From a9d4a4c50cdfa886e89f6ceb850ccd6992602890 Mon Sep 17 00:00:00 2001
From: Xargin <cao1988228@163.com>
Date: Tue, 14 Aug 2018 14:48:30 +0800
Subject: [PATCH] update d conf

---
 ch6-cloud/ch6-06-config.md | 67 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 67 insertions(+)

diff --git a/ch6-cloud/ch6-06-config.md b/ch6-cloud/ch6-06-config.md
index 3c757a4..02e633f 100644
--- a/ch6-cloud/ch6-06-config.md
+++ b/ch6-cloud/ch6-06-config.md
@@ -48,6 +48,73 @@ go func() {
 }()
 ```
 
+### 整合起来
+
+```go
+package main
+
+import (
+    "fmt"
+    "log"
+    "time"
+
+    "golang.org/x/net/context"
+
+    "github.com/coreos/etcd/client"
+)
+
+func watchAndUpdate() {
+}
+
+func set() error {
+    return nil
+}
+
+func get() (string, error) {
+    return "", nil
+}
+
+func main() {
+    cfg := client.Config{
+        Endpoints:               []string{"http://127.0.0.1:2379"},
+        Transport:               client.DefaultTransport,
+        HeaderTimeoutPerRequest: time.Second,
+    }
+
+    c, err := client.New(cfg)
+    if err != nil {
+        log.Fatal(err)
+    }
+    kapi := client.NewKeysAPI(c)
+    w := kapi.Watcher("/name", nil)
+    go func() {
+        for {
+            resp, err := w.Next(context.Background())
+            fmt.Println(resp, err)
+            fmt.Println("new values is ", resp.Node.Value)
+        }
+    }()
+
+    log.Print("Setting /name to alex")
+    resp, err := kapi.Set(context.Background(), "/name", "alex", nil)
+    if err != nil {
+        log.Fatal(err)
+    } else {
+        log.Printf("Set is done. Metadata is %q\n", resp)
+    }
+
+    log.Print("Getting /name key value")
+    resp, err = kapi.Get(context.Background(), "/name", nil)
+    if err != nil {
+        log.Fatal(err)
+    } else {
+        log.Printf("Get is done. Metadata is %q\n", resp)
+        log.Printf("%q key has %q value\n", resp.Node.Key, resp.Node.Value)
+    }
+    time.Sleep(time.Minute)
+}
+```
+
 ### 配置膨胀之后
 
 随着业务的发展，配置系统本身所承载的压力可能也会越来越大，配置文件可能成千上万。客户端同样上万，将配置内容存储在 etcd 内部便不再合适了。随着配置文件数量的膨胀，除了存储系统本身的吞吐量问题，还有配置信息的管理问题。我们需要对相应的配置进行权限管理，需要根据业务量进行配置存储的集群划分。如果客户端太多，导致了配置存储系统无法承受瞬时大量的 QPS，那可能还需要在客户端侧进行缓存优化，等等。