This cookbook covers the complete setup of the ChatCLI AIOps platform for a real production environment — from installation to validation with chaos engineering.
Prerequisites
- [x]Kubernetes cluster 1.25+- [x]Helm 3.x installed- [x]Prometheus Operator (for ServiceMonitor)- [x]Grafana (for dashboards)- [x]At least one LLM API key (OpenAI, Claude, Google AI)
1. Install the Operator
Install Operator via Helm (CRDs + RBAC + Controllers + Dashboard)
helm install chatcli-operator \
oci://ghcr.io/diillson/charts/chatcli-operator \
--namespace chatcli-system \
--create-namespace
Verify installed CRDs
kubectl get crd | grep platform.chatcli.io
You should see 17 CRDs:aiinsights.platform.chatcli.io
anomalies.platform.chatcli.io
approvalpolicies.platform.chatcli.io
approvalrequests.platform.chatcli.io
auditevents.platform.chatcli.io
chaosexperiments.platform.chatcli.io
clusterregistrations.platform.chatcli.io
escalationpolicies.platform.chatcli.io
incidentslas.platform.chatcli.io
instances.platform.chatcli.io
issues.platform.chatcli.io
notificationpolicies.platform.chatcli.io
postmortems.platform.chatcli.io
remediationplans.platform.chatcli.io
runbooks.platform.chatcli.io
servicelevelobjectives.platform.chatcli.io
sourcerepositories.platform.chatcli.io
Create Secret with API Keys
kubectl create secret generic chatcli-api-keys \
--namespace chatcli-system \
--from-literal=ANTHROPIC_API_KEY=sk-ant-xxx \
--from-literal=OPENAI_API_KEY=sk-xxx
2. Create ChatCLI Instance
apiVersion: platform.chatcli.io/v1alpha1
kind: Instance
metadata:
name: chatcli-prod
namespace: chatcli-system
spec:
replicas: 2
provider: CLAUDEAI
model: claude-sonnet-4-20250514
server:
port: 50051
metricsPort: 9090
tls:
enabled: true
secretName: chatcli-tls
token:
name: chatcli-auth
key: token
apiKeys:
name: chatcli-api-keys
watcher:
enabled: true
targets:
- deployment: api-gateway
namespace: production
metricsPort: 8080
metricsPath: /metrics
- deployment: payment-service
namespace: production
metricsPort: 8080
- deployment: user-service
namespace: production
interval: "30s"
window: "2h"
resources:
requests:
cpu: 500m
memory: 512Mi
limits:
cpu: "2"
memory: 1Gi
persistence:
enabled: true
size: 5Gi
To enable Prometheus metrics collection during incident analysis, add the PROMETHEUS_URL variable via Helm:helm upgrade chatcli-operator oci://ghcr.io/diillson/charts/chatcli-operator \
--set prometheusUrl="http://prometheus-server.monitoring.svc:9090"
TLS Secret: SANs and CA
This is where most installs fail silently. The Instance CR references secretName: chatcli-tls, but the Secret must be generated with two details that openssl req -x509 does not produce by default.
Generate the cert with subjectAltName
Without SANs covering the DNS name the operator uses to dial gRPC, the handshake fails with:
transport: authentication handshake failed: x509: certificate is not valid for any names, but wanted to match chatcli-prod.chatcli-system.svc.cluster.local
Use an explicit openssl.cnf:
cat > openssl.cnf <<'EOF'
[req]
distinguished_name = req_dn
x509_extensions = v_ext
prompt = no
[req_dn]
CN = chatcli-prod.chatcli-system.svc.cluster.local
[v_ext]
subjectAltName = @alt_names
[alt_names]
DNS.1 = chatcli-prod.chatcli-system.svc.cluster.local
DNS.2 = chatcli-prod.chatcli-system.svc
DNS.3 = chatcli-prod
DNS.4 = localhost
EOF
openssl req -x509 -newkey rsa:4096 -sha256 -days 825 -nodes \
-keyout tls.key -out tls.crt -config openssl.cnf -extensions v_ext
Verify with:
openssl x509 -in tls.crt -noout -text | grep -A1 'Subject Alternative Name'
Include ca.crt in the Secret
A self-signed cert is its own CA. If the Secret only contains tls.crt and tls.key, the operator connects but fails with:
transport: authentication handshake failed: x509: certificate signed by unknown authority
The WatcherBridge automatically reads the ca.crt key from the Secret referenced by the Instance and uses it as the trust root — so the Secret needs all three keys:
kubectl -n chatcli-system create secret generic chatcli-tls \
--from-file=tls.crt=tls.crt \
--from-file=tls.key=tls.key \
--from-file=ca.crt=tls.crt # self-signed: cert is its own CA
With ca.crt inside the Secret, you do not need to mount a CA ConfigMap or set SSL_CERT_FILE / CHATCLI_GRPC_TLS_CA on the operator deployment. That env var is a secondary path for multi-Instance setups sharing a CA and requires manual volume mounting (extraEnv + volume).
