High Availability
Learn how to design and implement high availability architectures to ensure your applications remain operational even during component failures.
Prerequisites
- Understanding of system architecture principles
- Experience with cloud infrastructure
- Knowledge of networking concepts
- Familiarity with load balancing
High Availability Overview

Visual representation of a high availability architecture with redundant components across multiple availability zones.
High Availability Architecture
Design a resilient high availability architecture:
// High availability architecture configuration
const haArchitecture = {
// Redundancy levels
redundancyLevels: {
n: {
description: 'Single component, no redundancy',
availability: '99.5%', // Typical single component availability
failureImpact: 'Service outage'
},
nPlusOne: {
description: 'N+1 redundancy (one additional component)',
availability: '99.9%', // Three nines
failureImpact: 'No impact if single component fails'
},
nPlusTwo: {
description: 'N+2 redundancy (two additional components)',
availability: '99.99%', // Four nines
failureImpact: 'No impact if two components fail'
},
twoN: {
description: '2N redundancy (full component duplication)',
availability: '99.999%', // Five nines
failureImpact: 'No impact if entire subsystem fails'
}
},
// System components
components: {
compute: {
type: 'Virtual Machines',
redundancyLevel: 'nPlusOne',
distribution: 'Multiple availability zones',
scalingStrategy: 'Auto-scaling group'
},
database: {
type: 'Managed Database',
redundancyLevel: 'nPlusOne',
distribution: 'Primary with hot standby',
replicationStrategy: 'Synchronous replication'
},
storage: {
type: 'Distributed Storage',
redundancyLevel: 'twoN',
distribution: 'Multiple availability zones',
replicationStrategy: 'Triple replication'
},
networking: {
type: 'Load Balancers',
redundancyLevel: 'nPlusOne',
distribution: 'Multiple availability zones',
failoverStrategy: 'Active-active'
}
},
// Availability zones
availabilityZones: {
primary: {
name: 'us-east-1a',
region: 'us-east-1',
components: ['compute', 'database', 'storage', 'networking']
},
secondary: {
name: 'us-east-1b',
region: 'us-east-1',
components: ['compute', 'database', 'storage', 'networking']
},
tertiary: {
name: 'us-east-1c',
region: 'us-east-1',
components: ['compute', 'storage', 'networking']
}
},
// Calculate theoretical availability
calculateAvailability() {
let systemAvailability = 1.0;
for (const [componentName, component] of Object.entries(this.components)) {
const redundancyLevel = this.redundancyLevels[component.redundancyLevel];
const componentAvailability = this.parseAvailability(redundancyLevel.availability);
// Apply redundancy formula based on level
let effectiveAvailability;
switch (component.redundancyLevel) {
case 'n':
effectiveAvailability = componentAvailability;
break;
case 'nPlusOne':
effectiveAvailability = 1 - Math.pow(1 - componentAvailability, 2);
break;
case 'nPlusTwo':
effectiveAvailability = 1 - Math.pow(1 - componentAvailability, 3);
break;
case 'twoN':
effectiveAvailability = 1 - Math.pow(1 - componentAvailability, 2);
break;
default:
effectiveAvailability = componentAvailability;
}
// Multiply with system availability (series calculation)
systemAvailability *= effectiveAvailability;
}
return this.formatAvailability(systemAvailability);
},
// Parse availability percentage string to decimal
parseAvailability(availabilityStr) {
return parseFloat(availabilityStr.replace('%', '')) / 100;
},
// Format availability decimal to percentage string
formatAvailability(availability) {
return (availability * 100).toFixed(3) + '%';
}
}
Load Balancing Configuration
Set up load balancing for distributed traffic:
// Load balancer configuration
const loadBalancer = {
// Load balancer types
types: {
application: {
name: 'Application Load Balancer',
layer: 'Layer 7 (HTTP/HTTPS)',
features: [
'Path-based routing',
'Host-based routing',
'HTTP header routing',
'SSL termination',
