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Enterprise platforms require sophisticated incident response infrastructure:
# Incident Response & SLA Management: Alerting Stack, Escalation, and Service Level Agreements
## Overview
Enterprise platforms require sophisticated incident response infrastructure:
- **Alerting Stack**: Monitoring, detection, and notification
- **Escalation Policies**: On-call rotations, escalation chains
- **Runbooks**: Automated and manual remediation
- **SLA Management**: Uptime guarantees, response times
- **Post-Incident**: Root cause analysis, prevention
This guide covers complete incident response systems for platforms like Manus.
## 1. Alerting Stack Architecture
### 1.1 Recommended Stack
```typescript
/**
* Complete alerting stack for enterprise platform
*
* Stack:
* 1. Prometheus/Grafana - Metrics collection and visualization
* 2. AlertManager - Alert routing and grouping
* 3. PagerDuty - Incident management and on-call
* 4. Opsgenie - Backup alerting and escalation
* 5. Custom webhooks - Integration with internal systems
*/
interface AlertingStackConfig {
metricsCollection: {
tool: 'Prometheus';
scrapeInterval: 15; // seconds
retention: 15; // days
replicas: 3;
};
visualization: {
tool: 'Grafana';
dashboards: number;
alertRules: number;
};
alertRouting: {
tool: 'AlertManager';
grouping: 'by-labels';
groupWait: 10; // seconds
groupInterval: 10; // seconds
repeatInterval: 4; // hours
};
incidentManagement: {
primary: 'PagerDuty';
backup: 'Opsgenie';
features: [
'On-call scheduling',
'Escalation policies',
'Incident tracking',
'Post-mortem management'
];
};
customIntegration: {
webhooks: true;
slack: true;
email: true;
sms: true;
phone: true;
};
}
const recommendedAlertingStack: AlertingStackConfig = {
metricsCollection: {
tool: 'Prometheus',
scrapeInterval: 15,
retention: 15,
replicas: 3
},
visualization: {
tool: 'Grafana',
dashboards: 50,
alertRules: 200
},
alertRouting: {
tool: 'AlertManager',
grouping: 'by-labels',
groupWait: 10,
groupInterval: 10,
repeatInterval: 4
},
incidentManagement: {
primary: 'PagerDuty',
backup: 'Opsgenie',
features: [
'On-call scheduling',
'Escalation policies',
'Incident tracking',
'Post-mortem management'
]
},
customIntegration: {
webhooks: true,
slack: true,
email: true,
sms: true,
phone: true
}
};
```
## 2. Alert Rules and Thresholds
### 2.1 Comprehensive Alert Rules
```yaml
# Prometheus alert rules for Manus-like platform
groups:
- name: platform_alerts
interval: 15s
rules:
# API Performance Alerts
- alert: HighAPILatency
expr: histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m])) > 1
for: 5m
labels:
severity: warning
component: api
annotations:
summary: "High API latency detected"
description: "P99 latency is {{ $value }}s"
runbook: "https://wiki.company.com/runbooks/high-api-latency"
- alert: CriticalAPILatency
expr: histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m])) > 5
for: 2m
labels:
severity: critical
component: api
annotations:
summary: "Critical API latency"
description: "P99 latency is {{ $value }}s"
runbook: "https://wiki.company.com/runbooks/critical-api-latency"
# Error Rate Alerts
- alert: HighErrorRate
expr: rate(http_requests_total{status=~"5.."}[5m]) > 0.05
for: 5m
labels:
severity: warning
component: api
annotations:
summary: "High error rate detected"
description: "Error rate is {{ $value | humanizePercentage }}"
runbook: "https://wiki.company.com/runbooks/high-error-rate"
- alert: CriticalErrorRate
expr: rate(http_requests_total{status=~"5.."}[5m]) > 0.1
for: 2m
labels:
severity: critical
component: api
annotations:
summary: "Critical error rate"
description: "Error rate is {{ $value | humanizePercentage }}"
# Database Alerts
- alert: HighDatabaseLatency
expr: histogram_quantile(0.99, rate(db_query_duration_seconds_bucket[5m])) > 1
for: 5m
labels:
severity: warning
component: database
annotations:
