Ebpf_exporter: Prometheus exporter for custom eBPF metrics

栏目: IT技术 · 发布时间: 4年前

内容简介：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

ebpf_exporter

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

Reading material

Building and running

To build, you need to have libbcc installed:

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

You can use pre-compiled binary from Releases:

https://github.com/cloudflare/ebpf_exporter/releases

That still requires you to have libbcc . To build release binaries yourself:

$ make release-binaries

To build a package from latest sources:

$ go get -u -v github.com/cloudflare/ebpf_exporter/...

To run with bio config (you need root privileges):

$ ~/go/bin/ebpf_exporter --config.file=src/github.com/cloudflare/ebpf_exporter/examples/bio.yaml

If you pass --debug , you can see raw tables at /tables endpoint.

Benchmarking overhead

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

Supported scenarios

Currently the only supported way of getting data out of the kernel is via maps (we call them tables in configuration). See:

https://github.com/iovisor/bcc/blob/master/docs/reference_guide.md#maps

Seesection for real world examples.

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

Configuration

Skip toto see the full specification.

Examples

You can find additional examples in examples directory.

Unless otherwise specified, all examples are expected to work on Linux 4.14, which is the latest LTS release at the time of writing.

In general, exported to work from Linux 4.1. See BCC docs for more details:

https://github.com/iovisor/bcc/blob/master/INSTALL.md#kernel-configuration

Page cache operations for `syslog-ng` and `systemd-journald` (counters)

This program attaches to kernel functions responsible for managing page cache and counts pages going through them.

This is an adapted version of cachestat from bcc tools:

https://github.com/iovisor/bcc/blob/master/tools/cachestat_example.txt

Resulting metrics:

# HELP ebpf_exporter_page_cache_ops_total Page cache operation counters by type
# TYPE ebpf_exporter_page_cache_ops_total counter
ebpf_exporter_page_cache_ops_total{command="syslog-ng",op="account_page_dirtied"} 1531
ebpf_exporter_page_cache_ops_total{command="syslog-ng",op="add_to_page_cache_lru"} 1092
ebpf_exporter_page_cache_ops_total{command="syslog-ng",op="mark_buffer_dirty"} 31205
ebpf_exporter_page_cache_ops_total{command="syslog-ng",op="mark_page_accessed"} 54846
ebpf_exporter_page_cache_ops_total{command="systemd-journal",op="account_page_dirtied"} 104681
ebpf_exporter_page_cache_ops_total{command="systemd-journal",op="add_to_page_cache_lru"} 7330
ebpf_exporter_page_cache_ops_total{command="systemd-journal",op="mark_buffer_dirty"} 125486
ebpf_exporter_page_cache_ops_total{command="systemd-journal",op="mark_page_accessed"} 898214

You can check out cachestat source code to see how these translate:

https://github.com/iovisor/bcc/blob/master/tools/cachestat.py

programs:
  - name: cachestat
    metrics:
      counters:
        - name: page_cache_ops_total
          help: Page cache operation counters by type
          table: counts
          labels:
            - name: op
              size: 8
              decoders:
                - name: ksym
            - name: command
              size: 128
              decoders:
                - name: string
                - name: regexp
                  regexps:
                    - ^systemd-journal$
                    - ^syslog-ng$
    kprobes:
      add_to_page_cache_lru: do_count
      mark_page_accessed: do_count
      account_page_dirtied: do_count
      mark_buffer_dirty: do_count
    code: |
      #include <uapi/linux/ptrace.h>

      struct key_t {
          u64 ip;
          char command[128];
      };

      BPF_HASH(counts, struct key_t);

      int do_count(struct pt_regs *ctx) {
          struct key_t key = { .ip = PT_REGS_IP(ctx) - 1 };
          bpf_get_current_comm(&key.command, sizeof(key.command));

          counts.increment(key);

          return 0;
      }

Block IO histograms (histograms)

This program attaches to block io subsystem and reports metrics on disk latency and request sizes for separate disks.