'Session stickiness'
],
bestFor: ['Web applications', 'Microservices', 'Container-based applications']
},
network: {
name: 'Network Load Balancer',
layer: 'Layer 4 (TCP/UDP)',
features: [
'Ultra-low latency',
'Millions of requests per second',
'Static IP addresses',
'Preserve client IP addresses'
],
bestFor: ['TCP/UDP traffic', 'Extreme performance requirements', 'Static IP requirements']
},
global: {
name: 'Global Load Balancer',
layer: 'DNS-based',
features: [
'Geographic routing',
'Weighted routing',
'Latency-based routing',
'Health check integration',
'Disaster recovery'
],
bestFor: ['Multi-region deployments', 'Global user base', 'Disaster recovery']
}
},
// Algorithms
algorithms: {
roundRobin: {
name: 'Round Robin',
description: 'Distributes requests sequentially across all servers',
advantages: ['Simple implementation', 'Equal distribution'],
disadvantages: ['Doesn't account for server load', 'Doesn't consider request complexity']
},
leastConnections: {
name: 'Least Connections',
description: 'Directs traffic to server with fewest active connections',
advantages: ['Accounts for varying connection times', 'Prevents server overload'],
disadvantages: ['Doesn't account for connection complexity', 'Requires connection tracking']
},
leastResponseTime: {
name: 'Least Response Time',
description: 'Directs traffic to server with lowest response time',
advantages: ['Accounts for server performance', 'Improves user experience'],
disadvantages: ['More complex implementation', 'Requires response time monitoring']
},
ipHash: {
name: 'IP Hash',
description: 'Uses client IP to determine server (consistent hashing)',
advantages: ['Session persistence without cookies', 'Evenly distributed'],
disadvantages: ['Less flexible', 'Can be unbalanced with similar IPs']
},
weightedRoundRobin: {
name: 'Weighted Round Robin',
description: 'Round robin with server capacity weights',
advantages: ['Accounts for different server capacities', 'Simple implementation'],
disadvantages: ['Static weights may not reflect real-time conditions']
}
},
// Health checks
healthChecks: {
types: {
http: {
protocol: 'HTTP/HTTPS',
checks: ['Status code', 'Response body', 'Response time'],
interval: 30, // seconds
timeout: 5, // seconds
thresholds: {
healthy: 2,
unhealthy: 3
}
},
tcp: {
protocol: 'TCP',
checks: ['Connection establishment'],
interval: 30, // seconds
timeout: 5, // seconds
thresholds: {
healthy: 2,
unhealthy: 3
}
}
},
async configureHealthCheck(target, type, options = {}) {
const healthCheckType = this.healthChecks.types[type];
if (!healthCheckType) {
throw new Error(`Unknown health check type: ${type}`);
}
return {
target,
type,
protocol: options.protocol || healthCheckType.protocol,
port: options.port || 80,
path: options.path || '/health',
interval: options.interval || healthCheckType.interval,
timeout: options.timeout || healthCheckType.timeout,
thresholds: {
healthy: options.healthyThreshold || healthCheckType.thresholds.healthy,
unhealthy: options.unhealthyThreshold || healthCheckType.thresholds.unhealthy
}
};
}
},
// Configure load balancer
async configure(type, options = {}) {
const lbType = this.types[type];
if (!lbType) {
throw new Error(`Unknown load balancer type: ${type}`);
}
console.log(`Configuring ${lbType.name}`);
const algorithm = options.algorithm || 'roundRobin';
const healthCheckType = options.healthCheckType || 'http';
const config = {
name: options.name || `${type}-lb`,
type,
algorithm,
listeners: options.listeners || [
{ protocol: 'HTTP', port: 80 },
{ protocol: 'HTTPS', port: 443 }
],
targets: [],
healthCheck: await this.healthChecks.configureHealthCheck(
options.healthCheckTarget || '/health',
healthCheckType,
options.healthCheckOptions
),
stickinessEnabled: options.stickinessEnabled || false,
stickinessType: options.stickinessType || 'cookie',
stickinessExpiration: options.stickinessExpiration || 86400 // 1 day
};
// Add targets
if (options.targets && options.targets.length > 0) {
for (const target of options.targets) {
