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<ol class="chapter"><li class="chapter-item expanded affix "><li class="part-title">eBPF 实践教程：基于 libbpf 和 CO-RE</li><li class="chapter-item expanded "><a href="../0-introduce/index.html"><strong aria-hidden="true">1.</strong> eBPF 入门开发实践教程一：介绍 eBPF 的基本概念、常见的开发工具</a></li><li class="chapter-item expanded "><a href="../1-helloworld/index.html"><strong aria-hidden="true">2.</strong> eBPF 入门开发实践教程二：Hello World，基本框架和开发流程</a></li><li class="chapter-item expanded "><a href="../2-kprobe-unlink/index.html"><strong aria-hidden="true">3.</strong> eBPF 入门开发实践教程二：在 eBPF 中使用 kprobe 监测捕获 unlink 系统调用</a></li><li class="chapter-item expanded "><a href="../3-fentry-unlink/index.html"><strong aria-hidden="true">4.</strong> eBPF 入门开发实践教程三：在 eBPF 中使用 fentry 监测捕获 unlink 系统调用</a></li><li class="chapter-item expanded "><a href="../4-opensnoop/index.html"><strong aria-hidden="true">5.</strong> eBPF 入门开发实践教程四：在 eBPF 中捕获进程打开文件的系统调用集合，使用全局变量过滤进程 pid</a></li><li class="chapter-item expanded "><a href="../5-uprobe-bashreadline/index.html"><strong aria-hidden="true">6.</strong> eBPF 入门开发实践教程五：在 eBPF 中使用 uprobe 捕获 bash 的 readline 函数调用</a></li><li class="chapter-item expanded "><a href="../6-sigsnoop/index.html"><strong aria-hidden="true">7.</strong> eBPF 入门开发实践教程六：捕获进程发送信号的系统调用集合，使用 hash map 保存状态</a></li><li class="chapter-item expanded "><a href="../7-execsnoop/index.html"><strong aria-hidden="true">8.</strong> eBPF 入门实践教程七：捕获进程执行/退出时间，通过 perf event array 向用户态打印输出</a></li><li class="chapter-item expanded "><a href="../8-exitsnoop/index.html"><strong aria-hidden="true">9.</strong> eBPF 入门开发实践教程八：在 eBPF 中使用 exitsnoop 监控进程退出事件，使用 ring buffer 向用户态打印输出</a></li><li class="chapter-item expanded "><a href="../9-runqlat/index.html"><strong aria-hidden="true">10.</strong> eBPF 入门开发实践教程九：一个 Linux 内核 BPF 程序，通过柱状图来总结调度程序运行队列延迟，显示任务等待运行在 CPU 上的时间长度</a></li><li class="chapter-item expanded "><a href="../10-hardirqs/index.html"><strong aria-hidden="true">11.</strong> eBPF 入门开发实践教程十：在 eBPF 中使用 hardirqs 或 softirqs 捕获中断事件</a></li><li class="chapter-item expanded "><a href="../11-bootstrap/index.html"><strong aria-hidden="true">12.</strong> eBPF 入门开发实践教程十一：在 eBPF 中使用 bootstrap 开发用户态程序并跟踪 exec() 和 exit() 系统调用</a></li><li class="chapter-item expanded "><a href="../13-tcpconnlat/index.html" class="active"><strong aria-hidden="true">13.</strong> eBPF入门实践教程：使用 libbpf-bootstrap 开发程序统计 TCP 连接延时</a></li><li class="chapter-item expanded "><a href="../13-tcpconnlat/tcpconnlat.html"><strong aria-hidden="true">14.</strong> eBPF 入门实践教程：编写 eBPF 程序 tcpconnlat 测量 tcp 连接延时</a></li><li class="chapter-item expanded "><a href="../14-tcpstates/index.html"><strong aria-hidden="true">15.</strong> eBPF入门实践教程：使用 libbpf-bootstrap 开发程序统计 TCP 连接延时</a></li><li class="chapter-item expanded "><a href="../15-tcprtt/index.html"><strong aria-hidden="true">16.</strong> eBPF 入门实践教程：编写 eBPF 程序 Tcprtt 测量 TCP 连接的往返时间</a></li><li class="chapter-item expanded "><a href="../16-memleak/index.html"><strong aria-hidden="true">17.</strong> eBPF 入门实践教程：编写 eBPF 程序 Memleak 监控内存泄漏</a></li><li class="chapter-item expanded "><a href="../17-biopattern/index.html"><strong aria-hidden="true">18.</strong> eBPF 入门实践教程：编写 eBPF 程序 Biopattern: 统计随机/顺序磁盘 I/O</a></li><li class="chapter-item expanded "><a href="../18-further-reading/index.html"><strong aria-hidden="true">19.</strong> 更多的参考资料</a></li><li class="chapter-item expanded "><a href="../19-lsm-connect/index.html"><strong aria-hidden="true">20.</strong> eBPF 入门实践教程：使用 LSM 进行安全检测防御</a></li><li class="chapter-item expanded "><a href="../20-tc/index.html"><strong aria-hidden="true">21.</strong> eBPF 入门实践教程：使用 eBPF 进行 tc 流量控制</a></li><li class="chapter-item expanded affix "><li class="part-title">bcc 开发者教程</li><li class="chapter-item expanded "><a href="../bcc-documents/kernel-versions.html"><strong aria-hidden="true">22.