summary: "High database latency"
description: "P99 query latency is {{ $value }}s"
- alert: DatabaseConnectionPoolExhausted
expr: db_connection_pool_active / db_connection_pool_max > 0.9
for: 2m
labels:
severity: critical
component: database
annotations:
summary: "Database connection pool exhausted"
description: "Pool utilization is {{ $value | humanizePercentage }}"
- alert: ReplicationLagHigh
expr: pg_replication_lag_seconds > 5
for: 5m
labels:
severity: warning
component: database
annotations:
summary: "High database replication lag"
description: "Replication lag is {{ $value }}s"
# Kubernetes Alerts
- alert: PodCrashLooping
expr: rate(kube_pod_container_status_restarts_total[1h]) > 0.1
for: 5m
labels:
severity: warning
component: kubernetes
annotations:
summary: "Pod crash looping"
description: "Pod {{ $labels.pod }} is crash looping"
- alert: NodeNotReady
expr: kube_node_status_condition{condition="Ready",status="true"} == 0
for: 5m
labels:
severity: critical
component: kubernetes
annotations:
summary: "Kubernetes node not ready"
description: "Node {{ $labels.node }} is not ready"
# LLM Service Alerts
- alert: LLMProviderDown
expr: up{job="llm-provider"} == 0
for: 2m
labels:
severity: critical
component: llm
annotations:
summary: "LLM provider down"
description: "Provider {{ $labels.provider }} is down"
- alert: HighTokenCost
expr: rate(llm_tokens_used_total[1h]) * llm_cost_per_token > 1000
for: 10m
labels:
severity: warning
component: llm
annotations:
summary: "High LLM token cost"
description: "Hourly cost is ${{ $value }}"
# Infrastructure Alerts
- alert: HighCPUUsage
expr: (1 - avg by (instance) (rate(node_cpu_seconds_total{mode="idle"}[5m]))) > 0.9
for: 5m
labels:
severity: warning
component: infrastructure
annotations:
summary: "High CPU usage"
description: "CPU usage is {{ $value | humanizePercentage }}"
- alert: HighMemoryUsage
expr: (1 - (node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes)) > 0.9
for: 5m
labels:
severity: warning
component: infrastructure
annotations:
summary: "High memory usage"
description: "Memory usage is {{ $value | humanizePercentage }}"
- alert: DiskSpaceLow
expr: (node_filesystem_avail_bytes / node_filesystem_size_bytes) < 0.1
for: 5m
labels:
severity: warning
component: infrastructure
annotations:
summary: "Low disk space"
description: "Available disk space is {{ $value | humanizePercentage }}"
# SLA Alerts
- alert: SLAViolationWarning
expr: (1 - (increase(requests_success_total[1h]) / increase(requests_total[1h]))) > 0.005
for: 10m
labels:
severity: warning
component: sla
annotations:
summary: "SLA violation warning"
description: "Error rate is {{ $value | humanizePercentage }}"
- alert: SLAViolationCritical
expr: (1 - (increase(requests_success_total[1h]) / increase(requests_total[1h]))) > 0.01
for: 5m
labels:
severity: critical
component: sla
annotations:
summary: "Critical SLA violation"
description: "Error rate is {{ $value | humanizePercentage }}"
```
## 3. Escalation Policies
### 3.1 On-Call Escalation
```typescript
/**
* On-call escalation policies for incident management
*/
interface EscalationPolicy {
name: string;
levels: EscalationLevel[];
handoffTimeout: number; // seconds
repeatCycle: boolean;
}
interface EscalationLevel {
level: number;
delay: number; // seconds from previous level
targets: OnCallTarget[];
notificationChannels: NotificationChannel[];
}
interface OnCallTarget {
type: 'user' | 'schedule' | 'team';
id: string;
name: string;
}
interface NotificationChannel {
type: 'email' | 'sms' | 'phone' | 'slack' | 'webhook';
priority: 'low' | 'medium' | 'high' | 'urgent';
}
const escalationPolicies: Record<string, EscalationPolicy> = {
critical: {
name: 'Critical Incident Escalation',
levels: [
{
level: 1,
delay: 0,
targets: [
{ type: 'schedule', id: 'primary-oncall', name: 'Primary On-Call' }
],
notificationChannels: [
{ type: 'sms', priority: 'urgent' },