config.targets.push({
id: target.id,
host: target.host,
port: target.port || 80,
weight: target.weight || 1,
status: 'initial'
});
}
}
return config;
}
}
Database High Availability
Implement database high availability:
// Database high availability configuration
const databaseHA = {
// Replication types
replicationTypes: {
synchronous: {
name: 'Synchronous Replication',
description: 'Primary waits for replica acknowledgment before confirming write',
consistency: 'Strong',
latency: 'Higher',
dataLoss: 'None',
bestFor: ['Financial systems', 'Critical data', 'Regulatory requirements']
},
asynchronous: {
name: 'Asynchronous Replication',
description: 'Primary confirms write before replica acknowledgment',
consistency: 'Eventually consistent',
latency: 'Lower',
dataLoss: 'Potential for small window of loss',
bestFor: ['Geographically distributed systems', 'Performance-sensitive applications']
},
semiSynchronous: {
name: 'Semi-Synchronous Replication',
description: 'Hybrid approach with configurable durability guarantees',
consistency: 'Configurable',
latency: 'Moderate',
dataLoss: 'Configurable risk',
bestFor: ['Balance of performance and durability', 'Most web applications']
}
},
// Database HA architectures
architectures: {
primaryReplica: {
name: 'Primary-Replica',
description: 'Single primary with one or more read replicas',
components: ['Primary node', 'Replica nodes', 'Monitoring system'],
advantages: ['Simple setup', 'Read scalability', 'Backup options'],
disadvantages: ['Single write point', 'Failover requires promotion'],
availability: '99.9% - 99.95%'
},
multiPrimary: {
name: 'Multi-Primary (Multi-Master)',
description: 'Multiple nodes accepting writes with replication',
components: ['Multiple primary nodes', 'Replication manager', 'Conflict resolution'],
advantages: ['No single write point', 'Higher write availability', 'Geographic distribution'],
disadvantages: ['Complex conflict resolution', 'Consistency challenges', 'More complex setup'],
availability: '99.95% - 99.99%'
},
sharded: {
name: 'Sharded Cluster',
description: 'Data partitioned across multiple servers',
components: ['Shard servers', 'Config servers', 'Router servers'],
advantages: ['Horizontal scalability', 'Performance for large datasets', 'Workload isolation'],
disadvantages: ['Complex setup and maintenance', 'Uneven sharding challenges', 'Cross-shard transactions'],
availability: '99.9% - 99.99%'
}
},
// Failover strategies
failoverStrategies: {
automatic: {
name: 'Automatic Failover',
description: 'System automatically detects failure and promotes replica',
components: ['Health monitoring', 'Failover manager', 'DNS updater'],
timeToRecover: 'Seconds to minutes',
humanIntervention: 'None'
},
manual: {
name: 'Manual Failover',
description: 'Human operator initiates and manages failover process',
components: ['Monitoring alerts', 'Runbooks', 'Admin tools'],
timeToRecover: 'Minutes to hours',
humanIntervention: 'Required'
},
orchestrated: {
name: 'Orchestrated Failover',
description: 'Automated with approval gates and validation',
components: ['Orchestration platform', 'Validation tests', 'Approval workflow'],
timeToRecover: 'Minutes',
humanIntervention: 'Approval only'
}
},
// Configure database HA
async configure(dbType, architecture, options = {}) {
console.log(`Configuring ${dbType} with ${architecture} architecture`);
const architectureConfig = this.architectures[architecture];
if (!architectureConfig) {
throw new Error(`Unknown architecture: ${architecture}`);
}
const replicationType = options.replicationType || 'synchronous';
const replicationConfig = this.replicationTypes[replicationType];
if (!replicationConfig) {
throw new Error(`Unknown replication type: ${replicationType}`);
}
const failoverType = options.failoverType || 'automatic';
const failoverConfig = this.failoverStrategies[failoverType];
if (!failoverConfig) {
throw new Error(`Unknown failover type: ${failoverType}`);
}
// Create configuration