</strong> BPF Features by Linux Kernel Version</a></li><li class="chapter-item expanded "><a href="../bcc-documents/kernel_config.html"><strong aria-hidden="true">23.</strong> Kernel Configuration for BPF Features</a></li><li class="chapter-item expanded "><a href="../bcc-documents/reference_guide.html"><strong aria-hidden="true">24.</strong> bcc Reference Guide</a></li><li class="chapter-item expanded "><a href="../bcc-documents/special_filtering.html"><strong aria-hidden="true">25.</strong> Special Filtering</a></li><li class="chapter-item expanded "><a href="../bcc-documents/tutorial.html"><strong aria-hidden="true">26.</strong> bcc Tutorial</a></li><li class="chapter-item expanded "><a href="../bcc-documents/tutorial_bcc_python_developer.html"><strong aria-hidden="true">27.</strong> bcc Python Developer Tutorial</a></li></ol>
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<h1 id="ebpf入门实践教程使用-libbpf-bootstrap-开发程序统计-tcp-连接延时"><a class="header" href="#ebpf入门实践教程使用-libbpf-bootstrap-开发程序统计-tcp-连接延时">eBPF入门实践教程：使用 libbpf-bootstrap 开发程序统计 TCP 连接延时</a></h1>
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<h2 id="背景"><a class="header" href="#背景">背景</a></h2>
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<p>在互联网后端日常开发接口的时候中，不管你使用的是C、Java、PHP还是Golang，都避免不了需要调用mysql、redis等组件来获取数据，可能还需要执行一些rpc远程调用，或者再调用一些其它restful api。 在这些调用的底层，基本都是在使用TCP协议进行传输。这是因为在传输层协议中，TCP协议具备可靠的连接，错误重传，拥塞控制等优点，所以目前应用比UDP更广泛一些。但相对而言，tcp 连接也有一些缺点，例如建立连接的延时较长等。因此也会出现像 QUIC ，即 快速UDP网络连接 ( Quick UDP Internet Connections )这样的替代方案。</p>
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<p>tcp 连接延时分析对于网络性能分析优化或者故障排查都能起到不少作用。</p>
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<h2 id="tcpconnlat-的实现原理"><a class="header" href="#tcpconnlat-的实现原理">tcpconnlat 的实现原理</a></h2>
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<p>tcpconnlat 这个工具跟踪执行活动TCP连接的内核函数（例如，通过connect()系统调用），并显示本地测量的连接的延迟（时间），即从发送 SYN 到响应包的时间。</p>
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<h3 id="tcp-连接原理"><a class="header" href="#tcp-连接原理">tcp 连接原理</a></h3>
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<p>tcp 连接的整个过程如图所示：</p>
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<p><img src="tcpconnlat1.png" alt="tcpconnlate" /></p>
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<p>在这个连接过程中，我们来简单分析一下每一步的耗时：</p>
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<ol>
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<li>客户端发出SYNC包：客户端一般是通过connect系统调用来发出 SYN 的，这里牵涉到本机的系统调用和软中断的 CPU 耗时开销</li>
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<li>SYN传到服务器：SYN从客户端网卡被发出，这是一次长途远距离的网络传输</li>
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<li>服务器处理SYN包：内核通过软中断来收包，然后放到半连接队列中，然后再发出SYN/ACK响应。主要是 CPU 耗时开销</li>
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<li>SYC/ACK传到客户端：长途网络跋涉</li>
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<li>客户端处理 SYN/ACK：客户端内核收包并处理SYN后，经过几us的CPU处理，接着发出 ACK。同样是软中断处理开销</li>
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<li>ACK传到服务器：长途网络跋涉</li>
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<li>服务端收到ACK：服务器端内核收到并处理ACK，然后把对应的连接从半连接队列中取出来，然后放到全连接队列中。一次软中断CPU开销</li>
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<li>服务器端用户进程唤醒：正在被accpet系统调用阻塞的用户进程被唤醒，然后从全连接队列中取出来已经建立好的连接。一次上下文切换的CPU开销</li>
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</ol>
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<p>在客户端视角，在正常情况下一次TCP连接总的耗时也就就大约是一次网络RTT的耗时。但在某些情况下，可能会导致连接时的网络传输耗时上涨、CPU处理开销增加、甚至是连接失败。这种时候在发现延时过长之后，就可以结合其他信息进行分析。</p>
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<h3 id="ebpf-实现原理"><a class="header" href="#ebpf-实现原理">ebpf 实现原理</a></h3>
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<p>在 TCP 三次握手的时候，Linux 内核会维护两个队列，分别是：</p>
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<ul>
