eBPF Map Metrics Prometheus Exporter: Advanced Observability with eBPF Iterators#

This comprehensive guide explores building a standalone eBPF Map Metrics Prometheus exporter using eBPF Iterators—a powerful feature that enables comprehensive observability of eBPF programs without altering your existing application stack.

The Challenge: eBPF Observability#

One of the fundamental challenges in eBPF development is gaining visibility into eBPF map usage, performance metrics, and operational statistics. Traditional approaches often require:

Modifying existing applications to expose metrics
Adding instrumentation code to eBPF programs
Creating custom monitoring solutions for each use case
Dealing with performance overhead from metrics collection

1
graph TB
2
    subgraph "Traditional eBPF Monitoring Challenges"
3
        C1[Application Modification] --> C2[Code Instrumentation]
4
        C3[Custom Solutions] --> C4[Performance Overhead]
5
        C5[Limited Visibility] --> C6[Complex Integration]
6
    end
7

8
    subgraph "eBPF Iterator Solution"
9
        S1[No Code Changes] --> S2[Kernel-level Access]
10
        S3[Universal Monitoring] --> S4[Minimal Overhead]
11
        S5[Deep Visibility] --> S6[Simple Integration]
12
    end
13

14
    style C1 fill:#ffcdd2
15
    style C2 fill:#ffcdd2
16
    style C3 fill:#ffcdd2
17
    style C4 fill:#ffcdd2
18
    style C5 fill:#ffcdd2
19
    style C6 fill:#ffcdd2
20
    style S1 fill:#c8e6c9
21
    style S2 fill:#c8e6c9
22
    style S3 fill:#c8e6c9
23
    style S4 fill:#c8e6c9
24
    style S5 fill:#c8e6c9
25
    style S6 fill:#c8e6c9

Understanding eBPF Iterators#

eBPF Iterators represent a breakthrough in kernel data structure inspection, providing a safe and efficient way to traverse kernel data structures without compromising system stability.

What is an eBPF Iterator?#

An eBPF Iterator is a specialized type of eBPF program that allows users to iterate over specific types of kernel data structures by defining callback functions that are executed for every entry in various kernel structures.

1
graph LR
2
    subgraph "eBPF Iterator Architecture"
3
        subgraph "User Space"
4
            US1[Iterator Program] --> US2[Callback Definition]
5
        end
6

7
        subgraph "Kernel Space"
8
            KS1[Iterator Framework] --> KS2[Data Structure Traversal]
9
            KS3[Safety Verification] --> KS4[Callback Execution]
10
        end
11

12
        subgraph "Data Sources"
13
            DS1[BPF Maps] --> DS2[Task Lists]
14
            DS3[Network Structures] --> DS4[File Systems]
15
        end
16

17
        US1 --> KS1
18
        US2 --> KS4
19
        KS2 --> DS1
20
        KS2 --> DS2
21
        KS2 --> DS3
22
        KS2 --> DS4
23
    end
24

25
    style US1 fill:#e1f5fe
26
    style KS1 fill:#e8f5e8
27
    style DS1 fill:#f3e5f5

Key Iterator Capabilities#

eBPF Iterators can traverse various kernel data structures:

BPF Maps: Inspect map contents, usage statistics, and metadata
Task Structures: Analyze process information, CPU usage, and scheduling data
Network Structures: Examine socket states, connection information, and traffic patterns
File System Data: Access file descriptors, inode information, and I/O statistics

Iterator Types and Use Cases#

Common Iterator Categories#

1
graph TB
2
    subgraph "eBPF Iterator Types"
3
        subgraph "System Iterators"
4
            SI1[task] --> SI2[task_file]
5
            SI3[task_vma] --> SI4[tcp]
6
        end
7

8
        subgraph "BPF Iterators"
9
            BI1[bpf_map] --> BI2[bpf_map_elem]
10
            BI3[bpf_prog] --> BI4[bpf_link]
11
        end
12

13
        subgraph "Network Iterators"
14
            NI1[netlink] --> NI2[udp]
15
            NI3[unix] --> NI4[ipv6_route]
16
        end
17
    end
18

19
    style SI1 fill:#e1f5fe
20
    style BI1 fill:#f3e5f5
21
    style NI1 fill:#e8f5e8

Practical Applications#

System Monitoring:

CPU runtime analysis across all system tasks
Memory usage patterns and allocation tracking
Process lifecycle management and monitoring

Network Analysis:

Connection state monitoring and analysis
Traffic pattern identification and classification
Socket resource usage and optimization

BPF Program Observability:

Map utilization and performance metrics
Program execution statistics and profiling
Resource consumption analysis and optimization

Building the eBPF Map Metrics Exporter#

Let’s build a comprehensive eBPF Map Metrics Prometheus exporter using eBPF Iterators.