The following tools are working with similar concepts:

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="sda",operation="read",le="1e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="2e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="4e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="8e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="1.6e-05"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="3.2e-05"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="6.4e-05"} 2
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.000128"} 388
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.000256"} 20086
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.000512"} 21601
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.001024"} 22487
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.002048"} 25592
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.004096"} 26891
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.008192"} 27835
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.016384"} 28540
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.032768"} 28725
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.065536"} 28776
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.131072"} 28786
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.262144"} 28790
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="0.524288"} 28792
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="1.048576"} 28792
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="2.097152"} 28792
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="4.194304"} 28792
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="8.388608"} 28792
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="16.777216"} 28792
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="33.554432"} 28792
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="67.108864"} 28792
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="read",le="+Inf"} 28792
ebpf_exporter_bio_latency_seconds_sum{device="sda",operation="read"} 0
ebpf_exporter_bio_latency_seconds_count{device="sda",operation="read"} 28792
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="1e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="2e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="4e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="8e-06"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="1.6e-05"} 0
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="3.2e-05"} 508
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="6.4e-05"} 2828
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.000128"} 5701
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.000256"} 8520
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.000512"} 11975
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.001024"} 12448
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.002048"} 16798
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.004096"} 26909
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.008192"} 41248
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.016384"} 59030
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.032768"} 86501
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.065536"} 118934
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.131072"} 122148
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.262144"} 122373
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="0.524288"} 122462
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="1.048576"} 122470
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="2.097152"} 122470
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="4.194304"} 122470
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="8.388608"} 122470
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="16.777216"} 122470
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="33.554432"} 122470
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="67.108864"} 122470
ebpf_exporter_bio_latency_seconds_bucket{device="sda",operation="write",le="+Inf"} 122470
ebpf_exporter_bio_latency_seconds_sum{device="sda",operation="write"} 0
ebpf_exporter_bio_latency_seconds_count{device="sda",operation="write"} 122470
...

# HELP ebpf_exporter_bio_size_bytes Block IO size histogram with kibibyte buckets
# TYPE ebpf_exporter_bio_size_bytes histogram
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="1024"} 14
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="2048"} 14
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="4096"} 28778
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="8192"} 28778
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="16384"} 28778
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="32768"} 28778
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="65536"} 28779
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="131072"} 28781
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="262144"} 28785
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="524288"} 28792
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="1.048576e+06"} 28792
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="2.097152e+06"} 28792
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="4.194304e+06"} 28792
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="8.388608e+06"} 28792
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="1.6777216e+07"} 28792
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="3.3554432e+07"} 28792
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="read",le="+Inf"} 28792
ebpf_exporter_bio_size_bytes_sum{device="sda",operation="read"} 0
ebpf_exporter_bio_size_bytes_count{device="sda",operation="read"} 28792
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="1024"} 1507
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="2048"} 4007
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="4096"} 15902
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="8192"} 17726
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="16384"} 18429
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="32768"} 19639
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="65536"} 19676
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="131072"} 20367
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="262144"} 21952
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="524288"} 49636
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="1.048576e+06"} 122470
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="2.097152e+06"} 122470
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="4.194304e+06"} 122470
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="8.388608e+06"} 122470
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="1.6777216e+07"} 122470
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="3.3554432e+07"} 122470
ebpf_exporter_bio_size_bytes_bucket{device="sda",operation="write",le="+Inf"} 122470
ebpf_exporter_bio_size_bytes_sum{device="sda",operation="write"} 0
ebpf_exporter_bio_size_bytes_count{device="sda",operation="write"} 122470
...

