Technical Deep Dive

Built for Scale,
Engineered for Security

Discover the cloud-native architecture powering the world's most advanced security platform. Microservices, Kubernetes, and AI at its core.

99.99%
Uptime SLA
< 100ms
API Latency
10B+
Events/Day
15+
Global Regions

Modern Technology Stack

Built with best-in-class technologies for performance, security, and scalability

Frontend & UI

React 18
Modern UI framework
TypeScript
Type-safe development
GraphQL
Efficient data fetching
WebAssembly
High-performance modules

Backend Services

Go
High-performance microservices
Python
ML/AI services
Rust
Security-critical components
gRPC
Service communication

Data Layer

PostgreSQL
Primary data store
ClickHouse
Analytics database
Redis
Caching & sessions
Apache Kafka
Event streaming

Infrastructure

Kubernetes
Container orchestration
Istio
Service mesh
Terraform
Infrastructure as Code
Prometheus
Monitoring & alerting

Security Layer

Vault
Secrets management
OPA
Policy engine
Falco
Runtime security
Cert-Manager
TLS automation

ML/AI Platform

TensorFlow
Deep learning models
Kubeflow
ML workflows
Apache Spark
Data processing
MLflow
Model lifecycle

Open Source First

We believe in the power of open source. Our platform is built on proven open source technologies and we contribute back to the community with our own open source projects.

Layered Architecture Design

Each layer is designed for specific responsibilities, ensuring separation of concerns and maximum scalability

System Architecture

Edge Layer

Global CDN, DDoS protection, and intelligent routing

API Gateway

Unified API management, authentication, and throttling

Microservices

Domain-driven microservices with service mesh

Data Layer

Distributed data storage and streaming platform

Infrastructure

Kubernetes orchestration across multiple regions

Data flows from top to bottom

Microservices

Domain-driven microservices with service mesh

Auth Service
Threat Engine
Analytics
Reporting

Key Features:

  • Horizontally scalable with auto-scaling policies
  • Built-in redundancy and failover mechanisms
  • Comprehensive monitoring and observability
  • Zero-downtime deployments with blue-green strategy

Microservices First

Each service owns its data and can be developed, deployed, and scaled independently

Security by Design

Zero trust principles, encryption everywhere, and defense in depth at every layer

Cloud Native

Built for the cloud with Kubernetes, leveraging managed services for reliability

Security First

Defense in Depth

Multiple layers of security controls protect your data and infrastructure at every level of the stack

Network Security

DDoS Protection
CloudFlare Enterprise
active
WAF Rules
OWASP Top 10 protection
active
TLS 1.3
End-to-end encryption
active
mTLS
Service-to-service auth
active

Application Security

SAST/DAST
Continuous scanning
active
Dependency Scanning
CVE monitoring
active
Container Scanning
Image vulnerability checks
active
Code Signing
Verified deployments
active

Identity & Access

Zero Trust
Never trust, always verify
active
RBAC/ABAC
Fine-grained permissions
active
MFA Required
All admin access
active
SSO Integration
SAML/OIDC support
active

Data Security

Encryption at Rest
AES-256-GCM
active
Encryption in Transit
TLS everywhere
active
Key Management
HashiCorp Vault
active
Data Masking
PII protection
active

Compliance & Certifications

Meeting the highest standards of security and compliance

SOC 2 Type II

certified2024

ISO 27001

certified2024

HIPAA

certified2023

PCI DSS

certified2024

GDPR

compliantOngoing

FedRAMP

in-progressQ2 2025
0
Security breaches
< 1hr
Patch deployment
24/7
Security monitoring
100%
Encrypted data
Real-Time Processing

Data Flow Architecture

From ingestion to action in milliseconds. See how data flows through our platform to deliver real-time security insights.

Data Ingestion

Multiple data sources feed into our platform

Processing Pipeline

Real-time processing and enrichment

Analysis Engine

Advanced analytics and detection

Storage & Indexing

Optimized storage for different workloads

Response & Action

Automated response and alerting

Data Ingestion

Step 1

Multiple data sources feed into our platform

  • Agent telemetry (10K+ events/sec)
  • API integrations (REST/GraphQL)
  • Log aggregation (Syslog, Fluent)
  • Real-time streams (Webhooks)

Processing Pipeline

Step 2

Real-time processing and enrichment

  • Stream processing (Apache Kafka)
  • Data normalization & validation
  • Threat intelligence enrichment
  • ML model inference

Analysis Engine

Step 3

Advanced analytics and detection

  • Behavioral analysis
  • Anomaly detection
  • Pattern recognition
  • Risk scoring

Storage & Indexing

Step 4

Optimized storage for different workloads

  • Hot data in Redis (&lt; 24hrs)
  • Warm data in PostgreSQL (&lt; 30 days)
  • Cold data in S3 (long-term)
  • Full-text search in Elasticsearch

Response & Action

Step 5

Automated response and alerting

  • Real-time alerting
  • Automated remediation
  • Incident creation
  • Notification dispatch
< 100ms
End-to-end latency
10TB+
Daily processing
1M+
Events per second
99.99%
Detection accuracy
Proven at Scale

Built for Enterprise Scale

Our platform scales effortlessly to meet the demands of the world's largest organizations

Request Handling

+250%
1M+requests/sec

API requests processed per second across all regions

Data Ingestion

+180%
10TBper day

Security telemetry data processed daily

Active Endpoints

+320%
50M+devices

Endpoints protected globally

Alert Processing

-75%
&lt; 50mslatency

Average time to process and route alerts

Global Infrastructure

45+
Kubernetes Clusters
15
Global Regions
45+
Availability Zones
200+
Edge Locations

Intelligent Auto-Scaling

Our platform automatically scales resources based on demand, ensuring optimal performance during peak loads while minimizing costs during quiet periods.

  • Predictive Scaling
    ML models predict traffic patterns and pre-scale resources
  • Multi-Dimensional Scaling
    Scale based on CPU, memory, network, and custom metrics
  • Cost Optimization
    Automatic resource optimization saves 40% on infrastructure costs

Real-Time Scaling Metrics

CPU Utilization42%
Memory Usage58%
Active Pods847 / 2000
Request QueueHealthy
Auto-scaling StatusActive

Ready to Dive Deeper?

Explore our technical documentation, contribute to our open source projects, or connect with our engineering team.

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