Project Structure#

1
ebpf-map-exporter/
2
├── src/
3
│   ├── iterator.bpf.c          # eBPF Iterator program
4
│   ├── exporter.c              # User-space exporter
5
│   └── metrics.h               # Shared data structures
6
├── build/
7
│   └── Makefile
8
├── docker/
9
│   └── Dockerfile
10
└── README.md

eBPF Iterator Implementation#

First, let’s implement the eBPF iterator program that traverses BPF maps:

1
#include <vmlinux.h>
2
#include <bpf/bpf_helpers.h>
3
#include <bpf/bpf_tracing.h>
4
#include <bpf/bpf_core_read.h>
5

6
// Metrics data structure
7
struct bpf_map_metrics {
8
    __u32 map_id;
9
    __u32 map_type;
10
    __u32 key_size;
11
    __u32 value_size;
12
    __u32 max_entries;
13
    __u64 memory_usage;
14
    __u64 ops_count;
15
    char name[16];
16
};
17

18
// Output buffer for metrics
19
struct {
20
    __uint(type, BPF_MAP_TYPE_RINGBUF);
21
    __uint(max_entries, 256 * 1024);
22
} metrics_buffer SEC(".maps");
23

24
// Iterator for BPF maps
25
SEC("iter/bpf_map")
26
int collect_map_metrics(struct bpf_iter__bpf_map *ctx) {
27
    struct bpf_map *map = ctx->map;
28
    struct bpf_map_metrics *metrics;
29

30
    if (!map)
31
        return 0;
32

33
    // Reserve space in ring buffer
34
    metrics = bpf_ringbuf_reserve(&metrics_buffer, sizeof(*metrics), 0);
35
    if (!metrics)
36
        return 0;
37

38
    // Extract map information
39
    metrics->map_id = BPF_CORE_READ(map, id);
40
    metrics->map_type = BPF_CORE_READ(map, map_type);
41
    metrics->key_size = BPF_CORE_READ(map, key_size);
42
    metrics->value_size = BPF_CORE_READ(map, value_size);
43
    metrics->max_entries = BPF_CORE_READ(map, max_entries);
44

45
    // Calculate memory usage (approximate)
46
    __u32 entry_size = metrics->key_size + metrics->value_size;
47
    metrics->memory_usage = (__u64)entry_size * metrics->max_entries;
48

49
    // Get map name if available
50
    const char *name = BPF_CORE_READ(map, name);
51
    if (name) {
52
        bpf_probe_read_str(metrics->name, sizeof(metrics->name), name);
53
    } else {
54
        __builtin_memcpy(metrics->name, "unknown", 8);
55
    }
56

57
    // For demonstration, we'll use a simple counter
58
    // In a real implementation, you'd track actual operations
59
    metrics->ops_count = metrics->map_id * 100; // Placeholder
60

61
    // Submit metrics to user space
62
    bpf_ringbuf_submit(metrics, 0);
63

64
    return 0;
65
}
66

67
// Iterator for BPF map elements (for detailed analysis)
68
SEC("iter/bpf_map_elem")
69
int collect_map_element_metrics(struct bpf_iter__bpf_map_elem *ctx) {
70
    struct bpf_map *map = ctx->map;
71
    void *key = ctx->key;
72
    void *value = ctx->value;
73

74
    if (!map || !key || !value)
75
        return 0;
76

77
    // Here you could collect per-element statistics
78
    // For example: key distribution, value patterns, access frequency
79

80
    // This is a simplified example - real implementation would
81
    // collect more sophisticated metrics
82

83
    return 0;
84
}
85

86
// Iterator for BPF programs (to correlate with map usage)
87
SEC("iter/bpf_prog")
88
int collect_prog_metrics(struct bpf_iter__bpf_prog *ctx) {
89
    struct bpf_prog *prog = ctx->prog;
90

91
    if (!prog)
92
        return 0;
93

94
    // Collect program-related metrics that correlate with map usage
95
    // This could include execution statistics, memory usage, etc.
96

97
    return 0;
98
}
99

100
char _license[] SEC("license") = "GPL";

Advanced Map Analysis Iterator#

Let’s create a more sophisticated iterator that provides deeper insights:

1
#include <vmlinux.h>
2
#include <bpf/bpf_helpers.h>
3
#include <bpf/bpf_tracing.h>
4
#include <bpf/bpf_core_read.h>
5

6
// Advanced metrics structure
7
struct advanced_map_metrics {
8
    __u32 map_id;
9
    __u32 map_type;
10
    __u32 key_size;
11
    __u32 value_size;
12
    __u32 max_entries;
13
    __u32 current_entries;
14
    __u64 total_memory;
15
    __u64 used_memory;
16
    __u64 lookup_count;
17
    __u64 update_count;
18
    __u64 delete_count;
19
    __u64 creation_time;
20
    __u64 last_access_time;
21
    float utilization_ratio;
22
    char name[32];
23
    char prog_name[32];
24
};
25

26
// Enhanced output buffer
27
struct {
28
    __uint(type, BPF_MAP_TYPE_RINGBUF);
29
    __uint(max_entries, 1024 * 1024);
30
} advanced_metrics_buffer SEC(".maps");
31

32
// Map for tracking operation counts
33
struct {
34
    __uint(type, BPF_MAP_TYPE_HASH);
35
    __uint(max_entries, 1024);
36
    __type(key, __u32);
37
    __type(value, struct map_op_stats);
38
} map_op_tracker SEC(".maps");
39

40
struct map_op_stats {
41
    __u64 lookups;
42
    __u64 updates;
43
    __u64 deletes;
44
    __u64 last_op_time;
45
};
46

47
// Helper function to calculate map utilization
48
static float calculate_utilization(__u32 current, __u32 max) {
49
    if (max == 0)
50
        return 0.0;
51
    return (float)current / (float)max;
52
}
53

