diff --git a/.gitignore b/.gitignore
index 4e6417a74efe..d404dff495eb 100644
--- a/.gitignore
+++ b/.gitignore
@@ -33,5 +33,8 @@ hack/tls-setup/certs
 /tools/local-tester/bridge/bridge
 /tools/proto-annotations/proto-annotations
 /tools/benchmark/benchmark
+/tools/rw-benchmark/rw-benchmark
+/tools/rw-benchmark/rw_benchmark.html
+/tools/rw-benchmark/*.csv
 /out
 /etcd-dump-logs
diff --git a/CHANGELOG/CHANGELOG-3.6.md b/CHANGELOG/CHANGELOG-3.6.md
index 0d8924bf2452..680a10fb3229 100644
--- a/CHANGELOG/CHANGELOG-3.6.md
+++ b/CHANGELOG/CHANGELOG-3.6.md
@@ -74,9 +74,10 @@ See [code changes](https://github.com/etcd-io/etcd/compare/v3.5.0...v3.6.0).
 - Add [`etcd grpc-proxy start --endpoints-auto-sync-interval`](https://github.com/etcd-io/etcd/pull/14354) flag to enable and configure interval of auto sync of endpoints with server.
 - Add [`etcd grpc-proxy start --listen-cipher-suites`](https://github.com/etcd-io/etcd/pull/14308) flag to support adding configurable cipher list.
 
-### tools/benchmark
+### tools
 
-- [Add etcd client autoSync flag](https://github.com/etcd-io/etcd/pull/13416)
+- [Add etcd client autoSync flag for benchmark](https://github.com/etcd-io/etcd/pull/13416)
+- [Reimplement the rw-heatmaps using Golang and rename it to rw-benchmark](https://github.com/etcd-io/etcd/pull/15060)
 
 ### Metrics, Monitoring
 
diff --git a/Makefile b/Makefile
index 1044e776904b..6c0d1b3ba705 100644
--- a/Makefile
+++ b/Makefile
@@ -5,6 +5,10 @@ build:
 	./bin/etcdctl version
 	./bin/etcdutl version
 
+.PHONY: tools
+tools:
+	GO_BUILD_FLAGS="${GO_BUILD_FLAGS} -v" ./scripts/build_tools.sh
+
 # Tests
 
 GO_TEST_FLAGS?=
diff --git a/bill-of-materials.json b/bill-of-materials.json
index 9638e8e54aa2..3b7c4743cac8 100644
--- a/bill-of-materials.json
+++ b/bill-of-materials.json
@@ -8,6 +8,15 @@
 			}
 		]
 	},
+	{
+		"project": "github.com/ahrtr/gocontainer",
+		"licenses": [
+			{
+				"type": "MIT License",
+				"confidence": 1
+			}
+		]
+	},
 	{
 		"project": "github.com/anishathalye/porcupine",
 		"licenses": [
@@ -125,6 +134,15 @@
 			}
 		]
 	},
+	{
+		"project": "github.com/go-echarts/go-echarts/v2",
+		"licenses": [
+			{
+				"type": "MIT License",
+				"confidence": 1
+			}
+		]
+	},
 	{
 		"project": "github.com/go-logr/logr",
 		"licenses": [
diff --git a/go.mod b/go.mod
index 3339b0c2ccc5..5de78871b417 100644
--- a/go.mod
+++ b/go.mod
@@ -15,10 +15,12 @@ replace (
 )
 
 require (
+	github.com/ahrtr/gocontainer v0.3.0
 	github.com/bgentry/speakeasy v0.1.0
 	github.com/cheggaaa/pb/v3 v3.1.0
 	github.com/coreos/go-semver v0.3.0
 	github.com/dustin/go-humanize v1.0.0
+	github.com/go-echarts/go-echarts/v2 v2.2.5-0.20211021024243-33ae1aa415d6
 	github.com/spf13/cobra v1.6.1
 	github.com/stretchr/testify v1.8.1
 	go.etcd.io/bbolt v1.3.6
diff --git a/go.sum b/go.sum
index f5dbc0efb5a4..8a1a254edb2d 100644
--- a/go.sum
+++ b/go.sum
@@ -43,6 +43,8 @@ github.com/BurntSushi/xgb v0.0.0-20160522181843-27f122750802/go.mod h1:IVnqGOEym
 github.com/OneOfOne/xxhash v1.2.2/go.mod h1:HSdplMjZKSmBqAxg5vPj2TmRDmfkzw+cTzAElWljhcU=
 github.com/VividCortex/ewma v1.1.1 h1:MnEK4VOv6n0RSY4vtRe3h11qjxL3+t0B8yOL8iMXdcM=
 github.com/VividCortex/ewma v1.1.1/go.mod h1:2Tkkvm3sRDVXaiyucHiACn4cqf7DpdyLvmxzcbUokwA=
+github.com/ahrtr/gocontainer v0.3.0 h1:/4wM0VhaLEYZMoF6WT8ZHUmf2n9BVpCD3uMaKrA0iHY=
+github.com/ahrtr/gocontainer v0.3.0/go.mod h1:cQoR5/JTMoDNEkk5vGaohPZ+nnTQVB2nk2Y012WJWsM=
 github.com/alecthomas/template v0.0.0-20160405071501-a0175ee3bccc/go.mod h1:LOuyumcjzFXgccqObfd/Ljyb9UuFJ6TxHnclSeseNhc=
 github.com/alecthomas/template v0.0.0-20190718012654-fb15b899a751/go.mod h1:LOuyumcjzFXgccqObfd/Ljyb9UuFJ6TxHnclSeseNhc=
 github.com/alecthomas/units v0.0.0-20151022065526-2efee857e7cf/go.mod h1:ybxpYRFXyAe+OPACYpWeL0wqObRcbAqCMya13uyzqw0=
@@ -105,6 +107,8 @@ github.com/fatih/color v1.13.0 h1:8LOYc1KYPPmyKMuN8QV2DNRWNbLo6LZ0iLs8+mlH53w=
 github.com/fatih/color v1.13.0/go.mod h1:kLAiJbzzSOZDVNGyDpeOxJ47H46qBXwg5ILebYFFOfk=
 github.com/getsentry/raven-go v0.2.0 h1:no+xWJRb5ZI7eE8TWgIq1jLulQiIoLG0IfYxv5JYMGs=
 github.com/ghodss/yaml v1.0.0/go.mod h1:4dBDuWmgqj2HViK6kFavaiC9ZROes6MMH2rRYeMEF04=
+github.com/go-echarts/go-echarts/v2 v2.2.5-0.20211021024243-33ae1aa415d6 h1:+p0u+1svKoBC2xS6GzpmcDHShkAGqD+wUQLpxIpygM0=
+github.com/go-echarts/go-echarts/v2 v2.2.5-0.20211021024243-33ae1aa415d6/go.mod h1:6TOomEztzGDVDkOSCFBq3ed7xOYfbOqhaBzD0YV771A=
 github.com/go-gl/glfw v0.0.0-20190409004039-e6da0acd62b1/go.mod h1:vR7hzQXu2zJy9AVAgeJqvqgH9Q5CA+iKCZ2gyEVpxRU=
 github.com/go-gl/glfw/v3.3/glfw v0.0.0-20191125211704-12ad95a8df72/go.mod h1:tQ2UAYgL5IevRw8kRxooKSPJfGvJ9fJQFa0TUsXzTg8=
 github.com/go-gl/glfw/v3.3/glfw v0.0.0-20200222043503-6f7a984d4dc4/go.mod h1:tQ2UAYgL5IevRw8kRxooKSPJfGvJ9fJQFa0TUsXzTg8=
@@ -316,6 +320,7 @@ github.com/stretchr/testify v1.2.2/go.mod h1:a8OnRcib4nhh0OaRAV+Yts87kKdq0PP7pXf
 github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
 github.com/stretchr/testify v1.4.0/go.mod h1:j7eGeouHqKxXV5pUuKE4zz7dFj8WfuZ+81PSLYec5m4=
 github.com/stretchr/testify v1.5.1/go.mod h1:5W2xD1RspED5o8YsWQXVCued0rvSQ+mT+I5cxcmMvtA=
+github.com/stretchr/testify v1.6.0/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
 github.com/stretchr/testify v1.6.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
 github.com/stretchr/testify v1.7.0/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
 github.com/stretchr/testify v1.7.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
diff --git a/scripts/build_lib.sh b/scripts/build_lib.sh
index 9c297a191e5b..7842fa401515 100755
--- a/scripts/build_lib.sh
+++ b/scripts/build_lib.sh
@@ -64,6 +64,7 @@ tools_build() {
   out="bin"
   if [[ -n "${BINDIR}" ]]; then out="${BINDIR}"; fi
   tools_path="tools/benchmark
+    tools/rw-benchmark
     tools/etcd-dump-db
     tools/etcd-dump-logs
     tools/local-tester/bridge"
diff --git a/tools/rw-benchmark/README.md b/tools/rw-benchmark/README.md
new file mode 100644
index 000000000000..dc8e684febe3
--- /dev/null
+++ b/tools/rw-benchmark/README.md
@@ -0,0 +1,31 @@
+# etcd/tools/rw-benchmark
+
+`etcd/tools/rw-benchmark` is the mixed read/write performance evaluation tool for etcd clusters.
+
+## Execute
+
+### Benchmark
+To get a mixed read/write performance evaluation result:
+```sh
+# run with default configurations and specify the working directory
+./rw-benchmark.sh -w ${WORKING_DIR}
+```
+`rw-benchmark.sh` will automatically use the etcd binary compiled under `etcd/bin/tools` directory.
+
+Note: the result csv file will be saved to current working directory. The working directory is where etcd database is saved. The working directory is designed for scenarios where a different mounted disk is preferred.
+
+### Plot Graphs
+To generate a HTML page including all the line charts based on the benchmark result csv files:
+```sh
+# To generate a HTML page with each chart including one pair of read & write
+# benchmark results from one data csv file.
+./rw-benchmark -l "main" ${FIRST_CSV_FILE} 
+
+# To generate a HTML page with each chart including two pair of read & write 
+# benchmark results from two data csv files respectively.