const config = {
dbType,
architecture,
replication: {
type: replicationType,
...replicationConfig
},
failover: {
type: failoverType,
...failoverConfig
},
nodes: [],
monitoring: {
interval: options.monitoringInterval || 10, // seconds
healthEndpoint: options.healthEndpoint || '/health',
metrics: options.metrics || ['cpu', 'memory', 'connections', 'replication_lag']
}
};
// Configure nodes
if (options.nodes && options.nodes.length > 0) {
config.nodes = options.nodes.map(node => ({
id: node.id,
host: node.host,
port: node.port,
role: node.role || 'replica',
zone: node.zone,
priority: node.priority || 1
}));
} else {
// Create default nodes
const zones = ['us-east-1a', 'us-east-1b', 'us-east-1c'];
if (architecture === 'primaryReplica') {
config.nodes.push({
id: 'primary-1',
host: 'db-primary',
port: 5432,
role: 'primary',
zone: zones[0],
priority: 1
});
for (let i = 0; i < 2; i++) {
config.nodes.push({
id: `replica-${i+1}`,
host: `db-replica-${i+1}`,
port: 5432,
role: 'replica',
zone: zones[i+1],
priority: i+2
});
}
} else if (architecture === 'multiPrimary') {
for (let i = 0; i < 3; i++) {
config.nodes.push({
id: `primary-${i+1}`,
host: `db-primary-${i+1}`,
port: 5432,
role: 'primary',
zone: zones[i],
priority: i+1
});
}
} else if (architecture === 'sharded') {
// Config servers
for (let i = 0; i < 3; i++) {
config.nodes.push({
id: `config-${i+1}`,
host: `db-config-${i+1}`,
port: 27017,
role: 'config',
zone: zones[i % zones.length],
priority: 1
});
}
// Shard servers (2 shards with 3 nodes each)
for (let shard = 0; shard < 2; shard++) {
for (let node = 0; node < 3; node++) {
const role = node === 0 ? 'primary' : 'replica';
config.nodes.push({
id: `shard-${shard+1}-${role}-${node+1}`,
host: `db-shard-${shard+1}-${node+1}`,
port: 27017,
role: `shard-${role}`,
zone: zones[node % zones.length],
priority: node === 0 ? 1 : node+1,
shardId: shard+1
});
}
}
// Router servers
for (let i = 0; i < 2; i++) {
config.nodes.push({
id: `router-${i+1}`,
host: `db-router-${i+1}`,
port: 27017,
role: 'router',
zone: zones[i % zones.length],
priority: 1
});
}
}
}
return config;
}
}
Auto-Scaling Implementation
Configure auto-scaling for dynamic capacity:
// Auto-scaling configuration
const autoScaling = {
// Scaling types
scalingTypes: {
horizontal: {
name: 'Horizontal Scaling (Scaling Out)',
description: 'Add or remove instances to handle load',
advantages: ['Linear scalability', 'Improved availability', 'No downtime'],
disadvantages: ['State management challenges', 'Load balancing required', 'Potential data consistency issues'],
bestFor: ['Stateless applications', 'Web servers', 'Microservices']
},
vertical: {
name: 'Vertical Scaling (Scaling Up)',
description: 'Increase resources (CPU, memory) of existing instances',
advantages: ['Simpler implementation', 'Better for stateful applications', 'Less network overhead'],
disadvantages: ['Limited by hardware', 'Potential downtime', 'Not linearly scalable'],
bestFor: ['Databases', 'Monolithic applications', 'Memory-intensive workloads']
},
diagonal: {
name: 'Diagonal Scaling (Hybrid)',
description: 'Combination of horizontal and vertical scaling',
advantages: ['Flexible resource utilization', 'Cost optimization', 'Adaptable to workload'],
disadvantages: ['Complex implementation', 'Requires sophisticated monitoring', 'Advanced orchestration'],
bestFor: ['Complex applications', 'Variable workloads', 'Enterprise systems']
}
},
// Scaling metrics
metrics: {
cpu: {
name: 'CPU Utilization',
description: 'Percentage of CPU capacity in use',
thresholds: {
scaleOut: 70, // percentage
scaleIn: 30 // percentage
},
period: 300, // seconds
evaluationPeriods: 2
},
memory: {
name: 'Memory Utilization',
description: 'Percentage of memory in use',
thresholds: {
scaleOut: 75, // percentage
scaleIn: 40 // percentage
},
period: 300, // seconds
evaluationPeriods: 2
},
requests: {
name: 'Request Count',
description: 'Number of requests per instance',
thresholds: {
scaleOut: 1000, // requests per minute