54
// Helper function to estimate current entries (simplified)
55
static __u32 estimate_current_entries(struct bpf_map *map) {
56
    // This is a simplified estimation
57
    // Real implementation would need to traverse the map structure
58
    __u32 max_entries = BPF_CORE_READ(map, max_entries);
59
    return max_entries / 4; // Placeholder estimation
60
}
61

62
SEC("iter/bpf_map")
63
int collect_advanced_map_metrics(struct bpf_iter__bpf_map *ctx) {
64
    struct bpf_map *map = ctx->map;
65
    struct advanced_map_metrics *metrics;
66
    struct map_op_stats *op_stats;
67
    __u32 map_id;
68

69
    if (!map)
70
        return 0;
71

72
    map_id = BPF_CORE_READ(map, id);
73

74
    // Reserve space for advanced metrics
75
    metrics = bpf_ringbuf_reserve(&advanced_metrics_buffer, sizeof(*metrics), 0);
76
    if (!metrics)
77
        return 0;
78

79
    // Basic map information
80
    metrics->map_id = map_id;
81
    metrics->map_type = BPF_CORE_READ(map, map_type);
82
    metrics->key_size = BPF_CORE_READ(map, key_size);
83
    metrics->value_size = BPF_CORE_READ(map, value_size);
84
    metrics->max_entries = BPF_CORE_READ(map, max_entries);
85

86
    // Estimate current entries (in real implementation, this would be more accurate)
87
    metrics->current_entries = estimate_current_entries(map);
88

89
    // Memory calculations
90
    __u32 entry_size = metrics->key_size + metrics->value_size;
91
    metrics->total_memory = (__u64)entry_size * metrics->max_entries;
92
    metrics->used_memory = (__u64)entry_size * metrics->current_entries;
93

94
    // Calculate utilization ratio
95
    metrics->utilization_ratio = calculate_utilization(metrics->current_entries, metrics->max_entries);
96

97
    // Get operation statistics
98
    op_stats = bpf_map_lookup_elem(&map_op_tracker, &map_id);
99
    if (op_stats) {
100
        metrics->lookup_count = op_stats->lookups;
101
        metrics->update_count = op_stats->updates;
102
        metrics->delete_count = op_stats->deletes;
103
        metrics->last_access_time = op_stats->last_op_time;
104
    } else {
105
        // Initialize if not found
106
        metrics->lookup_count = 0;
107
        metrics->update_count = 0;
108
        metrics->delete_count = 0;
109
        metrics->last_access_time = 0;
110
    }
111

112
    // Timestamp
113
    metrics->creation_time = bpf_ktime_get_ns();
114

115
    // Extract map name
116
    const char *name = BPF_CORE_READ(map, name);
117
    if (name) {
118
        bpf_probe_read_str(metrics->name, sizeof(metrics->name), name);
119
    } else {
120
        __builtin_memcpy(metrics->name, "unnamed", 8);
121
    }
122

123
    // Get associated program name (if available)
124
    __builtin_memcpy(metrics->prog_name, "unknown", 8);
125

126
    // Submit advanced metrics
127
    bpf_ringbuf_submit(metrics, 0);
128

129
    return 0;
130
}
131

132
// Hook to track map operations (for more accurate statistics)
133
SEC("fentry/bpf_map_lookup_elem")
134
int track_map_lookup(struct bpf_map *map, void *key) {
135
    __u32 map_id = BPF_CORE_READ(map, id);
136
    struct map_op_stats *stats;
137
    struct map_op_stats new_stats = {0};
138

139
    stats = bpf_map_lookup_elem(&map_op_tracker, &map_id);
140
    if (!stats) {
141
        stats = &new_stats;
142
    }
143

144
    stats->lookups++;
145
    stats->last_op_time = bpf_ktime_get_ns();
146

147
    bpf_map_update_elem(&map_op_tracker, &map_id, stats, BPF_ANY);
148

149
    return 0;
150
}
151

152
SEC("fentry/bpf_map_update_elem")
153
int track_map_update(struct bpf_map *map, void *key, void *value, __u64 flags) {
154
    __u32 map_id = BPF_CORE_READ(map, id);
155
    struct map_op_stats *stats;
156
    struct map_op_stats new_stats = {0};
157

158
    stats = bpf_map_lookup_elem(&map_op_tracker, &map_id);
159
    if (!stats) {
160
        stats = &new_stats;
161
    }
162

163
    stats->updates++;
164
    stats->last_op_time = bpf_ktime_get_ns();
165

166
    bpf_map_update_elem(&map_op_tracker, &map_id, stats, BPF_ANY);
167

168
    return 0;
169
}
170

171
SEC("fentry/bpf_map_delete_elem")
172
int track_map_delete(struct bpf_map *map, void *key) {
173
    __u32 map_id = BPF_CORE_READ(map, id);
174
    struct map_op_stats *stats;
175
    struct map_op_stats new_stats = {0};
176

177
    stats = bpf_map_lookup_elem(&map_op_tracker, &map_id);
178
    if (!stats) {
179
        stats = &new_stats;
180
    }
181

182
    stats->deletes++;
183
    stats->last_op_time = bpf_ktime_get_ns();
184

185
    bpf_map_update_elem(&map_op_tracker, &map_id, stats, BPF_ANY);
186

187
    return 0;
188
}
189

190
char _license[] SEC("license") = "GPL";

User-Space Prometheus Exporter#

Now let’s implement the user-space component that consumes iterator output and exports Prometheus metrics:

1
#include <stdio.h>
2
#include <stdlib.h>
3
#include <string.h>
4
#include <unistd.h>
5
#include <signal.h>
6
#include <time.h>
7
#include <errno.h>
8
#include <sys/stat.h>
9
#include <microhttpd.h>
10
#include <bpf/libbpf.h>
11
#include <bpf/bpf.h>
12
#include "metrics.h"
13

14
#define METRICS_PORT 8080
15
#define METRICS_PATH "/metrics"
16
#define MAX_METRICS_SIZE 65536
17

18
// Global state
19
static struct bpf_object *obj = NULL;
20
static struct ring_buffer *rb = NULL;
21
static volatile int running = 1;
22
static char metrics_output[MAX_METRICS_SIZE];
23
static time_t last_update = 0;
24

25
// Metrics storage
26
struct metrics_store {
27
    struct advanced_map_metrics maps[1024];
28
    int count;
29
    time_t last_updated;
30
} metrics_store = {0};
31

32
// Signal handler
33
static void sig_handler(int sig) {
34
    running = 0;
35
}
36

37
// Ring buffer callback for processing metrics
38
static int handle_metrics(void *ctx, void *data, size_t data_sz) {
39
    struct advanced_map_metrics *metrics = data;
40

41
    if (metrics_store.count < 1024) {
42
        memcpy(&metrics_store.maps[metrics_store.count], metrics, sizeof(*metrics));
43
        metrics_store.count++;
44
        metrics_store.last_updated = time(NULL);
45
    }
46

47
    return 0;
48
}
49

50
// Generate Prometheus metrics format
51
static void generate_prometheus_metrics() {
52
    char *p = metrics_output;
53
    size_t remaining = MAX_METRICS_SIZE;
54
    int written;
55
    time_t now = time(NULL);
56

57
    // Clear previous metrics
58
    memset(metrics_output, 0, MAX_METRICS_SIZE);
59

60
    // Prometheus headers
61
    written = snprintf(p, remaining,
62
        "# HELP ebpf_map_info Information about eBPF maps\n"
63
        "# TYPE ebpf_map_info gauge\n");
64
    p += written;
65
    remaining -= written;
66

67
    written = snprintf(p, remaining,
68
        "# HELP ebpf_map_memory_bytes Memory usage of eBPF maps in bytes\n"
69
        "# TYPE ebpf_map_memory_bytes gauge\n");
70
    p += written;
71
    remaining -= written;
72

73
    written = snprintf(p, remaining,
74
        "# HELP ebpf_map_utilization_ratio Current utilization ratio of eBPF maps\n"
75
        "# TYPE ebpf_map_utilization_ratio gauge\n");
76
    p += written;
77
    remaining -= written;
78

79
    written = snprintf(p, remaining,
80
        "# HELP ebpf_map_operations_total Total operations performed on eBPF maps\n"
81
        "# TYPE ebpf_map_operations_total counter\n");
82
    p += written;
83
    remaining -= written;
84

85
    // Generate metrics for each map
86
    for (int i = 0; i < metrics_store.count && remaining > 0; i++) {
87
        struct advanced_map_metrics *m = &metrics_store.maps[i];
88

89
        // Map info metric
90
        written = snprintf(p, remaining,
91
            "ebpf_map_info{map_id=\"%u\",name=\"%s\",type=\"%u\",key_size=\"%u\",value_size=\"%u\",max_entries=\"%u\"} 1\n",
92
            m->map_id, m->name, m->map_type, m->key_size, m->value_size, m->max_entries);
93
        p += written;
94
        remaining -= written;
95

96
        // Memory usage metrics
97
        written = snprintf(p, remaining,
98
            "ebpf_map_memory_bytes{map_id=\"%u\",name=\"%s\",type=\"total\"} %lu\n",
99
            m->map_id, m->name, m->total_memory);
100
        p += written;
101
        remaining -= written;
102

103
        written = snprintf(p, remaining,
104
            "ebpf_map_memory_bytes{map_id=\"%u\",name=\"%s\",type=\"used\"} %lu\n",
105
            m->map_id, m->name, m->used_memory);
106
        p += written;
107
        remaining -= written;
108

109
        // Utilization ratio
110
        written = snprintf(p, remaining,
111
            "ebpf_map_utilization_ratio{map_id=\"%u\",name=\"%s\"} %.2f\n",
112
            m->map_id, m->name, m->utilization_ratio);
113
        p += written;
114
        remaining -= written;
115

116
        // Operation counters
117
        written = snprintf(p, remaining,
118
            "ebpf_map_operations_total{map_id=\"%u\",name=\"%s\",operation=\"lookup\"} %lu\n",
119
            m->map_id, m->name, m->lookup_count);
120
        p += written;
121
        remaining -= written;
122

123
        written = snprintf(p, remaining,
124
            "ebpf_map_operations_total{map_id=\"%u\",name=\"%s\",operation=\"update\"} %lu\n",
125
            m->map_id, m->name, m->update_count);
126
        p += written;
127
        remaining -= written;
128

129
        written = snprintf(p, remaining,
130
            "ebpf_map_operations_total{map_id=\"%u\",name=\"%s\",operation=\"delete\"} %lu\n",
131
            m->map_id, m->name, m->delete_count);
132
        p += written;
133
        remaining -= written;
134
    }
135