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<li>半连接队列，也称 SYN 队列；</li>
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<li>全连接队列，也称 accepet 队列；</li>
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</ul>
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<p>服务端收到客户端发起的 SYN 请求后，内核会把该连接存储到半连接队列，并向客户端响应 SYN+ACK，接着客户端会返回 ACK，服务端收到第三次握手的 ACK 后，内核会把连接从半连接队列移除，然后创建新的完全的连接，并将其添加到 accept 队列，等待进程调用 accept 函数时把连接取出来。</p>
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<p>我们的 ebpf 代码实现在 <a href="https://github.com/yunwei37/Eunomia/blob/master/bpftools/tcpconnlat/tcpconnlat.bpf.c">https://github.com/yunwei37/Eunomia/blob/master/bpftools/tcpconnlat/tcpconnlat.bpf.c</a> 中：</p>
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<p>它主要使用了 trace_tcp_rcv_state_process 和 kprobe/tcp_v4_connect 这样的跟踪点：</p>
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<pre><code class="language-c">
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SEC("kprobe/tcp_v4_connect")
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int BPF_KPROBE(tcp_v4_connect, struct sock *sk)
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{
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return trace_connect(sk);
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}
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SEC("kprobe/tcp_v6_connect")
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int BPF_KPROBE(tcp_v6_connect, struct sock *sk)
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{
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return trace_connect(sk);
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}
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SEC("kprobe/tcp_rcv_state_process")
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int BPF_KPROBE(tcp_rcv_state_process, struct sock *sk)
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{
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return handle_tcp_rcv_state_process(ctx, sk);
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}
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</code></pre>
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<p>在 trace_connect 中，我们跟踪新的 tcp 连接，记录到达时间，并且把它加入 map 中：</p>
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<pre><code class="language-c">struct {
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__uint(type, BPF_MAP_TYPE_HASH);
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__uint(max_entries, 4096);
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__type(key, struct sock *);
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__type(value, struct piddata);
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} start SEC(".maps");
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static int trace_connect(struct sock *sk)
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{
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u32 tgid = bpf_get_current_pid_tgid() >> 32;
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struct piddata piddata = {};
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if (targ_tgid && targ_tgid != tgid)
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return 0;
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bpf_get_current_comm(&piddata.comm, sizeof(piddata.comm));
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piddata.ts = bpf_ktime_get_ns();
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piddata.tgid = tgid;
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bpf_map_update_elem(&start, &sk, &piddata, 0);
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return 0;
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}
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</code></pre>