+./rw-benchmark -l "main:dev" ${FIRST_CSV_FILE} ${SECOND_CSV_FILE}
+```
+
+The read QPS is displayed as <span style="color:blue">blue</span>, and write QPS is displayed as <span style="color:red">red</span>. 
+The data in the second CSV file is rendered as dashed line if present. See example in [example/rw_benchmark.html](example/rw_benchmark.html).
+Note each line in the line chart can be hidden or displayed by clicking on the related legend.
diff --git a/tools/rw-benchmark/example/dev.csv b/tools/rw-benchmark/example/dev.csv
new file mode 100644
index 000000000000..b73cf165e28f
--- /dev/null
+++ b/tools/rw-benchmark/example/dev.csv
@@ -0,0 +1,450 @@
+type,ratio,conn_size,value_size,iter1,iter2,iter3,iter4,iter5,comment
+PARAM,,,,,,,,,"key_size=256,key_space_size=65536,backend_size=21474836480,range_limit=100"
+DATA,0.0078,32,16,245.3039:35907.7856,245.9720:36006.3388,249.4058:36508.7530,253.5596:37116.4270,250.7366:36703.4469,
+DATA,0.0078,64,16,254.0160:37182.3257,253.3490:37084.3820,256.7318:37578.2896,260.4655:38126.3240,261.4608:38272.0847,
+DATA,0.0078,128,16,262.7082:38454.4469,263.0416:38493.9911,264.3438:38691.6580,265.4096:38847.0270,271.3836:39722.8663,
+DATA,0.0078,256,16,269.6633:39465.8525,273.1094:39974.8167,275.0659:40216.2359,276.1103:40412.2910,277.1494:40558.5642,
+DATA,0.0078,512,16,283.7732:41529.8232,285.6024:41793.5425,283.8550:41532.4117,286.3505:41910.9292,286.5039:41924.1279,
+DATA,0.0078,1024,16,296.3893:43347.6227,294.5624:43082.5616,296.2384:43331.2918,296.3411:43348.3959,296.4917:43358.9956,
+DATA,0.0078,2048,16,303.5654:44347.1160,307.3025:44912.2690,304.3031:44457.5080,303.7355:44379.9010,307.0249:44869.9095,
+DATA,0.0078,4096,16,299.2113:43619.8452,308.2896:44953.8624,306.7261:44722.7202,302.8368:44147.8721,311.0803:45331.8404,
+DATA,0.0078,32,32,245.4262:35926.0714,245.2868:35905.9232,247.9258:36291.8726,251.0414:36748.3773,251.8507:36866.3259,
+DATA,0.0078,64,32,253.4841:37103.8275,256.5283:37551.1120,256.9161:37605.2321,259.7757:38024.6263,263.0550:38505.7050,
+DATA,0.0078,128,32,261.8840:38332.0061,265.8609:38880.0913,267.2260:39107.4491,268.8825:39357.4822,271.1324:39687.0379,
+DATA,0.0078,256,32,270.9987:39661.8881,270.3364:39566.6495,273.7607:40069.1395,275.8317:40370.3985,276.1555:40420.6694,
+DATA,0.0078,512,32,285.3112:41752.3532,286.4141:41921.8897,284.6794:41582.6788,287.7059:42103.5390,288.4593:42207.0728,
+DATA,0.0078,1024,32,294.6313:43101.7053,296.8888:43419.0507,296.9067:43425.4108,296.1054:43306.3025,298.5457:43666.6932,
+DATA,0.0078,2048,32,304.2676:44453.1484,305.3394:44619.8856,306.1261:44744.1478,308.0870:45003.8131,304.3376:44461.8427,
+DATA,0.0078,4096,32,301.2507:43929.5523,307.9588:44862.9134,307.3224:44800.4046,307.2125:44778.7150,307.8729:44870.9432,
+DATA,0.0078,32,64,247.5560:36237.9497,248.5397:36382.0009,250.9582:36735.8489,252.7836:37001.3028,254.5248:37257.7661,
+DATA,0.0078,64,64,255.3265:37374.1839,257.0772:37629.1600,258.3864:37821.7312,260.1196:38075.1992,263.7144:38602.9881,
+DATA,0.0078,128,64,257.5580:37697.9083,259.1785:37936.4356,260.9700:38196.4015,264.4438:38707.9825,265.7542:38899.5856,
+DATA,0.0078,256,64,273.0860:39966.5545,272.2796:39846.2562,274.0054:40099.5757,274.1302:40120.5171,278.4102:40749.9690,
+DATA,0.0078,512,64,282.6958:41306.5556,281.8350:41243.7066,282.5847:41354.2775,284.0854:41568.3294,283.0601:41427.9986,
+DATA,0.0078,1024,64,295.7037:43244.9124,294.8195:43120.1046,294.2447:43041.6226,294.6880:43106.3313,296.6594:43395.3474,
+DATA,0.0078,2048,64,305.9406:44708.2725,308.8593:45121.4582,305.5380:44635.7246,306.3365:44750.5638,306.9355:44846.2554,
+DATA,0.0078,4096,64,302.8041:44144.3848,310.5427:45266.6685,304.5057:44388.3417,311.2041:45359.7440,308.2669:44924.6234,
+DATA,0.0078,32,128,244.5960:35804.5336,247.0914:36170.0234,249.1690:36474.1612,251.7953:36858.6312,253.5863:37120.5320,
+DATA,0.0078,64,128,256.5514:37553.3141,257.9939:37765.4411,259.1628:37935.1997,261.6221:38296.7217,264.4253:38706.1891,
+DATA,0.0078,128,128,260.2760:38098.2561,261.4276:38266.6637,263.9492:38635.7555,264.6510:38737.8780,267.5009:39155.6445,
+DATA,0.0078,256,128,271.2933:39710.3744,270.3887:39577.8527,271.9555:39807.9712,272.3304:39856.1203,275.9455:40385.5599,
+DATA,0.0078,512,128,281.3126:41164.7704,283.8962:41537.1944,284.0447:41569.3827,284.0217:41556.7459,286.5323:41921.8665,
+DATA,0.0078,1024,128,296.7369:43398.6812,295.4814:43211.2698,296.7117:43401.2712,296.8471:43415.5686,296.6107:43379.8121,
+DATA,0.0078,2048,128,299.3453:43738.5757,299.9749:43826.8815,303.4636:44308.7493,302.7071:44220.5260,304.6584:44513.3662,
+DATA,0.0078,4096,128,301.8481:43997.1846,309.4917:45097.7546,306.5916:44698.2856,306.4367:44702.4568,304.5669:44404.4825,
+DATA,0.0078,32,256,245.7049:35966.8847,246.7623:36121.7315,247.9522:36296.0213,252.0113:36889.8499,251.4815:36812.6389,
+DATA,0.0078,64,256,254.0013:37179.8300,254.6351:37273.3363,257.0999:37633.0125,261.7172:38309.1466,263.0458:38502.9900,
+DATA,0.0078,128,256,262.6193:38440.6001,262.6473:38446.1040,264.9504:38752.0608,266.5987:39025.7768,268.9464:39366.7634,
+DATA,0.0078,256,256,271.4783:39735.1107,271.3949:39720.5355,273.7046:40057.2812,275.7635:40362.6068,275.0612:40256.7280,
+DATA,0.0078,512,256,284.9653:41695.1055,284.4362:41619.5236,283.6212:41497.9173,285.1754:41740.5573,290.1212:42451.6175,
+DATA,0.0078,1024,256,294.6859:43103.9550,291.0143:42566.4041,292.6760:42801.4983,292.9971:42855.5802,294.2554:43040.4185,
+DATA,0.0078,2048,256,302.6425:44209.5427,304.4568:44473.7784,302.6683:44236.6600,301.7085:44072.0469,303.5931:44350.5663,
+DATA,0.0078,4096,256,302.1649:44051.5963,300.6207:43823.2247,301.9759:44014.9101,299.3887:43647.6263,302.6554:44121.3072,
+DATA,0.0078,32,512,246.4472:36075.6652,247.9521:36295.8226,248.1986:36332.0343,251.2789:36782.8214,251.6665:36839.1718,
+DATA,0.0078,64,512,254.9960:37326.7352,253.6512:37129.9680,256.9369:37610.6968,259.7640:38023.0508,261.2666:38243.2208,
+DATA,0.0078,128,512,262.0199:38352.9274,262.0647:38360.6575,263.6960:38600.2108,265.1174:38806.9788,267.3974:39140.9617,
+DATA,0.0078,256,512,269.2336:39400.9049,269.2644:39409.9625,269.9892:39517.0987,271.4614:39728.1497,273.3548:40006.1864,
+DATA,0.0078,512,512,279.9374:40965.4856,282.9156:41397.3402,283.0245:41419.8212,284.4125:41629.0126,284.7382:41663.0691,
+DATA,0.0078,1024,512,290.4840:42487.0120,291.3584:42616.0709,292.7913:42819.0611,293.9338:43001.4140,294.8488:43126.4106,
+DATA,0.0078,2048,512,301.3523:44008.7125,300.2045:43862.8536,299.3167:43721.0893,302.1761:44150.3813,302.8751:44261.7487,
+DATA,0.0078,4096,512,299.5718:43672.6860,306.6884:44709.5265,309.5588:45128.4846,303.6135:44254.9947,308.5245:44978.9000,
+DATA,0.0078,32,1024,242.9162:35559.0238,241.1194:35295.4355,243.4934:35643.0954,246.9903:36154.8837,248.8257:36423.7090,
+DATA,0.0078,64,1024,253.1756:37058.1535,251.2068:36771.3661,253.5970:37122.1111,255.5374:37404.5467,258.3402:37816.1025,
+DATA,0.0078,128,1024,260.0573:38063.0746,260.5809:38141.0828,262.9449:38487.2369,263.3000:38541.1304,264.3973:38700.8223,
+DATA,0.0078,256,1024,270.5580:39599.2591,268.5317:39303.5105,269.7210:39475.3890,273.5503:40039.0487,273.7460:40068.5788,
+DATA,0.0078,512,1024,278.7953:40721.0110,277.5264:40608.3297,279.7073:40932.3902,281.8563:41247.7830,282.8999:41395.7588,
+DATA,0.0078,1024,1024,290.9346:42552.2334,288.5605:42211.0872,290.9595:42533.9821,290.6334:42507.8316,292.6158:42797.3576,
+DATA,0.0078,2048,1024,296.6684:43335.6262,300.9516:43975.3553,299.4936:43761.9856,297.9460:43538.1791,299.7838:43813.6001,
+DATA,0.0078,4096,1024,299.8189:43703.4650,307.4083:44803.8670,303.2560:44203.3426,304.7796:44418.8780,306.0158:44595.9284,
+DATA,0.125,32,16,2688.3306:21414.5487,2701.5095:21519.5545,2763.8310:22016.0304,2770.5615:22069.5965,2816.2995:22433.9932,
+DATA,0.125,64,16,2777.2219:22122.1914,2807.6785:22364.5989,2851.8292:22716.3155,2887.5275:23000.6138,2939.8964:23417.7319,
+DATA,0.125,128,16,3195.0390:25450.0320,3237.1515:25784.4008,3287.3610:26185.3980,3317.5577:26424.4016,3340.3211:26606.7545,
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diff --git a/tools/rw-benchmark/example/main.csv b/tools/rw-benchmark/example/main.csv
new file mode 100644
index 000000000000..1887b103a72f
--- /dev/null
+++ b/tools/rw-benchmark/example/main.csv
@@ -0,0 +1,450 @@
+type,ratio,conn_size,value_size,iter1,iter2,iter3,iter4,iter5,comment
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diff --git a/tools/rw-benchmark/example/rw_benchmark.html b/tools/rw-benchmark/example/rw_benchmark.html
new file mode 100644
index 000000000000..994fae0c94cb
--- /dev/null
+++ b/tools/rw-benchmark/example/rw_benchmark.html
@@ -0,0 +1,692 @@
+
+<!DOCTYPE html>
+<html>
+<head>
+    <meta charset="utf-8">
+    <title>Awesome go-echarts</title>
+    <script src="https://go-echarts.github.io/go-echarts-assets/assets/echarts.min.js"></script>