{ type: 'phone', priority: 'urgent' },
{ type: 'email', priority: 'high' },
{ type: 'slack', priority: 'high' }
]
},
{
level: 2,
delay: 300, // 5 minutes
targets: [
{ type: 'schedule', id: 'secondary-oncall', name: 'Secondary On-Call' }
],
notificationChannels: [
{ type: 'sms', priority: 'urgent' },
{ type: 'phone', priority: 'urgent' },
{ type: 'email', priority: 'high' }
]
},
{
level: 3,
delay: 600, // 10 minutes
targets: [
{ type: 'team', id: 'platform-team', name: 'Platform Team Lead' }
],
notificationChannels: [
{ type: 'sms', priority: 'urgent' },
{ type: 'phone', priority: 'urgent' },
{ type: 'email', priority: 'high' }
]
},
{
level: 4,
delay: 900, // 15 minutes
targets: [
{ type: 'user', id: 'cto', name: 'CTO' }
],
notificationChannels: [
{ type: 'phone', priority: 'urgent' },
{ type: 'email', priority: 'high' }
]
}
],
handoffTimeout: 3600, // 1 hour
repeatCycle: true
},
high: {
name: 'High Priority Escalation',
levels: [
{
level: 1,
delay: 0,
targets: [
{ type: 'schedule', id: 'primary-oncall', name: 'Primary On-Call' }
],
notificationChannels: [
{ type: 'email', priority: 'high' },
{ type: 'slack', priority: 'high' }
]
},
{
level: 2,
delay: 900, // 15 minutes
targets: [
{ type: 'schedule', id: 'secondary-oncall', name: 'Secondary On-Call' }
],
notificationChannels: [
{ type: 'email', priority: 'high' },
{ type: 'slack', priority: 'high' }
]
}
],
handoffTimeout: 7200, // 2 hours
repeatCycle: true
},
medium: {
name: 'Medium Priority Escalation',
levels: [
{
level: 1,
delay: 0,
targets: [
{ type: 'schedule', id: 'primary-oncall', name: 'Primary On-Call' }
],
notificationChannels: [
{ type: 'email', priority: 'medium' },
{ type: 'slack', priority: 'medium' }
]
}
],
handoffTimeout: 14400, // 4 hours
repeatCycle: false
}
};
class EscalationManager {
/**
* Execute escalation policy
*/
async executeEscalation(
incident: Incident,
policy: EscalationPolicy
): Promise<void> {
for (const level of policy.levels) {
// Wait for delay
await this.sleep(level.delay * 1000);
// Check if incident is resolved
const resolved = await this.isIncidentResolved(incident.id);
if (resolved) {
console.log(`Incident ${incident.id} resolved, stopping escalation`);
break;
}
// Notify targets
for (const target of level.targets) {
await this.notifyTarget(incident, target, level.notificationChannels);
}
// Wait for handoff timeout
const acknowledged = await this.waitForAcknowledgment(
incident.id,
policy.handoffTimeout
);
if (acknowledged) {
console.log(`Incident ${incident.id} acknowledged at level ${level.level}`);
break;
}
// If not acknowledged and not last level, continue to next
if (level.level < policy.levels.length) {
console.log(`No acknowledgment at level ${level.level}, escalating...`);
}
}
// If repeat cycle enabled and still not resolved, restart
if (policy.repeatCycle) {
const resolved = await this.isIncidentResolved(incident.id);
if (!resolved) {
await this.executeEscalation(incident, policy);
}
}
}
private async notifyTarget(
incident: Incident,
target: OnCallTarget,
channels: NotificationChannel[]
): Promise<void> {
// Implementation: Send notifications via all channels
}
private async waitForAcknowledgment(
incidentId: string,
timeout: number
): Promise<boolean> {
// Implementation: Wait for acknowledgment
return false;
}
private async isIncidentResolved(incidentId: string): Promise<boolean> {
// Implementation: Check incident status
return false;
}
private sleep(ms: number): Promise<void> {
return new Promise(resolve => setTimeout(resolve, ms));
}
}
interface Incident {
id: string;
severity: 'critical' | 'high' | 'medium' | 'low';
title: string;
description: string;
createdAt: Date;
resolvedAt?: Date;
assignee?: string;
}
```
## 4. SLA Management
### 4.1 SLA Definitions and Tracking
```typescript
/**
* SLA definitions and tracking for enterprise platform
*/
interface SLADefinition {
name: string;
availability: number; // 99.9, 99.99, etc.
