Prometheus exporter for custom eBPF metrics.

Motivation of this exporter is to allow you to write eBPF code and export metrics that are not otherwise accessible from the Linux kernel.

eBPF was described by Ingo Molnár as:

One of the more interesting features in this cycle is the ability to attach eBPF programs (user-defined, sandboxed bytecode executed by the kernel) to kprobes. This allows user-defined instrumentation on a live kernel image that can never crash, hang or interfere with the kernel negatively.

An easy way of thinking about this exporter is bcc tools as prometheus metrics:

• https://iovisor.github.io/bcc

We use libbpf rather than legacy bcc driven code, so it's more like libbpf-tools:

• https://github.com/iovisor/bcc/tree/master/libbpf-tools

• https://www.brendangregg.com/ebpf.html
• https://nakryiko.com/posts/bpf-core-reference-guide/
• https://nakryiko.com/posts/bpf-portability-and-co-re/
• https://nakryiko.com/posts/bcc-to-libbpf-howto-guide/
• https://libbpf.readthedocs.io/en/latest/program_types.html

ebpf_exporter depends on libbpf to load eBPF code into the kernel, and you need to have it installed on your system. Alternatively, you can use the bundled Dockerfile to have libbpf compiled in there.

• https://github.com/iovisor/bcc/blob/master/INSTALL.md

Note that there's a dependency between libbpf version you have installed and libbpfgo, which is Go's library to talk to libbpf

Currently we target libbpf v1.2, which has a stable interface.

We compile ebpf_exporter with libbpf statically compiled in, so there's only ever a chance of build time issues, never at run time.

To build a binary, clone the repo and run:

make build

If you're having trouble building on the host, you can try building in Docker:

docker build -t ebpf_exporter .
docker cp $(docker create ebpf_exporter):/ebpf_exporter ./

To build examples (see building examples section):

make -C examples clean build

To run with biolatency config:

sudo ./ebpf_exporter --config.dir examples --config.names biolatency

If you pass --debug, you can see raw maps at /maps endpoint and see debug output from libbpf itself.

A docker image can be built from this repo. It is not yet published.

To build the image, run the following:

docker build --tag ebpf_exporter .

To run it with the examples, you need to build them first (see above). Then you can run by running a privileged container and bind-mounting:

• $(pwd)/examples:/examples:ro to allow access to examples
• /sys/fs/cgroup:/sys/fs/cgroup:ro to allow resolving cgroups

You might have to bind-mount additional directories depending on your needs. You might also not need to bind-mount anything for simple kprobe examples.

The actual command to run the docker container (from the repo directory):

docker run --rm -it --privileged -p 9435:9435 \
  -v $(pwd)/examples:/examples \
  -v /sys/fs/cgroup:/sys/fs/cgroup:ro \
  ebpf_exporter --config.dir examples --config.names timers

For production use you would either bind-mount your own config and compiled bpf programs corresponding to it, or build your own image based on ours with your own config baked in.

See benchmark directory to get an idea of how low ebpf overhead is.

Currently the only supported way of getting data out of the kernel is via maps.

See examples section for real world examples.

If you have examples you want to share, please feel free to open a PR.

Skip to format to see the full specification.

You can find additional examples in examples directory.

Unless otherwise specified, all examples are expected to work on Linux 5.15, which is the latest LTS release at the time of writing. Thanks to CO-RE, examples are also supposed to work on any modern kernel with BTF enabled.

You can find the list of supported distros in libbpf README:

• https://github.com/libbpf/libbpf#bpf-co-re-compile-once--run-everywhere

To build examples, run:

make -C examples clean build

This will use clang to build examples with vmlinux.h we provide in this repo (see include for more on vmlinux.h).

Examples need to be compiled before they can be used.

Note that compiled examples can be used as is on any BTF enabled kernel with no runtime dependencies. Most modern Linux distributions have it enabled.

This config attaches to kernel tracepoints for timers subsystem and counts timers that fire with breakdown by timer name.