What if the cert is issued by cert-manager or ACM?
§2.1 above covers the fragile self-signed case. With cert-manager or AWS ACM the setup is simpler, but each issuer has its own gotcha:
| Issuer | ca.crt in Secret? | Where SAN must match | spec.server.address points to… |
|---|
| cert-manager + Let’s Encrypt / public ACME | No — CA already in the system trust store | Public FQDN (e.g. chatcli.example.com) | Public FQDN via Ingress/NLB with gRPC passthrough |
| cert-manager + internal ClusterIssuer (CA) | Yes — cert-manager writes ca.crt into the Secret automatically | dnsNames in the Certificate CR; include in-cluster names | In-cluster Service (<svc>.<ns>.svc.cluster.local) |
| AWS ACM Public | N/A — private key is not exportable | Public FQDN | Public FQDN via ALB/NLB (TLS terminates at the LB) |
| AWS ACM Private CA | Yes — include the Private CA bundle as ca.crt | Set at issuance; include in-cluster names | In-cluster Service |
| Self-signed (manual openssl — §2.1) | Yes — ca.crt=tls.crt (cert is its own CA) | Set via subjectAltName in openssl.cnf | In-cluster Service |
Key notes:
-
Publicly trusted cert → trust already exists. The operator code (
grpc_client.go) only sets RootCAs when a custom CA is provided; without one, Go uses the container’s ca-certificates bundle. That’s why Let’s Encrypt and ACM Public “just work” on the CA side — but spec.server.address must be the public FQDN, not the in-cluster Service, or the SAN won’t match.
-
cert-manager with an internal CA is the cleanest K8s path. The
Certificate CR below emits everything ready for WatcherBridge auto-trust — no manual openssl:
apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
name: chatcli-tls
namespace: chatcli-system
spec:
secretName: chatcli-tls # Same Secret referenced in the Instance CR
issuerRef:
name: internal-ca # ClusterIssuer with kind: CA
kind: ClusterIssuer
commonName: chatcli-prod.chatcli-system.svc.cluster.local
dnsNames:
- chatcli-prod.chatcli-system.svc.cluster.local
- chatcli-prod.chatcli-system.svc
- chatcli-prod
duration: 8760h # 1 year
renewBefore: 720h # renew 30 days before expiry
With Certificate.issuerRef.kind: CA, cert-manager automatically writes ca.crt into the generated Secret — WatcherBridge picks it up directly, no extra config.
-
ACM Public does not fit pod-to-pod gRPC. The private key is not exportable; only use when TLS terminates at the ALB/NLB and the operator dials the public endpoint.
-
ACM Private CA — export the Private CA bundle (
aws acm-pca get-certificate-authority-certificate) and include it as ca.crt in the Secret. From there on, it follows the auto-trust path.
2.2 Link Source Code Repositories (Optional)
Link your monitored applications’ source code repositories for code-aware diagnostics. The AI will receive context from recent commits, code snippets from stack traces, and configuration files.