responseTime: number; // ms
resolutionTime: number; // minutes
maintenanceWindow: number; // hours per month
}
interface SLAMetrics {
uptime: number;
downtime: number;
incidents: number;
mttr: number; // Mean Time To Resolution
mtbf: number; // Mean Time Between Failures
errorBudget: number;
}
const slaDefinitions: Record<string, SLADefinition> = {
enterprise: {
name: 'Enterprise SLA',
availability: 99.99, // 4 nines
responseTime: 100, // 100ms p99
resolutionTime: 15, // 15 minutes for critical
maintenanceWindow: 4 // 4 hours per month
},
premium: {
name: 'Premium SLA',
availability: 99.9, // 3 nines
responseTime: 200, // 200ms p99
resolutionTime: 30, // 30 minutes for critical
maintenanceWindow: 8 // 8 hours per month
},
standard: {
name: 'Standard SLA',
availability: 99.5, // 2.5 nines
responseTime: 500, // 500ms p99
resolutionTime: 60, // 60 minutes for critical
maintenanceWindow: 16 // 16 hours per month
}
};
class SLATracker {
/**
* Calculate uptime percentage
*/
calculateUptime(
totalTime: number, // seconds
downtime: number // seconds
): number {
return ((totalTime - downtime) / totalTime) * 100;
}
/**
* Calculate error budget
*/
calculateErrorBudget(sla: SLADefinition, period: 'month' | 'year'): number {
const periodSeconds = period === 'month' ? 30 * 24 * 60 * 60 : 365 * 24 * 60 * 60;
const allowedDowntime = periodSeconds * ((100 - sla.availability) / 100);
return allowedDowntime;
}
/**
* Check SLA violation
*/
checkSLAViolation(
metrics: SLAMetrics,
sla: SLADefinition,
period: 'month' | 'year'
): SLAViolationReport {
const errorBudget = this.calculateErrorBudget(sla, period);
const violated = metrics.downtime > errorBudget;
return {
violated,
uptime: metrics.uptime,
target: sla.availability,
downtime: metrics.downtime,
allowedDowntime: errorBudget,
violationAmount: Math.max(0, metrics.downtime - errorBudget),
creditPercentage: this.calculateCredit(metrics.uptime, sla.availability)
};
}
/**
* Calculate service credit
*/
private calculateCredit(uptime: number, target: number): number {
if (uptime >= target) {
return 0; // No credit
}
if (uptime >= target - 0.1) {
return 10; // 10% credit
} else if (uptime >= target - 0.5) {
return 25; // 25% credit
} else if (uptime >= target - 1.0) {
return 50; // 50% credit
} else {
return 100; // 100% credit
}
}
/**
* Generate SLA report
*/
generateSLAReport(
metrics: SLAMetrics,
sla: SLADefinition,
period: 'month' | 'year'
): SLAReport {
const violation = this.checkSLAViolation(metrics, sla, period);
return {
period,
sla: sla.name,
metrics,
violation,
summary: {
uptime: `${metrics.uptime.toFixed(3)}%`,
target: `${sla.availability}%`,
status: violation.violated ? 'VIOLATED' : 'MET',
creditEarned: `${violation.creditPercentage}%`
}
};
}
}
interface SLAViolationReport {
violated: boolean;
uptime: number;
target: number;
downtime: number;
allowedDowntime: number;
violationAmount: number;
creditPercentage: number;
}
interface SLAReport {
period: string;
sla: string;
metrics: SLAMetrics;
violation: SLAViolationReport;
summary: {
uptime: string;
target: string;
status: string;
creditEarned: string;
};
}
```
## 5. Runbooks and Automation
### 5.1 Automated Remediation
```typescript
/**
* Automated remediation runbooks
*/
interface Runbook {
id: string;
name: string;
trigger: AlertTrigger;
steps: RunbookStep[];
rollback: RunbookStep[];
timeout: number; // seconds
}
interface RunbookStep {
name: string;