To nicely plot these in Grafana, you'll need v5.1:

https://github.com/grafana/grafana/pull/11087

Ebpf_exporter: Prometheus exporter for custom eBPF metrics

programs:
  # See:
  # * https://github.com/iovisor/bcc/blob/master/tools/biolatency.py
  # * https://github.com/iovisor/bcc/blob/master/tools/biolatency_example.txt
  #
  # See also: bio-tracepoints.yaml
  - name: bio
    metrics:
      histograms:
        - name: bio_latency_seconds
          help: Block IO latency histogram
          table: io_latency
          bucket_type: exp2
          bucket_min: 0
          bucket_max: 26
          bucket_multiplier: 0.000001 # microseconds to seconds
          labels:
            - name: device
              size: 32
              decoders:
                - name: string
            - name: operation
              size: 8
              decoders:
                - name: uint
                - name: static_map
                  static_map:
                    1: read
                    2: write
            - name: bucket
              size: 8
              decoders:
                - name: uint
        - name: bio_size_bytes
          help: Block IO size histogram with kibibyte buckets
          table: io_size
          bucket_type: exp2
          bucket_min: 0
          bucket_max: 15
          bucket_multiplier: 1024 # kibibytes to bytes
          labels:
            - name: device
              size: 32
              decoders:
                - name: string
            - name: operation
              size: 8
              decoders:
                - name: uint
                - name: static_map
                  static_map:
                    1: read
                    2: write
            - name: bucket
              size: 8
              decoders:
                - name: uint
    kprobes:
      blk_start_request: trace_req_start
      blk_mq_start_request: trace_req_start
      blk_account_io_completion: trace_req_completion
    code: |
      #include <linux/blkdev.h>
      #include <linux/blk_types.h>

      typedef struct disk_key {
          char disk[32];
          u8 op;
          u64 slot;
      } disk_key_t;

      // Max number of disks we expect to see on the host
      const u8 max_disks = 255;

      // 27 buckets for latency, max range is 33.6s .. 67.1s
      const u8 max_latency_slot = 26;

      // 16 buckets per disk in kib, max range is 16mib .. 32mib
      const u8 max_size_slot = 15;

      // Hash to temporily hold the start time of each bio request, max 10k in-flight by default
      BPF_HASH(start, struct request *);

      // Histograms to record latencies
      BPF_HISTOGRAM(io_latency, disk_key_t, (max_latency_slot + 2) * max_disks);

      // Histograms to record sizes
      BPF_HISTOGRAM(io_size, disk_key_t, (max_size_slot + 2) * max_disks);

      // Record start time of a request
      int trace_req_start(struct pt_regs *ctx, struct request *req) {
          u64 ts = bpf_ktime_get_ns();
          start.update(&req, &ts);

          return 0;
      }

      // Calculate request duration and store in appropriate histogram bucket
      int trace_req_completion(struct pt_regs *ctx, struct request *req, unsigned int bytes) {
          u64 *tsp, delta;

          // Fetch timestamp and calculate delta
          tsp = start.lookup(&req);
          if (tsp == 0) {
              return 0; // missed issue
          }

          // There are write request with zero length on sector zero,
          // which do not seem to be real writes to device.
          if (req->__sector == 0 && req->__data_len == 0) {
            return 0;
          }

          // Disk that received the request
          struct gendisk *disk = req->rq_disk;

          // Delta in nanoseconds
          delta = bpf_ktime_get_ns() - *tsp;

          // Convert to microseconds
          delta /= 1000;

          // Latency histogram key
          u64 latency_slot = bpf_log2l(delta);

          // Cap latency bucket at max value
          if (latency_slot > max_latency_slot) {
              latency_slot = max_latency_slot;
          }

          disk_key_t latency_key = { .slot = latency_slot };
          bpf_probe_read(&latency_key.disk, sizeof(latency_key.disk), &disk->disk_name);

          // Size in kibibytes
          u64 size_kib = bytes / 1024;

          // Request size histogram key
          u64 size_slot = bpf_log2(size_kib);