136
    // Add timestamp
137
    written = snprintf(p, remaining,
138
        "# HELP ebpf_exporter_last_update_timestamp_seconds Last update timestamp\n"
139
        "# TYPE ebpf_exporter_last_update_timestamp_seconds gauge\n"
140
        "ebpf_exporter_last_update_timestamp_seconds %ld\n", now);
141

142
    last_update = now;
143
}
144

145
// HTTP request handler
146
static enum MHD_Result handle_request(void *cls, struct MHD_Connection *connection,
147
                                     const char *url, const char *method,
148
                                     const char *version, const char *upload_data,
149
                                     size_t *upload_data_size, void **con_cls) {
150
    struct MHD_Response *response;
151
    enum MHD_Result ret;
152

153
    if (strcmp(url, METRICS_PATH) != 0) {
154
        const char *not_found = "404 Not Found";
155
        response = MHD_create_response_from_buffer(strlen(not_found), (void*)not_found,
156
                                                  MHD_RESPMEM_PERSISTENT);
157
        ret = MHD_queue_response(connection, MHD_HTTP_NOT_FOUND, response);
158
        MHD_destroy_response(response);
159
        return ret;
160
    }
161

162
    // Generate fresh metrics if needed
163
    time_t now = time(NULL);
164
    if (now - last_update > 5) { // Update every 5 seconds
165
        generate_prometheus_metrics();
166
    }
167

168
    response = MHD_create_response_from_buffer(strlen(metrics_output),
169
                                              (void*)metrics_output,
170
                                              MHD_RESPMEM_MUST_COPY);
171

172
    MHD_add_response_header(response, "Content-Type", "text/plain; charset=utf-8");
173
    ret = MHD_queue_response(connection, MHD_HTTP_OK, response);
174
    MHD_destroy_response(response);
175

176
    return ret;
177
}
178

179
// Initialize eBPF program and iterator
180
static int init_ebpf() {
181
    int err;
182
    struct bpf_link *link;
183

184
    // Open and load eBPF object
185
    obj = bpf_object__open_file("advanced_iterator.bpf.o", NULL);
186
    if (libbpf_get_error(obj)) {
187
        fprintf(stderr, "Failed to open eBPF object\n");
188
        return -1;
189
    }
190

191
    err = bpf_object__load(obj);
192
    if (err) {
193
        fprintf(stderr, "Failed to load eBPF object: %d\n", err);
194
        return -1;
195
    }
196

197
    // Find and attach iterator program
198
    struct bpf_program *prog = bpf_object__find_program_by_name(obj, "collect_advanced_map_metrics");
199
    if (!prog) {
200
        fprintf(stderr, "Failed to find iterator program\n");
201
        return -1;
202
    }
203

204
    link = bpf_program__attach(prog);
205
    if (libbpf_get_error(link)) {
206
        fprintf(stderr, "Failed to attach iterator program\n");
207
        return -1;
208
    }
209

210
    // Set up ring buffer
211
    int map_fd = bpf_object__find_map_fd_by_name(obj, "advanced_metrics_buffer");
212
    if (map_fd < 0) {
213
        fprintf(stderr, "Failed to find metrics buffer map\n");
214
        return -1;
215
    }
216

217
    rb = ring_buffer__new(map_fd, handle_metrics, NULL, NULL);
218
    if (!rb) {
219
        fprintf(stderr, "Failed to create ring buffer\n");
220
        return -1;
221
    }
222

223
    printf("eBPF map metrics exporter initialized successfully\n");
224
    return 0;
225
}
226

227
// Metrics collection loop
228
static void *metrics_collector(void *arg) {
229
    while (running) {
230
        // Poll ring buffer for new metrics
231
        ring_buffer__poll(rb, 1000); // 1 second timeout
232

233
        // Periodically trigger iterator execution
234
        // This would typically be done through iterator attachment
235
        usleep(100000); // 100ms
236
    }
237
    return NULL;
238
}
239

240
int main(int argc, char **argv) {
241
    struct MHD_Daemon *daemon;
242
    pthread_t collector_thread;
243

244
    // Set up signal handlers
245
    signal(SIGINT, sig_handler);
246
    signal(SIGTERM, sig_handler);
247

248
    // Initialize eBPF components
249
    if (init_ebpf() < 0) {
250
        fprintf(stderr, "Failed to initialize eBPF components\n");
251
        return 1;
252
    }
253

254
    // Start metrics collection thread
255
    if (pthread_create(&collector_thread, NULL, metrics_collector, NULL) != 0) {
256
        fprintf(stderr, "Failed to create collector thread\n");
257
        return 1;
258
    }
259

260
    // Start HTTP server
261
    daemon = MHD_start_daemon(MHD_USE_INTERNAL_POLLING_THREAD,
262
                             METRICS_PORT,
263
                             NULL, NULL,
264
                             &handle_request, NULL,
265
                             MHD_OPTION_END);
266

267
    if (!daemon) {
268
        fprintf(stderr, "Failed to start HTTP server\n");
269
        return 1;
270
    }
271

272
    printf("eBPF Map Metrics Prometheus Exporter started on port %d\n", METRICS_PORT);
273
    printf("Metrics available at http://localhost:%d%s\n", METRICS_PORT, METRICS_PATH);
274

275
    // Main loop
276
    while (running) {
277
        sleep(1);
278
    }
279

280
    // Cleanup
281
    printf("\nShutting down...\n");
282
    MHD_stop_daemon(daemon);
283
    pthread_join(collector_thread, NULL);
284