Resulting metrics:

# HELP ebpf_exporter_timer_starts_total Timers fired in the kernel
# TYPE ebpf_exporter_timer_starts_total counter
ebpf_exporter_timer_starts_total{function="blk_stat_timer_fn"} 10
ebpf_exporter_timer_starts_total{function="commit_timeout	[jbd2]"} 1
ebpf_exporter_timer_starts_total{function="delayed_work_timer_fn"} 25
ebpf_exporter_timer_starts_total{function="dev_watchdog"} 1
ebpf_exporter_timer_starts_total{function="mix_interrupt_randomness"} 3
ebpf_exporter_timer_starts_total{function="neigh_timer_handler"} 1
ebpf_exporter_timer_starts_total{function="process_timeout"} 49
ebpf_exporter_timer_starts_total{function="reqsk_timer_handler"} 2
ebpf_exporter_timer_starts_total{function="tcp_delack_timer"} 5
ebpf_exporter_timer_starts_total{function="tcp_keepalive_timer"} 6
ebpf_exporter_timer_starts_total{function="tcp_orphan_update"} 16
ebpf_exporter_timer_starts_total{function="tcp_write_timer"} 12
ebpf_exporter_timer_starts_total{function="tw_timer_handler"} 1
ebpf_exporter_timer_starts_total{function="writeout_period"} 5

There's config file for it:

metrics:
  counters:
    - name: timer_starts_total
      help: Timers fired in the kernel
      labels:
        - name: function
          size: 8
          decoders:
            - name: ksym

And corresponding C code that compiles into an ELF file with eBPF bytecode:

#include <vmlinux.h>
#include <bpf/bpf_tracing.h>
#include "maps.bpf.h"

struct {
    __uint(type, BPF_MAP_TYPE_HASH);
    __uint(max_entries, 1024);
    __type(key, u64);
    __type(value, u64);
} timer_starts_total SEC(".maps");

SEC("tp_btf/timer_start")
int BPF_PROG(timer_start, struct timer_list *timer)
{
    u64 function = (u64) timer->function;
    increment_map(&timer_starts_total, &function, 1);
    return 0;
}

char LICENSE[] SEC("license") = "GPL";

This config attaches to block io subsystem and reports disk latency as a prometheus histogram, allowing you to compute percentiles.

The following tools are working with similar concepts:

• https://github.com/iovisor/bcc/blob/master/tools/biosnoop_example.txt
• https://github.com/iovisor/bcc/blob/master/tools/biolatency_example.txt
• https://github.com/iovisor/bcc/blob/master/tools/bitesize_example.txt

This program was the initial reason for the exporter and was heavily influenced by the experimental exporter from Daniel Swarbrick:

• https://github.com/dswarbrick/ebpf_exporter

Resulting metrics:

# HELP ebpf_exporter_bio_latency_seconds Block IO latency histogram
# TYPE ebpf_exporter_bio_latency_seconds histogram
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="1e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="2e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="4e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="8e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="1.6e-05"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="3.2e-05"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="6.4e-05"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.000128"} 22
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.000256"} 36
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.000512"} 40
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.001024"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.002048"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.004096"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.008192"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.016384"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.032768"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.065536"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.131072"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.262144"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="0.524288"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="1.048576"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="2.097152"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="4.194304"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="8.388608"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="16.777216"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="33.554432"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="67.108864"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="134.217728"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme0n1",operation="write",le="+Inf"} 48
ebpf_exporter_bio_latency_seconds_sum{device="nvme0n1",operation="write"} 0.021772
ebpf_exporter_bio_latency_seconds_count{device="nvme0n1",operation="write"} 48
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="1e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="2e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="4e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="8e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="1.6e-05"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="3.2e-05"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="6.4e-05"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.000128"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.000256"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.000512"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.001024"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.002048"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.004096"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.008192"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.016384"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.032768"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.065536"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.131072"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.262144"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="0.524288"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="1.048576"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="2.097152"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="4.194304"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="8.388608"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="16.777216"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="33.554432"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="67.108864"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="134.217728"} 1
ebpf_exporter_bio_latency_seconds_bucket{device="nvme1n1",operation="write",le="+Inf"} 1
ebpf_exporter_bio_latency_seconds_sum{device="nvme1n1",operation="write"} 0.0018239999999999999
ebpf_exporter_bio_latency_seconds_count{device="nvme1n1",operation="write"} 1

You can nicely plot this with Grafana:

The following concepts exists within ebpf_exporter.