+</head>
+
+<body>
+
+
+
+
+
+    <style> .box { justify-content:center; display:flex; flex-wrap:wrap } </style>
+    <div class="box"> 
+<div class="container">
+    <div class="item" id="iBEKkTunyILB" style="width:900px;height:500px;"></div>
+</div>
+
+<script type="text/javascript">
+    "use strict";
+    let goecharts_iBEKkTunyILB = echarts.init(document.getElementById('iBEKkTunyILB'), "white");
+    let option_iBEKkTunyILB = {"color":["#5470c6","#91cc75","#fac858","#ee6666","#73c0de","#3ba272","#fc8452","#9a60b4","#ea7ccc"],"legend":{"show":true,"type":"","left":"right","top":"middle","orient":"vertical"},"series":[{"name":"main read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":278.2156,"XAxisIndex":0,"YAxisIndex":0},{"value":290.16492,"XAxisIndex":0,"YAxisIndex":0},{"value":296.91728,"XAxisIndex":0,"YAxisIndex":0},{"value":306.77236000000005,"XAxisIndex":0,"YAxisIndex":0},{"value":317.7899,"XAxisIndex":0,"YAxisIndex":0},{"value":334.20196,"XAxisIndex":0,"YAxisIndex":0},{"value":341.26688,"XAxisIndex":0,"YAxisIndex":0},{"value":348.80714,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"solid"}},{"name":"dev read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":248.99557999999996,"XAxisIndex":0,"YAxisIndex":0},{"value":257.20462000000003,"XAxisIndex":0,"YAxisIndex":0},{"value":265.37736000000007,"XAxisIndex":0,"YAxisIndex":0},{"value":274.21966000000003,"XAxisIndex":0,"YAxisIndex":0},{"value":285.217,"XAxisIndex":0,"YAxisIndex":0},{"value":296.00458,"XAxisIndex":0,"YAxisIndex":0},{"value":305.18628,"XAxisIndex":0,"YAxisIndex":0},{"value":305.62882,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"dashed"}},{"name":"main write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":36089.55133999999,"XAxisIndex":0,"YAxisIndex":0},{"value":37638.73794,"XAxisIndex":0,"YAxisIndex":0},{"value":38513.10966,"XAxisIndex":0,"YAxisIndex":0},{"value":39788.1002,"XAxisIndex":0,"YAxisIndex":0},{"value":41209.12498,"XAxisIndex":0,"YAxisIndex":0},{"value":43313.28302,"XAxisIndex":0,"YAxisIndex":0},{"value":44181.18986,"XAxisIndex":0,"YAxisIndex":0},{"value":45052.72498,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"solid"}},{"name":"dev write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":36448.55026,"XAxisIndex":0,"YAxisIndex":0},{"value":37648.6812,"XAxisIndex":0,"YAxisIndex":0},{"value":38841.997859999996,"XAxisIndex":0,"YAxisIndex":0},{"value":40125.55206,"XAxisIndex":0,"YAxisIndex":0},{"value":41738.1669,"XAxisIndex":0,"YAxisIndex":0},{"value":43293.77352,"XAxisIndex":0,"YAxisIndex":0},{"value":44593.3407,"XAxisIndex":0,"YAxisIndex":0},{"value":44555.22806000001,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"dashed"}}],"title":{"text":"etcd rw benchmark (RW Ratio: 0.007800, Value Size: 16)"},"toolbox":{"show":true,"orient":"horizontal","left":"right","feature":{"saveAsImage":{"show":true,"title":"Save as image"},"dataView":{"show":true,"title":"Show as table","lang":["Data view","Turn off","Refresh"],"backgroundColor":""}}},"tooltip":{"show":true},"xAxis":[{"name":"Connections","data":[32,64,128,256,512,1024,2048,4096]}],"yAxis":[{"name":"QPS (Request/sec)"}]}
+;
+    goecharts_iBEKkTunyILB.setOption(option_iBEKkTunyILB);
+</script>
+ 
+<div class="container">
+    <div class="item" id="UYlEDnJLdEJP" style="width:900px;height:500px;"></div>
+</div>
+
+<script type="text/javascript">
+    "use strict";
+    let goecharts_UYlEDnJLdEJP = echarts.init(document.getElementById('UYlEDnJLdEJP'), "white");
+    let option_UYlEDnJLdEJP = {"color":["#5470c6","#91cc75","#fac858","#ee6666","#73c0de","#3ba272","#fc8452","#9a60b4","#ea7ccc"],"legend":{"show":true,"type":"","left":"right","top":"middle","orient":"vertical"},"series":[{"name":"main read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":279.18863999999996,"XAxisIndex":0,"YAxisIndex":0},{"value":287.71426,"XAxisIndex":0,"YAxisIndex":0},{"value":297.9268,"XAxisIndex":0,"YAxisIndex":0},{"value":306.28292,"XAxisIndex":0,"YAxisIndex":0},{"value":320.96889999999996,"XAxisIndex":0,"YAxisIndex":0},{"value":333.55958,"XAxisIndex":0,"YAxisIndex":0},{"value":342.39198,"XAxisIndex":0,"YAxisIndex":0},{"value":346.36728,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"solid"}},{"name":"dev read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":248.30617999999998,"XAxisIndex":0,"YAxisIndex":0},{"value":257.95184,"XAxisIndex":0,"YAxisIndex":0},{"value":266.99716,"XAxisIndex":0,"YAxisIndex":0},{"value":273.4166,"XAxisIndex":0,"YAxisIndex":0},{"value":286.51398,"XAxisIndex":0,"YAxisIndex":0},{"value":296.61557999999997,"XAxisIndex":0,"YAxisIndex":0},{"value":305.63154,"XAxisIndex":0,"YAxisIndex":0},{"value":306.32346,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"dashed"}},{"name":"main write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":36215.737819999995,"XAxisIndex":0,"YAxisIndex":0},{"value":37320.36386,"XAxisIndex":0,"YAxisIndex":0},{"value":38644.46612,"XAxisIndex":0,"YAxisIndex":0},{"value":39725.17856,"XAxisIndex":0,"YAxisIndex":0},{"value":41621.19066,"XAxisIndex":0,"YAxisIndex":0},{"value":43236.934259999995,"XAxisIndex":0,"YAxisIndex":0},{"value":44330.78666,"XAxisIndex":0,"YAxisIndex":0},{"value":44742.594260000005,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"solid"}},{"name":"dev write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":36347.71408,"XAxisIndex":0,"YAxisIndex":0},{"value":37758.100580000006,"XAxisIndex":0,"YAxisIndex":0},{"value":39072.81332,"XAxisIndex":0,"YAxisIndex":0},{"value":40017.748999999996,"XAxisIndex":0,"YAxisIndex":0},{"value":41913.5067,"XAxisIndex":0,"YAxisIndex":0},{"value":43383.832500000004,"XAxisIndex":0,"YAxisIndex":0},{"value":44656.56752,"XAxisIndex":0,"YAxisIndex":0},{"value":44648.5057,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"dashed"}}],"title":{"text":"etcd rw benchmark (RW Ratio: 0.007800, Value Size: 32)"},"toolbox":{"show":true,"orient":"horizontal","left":"right","feature":{"saveAsImage":{"show":true,"title":"Save as image"},"dataView":{"show":true,"title":"Show as table","lang":["Data view","Turn off","Refresh"],"backgroundColor":""}}},"tooltip":{"show":true},"xAxis":[{"name":"Connections","data":[32,64,128,256,512,1024,2048,4096]}],"yAxis":[{"name":"QPS (Request/sec)"}]}
+;
+    goecharts_UYlEDnJLdEJP.setOption(option_UYlEDnJLdEJP);
+</script>
+ 
+<div class="container">
+    <div class="item" id="YjVOwyXSppos" style="width:900px;height:500px;"></div>
+</div>
+
+<script type="text/javascript">
+    "use strict";
+    let goecharts_YjVOwyXSppos = echarts.init(document.getElementById('YjVOwyXSppos'), "white");
+    let option_YjVOwyXSppos = {"color":["#5470c6","#91cc75","#fac858","#ee6666","#73c0de","#3ba272","#fc8452","#9a60b4","#ea7ccc"],"legend":{"show":true,"type":"","left":"right","top":"middle","orient":"vertical"},"series":[{"name":"main read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":278.64603999999997,"XAxisIndex":0,"YAxisIndex":0},{"value":287.23774,"XAxisIndex":0,"YAxisIndex":0},{"value":298.46964,"XAxisIndex":0,"YAxisIndex":0},{"value":306.86954,"XAxisIndex":0,"YAxisIndex":0},{"value":320.26491999999996,"XAxisIndex":0,"YAxisIndex":0},{"value":333.08025999999995,"XAxisIndex":0,"YAxisIndex":0},{"value":342.2217,"XAxisIndex":0,"YAxisIndex":0},{"value":345.29074,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"solid"}},{"name":"dev read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":250.87246,"XAxisIndex":0,"YAxisIndex":0},{"value":258.92482000000007,"XAxisIndex":0,"YAxisIndex":0},{"value":261.58090000000004,"XAxisIndex":0,"YAxisIndex":0},{"value":274.38228000000004,"XAxisIndex":0,"YAxisIndex":0},{"value":282.8522,"XAxisIndex":0,"YAxisIndex":0},{"value":295.22306,"XAxisIndex":0,"YAxisIndex":0},{"value":306.72198,"XAxisIndex":0,"YAxisIndex":0},{"value":307.4647,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"dashed"}},{"name":"main write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":36144.97474,"XAxisIndex":0,"YAxisIndex":0},{"value":37258.82348,"XAxisIndex":0,"YAxisIndex":0},{"value":38714.213579999996,"XAxisIndex":0,"YAxisIndex":0},{"value":39801.1978,"XAxisIndex":0,"YAxisIndex":0},{"value":41524.52544,"XAxisIndex":0,"YAxisIndex":0},{"value":43169.10528,"XAxisIndex":0,"YAxisIndex":0},{"value":44308.463059999995,"XAxisIndex":0,"YAxisIndex":0},{"value":44607.34273999999,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"solid"}},{"name":"dev write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":36722.97368,"XAxisIndex":0,"YAxisIndex":0},{"value":37900.652480000004,"XAxisIndex":0,"YAxisIndex":0},{"value":38287.6627,"XAxisIndex":0,"YAxisIndex":0},{"value":40156.5745,"XAxisIndex":0,"YAxisIndex":0},{"value":41380.17354,"XAxisIndex":0,"YAxisIndex":0},{"value":43181.66366,"XAxisIndex":0,"YAxisIndex":0},{"value":44812.4549,"XAxisIndex":0,"YAxisIndex":0},{"value":44816.75248,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"dashed"}}],"title":{"text":"etcd rw benchmark (RW Ratio: 0.007800, Value Size: 64)"},"toolbox":{"show":true,"orient":"horizontal","left":"right","feature":{"saveAsImage":{"show":true,"title":"Save as image"},"dataView":{"show":true,"title":"Show as table","lang":["Data view","Turn off","Refresh"],"backgroundColor":""}}},"tooltip":{"show":true},"xAxis":[{"name":"Connections","data":[32,64,128,256,512,1024,2048,4096]}],"yAxis":[{"name":"QPS (Request/sec)"}]}
