I-ZeroOps Infrastructure Orchestration enama-AI Agents kanye ne-LangChain

Isingeniso

Esimeni esiguqukayo esithuthukayo sobunjiniyela besoftware kanye ne-DevOps, isidingo sokucula kwengqalasizinda esisebenza kahle nesabisayo sesilokhu sicindezela kakhulu. Izindlela zendabuko zokuphathwa kwengqalasizinda zivame ukuncika ekucushweni ngesandla nasekubhalweni, okungaholela kumaphutha, ukungahambisani, kanye nezingqinamba. Ukuze kubhekwane nalezi zinselelo, sekuvele ipharadigm entsha: I-orchestration yengqalasizinda ye-ZeroOps nama-agent e-AI kanye ne-LangChain.

Yini i-ZeroOps?

I-ZeroOps iyindlela yoguquko ekuphathweni kwengqalasizinda esebenzisa ama-agent e-AI kanye ne-automation ukuze kuqedwe isidingo sokucushwa ngesandla kanye nokubhala. Ngokuzenzakalela wonke umjikelezo wempilo yengqalasizinda, kusukela ekusetshenzisweni kuye ekukalweni nasekulungisweni, i-ZeroOps inika amandla izinhlangano ukuthi zithole amazinga angakaze abonwe okusebenza kahle, ukukala, nokuthembeka.

LangChain: I-AI-Powered Automation Framework

I-LangChain iwuhlaka lomthombo ovulekile olwenza abathuthukisi bakwazi ukwakha ukuhamba komsebenzi okuzenzakalelayo okunikwa amandla yi-AI besebenzisa imodeli yokuhlela elula, enembile. Ngokuhlinzeka nge-abstraction okusezingeni eliphezulu phezu kobunzima be-AI kanye ne-automation, i-LangChain yenza kube lula ukwakha amapayipi e-automation ayinkimbinkimbi akwazi ukuphatha ngisho nezindawo zengqalasizinda eziyinkimbinkimbi kakhulu.

Ama-AI Agents: Ukhiye We-ZeroOps

Abenzeli be-AI bayizingxenye zesofthiwe ezisebenzisa ukufunda komshini namanye amasu e-AI ukwenza imisebenzi ngokuzenzakalela nokwenza izinqumo. Ngomongo we-ZeroOps, ama-agent e-AI adlala indima ebalulekile ekuqapheni impilo yengqalasizinda, ukuthola okudidayo, nokuthatha izinyathelo zokulungisa ukuze kuqinisekiswe ukusebenza kahle.

I-StackGen ne-OpsVerse: Ukusheshisa i-AI-Driven Automation

I-StackGen kanye ne-OpsVerse angamathuluzi amabili aqanjiwe asheshisa i-automation eqhutshwa yi-AI yobunjiniyela kanye ne-DevOps workflows. I-StackGen iyithuluzi lokukhiqiza ikhodi elivumela abathuthukisi ukuthi bakhe izifanekiso zengqalasizinda yangokwezifiso besebenzisa i-syntax elula, echazayo. Ngakolunye uhlangothi, i-OpsVerse iyinkundla enikeza isikhombimsebenzisi esihlangene sokuphatha izindawo eziningi zengqalasizinda kanye nokuhamba komsebenzi okuzenzakalelayo.

Ukusebenzisa i-ZeroOps nge-LangChain nama-AI Agents

Ukuze usebenzise i-ZeroOps ngama-ejenti we-LangChain kanye ne-AI, sizolandela indlela yesinyathelo nesinyathelo:

Isinyathelo 1: Chaza Izifanekiso Zengqalasizinda

Sisebenzisa i-StackGen, sizochaza izifanekiso zengqalasizinda zangokwezifiso ezichaza ukumiswa kwengqalasizinda oyifunayo. Lokhu kuzobandakanya ukucaciswa kwemishini ebonakalayo, amanethiwekhi, isitoreji, nezinye izinsiza.

ngenisa i-stackgen


isifanekiso = stackgen.Template(
    igama="ingqalasizinda_yami",
    imithombo=[
        stackgen.Resource(
            igama="vm1",
            uhlobo="vm",
            izakhiwo={
                "cpu": 2,
                "inkumbulo": 4,
                "isitoreji": 100
            }
        ),
        stackgen.Resource(
            igama = "vm2",
            uhlobo="vm",
            izakhiwo={
                "cpu": 4,
                "inkumbulo": 8,
                "isitoreji": 200
            }
        )
    ]
)

# Khiqiza ikhodi yengqalasizinda
ingqalasizinda_code = template.generate()

Isinyathelo 2: Dala ama-AI Agents

Sisebenzisa i-LangChain, sizodala amanxusa e-AI akwazi ukuqapha impilo yengqalasizinda, abone okudidayo, futhi athathe izinyathelo zokulungisa. Sizochaza i-ejenti elula ehlola ukusetshenziswa kwe-CPU nezixwayiso uma yeqa umkhawulo othile.

ngenisa i-langchain

# Chaza i-ejenti ye-AI
i-ejenti = langchain.Agent(
    igama="cpu_ejenti",
    uhlobo="cpu",
    izakhiwo={
        "umkhawulo": 80
    }
)