type: 'check' | 'action' | 'notify' | 'wait';
condition?: string;
action?: string;
timeout?: number;
}
interface AlertTrigger {
alertName: string;
severity: string;
condition?: string;
}
const runbooks: Record<string, Runbook> = {
highAPILatency: {
id: 'high-api-latency',
name: 'High API Latency Remediation',
trigger: {
alertName: 'HighAPILatency',
severity: 'warning'
},
steps: [
{
name: 'Check API pod status',
type: 'check',
action: 'kubectl get pods -n api'
},
{
name: 'Check resource usage',
type: 'check',
action: 'kubectl top pods -n api'
},
{
name: 'Scale up API deployment',
type: 'action',
action: 'kubectl scale deployment api --replicas=20 -n api',
condition: 'pod_cpu_usage > 80%'
},
{
name: 'Wait for new pods',
type: 'wait',
timeout: 60
},
{
name: 'Verify latency improved',
type: 'check',
action: 'check_metric("http_request_duration_seconds_bucket", "< 1s")'
},
{
name: 'Notify on-call',
type: 'notify',
action: 'notify_slack("API latency remediated")'
}
],
rollback: [
{
name: 'Scale down API deployment',
type: 'action',
action: 'kubectl scale deployment api --replicas=10 -n api'
}
],
timeout: 300
},
databaseConnectionPoolExhausted: {
id: 'db-pool-exhausted',
name: 'Database Connection Pool Exhaustion',
trigger: {
alertName: 'DatabaseConnectionPoolExhausted',
severity: 'critical'
},
steps: [
{
name: 'Check active connections',
type: 'check',
action: 'SELECT count(*) FROM pg_stat_activity'
},
{
name: 'Identify long-running queries',
type: 'check',
action: 'SELECT * FROM pg_stat_activity WHERE state = "active" AND query_start < now() - interval "5 minutes"'
},
{
name: 'Terminate idle connections',
type: 'action',
action: 'SELECT pg_terminate_backend(pid) FROM pg_stat_activity WHERE state = "idle" AND query_start < now() - interval "10 minutes"'
},
{
name: 'Increase connection pool size',
type: 'action',
action: 'pgbouncer_update_config("default_pool_size=50")'
},
{
name: 'Notify database team',
type: 'notify',
action: 'page_on_call("database")'
}
],
rollback: [
{
name: 'Restore connection pool size',
type: 'action',
action: 'pgbouncer_update_config("default_pool_size=25")'
}
],
timeout: 600
},
highErrorRate: {
id: 'high-error-rate',
name: 'High Error Rate Remediation',
trigger: {
alertName: 'HighErrorRate',
severity: 'warning'
},
steps: [
{
name: 'Check error logs',
type: 'check',
action: 'kubectl logs -n api -l app=api --tail=100 | grep ERROR'
},
{
name: 'Identify error pattern',
type: 'check',
action: 'analyze_error_logs()'
},
{
name: 'Restart affected pods',
type: 'action',
action: 'kubectl rollout restart deployment/api -n api',
condition: 'error_pattern == "crash_loop"'
},
{
name: 'Rollback recent deployment',
type: 'action',
action: 'kubectl rollout undo deployment/api -n api',
condition: 'error_pattern == "regression"'
},
{
name: 'Verify error rate decreased',
type: 'check',
action: 'check_metric("http_requests_total{status=~\"5..\"}", "< 5%")'
}
],
rollback: [],
timeout: 900
}
};
class RunbookExecutor {
/**
* Execute runbook
*/
async executeRunbook(runbook: Runbook, incident: Incident): Promise<RunbookResult> {
const result: RunbookResult = {
runbookId: runbook.id,
incidentId: incident.id,
startTime: new Date(),
steps: [],
success: false,
error: null
};
try {
for (const step of runbook.steps) {
const stepResult = await this.executeStep(step);
result.steps.push({
name: step.name,
status: stepResult.success ? 'success' : 'failed',