          // Cap latency bucket at max value
          if (size_slot > max_size_slot) {
              size_slot = max_size_slot;
          }

          disk_key_t size_key = { .slot = size_slot };
          bpf_probe_read(&size_key.disk, sizeof(size_key.disk), &disk->disk_name);

          if ((req->cmd_flags & REQ_OP_MASK) == REQ_OP_WRITE) {
              latency_key.op = 2;
              size_key.op    = 2;
          } else {
              latency_key.op = 1;
              size_key.op    = 1;
          }

          io_latency.increment(latency_key);
          io_size.increment(size_key);

          // Increment sum keys
          latency_key.slot = max_latency_slot + 1;
          io_latency.increment(latency_key, delta);
          size_key.slot = max_size_slot + 1;
          io_size.increment(size_key, size_kib);

          start.delete(&req);

          return 0;
      }

There is also a tracepoint based equivalent of this example in examples .

Programs

Programs combine a piece of eBPF code running in the kernel with configuration describing how to export collected data as prometheus metrics. There may be multiple programs running from one exporter instance.

Metrics

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

Counters

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

Histograms

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 or linear
bucket_min : minimum bucket key
bucket_max : maximum bucket key
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.

If bucket_max + 1 contains a non-zero value, it will be used as a sum key in histogram, providing additional information.

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 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 bpf_log2l or integer division and you'll be good.

The side effect of implementing histograms this way is that some granularity is lost due to either taking log2 or division. We explicitly set _sum key of prometheus histogram to zero to avoid confusion around this.

Labels

Labels transform kernel map keys into prometheus labels.

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

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

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

u64
u32
u16

This means that the following struct:

typedef struct disk_key {
    char disk[32];
    u8 op;
    u64 slot;
} disk_key_t;

Is represented as:

disk
op
slot
slot

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

disk
op
slot

Decoders

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.

`ksym`

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

In your eBPF program you can use PT_REGS_IP(ctx) to get the address of the kprobe you attached to as a u64 variable. Note that sometimes you can observe PT_REGS_IP being off by one. You can subtract 1 in your code to make it point to the right instruction that can be found /proc/kallsyms .

`regexp`

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`

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_decoder_map:
        1: read
        2: write

`string`

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

`dname`

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

`uint`

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

Configuration file format

Configuration file is defined like this:

# List of eBPF programs to run
- programs:
  [ - <program> ]

`program`

Seesection for more details.

# Program name
name: <program name>
# Metrics attached to the program
[ metrics: metrics ]
# Kprobes (kernel functions) and their targets (eBPF functions)
kprobes:
  [ kprobename: target ... ]
# Kretprobes (kernel functions) and their targets (eBPF functions)
kretprobes:
  [ kprobename: target ... ]
# Tracepoints (category:name, i.e. timer:timer_start) and their targets (eBPF functions)
tracepoints:
  [ tracepoint: target ... ]
# Raw tracepoints (name, i.e. timer_start) and their targets (eBPF functions)
raw_tracepoints:
  [ tracepoint: target ... ]
# Perf events configuration
perf_events:
  [ - perf_event ]
# Cflags are passed to the bcc compiler, useful for preprocessing
cflags:
  [ - -I/include/path
    - -DMACRO_NAME=value ]
# Actual eBPF program code to inject in the kernel
code: [ code ]

`perf_event`

See llcstat as an example.

- type: [ perf event type code ]
  name: [ perf event name code ]
  target: [ target eBPF function ]
  sample_period: [ sample period ]
  sample_frequency: [ sample frequency ]

It's preferred to use sample_frequency to let kernel pick the sample period automatically, otherwise you may end up with invalid metrics on overflow.

`metrics`

Seesection for more details.

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

`counter`

Seesection for more details.

name: <prometheus counter name>
help: <prometheus metric help>
table: <eBPF table name to track>
labels:
  [ - label ]

`histogram`

Seesection for more details.

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

`label`

Seesection for more details.

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

`decoder`

Seesection for more details.

