curl --request GET \
--url https://api.example.com/api/v1/remediations/{name}{
"apiVersion": "v1",
"kind": "RemediationPlan",
"resourceMeta": {
"name": "remediation-inc-20260319-002-1",
"namespace": "production",
"creationTimestamp": "2026-03-19T15:09:00Z"
},
"spec": {
"name": "remediation-inc-20260319-002-1",
"namespace": "production",
"issueRef": "INC-20260319-002",
"attempt": 1,
"strategy": "Agentic mode: no matching runbook found",
"state": "Completed",
"startedAt": "2026-03-19T15:10:00Z",
"completedAt": "2026-03-19T15:16:00Z",
"result": "Issue resolved after 4 agentic steps",
"agenticMode": true,
"agenticStepCount": 4,
"actions": [],
"creationTimestamp": "2026-03-19T15:09:00Z",
"safetyConstraints": [
"Do not scale below current replica count",
"Verify health for 90 seconds after each action"
],
"evidence": [
{
"type": "action_success",
"data": "ScaleDeployment executed: replicas 3 -> 5",
"timestamp": "2026-03-19T15:11:00Z"
},
{
"type": "health_check",
"data": "All 5/5 pods ready after 45 seconds",
"timestamp": "2026-03-19T15:12:30Z"
}
],
"rollbackPerformed": false,
"rollbackResult": "",
"agenticHistory": [
{
"stepNumber": 1,
"aiMessage": "The deployment has 3 replicas but CPU usage is at 95%. The error rate spike correlates with high CPU. I'll scale up to reduce per-pod load.",
"action": {"type": "ScaleDeployment", "params": {"replicas": "5"}},
"observation": "ScaleDeployment executed successfully. New pods are starting.",
"timestamp": "2026-03-19T15:11:00Z"
},
{
"stepNumber": 2,
"aiMessage": "Pods are starting. Let me observe the metrics to verify the scale-up is helping.",
"action": null,
"observation": "5/5 pods ready. CPU usage dropped to 62%. Error rate decreasing.",
"timestamp": "2026-03-19T15:12:30Z"
},
{
"stepNumber": 3,
"aiMessage": "CPU is now at safe levels and error rate is dropping. Let me also adjust the HPA to prevent this from happening again.",
"action": {"type": "AdjustHPA", "params": {"maxReplicas": "8", "targetCPU": "70"}},
"observation": "HPA updated. maxReplicas=8, targetCPU=70%.",
"timestamp": "2026-03-19T15:14:00Z"
},
{
"stepNumber": 4,
"aiMessage": "The deployment is stable with healthy CPU usage and zero errors. The HPA will handle future load spikes. Issue resolved.",
"action": null,
"observation": "Health verified: all pods ready, error rate 0%, CPU 58%.",
"timestamp": "2026-03-19T15:16:00Z"
}
]
}
}
Retorna os detalhes completos do plano de remediação, incluindo evidencias de execução, informações de rollback, restrições de segurança e histórico de conversacao agentica
curl --request GET \
--url https://api.example.com/api/v1/remediations/{name}{
"apiVersion": "v1",
"kind": "RemediationPlan",
"resourceMeta": {
"name": "remediation-inc-20260319-002-1",
"namespace": "production",
"creationTimestamp": "2026-03-19T15:09:00Z"
},
"spec": {
"name": "remediation-inc-20260319-002-1",
"namespace": "production",
"issueRef": "INC-20260319-002",
"attempt": 1,
"strategy": "Agentic mode: no matching runbook found",
"state": "Completed",
"startedAt": "2026-03-19T15:10:00Z",
"completedAt": "2026-03-19T15:16:00Z",
"result": "Issue resolved after 4 agentic steps",
"agenticMode": true,
"agenticStepCount": 4,
"actions": [],
"creationTimestamp": "2026-03-19T15:09:00Z",
"safetyConstraints": [
"Do not scale below current replica count",
"Verify health for 90 seconds after each action"
],
"evidence": [
{
"type": "action_success",
"data": "ScaleDeployment executed: replicas 3 -> 5",
"timestamp": "2026-03-19T15:11:00Z"
},
{
"type": "health_check",
"data": "All 5/5 pods ready after 45 seconds",
"timestamp": "2026-03-19T15:12:30Z"
}
],
"rollbackPerformed": false,
"rollbackResult": "",
"agenticHistory": [
{
"stepNumber": 1,
"aiMessage": "The deployment has 3 replicas but CPU usage is at 95%. The error rate spike correlates with high CPU. I'll scale up to reduce per-pod load.",
"action": {"type": "ScaleDeployment", "params": {"replicas": "5"}},
"observation": "ScaleDeployment executed successfully. New pods are starting.",