+;
+    goecharts_YjVOwyXSppos.setOption(option_YjVOwyXSppos);
+</script>
+ 
+<div class="container">
+    <div class="item" id="MUWYlNtQvAJu" style="width:900px;height:500px;"></div>
+</div>
+
+<script type="text/javascript">
+    "use strict";
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+<script type="text/javascript">
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+<script type="text/javascript">
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+<script type="text/javascript">
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+    "use strict";
+    let goecharts_EPSQVGHAYFtT = echarts.init(document.getElementById('EPSQVGHAYFtT'), "white");
+    let option_EPSQVGHAYFtT = {"color":["#5470c6","#91cc75","#fac858","#ee6666","#73c0de","#3ba272","#fc8452","#9a60b4","#ea7ccc"],"legend":{"show":true,"type":"","left":"right","top":"middle","orient":"vertical"},"series":[{"name":"main read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":6513.360139999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6491.86628,"XAxisIndex":0,"YAxisIndex":0},{"value":6441.479539999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6498.1732600000005,"XAxisIndex":0,"YAxisIndex":0},{"value":6648.901260000001,"XAxisIndex":0,"YAxisIndex":0},{"value":6902.73464,"XAxisIndex":0,"YAxisIndex":0},{"value":7089.407980000001,"XAxisIndex":0,"YAxisIndex":0},{"value":7073.2035399999995,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"solid"}},{"name":"dev read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":6182.82632,"XAxisIndex":0,"YAxisIndex":0},{"value":6215.42172,"XAxisIndex":0,"YAxisIndex":0},{"value":6204.721159999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6371.616680000001,"XAxisIndex":0,"YAxisIndex":0},{"value":6540.127880000001,"XAxisIndex":0,"YAxisIndex":0},{"value":6836.13202,"XAxisIndex":0,"YAxisIndex":0},{"value":6893.610919999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6994.40122,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"dashed"}},{"name":"main write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":49.48378,"XAxisIndex":0,"YAxisIndex":0},{"value":49.32018,"XAxisIndex":0,"YAxisIndex":0},{"value":48.93696,"XAxisIndex":0,"YAxisIndex":0},{"value":49.36756,"XAxisIndex":0,"YAxisIndex":0},{"value":50.498940000000005,"XAxisIndex":0,"YAxisIndex":0},{"value":52.43526000000001,"XAxisIndex":0,"YAxisIndex":0},{"value":53.84316,"XAxisIndex":0,"YAxisIndex":0},{"value":53.702160000000006,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"solid"}},{"name":"dev write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":46.97262,"XAxisIndex":0,"YAxisIndex":0},{"value":47.21984,"XAxisIndex":0,"YAxisIndex":0},{"value":47.13854,"XAxisIndex":0,"YAxisIndex":0},{"value":48.405800000000006,"XAxisIndex":0,"YAxisIndex":0},{"value":49.68404,"XAxisIndex":0,"YAxisIndex":0},{"value":51.92968,"XAxisIndex":0,"YAxisIndex":0},{"value":52.35598,"XAxisIndex":0,"YAxisIndex":0},{"value":53.102940000000004,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"dashed"}}],"title":{"text":"etcd rw benchmark (RW Ratio: 128.000000, Value Size: 64)"},"toolbox":{"show":true,"orient":"horizontal","left":"right","feature":{"saveAsImage":{"show":true,"title":"Save as image"},"dataView":{"show":true,"title":"Show as table","lang":["Data view","Turn off","Refresh"],"backgroundColor":""}}},"tooltip":{"show":true},"xAxis":[{"name":"Connections","data":[32,64,128,256,512,1024,2048,4096]}],"yAxis":[{"name":"QPS (Request/sec)"}]}
+;
+    goecharts_EPSQVGHAYFtT.setOption(option_EPSQVGHAYFtT);
+</script>
+ 
+<div class="container">
+    <div class="item" id="logOaLZBOKJS" style="width:900px;height:500px;"></div>
+</div>
+
+<script type="text/javascript">
+    "use strict";
+    let goecharts_logOaLZBOKJS = echarts.init(document.getElementById('logOaLZBOKJS'), "white");
+    let option_logOaLZBOKJS = {"color":["#5470c6","#91cc75","#fac858","#ee6666","#73c0de","#3ba272","#fc8452","#9a60b4","#ea7ccc"],"legend":{"show":true,"type":"","left":"right","top":"middle","orient":"vertical"},"series":[{"name":"main read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":6563.334,"XAxisIndex":0,"YAxisIndex":0},{"value":6453.02124,"XAxisIndex":0,"YAxisIndex":0},{"value":6545.80464,"XAxisIndex":0,"YAxisIndex":0},{"value":6524.8865399999995,"XAxisIndex":0,"YAxisIndex":0},{"value":6624.172079999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6890.60668,"XAxisIndex":0,"YAxisIndex":0},{"value":6978.0979800000005,"XAxisIndex":0,"YAxisIndex":0},{"value":7032.200319999999,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"solid"}},{"name":"dev read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":6166.8214800000005,"XAxisIndex":0,"YAxisIndex":0},{"value":6147.0682,"XAxisIndex":0,"YAxisIndex":0},{"value":6081.5138,"XAxisIndex":0,"YAxisIndex":0},{"value":6343.27484,"XAxisIndex":0,"YAxisIndex":0},{"value":6645.593060000001,"XAxisIndex":0,"YAxisIndex":0},{"value":6801.842900000001,"XAxisIndex":0,"YAxisIndex":0},{"value":6959.033719999999,"XAxisIndex":0,"YAxisIndex":0},{"value":7074.25012,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"dashed"}},{"name":"main write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":49.8634,"XAxisIndex":0,"YAxisIndex":0},{"value":49.02518,"XAxisIndex":0,"YAxisIndex":0},{"value":49.72934,"XAxisIndex":0,"YAxisIndex":0},{"value":49.56942,"XAxisIndex":0,"YAxisIndex":0},{"value":50.32246,"XAxisIndex":0,"YAxisIndex":0},{"value":52.34192,"XAxisIndex":0,"YAxisIndex":0},{"value":52.99698000000001,"XAxisIndex":0,"YAxisIndex":0},{"value":53.39022,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"solid"}},{"name":"dev write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":46.851,"XAxisIndex":0,"YAxisIndex":0},{"value":46.70062,"XAxisIndex":0,"YAxisIndex":0},{"value":46.20254,"XAxisIndex":0,"YAxisIndex":0},{"value":48.19046000000001,"XAxisIndex":0,"YAxisIndex":0},{"value":50.4853,"XAxisIndex":0,"YAxisIndex":0},{"value":51.66835999999999,"XAxisIndex":0,"YAxisIndex":0},{"value":52.8524,"XAxisIndex":0,"YAxisIndex":0},{"value":53.70906,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"dashed"}}],"title":{"text":"etcd rw benchmark (RW Ratio: 128.000000, Value Size: 128)"},"toolbox":{"show":true,"orient":"horizontal","left":"right","feature":{"saveAsImage":{"show":true,"title":"Save as image"},"dataView":{"show":true,"title":"Show as table","lang":["Data view","Turn off","Refresh"],"backgroundColor":""}}},"tooltip":{"show":true},"xAxis":[{"name":"Connections","data":[32,64,128,256,512,1024,2048,4096]}],"yAxis":[{"name":"QPS (Request/sec)"}]}
+;
+    goecharts_logOaLZBOKJS.setOption(option_logOaLZBOKJS);
+</script>
+ 
+<div class="container">
+    <div class="item" id="pEEomKlkFQhi" style="width:900px;height:500px;"></div>
+</div>
+
+<script type="text/javascript">
+    "use strict";
+    let goecharts_pEEomKlkFQhi = echarts.init(document.getElementById('pEEomKlkFQhi'), "white");