285
    if (rb) ring_buffer__free(rb);
286
    if (obj) bpf_object__close(obj);
287

288
    return 0;
289
}

Shared Header File#

1
#ifndef METRICS_H
2
#define METRICS_H
3

4
#include <stdint.h>
5

6
// Shared structures between eBPF and user space
7
struct bpf_map_metrics {
8
    uint32_t map_id;
9
    uint32_t map_type;
10
    uint32_t key_size;
11
    uint32_t value_size;
12
    uint32_t max_entries;
13
    uint64_t memory_usage;
14
    uint64_t ops_count;
15
    char name[16];
16
};
17

18
struct advanced_map_metrics {
19
    uint32_t map_id;
20
    uint32_t map_type;
21
    uint32_t key_size;
22
    uint32_t value_size;
23
    uint32_t max_entries;
24
    uint32_t current_entries;
25
    uint64_t total_memory;
26
    uint64_t used_memory;
27
    uint64_t lookup_count;
28
    uint64_t update_count;
29
    uint64_t delete_count;
30
    uint64_t creation_time;
31
    uint64_t last_access_time;
32
    float utilization_ratio;
33
    char name[32];
34
    char prog_name[32];
35
};
36

37
struct map_op_stats {
38
    uint64_t lookups;
39
    uint64_t updates;
40
    uint64_t deletes;
41
    uint64_t last_op_time;
42
};
43

44
#endif // METRICS_H

Build System and Deployment#

Makefile#

1
# Makefile
2
CC = clang
3
CFLAGS = -O2 -g -Wall
4
BPF_CFLAGS = -target bpf -O2 -g -c
5

6
# System includes
7
LIBBPF_DIR = /usr/lib/x86_64-linux-gnu
8
LIBBPF_INCLUDE = /usr/include
9
MHD_LIBS = -lmicrohttpd
10
PTHREAD_LIBS = -lpthread
11

12
# eBPF object files
13
BPF_OBJECTS = iterator.bpf.o advanced_iterator.bpf.o
14

15
# User space binary
16
USER_BINARY = ebpf-map-exporter
17

18
.PHONY: all clean install
19

20
all: $(BPF_OBJECTS) $(USER_BINARY)
21

22
# Compile eBPF programs
23
%.bpf.o: %.bpf.c
24
  $(CC) $(BPF_CFLAGS) -I$(LIBBPF_INCLUDE) -c $< -o $@
25

26
# Generate vmlinux.h if needed
27
vmlinux.h:
28
  bpftool btf dump file /sys/kernel/btf/vmlinux format c > vmlinux.h
29

30
# Compile user space program
31
$(USER_BINARY): exporter.c $(BPF_OBJECTS)
32
  $(CC) $(CFLAGS) -I$(LIBBPF_INCLUDE) $< -L$(LIBBPF_DIR) \
33
    -lbpf $(MHD_LIBS) $(PTHREAD_LIBS) -o $@
34

35
# Install system-wide
36
install: all
37
  sudo cp $(USER_BINARY) /usr/local/bin/
38
  sudo cp $(BPF_OBJECTS) /usr/local/share/ebpf-exporter/
39
  sudo systemctl daemon-reload
40

41
# Clean build artifacts
42
clean:
43
  rm -f *.o $(USER_BINARY) vmlinux.h
44

45
# Development targets
46
dev: all
47
  sudo ./$(USER_BINARY)
48

49
test: all
50
  # Run basic functionality tests
51
  sudo timeout 10s ./$(USER_BINARY) &
52
  sleep 5
53
  curl -s http://localhost:8080/metrics | head -20
54
  pkill -f $(USER_BINARY)
55

56
# Docker build
57
docker:
58
  docker build -t ebpf-map-exporter -f docker/Dockerfile .
59

60
.SUFFIXES: .bpf.c .bpf.o

Docker Configuration#

1
# docker/Dockerfile
2
FROM ubuntu:22.04
3

4
# Install dependencies
5
RUN apt-get update && apt-get install -y \
6
    clang \
7
    libbpf-dev \
8
    libmicrohttpd-dev \
9
    linux-tools-common \
10
    linux-tools-generic \
11
    bpftool \
12
    && rm -rf /var/lib/apt/lists/*
13

14
# Create working directory
15
WORKDIR /app
16

17
# Copy source code
18
COPY src/ ./src/
19
COPY build/Makefile ./
20

21
# Build the application
22
RUN make all
23

24
# Create non-root user for security
25
RUN useradd -r -s /bin/false ebpf-exporter
26

27
# Expose metrics port
28
EXPOSE 8080
29

30
# Set capabilities for eBPF operations
31
# Note: In production, consider using privileged containers or specific capabilities
32
USER root
33

34
# Start the exporter
35
CMD ["./ebpf-map-exporter"]

Systemd Service Configuration#

1
[Unit]
2
Description=eBPF Map Metrics Prometheus Exporter
3
After=network.target
4
Wants=network.target
5

6
[Service]
7
Type=simple
8
User=root
9
Group=root
10
ExecStart=/usr/local/bin/ebpf-map-exporter
11
Restart=always
12
RestartSec=5
13
StandardOutput=journal
14
StandardError=journal
15

16
# Security settings
17
NoNewPrivileges=true
18
ProtectSystem=strict
19
ProtectHome=true
20
ReadWritePaths=/tmp
21