scaleIn: 300 // requests per minute
},
period: 60, // seconds
evaluationPeriods: 3
},
responseTime: {
name: 'Response Time',
description: 'Average response time in milliseconds',
thresholds: {
scaleOut: 500, // milliseconds
scaleIn: 200 // milliseconds
},
period: 60, // seconds
evaluationPeriods: 3
},
custom: {
name: 'Custom Metric',
description: 'User-defined metric for scaling',
thresholds: {
scaleOut: null, // to be defined
scaleIn: null // to be defined
},
period: 60, // seconds
evaluationPeriods: 3
}
},
// Scaling policies
policies: {
targetTracking: {
name: 'Target Tracking',
description: 'Maintain a specific target value for a metric',
configuration: {
targetValue: null, // to be defined
metric: null, // to be defined
scaleOutCooldown: 300, // seconds
scaleInCooldown: 300 // seconds
}
},
stepScaling: {
name: 'Step Scaling',
description: 'Scale based on metric thresholds with step adjustments',
configuration: {
metric: null, // to be defined
adjustments: [
{ lower: null, upper: null, adjustment: null } // to be defined
],
scaleOutCooldown: 300, // seconds
scaleInCooldown: 300 // seconds
}
},
scheduled: {
name: 'Scheduled Scaling',
description: 'Scale based on predictable schedules',
configuration: {
schedules: [
{ recurrence: null, minCapacity: null, maxCapacity: null } // to be defined
]
}
},
predictive: {
name: 'Predictive Scaling',
description: 'Scale based on load forecasting and machine learning',
configuration: {
forecastingModel: 'ml.timeseries',
metricPattern: 'daily', // daily, weekly, monthly
lookbackDays: 14,
forecastHorizon: 48, // hours
scaleOutCooldown: 300, // seconds
scaleInCooldown: 300 // seconds
}
}
},
// Configure auto-scaling
async configure(resourceType, scalingType, options = {}) {
console.log(`Configuring ${scalingType} scaling for ${resourceType}`);
const scalingTypeConfig = this.scalingTypes[scalingType];
if (!scalingTypeConfig) {
throw new Error(`Unknown scaling type: ${scalingType}`);
}
// Create configuration
const config = {
resourceType,
scalingType,
capacity: {
min: options.minCapacity || 2,
max: options.maxCapacity || 10,
desired: options.desiredCapacity || 2
},
metrics: [],
policies: [],
cooldown: {
scaleOut: options.scaleOutCooldown || 300, // seconds
scaleIn: options.scaleInCooldown || 300 // seconds
}
};
// Configure metrics
if (options.metrics && options.metrics.length > 0) {
for (const metricName of options.metrics) {
const metric = this.metrics[metricName];
if (!metric) {
console.warn(`Unknown metric: ${metricName}, skipping`);
continue;
}
config.metrics.push({
name: metric.name,
type: metricName,
thresholds: { ...metric.thresholds },
period: options.metricPeriod || metric.period,
evaluationPeriods: options.evaluationPeriods || metric.evaluationPeriods
});
}
} else {
// Default to CPU utilization
config.metrics.push({
name: this.metrics.cpu.name,
type: 'cpu',
thresholds: { ...this.metrics.cpu.thresholds },
period: options.metricPeriod || this.metrics.cpu.period,
evaluationPeriods: options.evaluationPeriods || this.metrics.cpu.evaluationPeriods
});
}
// Configure policies
if (options.policies && options.policies.length > 0) {
for (const policyConfig of options.policies) {
const policyType = policyConfig.type;
const policy = this.policies[policyType];
if (!policy) {
console.warn(`Unknown policy type: ${policyType}, skipping`);
continue;
}
const policyConfiguration = {
name: policy.name,
type: policyType,
...JSON.parse(JSON.stringify(policy.configuration)) // Deep clone
};
// Override with provided configuration
if (policyConfig.configuration) {
Object.assign(policyConfiguration, policyConfig.configuration);
}
config.policies.push(policyConfiguration);
}
} else {
// Default to target tracking policy
config.policies.push({
name: this.policies.targetTracking.name,
type: 'targetTracking',
targetValue: 70, // 70% CPU utilization
metric: 'cpu',
scaleOutCooldown: config.cooldown.scaleOut,
scaleInCooldown: config.cooldown.scaleIn
});
}
return config;
}
}