+    let option_pEEomKlkFQhi = {"color":["#5470c6","#91cc75","#fac858","#ee6666","#73c0de","#3ba272","#fc8452","#9a60b4","#ea7ccc"],"legend":{"show":true,"type":"","left":"right","top":"middle","orient":"vertical"},"series":[{"name":"main read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":6339.865059999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6390.86628,"XAxisIndex":0,"YAxisIndex":0},{"value":6305.813179999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6317.66476,"XAxisIndex":0,"YAxisIndex":0},{"value":6544.10894,"XAxisIndex":0,"YAxisIndex":0},{"value":6705.747939999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6924.91494,"XAxisIndex":0,"YAxisIndex":0},{"value":6891.73986,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"solid"}},{"name":"dev read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":6107.6567000000005,"XAxisIndex":0,"YAxisIndex":0},{"value":6127.67534,"XAxisIndex":0,"YAxisIndex":0},{"value":6065.09264,"XAxisIndex":0,"YAxisIndex":0},{"value":6225.39636,"XAxisIndex":0,"YAxisIndex":0},{"value":6432.854759999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6745.976419999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6826.357980000001,"XAxisIndex":0,"YAxisIndex":0},{"value":6820.39268,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"dashed"}},{"name":"main write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":48.1657,"XAxisIndex":0,"YAxisIndex":0},{"value":48.552859999999995,"XAxisIndex":0,"YAxisIndex":0},{"value":47.90666,"XAxisIndex":0,"YAxisIndex":0},{"value":47.99548,"XAxisIndex":0,"YAxisIndex":0},{"value":49.71426,"XAxisIndex":0,"YAxisIndex":0},{"value":50.939620000000005,"XAxisIndex":0,"YAxisIndex":0},{"value":52.593939999999996,"XAxisIndex":0,"YAxisIndex":0},{"value":52.32374,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"solid"}},{"name":"dev write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":46.40151999999999,"XAxisIndex":0,"YAxisIndex":0},{"value":46.55334,"XAxisIndex":0,"YAxisIndex":0},{"value":46.07768,"XAxisIndex":0,"YAxisIndex":0},{"value":47.295139999999996,"XAxisIndex":0,"YAxisIndex":0},{"value":48.86996,"XAxisIndex":0,"YAxisIndex":0},{"value":51.243359999999996,"XAxisIndex":0,"YAxisIndex":0},{"value":51.843900000000005,"XAxisIndex":0,"YAxisIndex":0},{"value":51.78312,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"dashed"}}],"title":{"text":"etcd rw benchmark (RW Ratio: 128.000000, Value Size: 256)"},"toolbox":{"show":true,"orient":"horizontal","left":"right","feature":{"saveAsImage":{"show":true,"title":"Save as image"},"dataView":{"show":true,"title":"Show as table","lang":["Data view","Turn off","Refresh"],"backgroundColor":""}}},"tooltip":{"show":true},"xAxis":[{"name":"Connections","data":[32,64,128,256,512,1024,2048,4096]}],"yAxis":[{"name":"QPS (Request/sec)"}]}
+;
+    goecharts_pEEomKlkFQhi.setOption(option_pEEomKlkFQhi);
+</script>
+ 
+<div class="container">
+    <div class="item" id="URkFBnAGMZKK" style="width:900px;height:500px;"></div>
+</div>
+
+<script type="text/javascript">
+    "use strict";
+    let goecharts_URkFBnAGMZKK = echarts.init(document.getElementById('URkFBnAGMZKK'), "white");
+    let option_URkFBnAGMZKK = {"color":["#5470c6","#91cc75","#fac858","#ee6666","#73c0de","#3ba272","#fc8452","#9a60b4","#ea7ccc"],"legend":{"show":true,"type":"","left":"right","top":"middle","orient":"vertical"},"series":[{"name":"main read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":6084.68144,"XAxisIndex":0,"YAxisIndex":0},{"value":6096.4272200000005,"XAxisIndex":0,"YAxisIndex":0},{"value":6020.67542,"XAxisIndex":0,"YAxisIndex":0},{"value":6062.26508,"XAxisIndex":0,"YAxisIndex":0},{"value":6251.69856,"XAxisIndex":0,"YAxisIndex":0},{"value":6361.026339999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6505.11262,"XAxisIndex":0,"YAxisIndex":0},{"value":6553.78302,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"solid"}},{"name":"dev read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":5913.395600000001,"XAxisIndex":0,"YAxisIndex":0},{"value":5877.077139999999,"XAxisIndex":0,"YAxisIndex":0},{"value":5819.76226,"XAxisIndex":0,"YAxisIndex":0},{"value":5965.820720000001,"XAxisIndex":0,"YAxisIndex":0},{"value":6152.591839999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6358.937639999999,"XAxisIndex":0,"YAxisIndex":0},{"value":6433.90518,"XAxisIndex":0,"YAxisIndex":0},{"value":6554.260100000001,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"dashed"}},{"name":"main write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":46.22696,"XAxisIndex":0,"YAxisIndex":0},{"value":46.31588,"XAxisIndex":0,"YAxisIndex":0},{"value":45.74004000000001,"XAxisIndex":0,"YAxisIndex":0},{"value":46.05556,"XAxisIndex":0,"YAxisIndex":0},{"value":47.49344,"XAxisIndex":0,"YAxisIndex":0},{"value":48.3206,"XAxisIndex":0,"YAxisIndex":0},{"value":49.40689999999999,"XAxisIndex":0,"YAxisIndex":0},{"value":49.76168,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"solid"}},{"name":"dev write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":44.92564,"XAxisIndex":0,"YAxisIndex":0},{"value":44.64952,"XAxisIndex":0,"YAxisIndex":0},{"value":44.21376,"XAxisIndex":0,"YAxisIndex":0},{"value":45.322520000000004,"XAxisIndex":0,"YAxisIndex":0},{"value":46.740640000000006,"XAxisIndex":0,"YAxisIndex":0},{"value":48.30436,"XAxisIndex":0,"YAxisIndex":0},{"value":48.86556,"XAxisIndex":0,"YAxisIndex":0},{"value":49.765,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"dashed"}}],"title":{"text":"etcd rw benchmark (RW Ratio: 128.000000, Value Size: 512)"},"toolbox":{"show":true,"orient":"horizontal","left":"right","feature":{"saveAsImage":{"show":true,"title":"Save as image"},"dataView":{"show":true,"title":"Show as table","lang":["Data view","Turn off","Refresh"],"backgroundColor":""}}},"tooltip":{"show":true},"xAxis":[{"name":"Connections","data":[32,64,128,256,512,1024,2048,4096]}],"yAxis":[{"name":"QPS (Request/sec)"}]}
+;
+    goecharts_URkFBnAGMZKK.setOption(option_URkFBnAGMZKK);
+</script>
+ 
+<div class="container">
+    <div class="item" id="KqEDeSQoFmks" style="width:900px;height:500px;"></div>
+</div>
+
+<script type="text/javascript">
+    "use strict";
+    let goecharts_KqEDeSQoFmks = echarts.init(document.getElementById('KqEDeSQoFmks'), "white");
+    let option_KqEDeSQoFmks = {"color":["#5470c6","#91cc75","#fac858","#ee6666","#73c0de","#3ba272","#fc8452","#9a60b4","#ea7ccc"],"legend":{"show":true,"type":"","left":"right","top":"middle","orient":"vertical"},"series":[{"name":"main read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":5775.75606,"XAxisIndex":0,"YAxisIndex":0},{"value":5762.85164,"XAxisIndex":0,"YAxisIndex":0},{"value":5667.0429,"XAxisIndex":0,"YAxisIndex":0},{"value":5727.56048,"XAxisIndex":0,"YAxisIndex":0},{"value":5825.81242,"XAxisIndex":0,"YAxisIndex":0},{"value":5977.13098,"XAxisIndex":0,"YAxisIndex":0},{"value":6077.483280000001,"XAxisIndex":0,"YAxisIndex":0},{"value":6064.476499999999,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"solid"}},{"name":"dev read","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":5535.41064,"XAxisIndex":0,"YAxisIndex":0},{"value":5510.295899999999,"XAxisIndex":0,"YAxisIndex":0},{"value":5506.04326,"XAxisIndex":0,"YAxisIndex":0},{"value":5602.50924,"XAxisIndex":0,"YAxisIndex":0},{"value":5754.87882,"XAxisIndex":0,"YAxisIndex":0},{"value":5910.0093799999995,"XAxisIndex":0,"YAxisIndex":0},{"value":6055.96068,"XAxisIndex":0,"YAxisIndex":0},{"value":6073.832020000001,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Blue","type":"dashed"}},{"name":"main write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":43.87996,"XAxisIndex":0,"YAxisIndex":0},{"value":43.781760000000006,"XAxisIndex":0,"YAxisIndex":0},{"value":43.05354,"XAxisIndex":0,"YAxisIndex":0},{"value":43.51276,"XAxisIndex":0,"YAxisIndex":0},{"value":44.2579,"XAxisIndex":0,"YAxisIndex":0},{"value":45.405100000000004,"XAxisIndex":0,"YAxisIndex":0},{"value":46.15978,"XAxisIndex":0,"YAxisIndex":0},{"value":46.0467,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"solid"}},{"name":"dev write","type":"line","showSymbol":false,"waveAnimation":false,"renderLabelForZeroData":false,"selectedMode":false,"animation":false,"data":[{"value":42.054019999999994,"XAxisIndex":0,"YAxisIndex":0},{"value":41.86308,"XAxisIndex":0,"YAxisIndex":0},{"value":41.83048,"XAxisIndex":0,"YAxisIndex":0},{"value":42.56302,"XAxisIndex":0,"YAxisIndex":0},{"value":43.71962,"XAxisIndex":0,"YAxisIndex":0},{"value":44.89298,"XAxisIndex":0,"YAxisIndex":0},{"value":45.995979999999996,"XAxisIndex":0,"YAxisIndex":0},{"value":46.11844,"XAxisIndex":0,"YAxisIndex":0}],"lineStyle":{"color":"Red","type":"dashed"}}],"title":{"text":"etcd rw benchmark (RW Ratio: 128.000000, Value Size: 1024)"},"toolbox":{"show":true,"orient":"horizontal","left":"right","feature":{"saveAsImage":{"show":true,"title":"Save as image"},"dataView":{"show":true,"title":"Show as table","lang":["Data view","Turn off","Refresh"],"backgroundColor":""}}},"tooltip":{"show":true},"xAxis":[{"name":"Connections","data":[32,64,128,256,512,1024,2048,4096]}],"yAxis":[{"name":"QPS (Request/sec)"}]}
+;
+    goecharts_KqEDeSQoFmks.setOption(option_KqEDeSQoFmks);
+</script>
+ </div>
+
+</body>
+</html>
diff --git a/tools/rw-benchmark/plot_data.go b/tools/rw-benchmark/plot_data.go
new file mode 100644
index 000000000000..8e3275758171
--- /dev/null
+++ b/tools/rw-benchmark/plot_data.go
@@ -0,0 +1,465 @@
+// Copyright 2022 The etcd Authors
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+package main
+
+import (
+	"encoding/csv"
+	"flag"
+	"fmt"
+	"io"
+	"os"
+	"reflect"
+	"strconv"
+	"strings"
+
+	"github.com/ahrtr/gocontainer/map/linkedmap"
+	"github.com/go-echarts/go-echarts/v2/charts"
+	"github.com/go-echarts/go-echarts/v2/components"
+	"github.com/go-echarts/go-echarts/v2/opts"
+)
+
+type params struct {
+	legends  []string
+	layout   components.Layout
+	csvFiles []string
+	outFile  string
+}
+
+func usage() string {
+	return strings.TrimLeft(`
+rw-benchmark is a tool for visualize etcd read-write performance result.