"timestamp": "2026-03-19T15:11:00Z"
},
{
"stepNumber": 2,
"aiMessage": "Pods are starting. Let me observe the metrics to verify the scale-up is helping.",
"action": null,
"observation": "5/5 pods ready. CPU usage dropped to 62%. Error rate decreasing.",
"timestamp": "2026-03-19T15:12:30Z"
},
{
"stepNumber": 3,
"aiMessage": "CPU is now at safe levels and error rate is dropping. Let me also adjust the HPA to prevent this from happening again.",
"action": {"type": "AdjustHPA", "params": {"maxReplicas": "8", "targetCPU": "70"}},
"observation": "HPA updated. maxReplicas=8, targetCPU=70%.",
"timestamp": "2026-03-19T15:14:00Z"
},
{
"stepNumber": 4,
"aiMessage": "The deployment is stable with healthy CPU usage and zero errors. The HPA will handle future load spikes. Issue resolved.",
"action": null,
"observation": "Health verified: all pods ready, error rate 0%, CPU 58%.",
"timestamp": "2026-03-19T15:16:00Z"
}
]
}
}
| Campo | Descrição |
|---|---|
safetyConstraints | Restrições que devem ser respeitadas durante a execução |
evidence | Evidencias coletadas durante a execução (logs, metricas, falhas, rollbacks) |
rollbackPerformed | Se o rollback automático foi acionado |
rollbackResult | Resultado da tentativa de rollback |
agenticHistory | Raciocinio e ações passo a passo da IA (apenas modo agentico) |
agenticMode e true, o array agenticHistory mostra a conversacao completa da IA:
aiMessage: O raciocinio da IA para cada passoaction: A ação concreta proposta (null se for um passo apenas de observacao)observation: O resultado após executar a acaostepNumber: Número sequencial do passo{
"apiVersion": "v1",
"kind": "RemediationPlan",
"resourceMeta": {
"name": "remediation-inc-20260319-002-1",
"namespace": "production",
"creationTimestamp": "2026-03-19T15:09:00Z"
},
"spec": {
"name": "remediation-inc-20260319-002-1",
"namespace": "production",
"issueRef": "INC-20260319-002",
"attempt": 1,
"strategy": "Agentic mode: no matching runbook found",
"state": "Completed",
"startedAt": "2026-03-19T15:10:00Z",
"completedAt": "2026-03-19T15:16:00Z",
"result": "Issue resolved after 4 agentic steps",
"agenticMode": true,
"agenticStepCount": 4,
"actions": [],
"creationTimestamp": "2026-03-19T15:09:00Z",
"safetyConstraints": [
"Do not scale below current replica count",
"Verify health for 90 seconds after each action"
],
"evidence": [
{
"type": "action_success",
"data": "ScaleDeployment executed: replicas 3 -> 5",
"timestamp": "2026-03-19T15:11:00Z"
},
{
"type": "health_check",
"data": "All 5/5 pods ready after 45 seconds",
"timestamp": "2026-03-19T15:12:30Z"
}
],
"rollbackPerformed": false,
"rollbackResult": "",
"agenticHistory": [
{
"stepNumber": 1,
"aiMessage": "The deployment has 3 replicas but CPU usage is at 95%. The error rate spike correlates with high CPU. I'll scale up to reduce per-pod load.",
"action": {"type": "ScaleDeployment", "params": {"replicas": "5"}},
"observation": "ScaleDeployment executed successfully. New pods are starting.",
"timestamp": "2026-03-19T15:11:00Z"
},
{
"stepNumber": 2,
"aiMessage": "Pods are starting. Let me observe the metrics to verify the scale-up is helping.",
"action": null,
"observation": "5/5 pods ready. CPU usage dropped to 62%. Error rate decreasing.",
"timestamp": "2026-03-19T15:12:30Z"
},
{
"stepNumber": 3,
"aiMessage": "CPU is now at safe levels and error rate is dropping. Let me also adjust the HPA to prevent this from happening again.",
"action": {"type": "AdjustHPA", "params": {"maxReplicas": "8", "targetCPU": "70"}},
"observation": "HPA updated. maxReplicas=8, targetCPU=70%.",
"timestamp": "2026-03-19T15:14:00Z"
},
{
"stepNumber": 4,
"aiMessage": "The deployment is stable with healthy CPU usage and zero errors. The HPA will handle future load spikes. Issue resolved.",
"action": null,
"observation": "Health verified: all pods ready, error rate 0%, CPU 58%.",
"timestamp": "2026-03-19T15:16:00Z"
}
]
}
}
{
"apiVersion": "v1",
"kind": "Error",
"error": {
"code": 404,
"message": "Remediation plan not found: remediation-inc-20260319-999"
}
}