相关：在ELK中合并日志和查询 https://stackoverflow.com/questions/28429607/combine-logs-and-query-in-elk
我们正在设置 ELK，并希望在 Kibana 4 中创建可视化。
这里的问题是我们想要在两种不同类型的消息之间建立关联。
简化一下：
- 消息类型1字段：message_type、common_id_number、byte_count、
...
- 消息类型 2 字段：message_type、common_id_number、主机名、...
两条消息在elasticsearch 中共享相同的索引。
正如您所看到的，我们试图在不考虑 common_id_number 的情况下绘制图表，但似乎我们必须使用它。但我们还不知道怎么做。
有什么帮助吗？
EDIT
这些是ES模板中的相关字段定义：
"URIHost" : {
"type" : "string",
"norms" : {
"enabled" : false
},
"fields" : {
"raw" : {
"type" : "string",
"index" : "not_analyzed",
"ignore_above" : 256
}
}
},
"Type" : {
"type" : "string",
"norms" : {
"enabled" : false
},
"fields" : {
"raw" : {
"type" : "string",
"index" : "not_analyzed",
"ignore_above" : 256
}
}
},
"SessionID" : {
"type" : "long"
},
"Bytes" : {
"type" : "long"
},
"BytesReceived" : {
"type" : "long"
},
"BytesSent" : {
"type" : "long"
},
这是一个TRAFFIC类型，编辑后的文档：
{
"_index": "logstash-2015.11.05",
"_type": "paloalto",
"_id": "AVDZqdBjpQiRid-uxPjE",
"_score": null,
"_source": {
"@version": "1",
"@timestamp": "2015-11-05T21:59:55.543Z",
"syslog_severity_code": 5,
"syslog_facility_code": 1,
"syslog_timestamp": "Nov 5 22:59:58",
"Type": "TRAFFIC",
"SessionID": 21713,
"Bytes": 939,
"BytesSent": 480,
"BytesReceived": 459,
},
"fields": {
"@timestamp": [
1446760795543
]
},
"sort": [
1446760795543
]
}
这是一个威胁类型的文档：
{
"_index": "logstash-2015.11.05",
"_type": "paloalto",
"_id": "AVDZqVNIpQiRid-uxPjC",
"_score": null,
"_source": {
"@version": "1",
"@timestamp": "2015-11-05T21:59:23.440Z",
"syslog_severity_code": 5,
"syslog_facility_code": 1,
"syslog_timestamp": "Nov 5 22:59:26",
"Type": "THREAT",
"SessionID": 21713,
"URIHost": "whatever.nevermind.com",
"URIPath": "/connectiontest.html"
},
"fields": {
"@timestamp": [
1446760763440
]
},
"sort": [
1446760763440
]
}
这是logstash“过滤器”配置：
filter {
if [type] == "paloalto" {
syslog_pri {
remove_field => [ "syslog_facility", "syslog_severity" ]
}
grok {
match => {
"message" => "%{SYSLOGTIMESTAMP:syslog_timestamp} %{HOSTNAME:hostname} %{INT},%{YEAR}/%{MONTHNUM}/%{MONTHDAY} %{TIME},%{INT},%{WORD:Type},%{GREEDYDATA:log}"
}
remove_field => [ "message" ]
}
if [Type] == "THREAT" {
csv {
source => "log"
columns => [ "Threat_OR_ContentType", "ConfigVersion", "GenerateTime", "SourceAddress", "DestinationAddress", "NATSourceIP", "NATDestinationIP", "Rule", "SourceUser", "DestinationUser", "Application", "VirtualSystem", "SourceZone", "DestinationZone", "InboundInterface", "OutboundInterface", "LogAction", "TimeLogged", "SessionID", "RepeatCount", "SourcePort", "DestinationPort", "NATSourcePort", "NATDestinationPort", "Flags", "IPProtocol", "Action", "URL", "Threat_OR_ContentName", "reportid", "Category", "Severity", "Direction", "seqno", "actionflags", "SourceCountry", "DestinationCountry", "cpadding", "contenttype", "pcap_id", "filedigest", "cloud", "url_idx", "user_agent", "filetype", "xff", "referer", "sender", "subject", "recipient" ]
remove_field => [ "log" ]
}
mutate {
convert => {
"SessionID" => "integer"
"SourcePort" => "integer"
"DestinationPort" => "integer"
"NATSourcePort" => "integer"
"NATDestinationPort" => "integer"
}
remove_field => [ "ConfigVersion", "GenerateTime", "VirtualSystem", "InboundInterface", "OutboundInterface", "LogAction", "TimeLogged", "RepeatCount", "Flags", "Action", "reportid", "Severity", "seqno", "actionflags", "cpadding", "pcap_id", "filedigest", "recipient" ]
}
grok {
match => {
"URL" => "%{URIHOST:URIHost}%{URIPATH:URIPath}(%{URIPARAM:URIParam})?"
}
remove_field => [ "URL" ]
}
}
else if [Type] == "TRAFFIC" {
csv {
source => "log"
columns => [ "Threat_OR_ContentType", "ConfigVersion", "GenerateTime", "SourceAddress", "DestinationAddress", "NATSourceIP", "NATDestinationIP", "Rule", "SourceUser", "DestinationUser", "Application", "VirtualSystem", "SourceZone", "DestinationZone", "InboundInterface", "OutboundInterface", "LogAction", "TimeLogged", "SessionID", "RepeatCount", "SourcePort", "DestinationPort", "NATSourcePort", "NATDestinationPort", "Flags", "IPProtocol", "Action", "Bytes", "BytesSent", "BytesReceived", "Packets", "StartTime", "ElapsedTimeInSecs", "Category", "Padding", "seqno", "actionflags", "SourceCountry", "DestinationCountry", "cpadding", "pkts_sent", "pkts_received", "session_end_reason" ]
remove_field => [ "log" ]
}
mutate {
convert => {
"SessionID" => "integer"
"SourcePort" => "integer"
"DestinationPort" => "integer"
"NATSourcePort" => "integer"
"NATDestinationPort" => "integer"
"Bytes" => "integer"
"BytesSent" => "integer"
"BytesReceived" => "integer"
"ElapsedTimeInSecs" => "integer"
}
remove_field => [ "ConfigVersion", "GenerateTime", "VirtualSystem", "InboundInterface", "OutboundInterface", "LogAction", "TimeLogged", "RepeatCount", "Flags", "Action", "Packets", "StartTime", "seqno", "actionflags", "cpadding", "pcap_id", "filedigest", "recipient" ]
}
}
date {
match => [ "syslog_timastamp", "MMM d HH:mm:ss", "MMM dd HH:mm:ss" ]
timezone => "CET"
remove_field => [ "syslog_timestamp" ]
}
}
}
我们试图做的是将 URIHost 项可视化为 X 轴，将字节、BytesSent 和 BytesReceived 总和可视化为 Y 轴。