+
+Usage:
+    rw-benchmark [options] result-file1.csv [result-file2.csv]
+
+Additional options:
+    -legend: Comma separated names of legends, such as "main,pr".
+    -layout: The layout of the page, valid values: none, center and flex.
+    -o: The HTML file name in which the benchmark data will be rendered, defaults to rw_benchmark.html.
+    -h: Print usage.
+`, "\n")
+}
+
+// parseParams parses all the options and arguments
+func parseParams(args ...string) (params, error) {
+	var ps params
+	// Require at least one argument.
+	//
+	// Usually when users use a tool in the first time, they don't know how
+	// to use it, so usually they just execute the command without any
+	// arguments. So it would be better to display the usage instead of an
+	// error message in this case.
+	if len(args) == 0 {
+		fmt.Fprintln(os.Stderr, usage())
+		os.Exit(2)
+	}
+
+	var (
+		help    bool
+		legend  string
+		layout  string
+		outFile string
+
+		err error
+	)
+	fs := flag.NewFlagSet("", flag.ContinueOnError)
+	fs.BoolVar(&help, "h", false, "Print the usage")
+	fs.StringVar(&legend, "legend", "", "The comma separated names of legends")
+	fs.StringVar(&layout, "layout", "flex", "The layout of the page, valid values: none, center and flex.")
+	fs.StringVar(&outFile, "o", "rw_benchmark.html", "The HTML file name in which the benchmark data will be rendered")
+	if err = fs.Parse(args); err != nil {
+		return ps, err
+	} else if help {
+		fmt.Fprint(os.Stderr, usage())
+		os.Exit(2)
+	}
+
+	// At most two csv files can be provided.
+	if fs.NArg() < 1 || fs.NArg() > 2 {
+		return ps, fmt.Errorf("unexpected number of arguments: %d, only 1 or 2 csv files are expected", fs.NArg())
+	}
+
+	if ps.layout, err = parseLayout(layout); err != nil {
+		return ps, err
+	}
+
+	ps.outFile = outFile
+
+	csvFile1 := fs.Arg(0)
+	ps.csvFiles = append(ps.csvFiles, csvFile1)
+	csvFile2 := fs.Arg(1)
+	if len(csvFile2) > 0 {
+		ps.csvFiles = append(ps.csvFiles, csvFile2)
+	}
+
+	if len(legend) > 0 {
+		ps.legends = strings.Split(legend, ",")
+	} else {
+		// If no legend is provided, defaults to "1" and "2".
+		for i := range ps.csvFiles {
+			ps.legends = append(ps.legends, fmt.Sprintf("%d", i+1))
+		}
+	}
+
+	if len(ps.legends) != len(ps.csvFiles) {
+		return ps, fmt.Errorf("the number of legends(%d) doesn't match the number of csv files(%d)", len(ps.legends), len(ps.csvFiles))
+	}
+
+	return ps, nil
+}
+
+func parseLayout(layout string) (components.Layout, error) {
+	switch layout {
+	case "none":
+		return components.PageNoneLayout, nil
+	case "center":
+		return components.PageCenterLayout, nil
+	case "flex":
+		return components.PageFlexLayout, nil
+	default:
+		return components.PageNoneLayout, fmt.Errorf("invalid layout %q", layout)
+	}
+}
+
+// loadCSV loads the data in a given csv file
+//
+// The return value is a map with three levels:
+//
+//	Level 1 (lmRatio):     Ratio --> lmValueSize
+//	Level 2 (lmValueSize): ValueSize --> lmConns
+//	Level 3 (lmConns):     ConnSize --> [2]float64
+//
+// In the value(array) of the 3rd map, the first value is the
+// read-qps, the second value is the write-qps.
+func loadCSV(filename string) (linkedmap.Interface, error) {
+	// Open the CSV file
+	f, err := os.Open(filename)
+	if err != nil {
+		return nil, fmt.Errorf("failed to open csv file %q, error: %w", filename, err)
+	}
+	defer f.Close()
+
+	// Read the CSV file
+	csvReader := csv.NewReader(f)
+	records, err := csvReader.ReadAll()
+	if err != nil {
+		return nil, fmt.Errorf("failed to read csv file %q, error: %w", filename, err)
+	}
+
+	lmRatio := linkedmap.New()
+	// Parse the data
+	for i, rec := range records {
+		// When `REPEAT_COUNT` is 1, then there are 6 fields in each record.
+		// Example:
+		//     DATA,0.007,32,16,245.3039:35907.7856,
+		if len(rec) >= 6 && rec[0] == "DATA" {
+			// 0.007 in above example
+			ratio, err := strconv.ParseFloat(rec[1], 64)
+			if err != nil {
+				return nil, fmt.Errorf("failed to parse ratio %q at file %q:%d, error: %w", rec[1], filename, i, err)
+			}
+
+			// 32 in above example
+			conns, err := strconv.ParseUint(rec[2], 10, 64)
+			if err != nil {
+				return nil, fmt.Errorf("failed to parse conns %q at file %q:%d, error: %w", rec[2], filename, i, err)
+			}
+
+			// 16 in above example
+			valSize, err := strconv.ParseUint(rec[3], 10, 64)
+			if err != nil {
+				return nil, fmt.Errorf("failed to parse value_size %q at file %q:%d, error: %w", rec[3], filename, i, err)
+			}
+
+			// parse all the QPS values. Note: the last column is empty.
+			var (
+				cnt         = len(rec) - 5
+				avgReadQPS  float64
+				avgWriteQPS float64
+				sumReadQPS  float64
+				sumWriteQPS float64
+			)
+			for j := 4; j < len(rec)-1; j++ {
+				// 245.3039:35907.7856 in above example
+				qps := strings.Split(rec[j], ":")
+				if len(qps) != 2 {
+					return nil, fmt.Errorf("unexpected qps values %q at file %q:%d", rec[j], filename, i)
+				}
+				readQPS, err := strconv.ParseFloat(qps[0], 64)
+				if err != nil {
+					return nil, fmt.Errorf("failed to parse read qps %q at file %q:%d, error: %w", qps[0], filename, i, err)
+				}
+				sumReadQPS += readQPS
+				writeQPS, err := strconv.ParseFloat(qps[1], 64)
+				if err != nil {
+					return nil, fmt.Errorf("failed to parse write qps %q at file %q:%d, error: %w", qps[1], filename, i, err)
+				}
+				sumWriteQPS += writeQPS
+			}
+			avgReadQPS, avgWriteQPS = sumReadQPS/float64(cnt), sumWriteQPS/float64(cnt)
+
+			// Save the data into LinkedMap.
+			// The first level map: lmRatio
+			var (
+				lmValueSize linkedmap.Interface
+				lmConn      linkedmap.Interface
+			)
+			lm := lmRatio.Get(ratio)
+			if lm == nil {
+				lmValueSize = linkedmap.New()
+				lmRatio.Put(ratio, lmValueSize)
+			} else {
+				lmValueSize = lm.(linkedmap.Interface)
+			}
+
+			// The second level map: lmValueSize
+			lm = lmValueSize.Get(valSize)
+			if lm == nil {
+				lmConn = linkedmap.New()
+				lmValueSize.Put(valSize, lmConn)
+			} else {
+				lmConn = lm.(linkedmap.Interface)
+			}
+
+			// The third level map: lmConns
+			lmConn.Put(conns, [2]float64{avgReadQPS, avgWriteQPS})
+		}
+	}
+	return lmRatio, nil
+}
+
+func loadData(files ...string) ([]linkedmap.Interface, error) {
+	var dataMaps []linkedmap.Interface
+	for _, f := range files {
+		lm, err := loadCSV(f)
+		if err != nil {
+			return nil, err
+		}
+		dataMaps = append(dataMaps, lm)
+	}
+
+	return dataMaps, nil
+}
+
+// convertBenchmarkData converts the benchmark data to format
+// which is suitable for the line chart.
