Architecture Built for Scale & Performance

HyperObserve's architecture leverages eBPF technology to deliver unprecedented observability without compromising performance.

Four-Layer Architecture

Each layer is optimized for its specific purpose

Collection Layer

eBPF Programs

Kernel-level data collection

Protocol Decoders

Wire protocol analysis

System Collectors

OS and hardware metrics

Log Parsers

Structured log extraction

Processing Layer

Event Processor

Real-time event correlation

Metric Aggregator

Time-series data processing

Trace Builder

Distributed trace reconstruction

Enrichment Engine

Context and metadata addition

Intelligence Layer

ML Pipeline

Anomaly detection and prediction

Pattern Recognition

Behavioral analysis

Root Cause Engine

Automated problem diagnosis

Knowledge Graph

Service dependency mapping

Presentation Layer

Query Engine

Fast data retrieval

Dashboard Service

Real-time visualization

Alert Manager

Intelligent notifications

API Gateway

Integration endpoints

eBPF: The Core Technology

Extended Berkeley Packet Filter (eBPF) allows us to run sandboxed programs in the Linux kernel without changing kernel source code or loading kernel modules.

Safe & Secure

eBPF programs are verified before execution, ensuring system safety

High Performance

JIT-compiled to native code for minimal overhead

Complete Visibility

Access to all system calls, network events, and kernel functions

# eBPF Program Example
SEC("kprobe/tcp_v4_connect")
int trace_connect(struct pt_regs *ctx) {
    struct sock *sk;
    struct sockaddr_in *addr;
    
    // Extract socket and address
    sk = (struct sock *)PT_REGS_PARM1(ctx);
    addr = (struct sockaddr_in *)PT_REGS_PARM2(ctx);
    
    // Capture connection details
    struct conn_event event = {};
    event.pid = bpf_get_current_pid_tgid() >> 32;
    event.daddr = addr->sin_addr.s_addr;
    event.dport = ntohs(addr->sin_port);
    
    // Send to userspace
    bpf_perf_event_output(ctx, &events, 
        BPF_F_CURRENT_CPU, &event, sizeof(event));
    
    return 0;
}

Performance at Scale

Built to handle enterprise-scale deployments

1M+ events/sec per node
Data Ingestion
<100ms p99 latency
Query Performance
Configurable (1d to 5y)
Data Retention
10:1 average
Compression Ratio
<2% on monitored hosts
CPU Overhead
<50MB per agent
Memory Usage

Data Flow Architecture

From kernel events to actionable insights

Linux Kernel

System Events

eBPF Programs

Data Collection

Processing

Aggregation

Platform

Insights

Microseconds

Event capture latency

Real-time

Data processing

Instant

Alert delivery

Built for Your Scale

Whether you have 10 servers or 10,000, HyperObserve scales effortlessly