eBPF Explained: What It Is, Why It Matters, and How It Works#

The Evolution from BPF to eBPF#

Originally, Berkeley Packet Filter (BPF) was created in 1992 for network packet filtering. It allowed users to write simple programs that could filter network packets efficiently. However, its capabilities were limited to network packet inspection.

Extended BPF (eBPF), introduced in Linux 3.18 and fully available since Linux 4.4, dramatically expanded these capabilities:

• 64-bit instruction set (vs 32-bit in classic BPF)
• More registers (10 vs 2)
• Access to kernel functions through helper calls
• Maps for storing state between events
• Support for various program types beyond packet filtering

1. Safety First#

Before any eBPF program runs, it goes through a rigorous verification process:

• Static analysis ensures no infinite loops
• Memory access validation prevents out-of-bounds access
• Type checking ensures proper data handling
• Privilege verification enforces security boundaries

2. Performance at Scale#

• JIT Compilation: eBPF bytecode is compiled to native machine code
• In-kernel execution: No context switches between kernel and user space
• Event-driven: Programs run only when specific events occur
• Near-native performance: JIT-compiled code runs almost as fast as kernel modules

3. Dynamic Programmability#

• Load and unload programs at runtime
• No kernel restarts required
• No kernel recompilation needed
• Update functionality on live systems

1. Program Development#

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// Example: Simple eBPF program counting system calls
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#include <linux/bpf.h>
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#include <bpf/bpf_helpers.h>
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struct {
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    __uint(type, BPF_MAP_TYPE_HASH);
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    __uint(max_entries, 256);
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    __type(key, __u32);
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    __type(value, __u64);
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} syscall_count SEC(".maps");
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SEC("tracepoint/syscalls/sys_enter")
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int count_syscalls(void *ctx) {
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    __u32 pid = bpf_get_current_pid_tgid() >> 32;
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    __u64 *count, init_val = 1;
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    count = bpf_map_lookup_elem(&syscall_count, &pid);
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    if (count)
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        (*count)++;
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    else
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        bpf_map_update_elem(&syscall_count, &pid, &init_val, BPF_ANY);
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    return 0;
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}

2. Compilation Process#

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# Compile eBPF program to bytecode
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clang -O2 -target bpf -c program.c -o program.o

3. Loading and Verification#

When loading an eBPF program:

1. Bytecode submission: User space submits compiled bytecode to kernel
2. Verification: The verifier performs extensive checks (10,000+ lines of code)
3. JIT compilation: Bytecode is compiled to native machine instructions
4. Attachment: Program is attached to a specific kernel hook point

4. Execution Flow#

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Event Occurs → Hook Triggered → eBPF Program Executes → Results Stored/Actions Taken

1. Program Types#

Different program types for different use cases:

• XDP (eXpress Data Path): Packet processing at the network driver level
• TC (Traffic Control): Network traffic shaping and filtering
• Tracepoints: Instrumentation at predefined kernel locations
• Kprobes/Kretprobes: Dynamic instrumentation of kernel functions
• Uprobes/Uretprobes: User-space function instrumentation
• Perf Events: Performance monitoring and profiling
• Cgroup: Resource control and accounting

2. Maps#

eBPF maps are key-value data structures for:

• State storage: Persist data between program invocations
• Communication: Share data between eBPF programs and user space
• Configuration: Pass parameters from user space to kernel

Common map types:

• Hash tables
• Arrays
• Ring buffers
• Stack traces
• LPM (Longest Prefix Match) tries
• Bloom filters

3. Helper Functions#

Stable API for kernel functionality:

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// Examples of helper functions
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bpf_get_current_pid_tgid()  // Get process/thread ID
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bpf_ktime_get_ns()          // Get timestamp
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bpf_map_lookup_elem()       // Look up map element
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bpf_probe_read()            // Safe kernel memory read
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bpf_redirect()              // Redirect network packets

vs. Kernel Modules#

vs. User-space Solutions#

• Lower overhead: No kernel-user context switches
• Complete visibility: Access to all kernel events
• Real-time response: Immediate reaction to events
• Kernel-level enforcement: Cannot be bypassed by user processes

Performance Gains#

• Netflix: 40% reduction in CPU usage for network load balancing
• Cloudflare: Microsecond-level DDoS mitigation
• Facebook: 10x improvement in packet processing performance

Security Enhancements#

• Runtime security: Detect and prevent malicious behavior in real-time
• Zero-trust networking: Implement fine-grained network policies
• Compliance: Audit all system calls and file access

Observability Revolution#

• Distributed tracing: Track requests across microservices
• Performance profiling: Identify bottlenecks with minimal overhead
• Custom metrics: Generate application-specific insights

Prerequisites#

1. Linux kernel 4.4+ (newer is better)
2. Development tools: clang, llvm, libbpf
3. Privileges: CAP_BPF capability or root access

Learning Path#

1. Start with high-level tools: bpftrace for simple scripts
2. Explore BCC tools: Pre-built tools for common tasks
3. Learn libbpf: Modern C API for eBPF development
4. Try language bindings: Go, Rust, Python for easier development

Hello World Example#

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# Using bpftrace - trace all open() system calls
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sudo bpftrace -e 'tracepoint:syscalls:sys_enter_open { printf("%s opened %s\n", comm, str(args->filename)); }'

Emerging Trends#

1. Cross-platform support: Windows and macOS implementations
2. Hardware acceleration: eBPF offload to SmartNICs
3. WebAssembly integration: Wasm-bpf for portable eBPF programs
4. AI/ML integration: LLMs generating eBPF programs

Growing Ecosystem#

• Cloud Native: Kubernetes CNI plugins (Cilium, Calico)
• Security: Runtime protection (Falco, Tetragon)
• Observability: APM solutions (Pixie, Parca)
• Networking: Load balancers, firewalls, service meshes