+func convertBenchmarkData(lmConn linkedmap.Interface) ([]uint64, []float64, []float64) {
+	var (
+		conns []uint64
+		rQPS  []float64
+		wQPS  []float64
+	)
+	it, hasNext := lmConn.Iterator()
+	var k, v interface{}
+	for hasNext {
+		k, v, hasNext = it()
+		connSize := k.(uint64)
+		rwQPS := v.([2]float64)
+		conns = append(conns, connSize)
+		rQPS = append(rQPS, rwQPS[0])
+		wQPS = append(wQPS, rwQPS[1])
+	}
+
+	return conns, rQPS, wQPS
+}
+
+func generateLineData(qps []float64) []opts.LineData {
+	items := make([]opts.LineData, 0)
+	for _, v := range qps {
+		items = append(items, opts.LineData{Value: v})
+	}
+	return items
+}
+
+// renderChart visualizes the benchmark data in a line chart.
+// Note:
+//  1. Each line chart is related to a ratio and valueSize combination.
+//  2. The data in both CSV files are rendered in one line chart if the second file is present.
+func renderChart(page *components.Page, ratio float64, valueSize uint64, legends []string, conns []uint64, rQPSs [][]float64, wQPSs [][]float64) {
+	// create a new line instance
+	line := charts.NewLine()
+	// set some global options like Title/Legend/ToolTip
+	line.SetGlobalOptions(
+		charts.WithTitleOpts(opts.Title{
+			Title: fmt.Sprintf("etcd rw benchmark (RW Ratio: %f, Value Size: %d)", ratio, valueSize),
+		}),
+		charts.WithYAxisOpts(opts.YAxis{
+			Name: "QPS (Request/sec)",
+		}),
+		charts.WithXAxisOpts(opts.XAxis{
+			Name: "Connections",
+		}),
+		charts.WithTooltipOpts(opts.Tooltip{Show: true}),
+		charts.WithLegendOpts(opts.Legend{
+			Show:   true,
+			Orient: "vertical",
+			Left:   "right",
+			Top:    "middle",
+		}),
+		charts.WithToolboxOpts(opts.Toolbox{
+			Show:   true,
+			Orient: "horizontal",
+			Left:   "right",
+			Feature: &opts.ToolBoxFeature{
+				SaveAsImage: &opts.ToolBoxFeatureSaveAsImage{
+					Show: true, Title: "Save as image"},
+				DataView: &opts.ToolBoxFeatureDataView{
+					Show:  true,
+					Title: "Show as table",
+					Lang:  []string{"Data view", "Turn off", "Refresh"},
+				},
+			}}))
+
+	// Set data for X axis
+	line.SetXAxis(conns)
+
+	// Render read QPS from the first CSV file
+	line.AddSeries(fmt.Sprintf("%s read", legends[0]), generateLineData(rQPSs[0]),
+		charts.WithLineStyleOpts(opts.LineStyle{
+			Color: "Blue",
+			Type:  "solid",
+		}))
+
+	// Render read QPS from the second CSV file
+	if len(rQPSs) > 1 {
+		line.AddSeries(fmt.Sprintf("%s read", legends[1]), generateLineData(rQPSs[1]),
+			charts.WithLineStyleOpts(opts.LineStyle{
+				Color: "Blue",
+				Type:  "dashed",
+			}))
+	}
+
+	// Render write QPS from the first CSV file
+	line.AddSeries(fmt.Sprintf("%s write", legends[0]), generateLineData(wQPSs[0]),
+		charts.WithLineStyleOpts(opts.LineStyle{
+			Color: "Red",
+			Type:  "solid",
+		}))
+
+	// Render write QPS from the second CSV file
+	if len(wQPSs) > 1 {
+		line.AddSeries(fmt.Sprintf("%s write", legends[1]), generateLineData(wQPSs[1]),
+			charts.WithLineStyleOpts(opts.LineStyle{
+				Color: "Red",
+				Type:  "dashed",
+			}))
+	}
+
+	page.AddCharts(line)
+}
+
+// renderPage renders all data in one HTML page, which may contain multiple
+// line charts, each of which is related to a read/write ratio and valueSize
+// combination.
+//
+// Each element in the `dataMap` is a map with three levels, please see
+// comment for function `loadCSV`.
+func renderPage(dataMap []linkedmap.Interface, ps params) error {
+	page := components.NewPage()
+	page.SetLayout(ps.layout)
+
+	it1, hasNext1 := dataMap[0].Iterator()
+	var k1, v1 interface{}
+	// Loop the first level map (lmRatio)
+	for hasNext1 {
+		k1, v1, hasNext1 = it1()
+
+		ratio := k1.(float64)
+		lmValueSize := v1.(linkedmap.Interface)
+
+		// Loop the second level map (lmValueSize)
+		it2, hasNext2 := lmValueSize.Iterator()
+		var k2, v2 interface{}
+		for hasNext2 {
+			k2, v2, hasNext2 = it2()
+			valueSize := k2.(uint64)
+			lmConn := v2.(linkedmap.Interface)
+
+			var (
+				conns []uint64
+				rQPSs [][]float64
+				wQPSs [][]float64
+			)
+			// Loop the third level map (lmConn) to convert the benchmark data
+			conns, rQPS1, wQPS1 := convertBenchmarkData(lmConn)
+			rQPSs = append(rQPSs, rQPS1)
+			wQPSs = append(wQPSs, wQPS1)
+
+			// Convert the related benchmark data in the second CSV file if present.
+			if len(dataMap) > 1 {
+				if lm1 := dataMap[1].Get(ratio); lm1 != nil {
+					lmValueSize2 := lm1.(linkedmap.Interface)
+
+					if lm2 := lmValueSize2.Get(valueSize); lm2 != nil {
+						lmConn2 := lm2.(linkedmap.Interface)
+						conn2, rQPS2, wQPS2 := convertBenchmarkData(lmConn2)
+						if reflect.DeepEqual(conns, conn2) {
+							rQPSs = append(rQPSs, rQPS2)
+							wQPSs = append(wQPSs, wQPS2)
+						} else {
+							fmt.Fprintf(os.Stderr, "[Ratio: %f, ValueSize: %d] ignore the benchmark data in the second CSV file due to different conns, %v vs %v\n",
+								ratio, valueSize, conns, conn2)
+						}
+					} else {
+						fmt.Fprintf(os.Stderr, "[Ratio: %f, ValueSize: %d] ignore the benchmark data in the second CSV file due to valueSize not found\n",
+							ratio, valueSize)
+					}
+				} else {
+					fmt.Fprintf(os.Stderr, "[Ratio: %f, ValueSize: %d] ignore the benchmark data in the second CSV file due to ratio not found\n",
+						ratio, valueSize)
+				}
+			}
+
+			renderChart(page, ratio, valueSize, ps.legends, conns, rQPSs, wQPSs)
+		}
+	}
+
+	f, err := os.Create(ps.outFile)
+	if err != nil {
+		return fmt.Errorf("failed to create file: %w", err)
+	}
+	page.Render(io.MultiWriter(f))
+
+	return nil
+}
+
+func main() {
+	// parse CLI flags and arguments
+	//legends, csvFiles, outFile, err := parseParams(os.Args[1:]...)
+	ps, err := parseParams(os.Args[1:]...)
+	if err != nil {
+		fmt.Fprintf(os.Stderr, "Failed to parse the parameters: %v\n", err)
+		exit()
+	}
+
+	// load data of CSV files (1 or 2 files are expected)
+	dataMap, err := loadData(ps.csvFiles...)
+	if err != nil {
+		fmt.Fprintf(os.Stderr, "Failed to load data file(s): %v\n", err)
+		exit()
+	}
+
+	// render all data in one HTML page
+	if err = renderPage(dataMap, ps); err != nil {
+		fmt.Fprintf(os.Stderr, "Failed to render data to HTML page: %v\n", err)
+		exit()
+	}
+}
+
+func exit() {
+	fmt.Fprintf(os.Stderr, "\n")
+	fmt.Fprintf(os.Stderr, "Run `rw-benchmark -h` to print usage info.\n")
+	os.Exit(1)
+}
diff --git a/tools/rw-heatmaps/rw-benchmark.sh b/tools/rw-benchmark/rw-benchmark.sh
similarity index 100%
rename from tools/rw-heatmaps/rw-benchmark.sh
rename to tools/rw-benchmark/rw-benchmark.sh
diff --git a/tools/rw-heatmaps/README.md b/tools/rw-heatmaps/README.md
deleted file mode 100644
index 893ea9871cd3..000000000000
--- a/tools/rw-heatmaps/README.md
+++ /dev/null
@@ -1,26 +0,0 @@
-# etcd/tools/rw-heatmaps
-
-`etcd/tools/rw-heatmaps` is the mixed read/write performance evaluation tool for etcd clusters.
-
-## Execute
-
-### Benchmark
-To get a mixed read/write performance evaluation result:
-```sh
-# run with default configurations and specify the working directory
-./rw-benchmark.sh -w ${WORKING_DIR}
-```
-`rw-benchmark.sh` will automatically use the etcd binary compiled under `etcd/bin/` directory.
-
-Note: the result csv file will be saved to current working directory. The working directory is where etcd database is saved. The working directory is designed for scenarios where a different mounted disk is preferred.
-
-### Plot Graphs
-To generate two images (read and write) based on the benchmark result csv file:
-```sh
-# to generate a pair of read & write images from one data csv file
-./plot_data.py ${FIRST_CSV_FILE} -t ${IMAGE_TITLE} -o ${OUTPUT_IMAGE_NAME}
-
-
-# to generate a pair of read & write images by comparing two data csv files
-./plot_data.py ${FIRST_CSV_FILE} ${SECOND_CSV_FILE} -t ${IMAGE_TITLE} -o ${OUTPUT_IMAGE_NAME}
-```
diff --git a/tools/rw-heatmaps/plot_data.py b/tools/rw-heatmaps/plot_data.py
deleted file mode 100755
index 217eb6f8a8b1..000000000000
--- a/tools/rw-heatmaps/plot_data.py
+++ /dev/null
@@ -1,281 +0,0 @@
-#!/usr/bin/env python3
-import sys
-import os
-import argparse
-import logging
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import matplotlib.colors as colors
-
-logging.basicConfig(format='[%(levelname)s %(asctime)s %(name)s] %(message)s')
-logger = logging.getLogger(__name__)
-logger.setLevel(logging.INFO)
-
-params = None
-
-
-def parse_args():
-    parser = argparse.ArgumentParser(
-        description='plot graph using mixed read/write result file.')
