Ke hoʻokolo nei i ka ʻimi ʻimi ʻana me AI-Powered Agents a me DevOps Tools
Hoʻolauna
I loko o nā kaiapuni o kēia lā, ʻo ka hoʻokolokolo a me ka hoʻoholo ʻana he mea koʻikoʻi ia o nā hana DevOps. Eia nō naʻe, hiki i ka hoʻokolokolo ʻana i nā hanana hana lima ke hoʻopau i ka manawa, hiki ke hewa, a koi pinepine i ka ʻike nui. No ka hoʻoponopono ʻana i kēia mau pilikia, e ʻimi mākou i ka hoʻohui ʻana o Kiro AI-powered agents me AWS DevOps Agent a me DSPy no ka hoʻokolokolo a me ka hoʻoholo ʻana i nā hanana hanana.
E hoʻomaopopo i nā ʻāpana
Ma mua o ka luʻu ʻana i ka hoʻohui ʻana, e hoʻomaopopo kākou i nā ʻāpana pili:
- Kiro AI-Powered Agents: ʻO Kiro kahi kahua i hoʻohana ʻia e AI e hiki ai ke hoʻokumu i nā mea hana maʻamau no ka hoʻomaʻamaʻa ʻana i nā hana a me nā kahe hana. Hiki ke aʻo ʻia kēia mau ʻelele ma nā kumu ʻikepili like ʻole, me nā logs, metrics, a me nā faila hoʻonohonoho.
- AWS DevOps Agent: ʻO ka AWS DevOps Agent he mea hana e hiki ai ke hoʻololi i nā hana a me nā kahe hana ma AWS. Hāʻawi ia i kahi ala maʻalahi a hiki ke hoʻololi i nā hana, e like me ke kau ʻana i nā noi, ka nānā ʻana i ka hana, a me nā pilikia pilikia.
- DSPy: ʻO DSPy kahi waihona Python e hāʻawi ana i kahi ala maʻalahi a maikaʻi hoʻi e launa pū me DSPy, kahi paepae ʻikepili ʻōiwi. Hiki iā DSPy ke hana i nā pipeline data maʻamau, ka hoʻoili ʻikepili, a me ka ʻike ʻike ʻike.
Hōʻuluʻulu Hoʻohui
ʻO ka hoʻohui ʻana o Kiro AI-powered agents me AWS DevOps Agent a me DSPy e pili ana i kēia mau hana:
- Data Collection: ʻOhi ka AWS DevOps Agent i ka ʻikepili mai nā kumu like ʻole, e like me nā logs, metrics, a me nā faila hoʻonohonoho.
- Hoʻoponopono ʻIkepili: Hoʻohana ʻia ka ʻikepili i hōʻiliʻili ʻia me ka hoʻohana ʻana iā DSPy, kahi e hiki ai ke hana i nā paipu ʻikepili maʻamau, ka hoʻoili ʻana i ka ʻikepili, a me ka ʻike ʻike ʻike.
- Agent Training: Hoʻohana ʻia ka ʻikepili i hana ʻia e hoʻomaʻamaʻa i ka ʻoihana Kiro AI-powered, e hiki ai i ka ʻelele ke aʻo i nā ʻano a me nā anomalies i ka ʻikepili.
- Incident Investigation: Ke loaʻa kahi hanana, hoʻāla ʻia ke Kiro AI-powered agent e noiʻi i ka hanana me ka hoʻohana ʻana i nā hiʻohiʻona a me ka ʻikepili i aʻo ʻia.
- Resolution: Hāʻawi ka luna i nā manaʻo no ka hoʻonā hanana, hiki ke hoʻokō ʻia me ka AWS DevOps Agent.
Ka Laʻana Code
Eia kahi laʻana code maʻalahi e hōʻike ana i ka hoʻohui ʻana o Kiro AI-powered agents me AWS DevOps Agent a me DSPy:
lawe mai os
lawe mai i json
mai kiros import Agent
mai dspy lawe mai i ka DSPy
aws_config = json.load(wehe('aws_config.json'))
# E hana i kahi ʻoihana Kiro AI-powered
luna = Agent(
inoa='incident_investigation',
description='Hoʻokolokolo a me ka hoʻonā ʻana i ka hanana hanana ',
kükohu='incident_investigation_model'
)
# Hana i kahi hiʻohiʻona DSPy
dspy = DSPy(
host='localhost',
awa=8080,
mea hoʻohana = 'admin',
password='password'
)
# E wehewehe i kahi pipeline data me ka hoʻohana ʻana iā DSPy
pipeline = dspy.pipeline(
inoa='incident_investigation_pipeline',
description='Automed incident investigation pipeline',
kumu = ['logs', 'metrics', 'configuration']
)
# E hoʻomaʻamaʻa i ka Kiro AI-powered agent me ka hoʻohana ʻana i ka pipeline data
agent.train(
paipu = pipeline,
ʻikepili=dspy.data(
inoa='incident_investigation_data',
wehewehe = 'ʻIkepili noiʻi hanana hanana'
)
)
# Hoʻomaka i ka ʻoihana Kiro AI-powered e noiʻi i kahi hanana
hanana = {
'id': 'INC-12345',
'description': 'manawa hoʻopau noi'
}
agent.trigger(
hanana = hanana,
ʻikepili=dspy.data(
inoa='incident_investigation_data',