Monitoring and Alerting
Set up monitoring and alerting for high availability:
// High availability monitoring system
const haMonitoring = {
// Monitoring components
components: {
infrastructure: {
name: 'Infrastructure Monitoring',
metrics: [
'cpu_utilization',
'memory_utilization',
'disk_usage',
'network_throughput',
'load_average'
],
interval: 60, // seconds
retention: 90 // days
},
application: {
name: 'Application Monitoring',
metrics: [
'request_count',
'error_rate',
'response_time',
'throughput',
'apdex_score'
],
interval: 30, // seconds
retention: 30 // days
},
database: {
name: 'Database Monitoring',
metrics: [
'query_performance',
'connection_count',
'replication_lag',
'transaction_rate',
'lock_wait_time'
],
interval: 60, // seconds
retention: 30 // days
},
availability: {
name: 'Availability Monitoring',
metrics: [
'uptime',
'endpoint_availability',
'ssl_certificate_validity',
'dns_resolution',
'ping_response'
],
interval: 60, // seconds
retention: 365 // days
}
},
// Alert thresholds
alertThresholds: {
critical: {
cpu_utilization: 90, // percentage
memory_utilization: 90, // percentage
disk_usage: 90, // percentage
error_rate: 5, // percentage
response_time: 1000, // milliseconds
replication_lag: 300, // seconds
uptime: 99.9 // percentage (alert if below)
},
warning: {
cpu_utilization: 80, // percentage
memory_utilization: 80, // percentage
disk_usage: 80, // percentage
error_rate: 2, // percentage
response_time: 500, // milliseconds
replication_lag: 60, // seconds
uptime: 99.95 // percentage (alert if below)
}
},
// Health checks
healthChecks: {
types: {
http: {
protocol: 'HTTP/HTTPS',
method: 'GET',
expectedStatus: 200,
timeout: 5, // seconds
interval: 30 // seconds
},
tcp: {
protocol: 'TCP',
port: 80,
timeout: 3, // seconds
interval: 30 // seconds
},
dns: {
protocol: 'DNS',
recordType: 'A',
timeout: 2, // seconds
interval: 60 // seconds
}
},
async configureHealthCheck(name, type, endpoint, options = {}) {
const healthCheckType = this.healthChecks.types[type];
if (!healthCheckType) {
throw new Error(`Unknown health check type: ${type}`);
}
return {
name,
type,
endpoint,
protocol: options.protocol || healthCheckType.protocol,
interval: options.interval || healthCheckType.interval,
timeout: options.timeout || healthCheckType.timeout,
threshold: options.threshold || 3,
regions: options.regions || ['us-east-1', 'us-west-2', 'eu-west-1'],
alertChannels: options.alertChannels || ['email', 'slack', 'pagerduty']
};
}
},
// Dashboards
dashboards: {
types: {
overview: {
name: 'System Overview',
description: 'High-level system health and performance',
panels: [
'system_health',
'error_rates',
'response_times',
'throughput',
'availability'
]
},
infrastructure: {
name: 'Infrastructure Performance',
description: 'Detailed infrastructure metrics',
panels: [
'cpu_usage',
'memory_usage',
'disk_performance',
'network_traffic',
'load_balancer_metrics'
]
},
availability: {
name: 'Availability Metrics',
description: 'System and component availability',
panels: [
'uptime',
'outages',
'response_success',
'apdex_score',
'sla_compliance'
]
}
},
async createDashboard(type, options = {}) {
const dashboardType = this.dashboards.types[type];
if (!dashboardType) {
throw new Error(`Unknown dashboard type: ${type}`);
}
return {
name: options.name || dashboardType.name,
type,
description: options.description || dashboardType.description,
panels: options.panels || dashboardType.panels,
refreshRate: options.refreshRate || 60, // seconds
timeRange: options.timeRange || '24h',
accessRoles: options.accessRoles || ['admin', 'operations']
};
}
},
// Configure monitoring
async configure(components = [], options = {}) {
console.log('Configuring high availability monitoring');
const config = {
components: {},
healthChecks: [],
dashboards: [],
alerting: {
channels: options.alertChannels || ['email', 'slack', 'pagerduty'],
policies: options.alertPolicies || {
critical: {
channels: ['email', 'slack', 'pagerduty'],
escalation: true,