-    parser.add_argument('input_file_a', type=str,
-                        help='first input data files in csv format. (required)')
-    parser.add_argument('input_file_b', type=str, nargs='?',
-                        help='second input data files in csv format. (optional)')
-    parser.add_argument('-t', '--title', dest='title', type=str, required=True,
-                        help='plot graph title string')
-    parser.add_argument('-z', '--zero-centered', dest='zero', action='store_true', required=False,
-                        help='plot the improvement graph with white color represents 0.0',
-                        default=True)
-    parser.add_argument('--no-zero-centered', dest='zero', action='store_false', required=False,
-                        help='plot the improvement graph without white color represents 0.0')
-    parser.add_argument('-o', '--output-image-file', dest='output', type=str, required=True,
-                        help='output image filename')
-    parser.add_argument('-F', '--output-format', dest='format', type=str, default='png',
-                        help='output image file format. default: jpg')
-    return parser.parse_args()
-
-
-def load_data_files(*args):
-    df_list = []
-    try:
-        for i in args:
-            if i is not None:
-                logger.debug('loading csv file {}'.format(i))
-                df_list.append(pd.read_csv(i))
-    except FileNotFoundError as e:
-        logger.error(str(e))
-        sys.exit(1)
-    res = []
-    try:
-        for df in df_list:
-            param_df = df[df['type'] == 'PARAM']
-            param_str = ''
-            if len(param_df) != 0:
-                param_str = param_df['comment'].iloc[0]
-            new_df = df[df['type'] == 'DATA'][[
-                'ratio', 'conn_size', 'value_size']].copy()
-            cols = [x for x in df.columns if x.find('iter') != -1]
-            tmp = [df[df['type'] == 'DATA'][x].str.split(':') for x in cols]
-
-            read_df = [x.apply(lambda x: float(x[0])) for x in tmp]
-            read_avg = sum(read_df) / len(read_df)
-            new_df['read'] = read_avg
-
-            write_df = [x.apply(lambda x: float(x[1])) for x in tmp]
-            write_avg = sum(write_df) / len(write_df)
-            new_df['write'] = write_avg
-
-            new_df['ratio'] = new_df['ratio'].astype(float)
-            new_df['conn_size'] = new_df['conn_size'].astype(int)
-            new_df['value_size'] = new_df['value_size'].astype(int)
-            res.append({
-                'dataframe': new_df,
-                'param': param_str
-            })
-    except Exception as e:
-        logger.error(str(e))
-        sys.exit(1)
-    return res
-
-
-# This is copied directly from matplotlib source code. Some early versions of matplotlib
-# do not have CenteredNorm class
-class CenteredNorm(colors.Normalize):
-
-    def __init__(self, vcenter=0, halfrange=None, clip=False):
-        """
-        Normalize symmetrical data around a center (0 by default).
-
-        Unlike `TwoSlopeNorm`, `CenteredNorm` applies an equal rate of change
-        around the center.
-
-        Useful when mapping symmetrical data around a conceptual center
-        e.g., data that range from -2 to 4, with 0 as the midpoint, and
-        with equal rates of change around that midpoint.
-
-        Parameters
-        ----------
-        vcenter : float, default: 0
-            The data value that defines ``0.5`` in the normalization.
-        halfrange : float, optional
-            The range of data values that defines a range of ``0.5`` in the
-            normalization, so that *vcenter* - *halfrange* is ``0.0`` and
-            *vcenter* + *halfrange* is ``1.0`` in the normalization.
-            Defaults to the largest absolute difference to *vcenter* for
-            the values in the dataset.
-
-        Examples
-        --------
-        This maps data values -2 to 0.25, 0 to 0.5, and 4 to 1.0
-        (assuming equal rates of change above and below 0.0):
-
-            >>> import matplotlib.colors as mcolors
-            >>> norm = mcolors.CenteredNorm(halfrange=4.0)
-            >>> data = [-2., 0., 4.]
-            >>> norm(data)
-            array([0.25, 0.5 , 1.  ])
-        """
-        self._vcenter = vcenter
-        self.vmin = None
-        self.vmax = None
-        # calling the halfrange setter to set vmin and vmax
-        self.halfrange = halfrange
-        self.clip = clip
-
-    def _set_vmin_vmax(self):
-        """
-        Set *vmin* and *vmax* based on *vcenter* and *halfrange*.
-        """
-        self.vmax = self._vcenter + self._halfrange
-        self.vmin = self._vcenter - self._halfrange
-
-    def autoscale(self, A):
-        """
-        Set *halfrange* to ``max(abs(A-vcenter))``, then set *vmin* and *vmax*.
-        """
-        A = np.asanyarray(A)
-        self._halfrange = max(self._vcenter-A.min(),
-                              A.max()-self._vcenter)
-        self._set_vmin_vmax()
-
-    def autoscale_None(self, A):
-        """Set *vmin* and *vmax*."""
-        A = np.asanyarray(A)
-        if self._halfrange is None and A.size:
-            self.autoscale(A)
-
-    @property
-    def vcenter(self):
-        return self._vcenter
-
-    @vcenter.setter
-    def vcenter(self, vcenter):
-        self._vcenter = vcenter
-        if self.vmax is not None:
-            # recompute halfrange assuming vmin and vmax represent
-            # min and max of data
-            self._halfrange = max(self._vcenter-self.vmin,
-                                  self.vmax-self._vcenter)
-            self._set_vmin_vmax()
-
-    @property
-    def halfrange(self):
-        return self._halfrange
-
-    @halfrange.setter
-    def halfrange(self, halfrange):
-        if halfrange is None:
-            self._halfrange = None
-            self.vmin = None
-            self.vmax = None
-        else:
-            self._halfrange = abs(halfrange)
-
-    def __call__(self, value, clip=None):
-        if self._halfrange is not None:
-            # enforce symmetry, reset vmin and vmax
-            self._set_vmin_vmax()
-        return super().__call__(value, clip=clip)
-
-
-# plot type is the type of the data to plot. Either 'read' or 'write'
-def plot_data(title, plot_type, cmap_name_default, *args):
-    if len(args) == 1:
-        fig_size = (12, 16)
-        df0 = args[0]['dataframe']
-        df0param = args[0]['param']
-        fig = plt.figure(figsize=fig_size)
-        count = 0
-        for val, df in df0.groupby('ratio'):
-            count += 1
-            plt.subplot(4, 2, count)
-            plt.tripcolor(df['conn_size'], df['value_size'], df[plot_type])
-            plt.title('R/W Ratio {:.4f} [{:.2f}, {:.2f}]'.format(val, df[plot_type].min(),
-                                                                 df[plot_type].max()))
-            plt.yscale('log', base=2)
-            plt.ylabel('Value Size')
-            plt.xscale('log', base=2)
-            plt.xlabel('Connections Amount')
-            plt.colorbar()
-            plt.tight_layout()
-        fig.suptitle('{} [{}]\n{}'.format(title, plot_type.upper(), df0param))
-    elif len(args) == 2:
-        fig_size = (12, 26)
-        df0 = args[0]['dataframe']
-        df0param = args[0]['param']
-        df1 = args[1]['dataframe']
-        df1param = args[1]['param']
-        fig = plt.figure(figsize=fig_size)
-        col = 0
-        delta_df = df1.copy()
-        delta_df[[plot_type]] = ((df1[[plot_type]] - df0[[plot_type]]) /
-                                 df0[[plot_type]]) * 100
-        for tmp in [df0, df1, delta_df]:
-            row = 0
-            for val, df in tmp.groupby('ratio'):
-                pos = row * 3 + col + 1
-                plt.subplot(8, 3, pos)
-                norm = None
-                if col == 2:
-                    cmap_name = 'bwr'
-                    if params.zero:
-                        norm = CenteredNorm()
-                else:
-                    cmap_name = cmap_name_default
-                plt.tripcolor(df['conn_size'], df['value_size'], df[plot_type],
-                              norm=norm,
-                              cmap=plt.get_cmap(cmap_name))
-                if row == 0:
-                    if col == 0:
-                        plt.title('{}\nR/W Ratio {:.4f} [{:.1f}, {:.1f}]'.format(
-                            os.path.basename(params.input_file_a),
-                            val, df[plot_type].min(), df[plot_type].max()))
-                    elif col == 1:
-                        plt.title('{}\nR/W Ratio {:.4f} [{:.1f}, {:.1f}]'.format(
-                            os.path.basename(params.input_file_b),
-                            val, df[plot_type].min(), df[plot_type].max()))
-                    elif col == 2:
-                        plt.title('Gain\nR/W Ratio {:.4f} [{:.2f}%, {:.2f}%]'.format(val, df[plot_type].min(),
-                                                                                     df[plot_type].max()))
-                else:
-                    if col == 2:
-                        plt.title('R/W Ratio {:.4f} [{:.2f}%, {:.2f}%]'.format(val, df[plot_type].min(),
-                                                                               df[plot_type].max()))
-                    else:
-                        plt.title('R/W Ratio {:.4f} [{:.1f}, {:.1f}]'.format(val, df[plot_type].min(),
-                                                                             df[plot_type].max()))
-                plt.yscale('log', base=2)
-                plt.ylabel('Value Size')
-                plt.xscale('log', base=2)
-                plt.xlabel('Connections Amount')
-
-                if col == 2:
-                    plt.colorbar(format='%.2f%%')
-                else:
-                    plt.colorbar()
-                plt.tight_layout()
-                row += 1
-            col += 1
-        fig.suptitle('{} [{}]\n{}    {}\n{}    {}'.format(
-            title, plot_type.upper(), os.path.basename(params.input_file_a), df0param,
-            os.path.basename(params.input_file_b), df1param))
-    else:
-        raise Exception('invalid plot input data')
-    fig.subplots_adjust(top=0.93)
-    plt.savefig("{}_{}.{}".format(params.output, plot_type,
-                params.format), format=params.format)
-
-
-def main():
-    global params
-    logging.basicConfig()
-    params = parse_args()
-    result = load_data_files(params.input_file_a, params.input_file_b)
-    for i in [('read', 'viridis'), ('write', 'plasma')]:
-        plot_type, cmap_name = i
-        plot_data(params.title, plot_type, cmap_name, *result)
-
-
-if __name__ == '__main__':
-    main()