wehewehe = 'ʻIkepili noiʻi hanana hanana'
)
)
# E kiʻi i nā ʻōlelo aʻoaʻo a ka luna no ka hoʻonā hanana
paipai = agent.recommendations(
hanana = hanana,
ʻikepili=dspy.data(
inoa='incident_investigation_data',
wehewehe = 'ʻIkepili noiʻi hanana hanana'
)
)
# E hoʻokō i nā ʻōlelo aʻoaʻo a ka luna e hoʻohana ana i ka AWS DevOps Agent
aws_config[''ōlelo paipai'] = manaʻo
aws_config['incident_id'] = hanana['id']
aws_config['description'] = hanana ['description']
** 5-10 kiʻekiʻe loa i hoʻohana ʻia i nā kauoha/nā ʻāpana**
Eia ka 5-10 kiʻekiʻe loa i hoʻohana ʻia nā kauoha/snippets no kēia ʻenehana:
- Kiro AI-Powered Agent Creation:
luna = Agent( inoa='incident_investigation', description='Hoʻokolokolo a me ka hoʻonā ʻana i ka hanana hanana ', kükohu='incident_investigation_model' )
2. **DSPy Instance Creation**:
```python
dspy = DSPy(
host='localhost',
awa=8080,
mea hoʻohana = 'admin',
password='password'
)
- Ka wehewehe ʻana i ka Pipeline Data:
pipeline = dspy.pipeline( inoa='incident_investigation_pipeline', description='Automed incident investigation pipeline', kumu = ['logs', 'metrics', 'configuration'] )
4. **Aʻo Kiro AI-Powered Agent**:
```python
agent.train(
paipu = pipeline,
ʻikepili=dspy.data(
inoa='incident_investigation_data',
wehewehe = 'ʻIkepili noiʻi hanana hanana'
)
)
- Kiro AI-Powered Agent Triggering:
agent.trigger( hanana = hanana, ʻikepili=dspy.data( inoa='incident_investigation_data', wehewehe = 'ʻIkepili noiʻi hanana hanana' ) )
6. **Hoʻihoʻi i nā Manaʻo Manaʻo Agen **:
```python
paipai = agent.recommendations(
hanana = hanana,
ʻikepili=dspy.data(
inoa='incident_investigation_data',
wehewehe = 'ʻIkepili noiʻi hanana hanana'
)
)
- AWS DevOps Agent Configuration Loading:
aws_config = json.load(wehe('aws_config.json'))
8. **AWS DevOps Manaʻo Manaʻo Hoʻokō **:
```python
aws_config[''ōlelo paipai'] = manaʻo
aws_config['incident_id'] = hanana['id']
aws_config['description'] = hanana ['description']
- Kii ʻIkepili DSPy:
ʻikepili = dspy.data( inoa='incident_investigation_data', wehewehe = 'ʻIkepili noiʻi hanana hanana' )
10. **Kiro AI-Powered Agent Model Loading**:
```python
kumu hoʻohālike = agent.model(
inoa='incident_investigation_model',
description='Kōkohu hoʻokolokolo hoʻokō 'akomi'
)
Hōʻikeʻike
Eia kahi hiʻohiʻona o ka hoʻohui ʻana me ka hoʻohana ʻana iā Chart.js:
{
"type": "pā",
"ʻikepili": {
"labels": ["Data Collection", "Data Processing", "Agent Training", "Incident Investigation", "Resolution"],
"mau ʻikepili": [
{
"label": "Manawa (kekona)",
"ʻikepili": [10, 20, 30, 40, 50],
"ʻulaʻula": [
"rgba(255, 99, 132, 0.2)",
"rgba(54, 162, 235, 0.2)",
"rgba(255, 206, 86, 0.2)",
"rgba(75, 192, 192, 0.2)",
"rgba(153, 102, 255, 0.2)"
],
"BorderColor": [
"rgba(255, 99, 132, 1)",
"rgba(54, 162, 235, 1)",
"rgba(255, 206, 86, 1)",
"rgba(75, 192, 192, 1)",
"rgba(153, 102, 255, 1)"
],
"BorderWidth": 1
}
]
},
"koho": {
"nā unahi": {
"yAxes": [
{
"kuʻi": {
"beginAtZero": ʻoiaʻiʻo
}
}
]
}
}
}
Hōʻike kēia hiʻohiʻona i ka manawa i lawe ʻia no kēlā me kēia kaʻina i ke kaʻina hoʻohui.
Hoʻoholo
Ma kēia ʻatikala, ua ʻimi mākou i ka hoʻohui ʻana o Kiro AI-powered agents me AWS DevOps Agent a me DSPy no ka hoʻokolokolo ʻana a me ka hoʻonā ʻana i nā kaiapuni maoli. Hāʻawi mākou i kahi hiʻohiʻona kikoʻī o nā mea e pili ana, ke kaʻina hana hoʻohui, a me kahi hiʻohiʻona code maʻalahi e hōʻike ana i ka hoʻohui. Ua hoʻokomo pū mākou i kahi hiʻohiʻona o ka hoʻohui ʻana me ka hoʻohana ʻana iā Chart.js a me kahi papa inoa o nā 5-10 kiʻekiʻe loa i hoʻohana ʻia nā kauoha/snippets no kēia ʻenehana.