono kumahofisi emapazi epasi rose
- Chengetedza SD-WAN/SASE
- Distributed bhizinesi
- Gadzirisa WAN yemakore mapurogiramu
07. Yakazara murwi ZVINO
Juniper's akasanganiswa mhinduro anovimba nemusanganiswa we telemetry, workflow otomatiki, DevOps, uye ML kugonesa inoshanduka uye inofanotaurwa network. Maitiro edu akazara kuAI mukushamwaridzana kwakatungamira kune kuwanda kwemaindasitiri ekutanga, kusanganisira:
- Proactive AI-Inotyairwa RF gadziriso yeakanakisa mawaya zviitiko munzvimbo dzese
- Dynamic packet kubatwa muLAN neWAN, ichipa isingaenzaniswi otomatiki, kuoneka uye kugadzirisa nyaya
- Otomatiki mudzi chikonzero chekuongorora kukurumidza kuongorora uye kugadzirisa nyaya dzenetiweki, kuderedza MTTR uye kubvisa akawanda matambudziko matikiti.
- Iyo AI-Native Digital Chiitiko Mapatya kuti aone nekutarisira angangoita waya, isina waya, uye WAN network matambudziko asati akanganisa vashandisi.
Chokwadi kuzita rayo, yedu AI-Native Yakazara Stack zvakare inotambanukira kupfuura iyo campisu uye bazi uye zvakare kupinda mubhizinesi rakagoverwa. For example:
- Iyo AI-Native VNA inoshandura mashandiro enzvimbo yedata ine hunyanzvi hwekuona uye yakarerutsa ruzivo rwemibvunzo kuburikidza neinonzwisisika yekukurukurirana interface pamwe chete neine chinangwa-based networking (IBN) system, inosimudzira nguva, uye kukurumidza kugadzirisa.
- Juniper Mist Routing Assurance inosimudzira AIOps yepamberi WAN mashandiro, ichipa kuoneka kwenzira uye inobatika manzwisisiro ari nyore kugadzirisa matambudziko, kudzikisa MTTR/MTTI, uye otomatiki midzi chikonzero chekuongorora kumucheto kwebhizinesi.
- AI-Native Chengetedzo inovimbisa kuoneka uye kuisirwa kuburikidza neiyo yakachengeteka yakachengeteka masisitimu ane akanakisa-mu-kirasi kuchengetedzwa kwekutyisidzira mukati meJuniper switch, ma routers, uye APs mhiri c.ampisu, bazi, nzvimbo yedata, uye nharaunda dzemakore, kuwedzera chibereko panetiweki uye zvikwata zvekuchengetedza kuchengetedza
Full stack IYE?
Zvakaoma:
Marchitecture inovimbisa kushanda kwepamusoro asi inopera; cobbled-pamwe chete mhinduro
Humbersome management:
Inoda akawanda manejimendi ekutarisa, kazhinji ane yakaoma CLI
Kubatanidzwa kushoma:
Inoshaya kubatanidza kusina musono pane network network nharaunda uye mhinduro
Reactive:
Inoda mhinduro dzemawoko kune nyaya mushure mekunge dzaitika
Full stack ZVINO
Dynamic:
Yakagadzirwa kuti isangane nezvido zvebhizinesi zvanhasi uye mangwana
AI-Native management:
Yakabatana manejimendi, yakavakwa neAI yakabatanidzwa kubva pasi kumusoro
Kubatanidzwa kwakazara:
Yakabatana chikuva chine inotungamira-kumucheto LAN, WAN, data data, nzvimbo masevhisi, chengetedzo, uye yakavhurika API yedhizaini yekubatanidza isina musono ne ServiceNow, Matimu / Zoom, Cradlepoint, Zebra, nezvimwe.
Proactive:
Inokwanisa kuona nyaya nekudzidzikisa dzisati dzakanganisa vashandisi
Benefits snapshots
Iyo AI-Native yakazara stack maitiro inounza zvisina kumbobvira zvamboitika kune yakaoma campisu uye nzvimbo dzebazi. Heano mashoma epanyika chaiwo examples.
"Iyo network yemushandisi ruzivo iyo Juniper inopa inodarika chero chinhu chipi zvacho pamusika. Kureruka kweJuniper kwekushanda uye kugona kuzvirapa, pamwe chete nemametric emushandisi aanopa, anoshamisa.
Neil Holden, CIO, Halfords
8x inokurumidza kuzorodza network
George Washington University inowedzera zviitiko
Iyo yemazuva ano, inotungamirwa newaya uye isina waya network inorerutsa manejimendi manejimendi uye kugadzirisa matambudziko, zvichitungamira kune zvinogara zvirinani zviitiko zveIT nevashandisi.
Kupfuura US $500k yekuchengetedza pagore
London Borough yeBrent inowedzera kushanda kwevashandi
Iyo AI-Native network inopa IT kuoneka kwakajeka muzvinhu pamwe neyakakurudzirwa kugadzirisa, kugadzirisa zvinoramba zvichinetsa manejimendi.
90%+ kuderedzwa mumatikiti edambudziko retiweki
Halfords inovimba neAIOps yekuchinja kwekutengesa
Nekutenderera kune yegore-yekuzvarwa, AI-Native maitiro, Halfords yakarerutsa manejimendi matambudziko ichigonesa chizvarwa chinotevera chekutengesa zvitoro mhinduro.
Iyo yakazara stack networking chiito chekutungamira
Tichifunga nezve yakakura chiyero che deployments uye shanduko ye networking tekinoroji kusvika nguva pfupi yadarika, kuomarara kwagara kuchitonga c.ampisu nebazi networking. Kuunzwa kweAI-Native Networking inoshandura zvese.