Configs describe how to extract metrics from kernel. Each config has a corresponding eBPF code that runs in kernel to produce these metrics.

Multiple configs can be loaded at the same time.

Metrics define what values we get from eBPF program running in the kernel.

Counters from maps are direct transformations: you pull data out of kernel, transform map keys into sets of labels and export them as prometheus counters.

Histograms from maps are a bit more complex than counters. Maps in the kernel cannot be nested, so we need to pack keys in the kernel and unpack in user space.

We get from this:

sda, read, 1ms -> 10 ops
sda, read, 2ms -> 25 ops
sda, read, 4ms -> 51 ops

To this:

sda, read -> [1ms -> 10 ops, 2ms -> 25 ops, 4ms -> 51 ops]

Prometheus histograms expect to have all buckets when we report a metric, but the kernel creates keys as events occur, which means we need to backfill the missing data.

That's why for histogram configuration we have the following keys:

• bucket_type: can be either exp2, linear, or fixed
• bucket_min: minimum bucket key (exp2 and linear only)
• bucket_max: maximum bucket key (exp2 and linear only)
• bucket_keys: maximum bucket key (fixed only)
• bucket_multiplier: multiplier for bucket keys (default is 1)

For exp2 histograms we expect kernel to provide a map with linear keys that are log2 of actual values. We then go from bucket_min to bucket_max in user space and remap keys by exponentiating them:

count = 0
for i = bucket_min; i < bucket_max; i++ {
  count += map.get(i, 0)
  result[exp2(i) * bucket_multiplier] = count
}

Here map is the map from the kernel and result is what goes to prometheus.

We take cumulative count, because this is what prometheus expects.

For linear histograms we expect kernel to provide a map with linear keys that are results of integer division of original value by bucket_multiplier. To reconstruct the histogram in user space we do the following:

count = 0
for i = bucket_min; i < bucket_max; i++ {
  count += map.get(i, 0)
  result[i * bucket_multiplier] = count
}

For fixed histograms we expect kernel to provide a map with fixed keys defined by the user.

count = 0
for i = 0; i < len(bucket_keys); i++ {
  count  += map.get(bucket_keys[i], 0)
  result[bucket_keys[i] * multiplier] = count
}

For exp2 and linear histograms, if bucket_max + 1 contains a non-zero value, it will be used as the sum key in histogram, providing additional information and allowing richer metrics.

For fixed histograms, if buckets_keys[len(bucket_keys) - 1 ] + 1 contains a non-zero value, it will be used as the sum key.

For both exp2 and linear histograms it is important that kernel does not count events into buckets outside of [bucket_min, bucket_max] range. If you encounter a value above your range, truncate it to be in it. You're losing +Inf bucket, but usually it's not that big of a deal.

Each kernel map key must count values under that key's value to match the behavior of prometheus. For example, exp2 histogram key 3 should count values for (exp2(2), exp2(3)] interval: (4, 8]. To put it simply: use log2l or integer division and you'll be good.

Labels transform kernel map keys into prometheus labels.

Maps coming from the kernel are binary encoded. Values are always u64, but keys can be either primitive types like u64 or complex structs.

Each label can be transformed with decoders (see below) according to metric configuration. Generally the number of labels matches the number of elements in the kernel map key.