duration: stepResult.duration,
output: stepResult.output
});
if (!stepResult.success) {
throw new Error(`Step failed: ${step.name}`);
}
}
result.success = true;
} catch (error) {
result.error = (error as Error).message;
// Execute rollback
for (const step of runbook.rollback) {
await this.executeStep(step);
}
}
result.endTime = new Date();
return result;
}
private async executeStep(step: RunbookStep): Promise<StepResult> {
const startTime = Date.now();
try {
let output = '';
switch (step.type) {
case 'check':
output = await this.executeCheck(step.action!);
break;
case 'action':
output = await this.executeAction(step.action!);
break;
case 'notify':
output = await this.executeNotification(step.action!);
break;
case 'wait':
await this.sleep((step.timeout || 60) * 1000);
output = 'Waited ' + (step.timeout || 60) + 's';
break;
}
return {
success: true,
duration: Date.now() - startTime,
output
};
} catch (error) {
return {
success: false,
duration: Date.now() - startTime,
output: (error as Error).message
};
}
}
private async executeCheck(action: string): Promise<string> {
// Implementation
return '';
}
private async executeAction(action: string): Promise<string> {
// Implementation
return '';
}
private async executeNotification(action: string): Promise<string> {
// Implementation
return '';
}
private sleep(ms: number): Promise<void> {
return new Promise(resolve => setTimeout(resolve, ms));
}
}
interface RunbookResult {
runbookId: string;
incidentId: string;
startTime: Date;
endTime?: Date;
steps: StepResult[];
success: boolean;
error: string | null;
}
interface StepResult {
name?: string;
status?: string;
success: boolean;
duration: number;
output: string;
}
```
## 6. Post-Incident Management
### 6.1 Post-Mortem Process
```typescript
/**
* Post-mortem and root cause analysis
*/
interface PostMortem {
incidentId: string;
title: string;
severity: string;
startTime: Date;
endTime: Date;
duration: number; // minutes
impact: IncidentImpact;
timeline: TimelineEvent[];
rootCauses: RootCause[];
actionItems: ActionItem[];
lessons: string[];
}
interface IncidentImpact {
affectedUsers: number;
affectedServices: string[];
downtime: number; // seconds
dataLoss: boolean;
revenue: number; // estimated loss
}
interface TimelineEvent {
timestamp: Date;
event: string;
actor: string;
}
interface RootCause {
cause: string;
category: string;
preventable: boolean;
}
interface ActionItem {
title: string;
owner: string;
dueDate: Date;
priority: 'high' | 'medium' | 'low';
status: 'open' | 'in-progress' | 'done';
}
class PostMortemManager {
/**
* Generate post-mortem report
*/
generatePostMortem(incident: Incident, events: TimelineEvent[]): PostMortem {
const duration = (incident.resolvedAt!.getTime() - incident.createdAt.getTime()) / 60000;
const postMortem: PostMortem = {
incidentId: incident.id,
title: incident.title,
severity: incident.severity,
startTime: incident.createdAt,
endTime: incident.resolvedAt!,
duration,
impact: this.calculateImpact(incident),
timeline: events,
rootCauses: [],
actionItems: [],
lessons: []
};
return postMortem;
}
/**
* Identify root causes
*/
identifyRootCauses(postMortem: PostMortem): RootCause[] {
const causes: RootCause[] = [];
// Analyze timeline for patterns
for (let i = 0; i < postMortem.timeline.length; i++) {
const event = postMortem.timeline[i];
// Look for contributing factors
if (event.event.includes('deployment')) {
causes.push({