22
# Required for eBPF operations
23
AmbientCapabilities=CAP_SYS_ADMIN CAP_BPF
24
CapabilityBoundingSet=CAP_SYS_ADMIN CAP_BPF
25

26
[Install]
27
WantedBy=multi-user.target

Advanced Iterator Examples#

Task CPU Usage Iterator#

1
#include <vmlinux.h>
2
#include <bpf/bpf_helpers.h>
3
#include <bpf/bpf_tracing.h>
4

5
struct task_cpu_metrics {
6
    __u32 pid;
7
    __u32 tgid;
8
    __u64 utime;
9
    __u64 stime;
10
    __u64 runtime;
11
    char comm[16];
12
};
13

14
struct {
15
    __uint(type, BPF_MAP_TYPE_RINGBUF);
16
    __uint(max_entries, 256 * 1024);
17
} task_metrics_buffer SEC(".maps");
18

19
SEC("iter/task")
20
int collect_task_cpu_metrics(struct bpf_iter__task *ctx) {
21
    struct task_struct *task = ctx->task;
22
    struct task_cpu_metrics *metrics;
23

24
    if (!task)
25
        return 0;
26

27
    metrics = bpf_ringbuf_reserve(&task_metrics_buffer, sizeof(*metrics), 0);
28
    if (!metrics)
29
        return 0;
30

31
    // Extract task information
32
    metrics->pid = BPF_CORE_READ(task, pid);
33
    metrics->tgid = BPF_CORE_READ(task, tgid);
34

35
    // Get CPU usage statistics
36
    metrics->utime = BPF_CORE_READ(task, utime);
37
    metrics->stime = BPF_CORE_READ(task, stime);
38

39
    // Calculate total runtime
40
    metrics->runtime = metrics->utime + metrics->stime;
41

42
    // Get process name
43
    bpf_probe_read_str(metrics->comm, sizeof(metrics->comm),
44
                       BPF_CORE_READ(task, comm));
45

46
    bpf_ringbuf_submit(metrics, 0);
47
    return 0;
48
}
49

50
char _license[] SEC("license") = "GPL";

Network Connection Iterator#

1
#include <vmlinux.h>
2
#include <bpf/bpf_helpers.h>
3
#include <bpf/bpf_tracing.h>
4

5
struct connection_metrics {
6
    __be32 src_addr;
7
    __be32 dst_addr;
8
    __be16 src_port;
9
    __be16 dst_port;
10
    __u8 state;
11
    __u64 rx_bytes;
12
    __u64 tx_bytes;
13
    __u64 rx_packets;
14
    __u64 tx_packets;
15
};
16

17
struct {
18
    __uint(type, BPF_MAP_TYPE_RINGBUF);
19
    __uint(max_entries, 512 * 1024);
20
} connection_metrics_buffer SEC(".maps");
21

22
SEC("iter/tcp")
23
int collect_tcp_connection_metrics(struct bpf_iter__tcp *ctx) {
24
    struct sock *sk = ctx->sk;
25
    struct connection_metrics *metrics;
26

27
    if (!sk)
28
        return 0;
29

30
    metrics = bpf_ringbuf_reserve(&connection_metrics_buffer, sizeof(*metrics), 0);
31
    if (!metrics)
32
        return 0;
33

34
    // Extract connection information
35
    struct inet_sock *inet = (struct inet_sock *)sk;
36

37
    metrics->src_addr = BPF_CORE_READ(inet, inet_saddr);
38
    metrics->dst_addr = BPF_CORE_READ(inet, inet_daddr);
39
    metrics->src_port = BPF_CORE_READ(inet, inet_sport);
40
    metrics->dst_port = BPF_CORE_READ(inet, inet_dport);
41

42
    // Get connection state
43
    metrics->state = BPF_CORE_READ(sk, __sk_common.skc_state);
44

45
    // Extract traffic statistics (simplified)
46
    metrics->rx_bytes = BPF_CORE_READ(sk, sk_napi_id); // Placeholder
47
    metrics->tx_bytes = BPF_CORE_READ(sk, sk_napi_id); // Placeholder
48
    metrics->rx_packets = 0; // Would need more complex extraction
49
    metrics->tx_packets = 0; // Would need more complex extraction
50

51
    bpf_ringbuf_submit(metrics, 0);
52
    return 0;
53
}
54

55
char _license[] SEC("license") = "GPL";

Prometheus Integration and Grafana Dashboards#

Prometheus Configuration#

1
global:
2
  scrape_interval: 15s
3
  evaluation_interval: 15s
4

5
scrape_configs:
6
  - job_name: "ebpf-map-exporter"
7
    static_configs:
8
      - targets: ["localhost:8080"]
9
    scrape_interval: 10s
10
    metrics_path: /metrics

Grafana Dashboard JSON#

1
{
2
  "dashboard": {
3
    "title": "eBPF Map Metrics",
4
    "panels": [
5
      {
6
        "title": "Map Memory Usage",
7
        "type": "graph",
8
        "targets": [
9
          {
10
            "expr": "ebpf_map_memory_bytes",
11
            "legendFormat": "{{name}} - {{type}}"
12
          }
13
        ]
14
      },
15
      {
16
        "title": "Map Utilization",
17
        "type": "singlestat",
18
        "targets": [
19
          {
20
            "expr": "ebpf_map_utilization_ratio",
21
            "legendFormat": "{{name}}"
22
          }
23
        ]
24
      },
25
      {
26
        "title": "Map Operations Rate",
27
        "type": "graph",
28
        "targets": [
29
          {
30
            "expr": "rate(ebpf_map_operations_total[5m])",
31
            "legendFormat": "{{name}} - {{operation}}"
32
          }
33
        ]
34
      }
35
    ]
36
  }
37
}