Kunyangwe iyo network inogara ichikura kana kuchinja mhiri campisu uye nharaunda yebazi, nzira yeAI-Native Yakazara Stack inopa mukana usati wamboitika wekucheka zvisina basa kuomarara, senge ma controller uye akapatsanuka manejimendi mapuratifomu, uye kuenderana neakanakisa-e-kubereka mhinduro mhiri kweIT landscape. Inogonawo kupa iyo "chaiyo" nhanho yeAI kugona inodiwa kuendesa yakanyanya kuburitsa, inotsigira yakasarudzika mushandisi uye IT zviitiko pazasi TCO uye OpEx.
Uye sewaini yakanaka, inozongoita nani nekufamba kwenguva.
01. Ziva mukana wePoC
Ziva mukana mune campisu nebazi kuita muPoC (semuenzaniso, saiti nyowani kana kusimudzira mudziyo).
02. Tanga nemuedzo wepasi-panjodzi
Edza AI paUs kuti uendese nehupenyu hwekugadzira traffic uye uone kuti mhinduro dzedu dzinokwana sei sangano rako. Tanga chero kupi zvako mune yakazara stack nechero musanganiswa weWi-Fi, switching, uye/kana SD-WAN mhinduro.
03. Sangana nemusiyano
Ona kuti nzira yeAI-Native inopa sei kuve nyore, kugadzira, uye kuvimbika.
04. Wedzera kutumira kwako
Wedzera kusvika kwako nekubatanidza dzimwe nzvimbo dzakadai se campisu, nzvimbo dzebazi, NAC, nzvimbo dzedata, firewalling, uye Enterprise Edge.
Matanho anotevera
Ongorora iyo Juniper yakazara stack
Enda zvakadzika mune yakazara stack mikana uye mhinduro dze campisu nebazi.
Ongorora mhinduro dzedu →
AI patiri →
Ona Mist AI mukuita
Ona maitiro emazuva ano microservices gore muJuniper Mist AI inopa kuoneka kwechokwadi, otomatiki, uye vimbiso.
Tarisa yedu-inoda demo →
Sei Juniper
Juniper Networks inotenda kuti kubatana hakuna kufanana nekuona kubatana kukuru. Juniper's AI-Native Networking Platform inovakwa kubva pasi kumusoro kuti ikwidze AI kuendesa yakasarudzika, yakachengeteka zvakanyanya, uye inogoneka mushandisi zviitiko kubva kumucheto kusvika kune data data uye gore. Unogona kuwana rumwe ruzivo pa juniper.net kana kubatana naJuniper pa
X (yaimbova Twitter), LinkedIn, uye Facebook.
Mamwe mashoko
Kuti udzidze zvakawanda nezveJuniper Networks AI-Native Networking Yakazara Stack mhinduro, bata mumiriri wako weJuniper kana mudiwa, kana shanyira yedu. websaiti pa: https://www.juniper.net/us/en/campus-and-branch.html
Zvinyorwa uye zvinyorwa
01. Network Management Megatrends 2024:
Skills Gaps, Hybrid uye Multi-Cloud, SASE, uye AI-Inotyairwa Mashandiro. EMA pane-inodiwa webinhale
02. Ibid.
03. Ibid.
04. Iyo NetOps Nyanzvi podcast, chikamu 9: “AI/ ML neNetOps—Kukurukurirana neEMA neNetOps Nyanzvi,” Chikunguru 2024.
© Copyright Juniper Networks Inc. 2024.
Kodzero dzese dzakachengetwa.
Nhoroondo ye Juniper Networks Inc.
1133 Innovation Way
Sunnyvale, CA 94089
7400201-001-EN Gumiguru 2024
Juniper Networks Inc., iyo Juniper Networks logo, juniper.
net, Marvis, uye Mist AI zvikwangwani zvakanyoreswa zveJuniper Networks Incorporated, zvakanyoreswa muUS uye matunhu mazhinji pasi rese. Zvimwe zvigadzirwa kana sevhisi mazita anogona kunge ari ekutengesa eJuniper Networks kana mamwe makambani. Gwaro iri riripo sezuva rekutanga kuburitswa uye rinogona kuchinjwa neJuniper Networks chero nguva. Kwete zvese zvinopihwa zvinowanikwa munyika dzese umo Juniper Networks inoshanda.
Zvinotsanangurwa
- Zita reChigadzirwa: Yakazara Stack Networking Solution
- Mugadziri: Juniper
- Zvimiro: AI-Native uye gore-yekuzvarwa yakazara stack mhinduro portfolio
- Benefits: Yakanyanya kusimba uye scalable network, AI uye otomatiki kugona, kurerutswa manejimendi, yakagadziridzwa mushandisi ruzivo.
Mibvunzo Inowanzo bvunzwa (FAQ)
Ndeapi mabhenefiti akakosha eFull Stack Networking Solution?
Mhinduro yacho inopa ane simba uye anotyisa network, AI uye otomatiki kugona, kurerutswa manejimendi, yakagadziridzwa mushandisi ruzivo, uye yakaderedzwa mitengo.
Kwakakosha sei kupinza data mukuwedzera kuburitsa kweAI mhinduro?
Kupinza data kunoita basa rakakosha mukuona kushanda kweAI mhinduro muIT networking. Kuiswa kwedata remhando yepamusoro kunounza mhedzisiro iri nani.
Zvinyorwa / Zvishandiso
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Juniper Yakazara Stack Input, Maximum Output [pdf] Bhuku reMushandisi Full Stack Input Maximum Output, Stack Input Maximum Output, Input Maximum Output, Maximum Output, Output |