cause: 'Recent deployment introduced regression',
category: 'deployment',
preventable: true
});
}
if (event.event.includes('database')) {
causes.push({
cause: 'Database performance degradation',
category: 'infrastructure',
preventable: true
});
}
}
return causes;
}
/**
* Generate action items
*/
generateActionItems(postMortem: PostMortem): ActionItem[] {
const items: ActionItem[] = [];
for (const cause of postMortem.rootCauses) {
if (cause.preventable) {
items.push({
title: `Implement prevention for: ${cause.cause}`,
owner: 'TBD',
dueDate: new Date(Date.now() + 7 * 24 * 60 * 60 * 1000), // 1 week
priority: 'high',
status: 'open'
});
}
}
return items;
}
private calculateImpact(incident: Incident): IncidentImpact {
// Implementation: Calculate actual impact
return {
affectedUsers: 0,
affectedServices: [],
downtime: 0,
dataLoss: false,
revenue: 0
};
}
}
```
## 7. Recommended SLA Tiers
### 7.1 SLA Tier Comparison
```typescript
const recommendedSLATiers = {
enterprise: {
availability: '99.99%', // 52 minutes downtime per year
responseTime: '100ms (p99)',
criticalResponseTime: '5 minutes',
criticalResolutionTime: '15 minutes',
monthlyPrice: 10000,
features: [
'Dedicated support team',
'24/7 on-call support',
'Priority incident response',
'Guaranteed SLA credits',
'Quarterly business reviews',
'Custom integrations'
]
},
premium: {
availability: '99.9%', // 8.7 hours downtime per year
responseTime: '200ms (p99)',
criticalResponseTime: '15 minutes',
criticalResolutionTime: '30 minutes',
monthlyPrice: 5000,
features: [
'Business hours support',
'On-call support',
'Standard incident response',
'SLA credits',
'Monthly reports',
'API access'
]
},
standard: {
availability: '99.5%', // 21.6 hours downtime per year
responseTime: '500ms (p99)',
criticalResponseTime: '30 minutes',
criticalResolutionTime: '60 minutes',
monthlyPrice: 2000,
features: [
'Business hours support',
'Email support',
'Standard incident response',
'Monthly reports',
'Community forum'
]
}
};
```
## 8. Implementation Checklist
- [ ] Set up Prometheus + AlertManager
- [ ] Configure Grafana dashboards
- [ ] Integrate with PagerDuty
- [ ] Set up Opsgenie backup
- [ ] Create alert rules
- [ ] Define escalation policies
- [ ] Write runbooks
- [ ] Set up automated remediation
- [ ] Configure SLA tracking
- [ ] Create post-mortem process
- [ ] Train on-call team
- [ ] Document procedures
## 9. Recommendations for Manus-like Platform
**Alerting Stack:**
- Primary: PagerDuty (incident management)
- Backup: Opsgenie (redundancy)
- Metrics: Prometheus (collection)
- Visualization: Grafana (dashboards)
- Custom: Webhooks to internal systems
**SLA Tiers:**
- **Enterprise**: 99.99% availability, $10k/month
- **Premium**: 99.9% availability, $5k/month
- **Standard**: 99.5% availability, $2k/month
**On-Call Rotation:**
- Primary: 24/7 coverage
- Secondary: Backup coverage
- Escalation: Team lead after 5 minutes
- Executive: After 10-15 minutes
This comprehensive incident response system ensures enterprise-grade reliability and customer satisfaction!
This guide will help you set up the complete GhostWriter stack: Backend (Go), Frontend (Web), and iOS App.
This guide provides instructions for comparing AGS data from the Google Cloud Storage (GCS) bucket with existing dataset layouts stored in Google Drive/Google Sheets.
1. In chat, type: `/edit <filename>`
**Project:** Zumodra HR/Management SaaS