# Chaza i-agent logic
def check_cpu_usage(vm):
    # Bheka ukusetshenziswa kwe-CPU
    cpu_usage = vm.get_cpu_usage()
    uma cpu_usage > agent.properties["threshold"]:
        # Qaphela uma ukusetshenziswa kwe-CPU kudlula umkhawulo
        buyisela "ukusetshenziswa kwe-CPU kweqa i-threshold"
    okunye:
        # Buyisa okuyize uma ukusetshenziswa kwe-CPU kungaphakathi komkhawulo
        buyisela Lutho

Isinyathelo 3: Hlanganisa ama-AI Agents nezifanekiso zengqalasizinda

Sizohlanganisa ama-ejenti e-AI nezifanekiso zengqalasizinda ukuze sakhe ipayipi elihlanganisiwe lokuzenzakalela. Leli payipi lizoqapha impilo yengqalasizinda, libone okungahambi kahle, futhi lithathe izinyathelo zokulungisa ukuze kuqinisekiswe ukusebenza kahle.

ngenisa i-langchain

# Chaza ipayipi le-automation
iphayiphi = langchain.Pipeline(
    igama="ipayipi_lami",
    ama-agent=[i-ejenti],
    izifanekiso=[isifanekiso]
)

# Sebenzisa ipayipi le-automation
pipeline.run()

Imiyalo/Amazwibela Aphezulu Okuyi-5-10

Nayi imiyalo/ amazwibela aphezulu angu-5-10 asetshenziswa kakhulu e-LangChain nama-AI ejenti:

1. langchain.Agent(igama="cpu_agent", type="cpu", properties={"threshold": 80})
2. stackgen.Template(igama="my_infrastructure", imithombo=[...])
3. langchain.Pipeline(igama="my_pipeline", agents=[i-ejenti], izifanekiso=[isifanekiso])
4. i-ejenti.run(hlola_cpu_ukusetshenziswa(vm))
5. isifanekiso.generate()
6. langchain.Agent.update_properties(i-ejenti, {"threshold": 90})
7. stackgen.Resource(igama="vm1", type="vm", properties={"cpu": 2, "memory": 4, "storage": 100})
8. langchain.Pipeline.remove_ejenti(ipayipi, i-ejenti)
9. langchain.Agent.add_property(i-ejenti, "isaziso", Iqiniso)
10. stackgen.Template.update_resource(template, "vm1", {"cpu": 4, "memory": 8, "storage": 200})

Ukubona

Nakhu ukubona ngeso lengqondo okulula kwepayipi lokuzenzakalela kusetshenziswa i-Chart.js:

{
  "type": "bar",
  "idatha": {
    "labels": ["Ukusetshenziswa kwe-CPU", "Ukusetshenziswa Kwememori", "Ukusetshenziswa Kwesitoreji"],
    "idathasethi": [
      {
        "label": "Threshold",
        "idatha": [80, 80, 80],
        "backgroundColor": "rgba(255, 99, 132, 0.2)",
        "borderColor": "rgba(255, 99, 132, 1)",
        "BorderWidth": 1
      },
      {
        "label": "Okwangempela",
        "idatha": [70, 70, 70],
        "backgroundColor": "rgba(54, 162, 235, 0.2)",
        "borderColor": "rgba(54, 162, 235, 1)",
        "BorderWidth": 1
      }
    ]
  },
  "izinketho": {
    "isihloko": {
      "Display": iqiniso,
      "text": "Ipayipi elizenzakalelayo"
    },
    "izikali": {
      "yAxes": [
        {
          "Display": iqiniso,
          "imikhaza": {
            "beginAtZero": kuyiqiniso
          }
        }
      ]
    }
  }
}

Lokhu kuboniswa kubonisa i-CPU yangempela, inkumbulo, nokusetshenziswa kwesitoreji uma kuqhathaniswa namanani e-threshold. Ipayipi elizenzakalelayo lingasebenzisa le datha ukuze lithole okudidayo futhi lithathe isinyathelo sokulungisa.

Isiphetho

I-orchestration yengqalasizinda ye-ZeroOps enabenzeli be-AI kanye ne-LangChain iyindlela eguquguqukayo yokuphathwa kwengqalasizinda eqeda isidingo sokucushwa ngesandla kanye nokubhala. Ngokusebenzisa ama-agent e-AI kanye ne-automation, izinhlangano zingafinyelela amazinga angakaze abonwe okusebenza kahle, ukuqina, nokuthembeka. Nge-StackGen ne-OpsVerse, abathuthukisi bangasheshisa i-automation eshayelwa yi-AI yobunjiniyela kanye nokugeleza komsebenzi kwe-DevOps. Ngokulandela indlela yesinyathelo ngesinyathelo echazwe kulesi sihloko, abathuthukisi bangasebenzisa i-ZeroOps ngama-ejenti we-LangChain kanye ne-AI ukuze bakhe ipayipi elihlanganisiwe lokuzenzakalela eliqapha impilo yengqalasizinda, lithole okudidayo, futhi lithathe izinyathelo zokulungisa ukuze kuqinisekiswe ukusebenza kahle.