autoRemediation: options.autoRemediation || false
},
warning: {
channels: ['email', 'slack'],
escalation: false,
autoRemediation: false
}
}
}
};
// Configure components
for (const component of components) {
const componentConfig = this.components[component];
if (!componentConfig) {
console.warn(`Unknown component: ${component}, skipping`);
continue;
}
config.components[component] = {
...componentConfig,
enabled: true
};
}
// Configure health checks
if (options.healthChecks && options.healthChecks.length > 0) {
for (const healthCheck of options.healthChecks) {
config.healthChecks.push(
await this.healthChecks.configureHealthCheck(
healthCheck.name,
healthCheck.type,
healthCheck.endpoint,
healthCheck.options
)
);
}
}
// Configure dashboards
if (options.dashboards && options.dashboards.length > 0) {
for (const dashboard of options.dashboards) {
config.dashboards.push(
await this.dashboards.createDashboard(
dashboard.type,
dashboard.options
)
);
}
} else {
// Create default overview dashboard
config.dashboards.push(
await this.dashboards.createDashboard('overview')
);
}
return config;
}
}
Best Practices
Architecture Design
Best practices for HA architecture:
- Eliminate single points of failure
- Implement redundancy at all layers
- Design for graceful degradation
- Automate recovery processes
Load Balancing
Optimize load balancing:
- Use health checks for all backends
- Implement session persistence
- Configure proper timeouts
- Monitor balancer performance
Data Management
Ensure data availability:
- Implement data replication
- Use distributed storage
- Regular backup verification
- Plan for data recovery
High Availability Principles
Redundancy
Duplicate critical components and systems to eliminate single points of failure. When one component fails, the redundant component takes over.
Examples:
- Multiple application servers behind a load balancer
- Database primary with standby replicas
- Redundant network paths
- Multiple power supplies
Fault Isolation
Design systems so that failures in one component don't cascade to others. Isolate components to contain failures within boundaries.
Examples:
- Multiple availability zones
- Bulkhead pattern in microservices
- Circuit breakers for API calls
- Resource quotas and limits
Replication
Maintain multiple copies of data across different locations to ensure data availability even if some storage systems fail.
Examples:
- Database replication
- Distributed file systems
- Content delivery networks
- Multi-region data stores
Automated Recovery
Implement systems that can automatically detect failures and recover without human intervention to minimize downtime.
Examples:
- Auto-scaling groups
- Self-healing systems
- Automated failover
- Health checks with remediation
Understanding Availability Levels
Availability | Downtime per Year | Downtime per Month | Typical Use Case |
---|---|---|---|
99% ("Two Nines") | 3.65 days | 7.2 hours | Development environments, non-critical internal tools |
99.9% ("Three Nines") | 8.76 hours | 43.8 minutes | Internal business applications, content websites |
99.95% ("Three and a Half Nines") | 4.38 hours | 21.9 minutes | E-commerce platforms, SaaS applications |
99.99% ("Four Nines") | 52.56 minutes | 4.38 minutes | Financial systems, critical business services |
99.999% ("Five Nines") | 5.26 minutes | 26.3 seconds | Telecommunications, emergency services, critical infrastructure |
Note: Achieving higher availability levels requires exponentially more investment in infrastructure, architecture, and operations. The appropriate availability target should be based on business requirements and cost considerations.
Common Challenges
Design Challenges
Common architecture issues:
- Overlooked single points of failure
- Improper redundancy implementation
- Network partition handling
- Cascading failures
Operational Challenges
Day-to-day operational issues:
- Split-brain scenarios
- Replication lag
- Failover timing issues
- Monitoring blind spots