apiVersion: platform.chatcli.io/v1alpha1
kind: SourceRepository
metadata:
name: api-gateway-repo
namespace: chatcli-system
spec:
url: "https://github.com/myorg/api-gateway.git"
branch: main
authType: token
secretRef: git-token
resource:
kind: Deployment
name: api-gateway
namespace: production
paths: ["cmd/", "internal/"]
language: "Go"
---
apiVersion: platform.chatcli.io/v1alpha1
kind: SourceRepository
metadata:
name: payment-service-repo
namespace: chatcli-system
spec:
url: "git@github.com:myorg/payment-service.git"
branch: main
authType: ssh
secretRef: git-ssh-key
resource:
kind: Deployment
name: payment-service
namespace: production
language: "Java"
apiVersion: platform.chatcli.io/v1alpha1
kind: NotificationPolicy
metadata:
name: prod-notifications
namespace: chatcli-system
spec:
enabled: true
channels:
- name: slack-incidents
type: slack
config:
webhook_url: "https://hooks.slack.com/services/T.../B.../xxx"
channel: "#incidents"
- name: pagerduty-critical
type: pagerduty
config:
routing_key: "R0xxxxxxxxxxxxxxxxxxxx"
- name: email-management
type: email
config:
smtp_host: smtp.gmail.com
smtp_port: "587"
from: aiops@company.com
to: "sre-team@company.com,management@company.com"
secretRef:
name: smtp-credentials
rules:
- name: critical-to-pagerduty
severities: [critical]
states: [Detected, Escalated]
channels: [pagerduty-critical, slack-incidents]
- name: high-to-slack
severities: [critical, high]
states: [Detected, Analyzing, Remediating, Resolved, Escalated]
channels: [slack-incidents]
- name: escalations-to-email
states: [Escalated]
channels: [email-management]
throttle:
maxPerHour: 20
deduplicationWindow: "5m"
apiVersion: platform.chatcli.io/v1alpha1
kind: EscalationPolicy
metadata:
name: prod-escalation
namespace: chatcli-system
spec:
enabled: true
severities: [critical, high]
levels:
- name: L1-OnCall
timeoutMinutes: 5
targets:
- type: oncall
name: primary-oncall
notifyChannels: [slack-incidents, pagerduty-critical]
repeatIntervalMinutes: 5
- name: L2-SeniorSRE
timeoutMinutes: 15
targets:
- type: team
name: sre-senior
notifyChannels: [slack-incidents, pagerduty-critical]
- name: L3-Engineering-Lead
timeoutMinutes: 30
targets:
- type: user
name: eng-lead@company.com
notifyChannels: [slack-incidents, email-management]
5. Define SLOs
apiVersion: platform.chatcli.io/v1alpha1
kind: ServiceLevelObjective
metadata:
name: api-gateway-availability
namespace: chatcli-system
spec:
serviceName: api-gateway
description: "API Gateway must maintain 99.9% availability"
enabled: true
indicator:
type: availability
metricSource: issues
resource:
kind: Deployment
name: api-gateway
namespace: production
target:
percentage: 99.9
window: "30d"
alertPolicy:
pageOnBudgetExhausted: true
notificationPolicyRef: prod-notifications
burnRateWindows:
- shortWindow: "1h"
longWindow: "6h"
burnRateThreshold: 14.4
severity: critical
- shortWindow: "6h"
longWindow: "72h"
burnRateThreshold: 6
severity: high
- shortWindow: "24h"
longWindow: "72h"
burnRateThreshold: 3
severity: medium
6. Define SLAs
apiVersion: platform.chatcli.io/v1alpha1
kind: IncidentSLA
metadata:
name: p1-sla
namespace: chatcli-system
spec:
severity: critical
responseTime: "5m"
resolutionTime: "1h"
escalationPolicyRef: prod-escalation
notificationPolicyRef: prod-notifications
businessHoursOnly: false
apiVersion: platform.chatcli.io/v1alpha1
kind: IncidentSLA
metadata:
name: p2-sla
namespace: chatcli-system
spec:
severity: high
responseTime: "15m"
resolutionTime: "4h"
escalationPolicyRef: prod-escalation
businessHoursOnly: true
businessHours:
timezone: "America/Sao_Paulo"
startHour: 9
endHour: 18
workDays: ["Monday","Tuesday","Wednesday","Thursday","Friday"]
apiVersion: platform.chatcli.io/v1alpha1
kind: ApprovalPolicy
metadata:
name: prod-approvals
namespace: chatcli-system
spec:
enabled: true
defaultMode: manual
rules:
- name: auto-low-confidence
match:
severities: [low]
actionTypes: [RestartDeployment, DeletePod]
mode: auto
autoApproveConditions:
minConfidence: 0.95
maxSeverity: low
historicalSuccessRate: 0.90
- name: quorum-production-rollback
match:
severities: [critical, high]
actionTypes: [RollbackDeployment, ScaleDeployment]
namespaces: [production]
mode: quorum
requiredApprovers: 2
timeoutMinutes: 15
changeWindow:
timezone: "America/Sao_Paulo"
allowedDays: ["Monday","Tuesday","Wednesday","Thursday","Friday"]
startHour: 9
endHour: 17
- name: manual-resource-changes
match:
actionTypes: [AdjustResources, PatchConfig]
mode: manual
timeoutMinutes: 30
8. Install Grafana Dashboards
# Create ConfigMap with dashboards
kubectl create configmap chatcli-grafana-dashboards \
--from-file=deploy/grafana/ \
-n monitoring \
--dry-run=client -o yaml | kubectl apply -f -
# Add label for Grafana sidecar auto-discovery
kubectl label configmap chatcli-grafana-dashboards \
grafana_dashboard=1 -n monitoring
# Install ServiceMonitors
kubectl apply -f deploy/grafana/dashboards-configmap.yaml
9. Validate with Chaos Engineering
Run chaos experiments only in environments with redundancy. Never on single-replica deployments.