For map keys that are represented as structs alignment rules apply:

• u64 must be aligned at 8 byte boundary
• u32 must be aligned at 4 byte boundary
• u16 must be aligned at 2 byte boundary

This means that the following struct:

struct disk_latency_key_t {
    u32 dev;
    u8 op;
    u64 slot;
};

Is represented as:

• 4 byte dev integer
• 1 byte op integer
• 3 byte padding to align slot
• 8 byte slot integer

When decoding, label sizes should be supplied with padding included:

• 4 for dev
• 4 for op (1 byte value + 3 byte padding)
• 8 byte slot

Decoders take a byte slice input of requested length and transform it into a byte slice representing a string. That byte slice can either be consumed by another decoder (for example string -> regexp) or or used as the final label value exporter to Prometheus.

Below are decoders we have built in.

With cgroup decoder you can turn the u64 from bpf_get_current_cgroup_id into a human readable string representing cgroup path, like:

• /sys/fs/cgroup/system.slice/ssh.service

Dname decoder read DNS qname from string in wire format, then decode it into '.' notation format. Could be used after string decoder. E.g.: \x07example\03com\x00 will become example.com. This decoder could be used after string decode, like the following example:

- name: qname
  decoders:
    - name: string
    - name: dname

Network IP decoded can turn byte encoded IPv4 and IPv6 addresses that kernel operates on into human readable form like 1.1.1.1.

KSym decoder takes kernel address and converts that to the function name.

In your eBPF program you can use PT_REGS_IP_CORE(ctx) to get the address of the function you attached to as a u64 variable. Note that for kprobes you need to wrap it with KPROBE_REGS_IP_FIX() from regs-ip.bpf.h.

With major-minor decoder you can turn kernel's combined u32 view of major and minor device numbers into a device name in /dev.

Regexp decoder takes list of strings from regexp configuration key of the decoder and ties to use each as a pattern in golang.org/pkg/regexp:

• https://golang.org/pkg/regexp

If decoder input matches any of the patterns, it is permitted. Otherwise, the whole metric label set is dropped.

An example to report metrics only for systemd-journal and syslog-ng:

- name: command
  decoders:
    - name: string
    - name: regexp
      regexps:
        - ^systemd-journal$
        - ^syslog-ng$

Static map decoder takes input and maps it to another value via static_map configuration key of the decoder. Values are expected as strings.

An example to match 1 to read and 2 to write:

- name: operation
  decoders:
    - name:static_map
      static_map:
        1: read
        2: write

Unknown keys will be replaced by "unknown:key_name" unless allow_unknown: true is specified in the decoder. For example, the above will decode 3 to unknown:3 and the below example will decode 3 to 3:

- name: operation
  decoders:
    - name:static_map
      allow_unknown: true
      static_map:
        1: read
        2: write

String decoder transforms possibly null terminated strings coming from the kernel into string usable for prometheus metrics.

Syscall decoder transforms syscall numbers into syscall names.

The tables can be regenerated by make syscalls. See scripts/mksyscalls.

UInt decoder transforms hex encoded uint values from the kernel into regular base10 numbers. For example: 0xe -> 14.

Per CPU map reading is fully supported. If the last decoder for a percpu map is called cpu (use 2 byte uint decoder), then cpu label is added automatically. If it's not present, then the percpu counters are aggregated into one global counter.

There is percpu-softirq in examples. See #226 for examples of different modes of operation for it.

Configuration file is defined like this:

# Metrics attached to the program
[ metrics: metrics ]
# Kernel symbol addresses to define as kaddr_{symbol} from /proc/kallsyms (consider CONFIG_KALLSYMS_ALL)
kaddrs:
  [ - symbol_to_resolve ]

See Metrics section for more details.

counters:
  [ - counter ]
histograms:
  [ - histogram ]

See Counters section for more details.

name: <prometheus counter name>
help: <prometheus metric help>
perf_event_array: <whether map is a BPF_MAP_TYPE_PERF_EVENT_ARRAY map: bool>
flush_interval: <how often should we flush metrics from the perf_event_array: time.Duration>
labels:
  [ - label ]

An example of perf_map can be found here.