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

Built-in metrics

`ebpf_exporter_enabled_programs`

This gauge reports a timeseries for every loaded logical program:

# HELP ebpf_exporter_enabled_programs The set of enabled programs
# TYPE ebpf_exporter_enabled_programs gauge
ebpf_exporter_enabled_programs{name="xfs_reclaim"} 1

`ebpf_exporter_ebpf_programs`

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_programs{function="xfs_fs_free_cached_objects_end",program="xfs_reclaim",tag="d5e845dc27b372e4"} 1
ebpf_exporter_ebpf_programs{function="xfs_fs_free_cached_objects_start",program="xfs_reclaim",tag="c2439d02dd0ba000"} 1
ebpf_exporter_ebpf_programs{function="xfs_fs_nr_cached_objects_end",program="xfs_reclaim",tag="598375893f34ef39"} 1
ebpf_exporter_ebpf_programs{function="xfs_fs_nr_cached_objects_start",program="xfs_reclaim",tag="cf30348184f983dd"} 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

License

MIT

以上就是本文的全部内容，希望本文的内容对大家的学习或者工作能带来一定的帮助，也希望大家多多支持码农网

查看所有标签

猜你喜欢:

Ebpf_exporter: Prometheus exporter for custom eBPF metrics

本站部分资源来源于网络，本站转载出于传递更多信息之目的，版权归原作者或者来源机构所有，如转载稿涉及版权问题，请联系我们。

码农书籍

自品牌

[美] 丹·斯柯伯尔（Dan Schawbel） / 佘卓桓 / 湖南文艺出版社 / 2016-1-1 / 39.80元

什么是自品牌？如何利用新媒体推广自己？如何放大自己的职业优势？细化到如何巩固“弱联系”人脉？如何在团队里合作与生存？如何开创自己的事业？这些都是职场人不得不面临的问题，但少有人告诉你答案，你需要利用书里分享的高效方法独辟蹊径，把自己变成职场里高性价比的人才。这是一本教你利用新型社交媒体开发职业潜能的自我管理读本，不管你是新人还是老鸟，都可以通过打造自品牌在职场中脱颖而出。如果不甘平庸，就亮......一起来看看《自品牌》这本书的介绍吧!

码农工具

Ebpf_exporter: Prometheus exporter for custom eBPF metrics

ebpf_exporter

Reading material

Building and running

Benchmarking overhead

Supported scenarios

Configuration

Examples

Page cache operations for `syslog-ng` and `systemd-journald` (counters)

Block IO histograms (histograms)

Programs

Metrics

Counters

Histograms

Labels

Decoders

`ksym`

`regexp`

`static_map`

`string`

`dname`

`uint`

Configuration file format

`program`

`perf_event`

`metrics`

`counter`

`histogram`

`label`

`decoder`

Built-in metrics

`ebpf_exporter_enabled_programs`

`ebpf_exporter_ebpf_programs`

License

自品牌

JS 压缩/解压工具

JSON 在线解析

RGB CMYK 转换工具

Ebpf_exporter: Prometheus exporter for custom eBPF metrics

ebpf_exporter

Reading material

Building and running

Benchmarking overhead

Supported scenarios

Configuration

Examples

Page cache operations for syslog-ng and systemd-journald (counters)

Block IO histograms (histograms)

Programs

Metrics

Counters

Histograms

Labels

Decoders

ksym

regexp

static_map

string

dname

uint

Configuration file format

program

perf_event

metrics

counter

histogram

label

decoder

Built-in metrics

ebpf_exporter_enabled_programs

ebpf_exporter_ebpf_programs

License

自品牌

JS 压缩/解压工具

JSON 在线解析

RGB CMYK 转换工具

Page cache operations for `syslog-ng` and `systemd-journald` (counters)

`ksym`

`regexp`

`static_map`

`string`

`dname`

`uint`

`program`

`perf_event`

`metrics`

`counter`

`histogram`

`label`

`decoder`

`ebpf_exporter_enabled_programs`

`ebpf_exporter_ebpf_programs`