Performance Optimization and Best Practices#

Memory Management#

1
// Optimized ring buffer usage
2
#define METRICS_BATCH_SIZE 64
3

4
struct metrics_batch {
5
    struct advanced_map_metrics metrics[METRICS_BATCH_SIZE];
6
    int count;
7
};
8

9
SEC("iter/bpf_map")
10
int optimized_collect_metrics(struct bpf_iter__bpf_map *ctx) {
11
    static struct metrics_batch batch = {0};
12
    struct bpf_map *map = ctx->map;
13

14
    if (!map)
15
        return 0;
16

17
    // Collect metrics in batch
18
    if (batch.count < METRICS_BATCH_SIZE) {
19
        collect_single_map_metrics(map, &batch.metrics[batch.count]);
20
        batch.count++;
21
    }
22

23
    // Submit when batch is full
24
    if (batch.count >= METRICS_BATCH_SIZE) {
25
        submit_metrics_batch(&batch);
26
        batch.count = 0;
27
    }
28

29
    return 0;
30
}

CPU Usage Optimization#

1
// Rate-limited metrics collection
2
struct {
3
    __uint(type, BPF_MAP_TYPE_HASH);
4
    __uint(max_entries, 1);
5
    __type(key, __u32);
6
    __type(value, __u64);
7
} last_collection_time SEC(".maps");
8

9
SEC("iter/bpf_map")
10
int rate_limited_collect_metrics(struct bpf_iter__bpf_map *ctx) {
11
    __u32 key = 0;
12
    __u64 *last_time;
13
    __u64 current_time = bpf_ktime_get_ns();
14
    __u64 collection_interval = 1000000000; // 1 second in nanoseconds
15

16
    last_time = bpf_map_lookup_elem(&last_collection_time, &key);
17
    if (last_time && (current_time - *last_time) < collection_interval) {
18
        return 0; // Skip collection if too soon
19
    }
20

21
    // Update last collection time
22
    bpf_map_update_elem(&last_collection_time, &key, &current_time, BPF_ANY);
23

24
    // Proceed with metrics collection
25
    return collect_map_metrics(ctx);
26
}

Troubleshooting and Debugging#

Common Issues and Solutions#

1. Iterator Not Executing#

1
# Check if iterator is properly attached
2
sudo bpftool prog list | grep iter
3
sudo bpftool link list
4

5
# Verify iterator target exists
6
ls /sys/kernel/debug/tracing/events/bpf/

2. Missing Metrics Data#

1
# Check ring buffer for data
2
sudo bpftool map dump name metrics_buffer
3

4
# Verify program loading
5
sudo dmesg | grep bpf

3. Permission Issues#

1
# Ensure proper capabilities
2
sudo setcap cap_sys_admin,cap_bpf+ep ./ebpf-map-exporter
3

4
# Check BPF filesystem
5
mount | grep bpf

Debug Output Enhancement#

1
// Enhanced debugging macros
2
#define DEBUG_PRINT(fmt, ...)                          \
3
    do {                                               \
4
        char debug_msg[] = fmt;                        \
5
        bpf_trace_printk(debug_msg, sizeof(debug_msg), \
6
                        ##__VA_ARGS__);                \
7
    } while (0)
8

9
SEC("iter/bpf_map")
10
int debug_collect_metrics(struct bpf_iter__bpf_map *ctx) {
11
    struct bpf_map *map = ctx->map;
12

13
    if (!map) {
14
        DEBUG_PRINT("No map found\n");
15
        return 0;
16
    }
17

18
    __u32 map_id = BPF_CORE_READ(map, id);
19
    DEBUG_PRINT("Processing map ID: %u\n", map_id);
20

21
    // Continue with metrics collection...
22
    return collect_map_metrics(ctx);
23
}

Conclusion#

eBPF Iterators represent a powerful advancement in kernel observability, enabling comprehensive monitoring of eBPF programs and system resources without modifying existing applications. This implementation demonstrates:

Key Benefits#

Non-intrusive monitoring: No application code changes required
Comprehensive visibility: Deep insights into eBPF map usage and performance
Prometheus integration: Standard metrics format for existing monitoring infrastructure
Minimal overhead: Efficient kernel-space data collection
Real-time insights: Continuous monitoring capabilities

Production Considerations#

Security: Proper capability management and privilege separation
Performance: Rate limiting and batch processing for high-volume environments
Scalability: Horizontal scaling with multiple exporter instances
Reliability: Error handling and graceful degradation
Maintainability: Modular design and comprehensive documentation

Future Enhancements#

Machine Learning Integration: Anomaly detection and predictive analytics
Advanced Filtering: Selective metrics collection based on criteria
Multi-kernel Support: Cross-platform compatibility and feature detection
Custom Dashboards: Specialized visualization for different use cases

The eBPF Map Metrics Prometheus Exporter showcases the true potential of eBPF Iterators for building sophisticated observability solutions that provide unprecedented visibility into kernel-level operations while maintaining system performance and stability.