apiVersion: platform.chatcli.io/v1alpha1
kind: ChaosExperiment
metadata:
name: validate-api-gateway-resilience
namespace: chatcli-system
spec:
experimentType: pod_kill
target:
kind: Deployment
name: api-gateway
namespace: production
duration: "2m"
parameters:
count: "1"
dryRun: true # Test in dry-run first!
enabled: true
safetyChecks:
minHealthyPods: 2
maxConcurrentExperiments: 1
abortOnIssueDetected: true
requireApproval: true
blockedNamespaces: ["kube-system", "monitoring"]
postExperiment:
verifyRecovery: true
recoveryTimeout: "5m"
runRemediationTest: false
Run in DryRun
kubectl apply -f chaos-experiment.yaml
kubectl get chaos -w
Verify result
kubectl get chaos validate-api-gateway-resilience -o yaml
Run for real (after validation)
Edit dryRun: false and reapply.
10. Access the Dashboard
# Port-forward to the REST API + Web UI
kubectl port-forward svc/chatcli-prod 8090:8090 -n chatcli-system
# Open in browser
open http://localhost:8090
The web dashboard shows:
- Overview with real-time stats
- Incidents with filters and actions (acknowledge, snooze)
- SLOs with error budget and burn rates
- Pending approvals
- PostMortems with timeline
- Federated clusters
- Searchable audit log
10.1 Expose the Dashboard via Ingress (alternative to port-forward)
To reach the dashboard from outside the cluster, create an Ingress pointing at the operator Service. When mounting under a sub-path, rewrite-target with a capture group is required — the dashboard’s static assets are served from / and would 404 otherwise:
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: chatcli-dashboard
namespace: chatcli-system
annotations:
nginx.ingress.kubernetes.io/rewrite-target: /$2
spec:
ingressClassName: nginx
rules:
- host: chatcli.example.com
http:
paths:
- path: /chatcli(/|$)(.*)
pathType: ImplementationSpecific
backend:
service:
name: chatcli-operator
port:
number: 8090
11. Common Troubleshooting
| Operator log error | Cause | Fix |
|---|
x509: certificate is not valid for any names | gRPC server cert missing SAN for spec.server.address | Regenerate cert with openssl.cnf + subjectAltName for the Service FQDN (see §2.1) |
x509: certificate signed by unknown authority | Self-signed cert with no trust configured | Add ca.crt key to the chatcli-tls Secret referenced by the Instance (see §2.1) |
no ready Instance found | Instance not Ready or in a different namespace | kubectl describe instance chatcli-prod -n chatcli-system — inspect status and events |
connection refused after TLS succeeds | Service has no endpoints or wrong gRPC port | kubectl get endpoints chatcli-prod -n chatcli-system must list pod IPs |
Production Checklist
- [x]Operator installed with 17 CRDs- [x]Instance created with TLS and auth- [x]Secret
chatcli-tls contains tls.crt, tls.key and ca.crt (self-signed: ca.crt=tls.crt)- [x]tls.crt has SANs for <instance>.<ns>.svc.cluster.local, <instance>.<ns>.svc and <instance>- [x]spec.server.address in the Instance matches one of the cert SANs- [x]Operator logs show Connected to Instance with no x509: errors within ~30s of the Instance becoming Ready- [x]Watcher monitoring target deployments- [x]NotificationPolicy with Slack + PagerDuty- [x]EscalationPolicy L1->L2->L3- [x]SLOs with burn rate alerting (Google SRE model)- [x]SLAs with response/resolution time per severity- [x]ApprovalPolicy with auto/quorum for production- [x]Grafana dashboards installed- [x]Chaos experiment validated in dry-run- [x]Web Dashboard accessible- [x]REST API with authentication configured