See Histograms section for more details.

name: <prometheus histogram name>
help: <prometheus metric help>
bucket_type: <map bucket type: exp2 or linear>
bucket_multiplier: <map bucket multiplier: float64>
bucket_min: <min bucket value: int>
bucket_max: <max bucket value: int>
labels:
  [ - label ]

See Labels section for more details.

name: <prometheus label name>
size: <field size with padding>
decoders:
  [ - decoder ]

See Decoders section for more details.

name: <decoder name>
# ... decoder specific configuration

This gauge reports a timeseries for every loaded config:

# HELP ebpf_exporter_enabled_configs The set of enabled configs
# TYPE ebpf_exporter_enabled_configs gauge
ebpf_exporter_enabled_configs{name="cachestat"} 1

This gauge reports information available for every ebpf program:

# HELP ebpf_exporter_ebpf_programs Info about ebpf programs
# TYPE ebpf_exporter_ebpf_programs gauge
ebpf_exporter_ebpf_program_info{config="cachestat",id="545",program="add_to_page_cache_lru",tag="6c007da3187b5b32"} 1
ebpf_exporter_ebpf_program_info{config="cachestat",id="546",program="mark_page_accessed",tag="6c007da3187b5b32"} 1
ebpf_exporter_ebpf_program_info{config="cachestat",id="547",program="folio_account_dirtied",tag="6c007da3187b5b32"} 1
ebpf_exporter_ebpf_program_info{config="cachestat",id="548",program="mark_buffer_dirty",tag="6c007da3187b5b32"} 1

Here tag can be used for tracing and performance analysis with two conditions:

• net.core.bpf_jit_kallsyms=1 sysctl is set
• --kallsyms=/proc/kallsyms is passed to perf record

Newer kernels allow --kallsyms to perf top as well, in the future it may not be required at all:

• https://www.spinics.net/lists/linux-perf-users/msg07216.html

This gauge reports whether individual programs were successfully attached.

# HELP ebpf_exporter_ebpf_program_attached Whether a program is attached
# TYPE ebpf_exporter_ebpf_program_attached gauge
ebpf_exporter_ebpf_program_attached{id="247"} 1
ebpf_exporter_ebpf_program_attached{id="248"} 1
ebpf_exporter_ebpf_program_attached{id="249"} 0
ebpf_exporter_ebpf_program_attached{id="250"} 1

It needs to be joined by id label with ebpf_exporter_ebpf_program_info to get more information about the program.

This counter reports how much time individual programs spent running.

# HELP ebpf_exporter_ebpf_program_run_time_seconds How long has the program been executing
# TYPE ebpf_exporter_ebpf_program_run_time_seconds counter
ebpf_exporter_ebpf_program_run_time_seconds{id="247"} 0
ebpf_exporter_ebpf_program_run_time_seconds{id="248"} 0.001252621
ebpf_exporter_ebpf_program_run_time_seconds{id="249"} 0
ebpf_exporter_ebpf_program_run_time_seconds{id="250"} 3.6668e-05

It requires kernel.bpf_stats_enabled sysctl to be enabled.

It needs to be joined by id label with ebpf_exporter_ebpf_program_info to get more information about the program.

This counter reports how many times individual programs ran.

# HELP ebpf_exporter_ebpf_program_run_count_total How many times has the program been executed
# TYPE ebpf_exporter_ebpf_program_run_count_total counter
ebpf_exporter_ebpf_program_run_count_total{id="247"} 0
ebpf_exporter_ebpf_program_run_count_total{id="248"} 11336
ebpf_exporter_ebpf_program_run_count_total{id="249"} 0
ebpf_exporter_ebpf_program_run_count_total{id="250"} 69

It requires kernel.bpf_stats_enabled sysctl to be enabled.

It needs to be joined by id label with ebpf_exporter_ebpf_program_info to get more information about the program.

MIT