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<p>在 handle_tcp_rcv_state_process 中，我们跟踪接收到的 tcp 数据包，从 map 从提取出对应的 connect 事件，并且计算延迟：</p>
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<pre><code class="language-c">static int handle_tcp_rcv_state_process(void *ctx, struct sock *sk)
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{
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struct piddata *piddatap;
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struct event event = {};
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s64 delta;
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u64 ts;
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if (BPF_CORE_READ(sk, __sk_common.skc_state) != TCP_SYN_SENT)
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return 0;
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piddatap = bpf_map_lookup_elem(&start, &sk);
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if (!piddatap)
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return 0;
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ts = bpf_ktime_get_ns();
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delta = (s64)(ts - piddatap->ts);
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if (delta < 0)
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goto cleanup;
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event.delta_us = delta / 1000U;
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if (targ_min_us && event.delta_us < targ_min_us)
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goto cleanup;
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__builtin_memcpy(&event.comm, piddatap->comm,
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sizeof(event.comm));
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event.ts_us = ts / 1000;
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event.tgid = piddatap->tgid;
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event.lport = BPF_CORE_READ(sk, __sk_common.skc_num);
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event.dport = BPF_CORE_READ(sk, __sk_common.skc_dport);
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event.af = BPF_CORE_READ(sk, __sk_common.skc_family);
|
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if (event.af == AF_INET) {
|
||
event.saddr_v4 = BPF_CORE_READ(sk, __sk_common.skc_rcv_saddr);
|
||
event.daddr_v4 = BPF_CORE_READ(sk, __sk_common.skc_daddr);
|
||
} else {
|
||
BPF_CORE_READ_INTO(&event.saddr_v6, sk,
|
||
__sk_common.skc_v6_rcv_saddr.in6_u.u6_addr32);
|
||
BPF_CORE_READ_INTO(&event.daddr_v6, sk,
|
||
__sk_common.skc_v6_daddr.in6_u.u6_addr32);
|
||
}
|
||
bpf_perf_event_output(ctx, &events, BPF_F_CURRENT_CPU,
|
||
&event, sizeof(event));
|
||
|
||
cleanup:
|
||
bpf_map_delete_elem(&start, &sk);
|
||
return 0;
|
||
}
|
||
</code></pre>
|
||
<h2 id="编译运行"><a class="header" href="#编译运行">编译运行</a></h2>
|
||
<pre><code class="language-console">$ make
|
||
...
|
||
BPF .output/tcpconnlat.bpf.o
|
||
GEN-SKEL .output/tcpconnlat.skel.h
|
||
CC .output/tcpconnlat.o
|
||
BINARY tcpconnlat
|
||
$ sudo ./tcpconnlat
|
||
PID COMM IP SADDR DADDR DPORT LAT(ms)
|
||
222564 wget 4 192.168.88.15 110.242.68.3 80 25.29
|
||
222684 wget 4 192.168.88.15 167.179.101.42 443 246.76
|
||
222726 ssh 4 192.168.88.15 167.179.101.42 22 241.17
|
||
222774 ssh 4 192.168.88.15 1.15.149.151 22 25.31
|
||
</code></pre>
|
||
<h2 id="总结"><a class="header" href="#总结">总结</a></h2>
|
||
<p>通过上面的实验，我们可以看到，tcpconnlat 工具的实现原理是基于内核的TCP连接的跟踪，并且可以跟踪到 tcp 连接的延迟时间；除了命令行使用方式之外，还可以将其和容器、k8s 等元信息综合起来，通过 <code>prometheus</code> 和 <code>grafana</code> 等工具进行网络性能分析。</p>
|
||
<p>来源：<a href="https://github.com/iovisor/bcc/blob/master/libbpf-tools/tcpconnlat.bpf.c">https://github.com/iovisor/bcc/blob/master/libbpf-tools/tcpconnlat.bpf.c</a></p>
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