{"id":213778,"date":"2021-02-15T17:17:38","date_gmt":"2021-02-15T16:17:38","guid":{"rendered":"https:\/\/www.interviewns.de\/?p=213778"},"modified":"2024-09-18T16:50:33","modified_gmt":"2024-09-18T14:50:33","slug":"multiside-traces-auto-correlations","status":"publish","type":"post","link":"https:\/\/www.interviewns.de\/en_us\/multiside-traces-auto-correlations\/","title":{"rendered":"Multiside traces  \/ auto-correlations"},"content":{"rendered":"\n[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_row _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_text _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;0px|||||&#8221; hover_enabled=&#8221;0&#8243;]<p><strong>IT Performance analysis is always a comparison task<\/strong> &#8211; usually between at least 2 states &#8211; an estimated, or precalculated or guesses, or before or somewhere else experienced or simply expcted <strong>&#8220;good&#8221; state<\/strong> &#8211; and the experience of a <strong>bad state<\/strong>.\u00a0<\/p>\n<p>comparisons can cover a multitude of scenarios like\u00a0<\/p>\n<ul>\n<li>yesterday good &#8211; today bad\u00a0<\/li>\n<li>my &#8220;guessed and understanding of &#8220;should be&#8221; vers. experienced bad\u00a0<\/li>\n<li>location A vers. location B\u00a0<\/li>\n<li>Application A vers. App B\u00a0<\/li>\n<li>user A vers. user B<\/li>\n<\/ul>\n<p>one of the most reliable ways to understand performance is analysis of packet data.\u00a0<\/p>\n<p><span>It is like a blood test \u2013 compared to ask the patient or measuring temperature. <\/span><\/p>\n<p><strong>Traces cannot lie \u2013 because they just provide measured and non-interpreted, unchanged data. <\/strong><\/p>\n<p>in this scenario is an approach described to use pcap data from 2 sides to easy and fast troubleshooting Performance issues of IT -services<\/p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_text _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;]<p><span>In each IT environment at least 3 areas are responsible for performance:<\/span><\/p>\n<ul>\n<li>The client Side<\/li>\n<li>The network<\/li>\n<li>The application\/server side (which can of course be very complex)<\/li>\n<\/ul>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_image src=&#8221;https:\/\/www.interviewns.de\/wp-content\/uploads\/2021\/02\/C_S.png&#8221; title_text=&#8221;C_S&#8221; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][\/et_pb_image][et_pb_text _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221; hover_enabled=&#8221;0&#8243; text_line_height=&#8221;1.6em&#8221;]<p><span>For a client the time between request and reply determines the external performance. <\/span>ngs.<\/p>\n[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_text _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221; hover_enabled=&#8221;0&#8243; header_font=&#8221;Poppins|700|||||||&#8221;]<h1><span>Performance issues<\/span><\/h1>\n<p><span>A client establishes a session to a server \u2013 and all data of this session should be in sync, like \u00a0<\/span><span>the number of sent client packets = number off received server-side packets <\/span><\/p>\n<ul>\n<li><span>Under <strong>optimal conditions<\/strong> &#8211; network time would not change \u2013 and performance is predictable. <\/span><\/li>\n<li><span>Under <strong>\u201cnormal\u201d conditions<\/strong> \u2013 network performance does change &#8211; and service performance changes.<\/span><\/li>\n<\/ul>\n<p><span>Latency can rise \u2013 by delays on components, by rerouting \u2013 from Berlin to Munich via NYC \u2013 packets are not received and acked &#8211; so retransmissions triggerd by sequencing or timeout may occur. <\/span><\/p>\n<p><span>And the service responsetime depends on server-resources, application design, architecture, backend and a high variety on components.<\/span><\/p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;71px|||||&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_text _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;]<h1><strong>If performance issues occur <\/strong><\/h1>\n<p><strong><span>Which side is causing the performance issues experienced by clients<\/span><\/strong><\/p>\n<ul>\n<li>If clients can rule out local error &#8211; it should be caused by <strong>network or server<\/strong><\/li>\n<li>If server receives a request and processes it instantly and fast \u2013 the cause is at <strong>client \u2013 or network<\/strong><\/li>\n<li>if the network can guaranty fast and error free end2end throughput \u2013 the cause must be <strong>client or server<\/strong><\/li>\n<\/ul>\n<p><span>\u00a0<\/span><span style=\"font-size: 26px;\">This happens often &#8211; that all sides declare their innocence based on their available information &#8211; but the problems persist!<\/span><\/p>\n<p><strong style=\"font-size: 26px;\">To resolve issues \u2013 people need to understand fast and precise \u2013 which side is responsible <\/strong><span style=\"font-size: 26px;\">This is not blaming game \u2013 if it is done with the right methods.<\/span><\/p>[\/et_pb_text][et_pb_text _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;80px||0px|||&#8221; hover_enabled=&#8221;0&#8243; header_font=&#8221;Poppins|700|||||||&#8221;]<h1><span>Method of analysis using packet capture <\/span><\/h1>\n<p><span>One of most precise methods for such situation is packet capture &amp; analytics. <\/span><\/p>\n<p><span>It is like a blood test \u2013 compared to ask the patient or measuring temperature. <\/span><\/p>\n<p><span>Traces cannot lie \u2013 because they just provide measured and non-interpreted, unchanged data. <\/span><\/p>\n<h2><span>\u00a0<\/span><\/h2>\n<h2><strong>Typical questions to clarify<\/strong><\/h2>\n<ul>\n<li>A client sends a request \u2013 was it received at the server?<\/li>\n<li>was it correct received?<\/li>\n<li>What is the delay between send and receive?<\/li>\n<li>A client sends request retransmission \u2013 why was retransmitted?<\/li>\n<li>was first request NOT received by server ? did he replied and reply was not received at client ?<\/li>\n<li>where both request received at the sever ?<\/li>\n<li>If packet loss occurs \u2013 where does it happen ?<\/li>\n<li>Are there any differences between send \u2013 and receive order?<\/li>\n<li>client request \u2013 received out-of-order ?<\/li>\n<li>Is TTL constant at the receiver side?<\/li>\n<\/ul>\n<p><span>These are very essential questions &#8211; and answers of those can point to the cause of delay<\/span><\/p>\n<p><span>But \u2013 using single trace file tools \u2013 this sounds like a huge manual work \u2013 comparing packets by packets in wireshark. \u00a0<\/span><\/p>\n<h1><span style=\"font-size: 14px; color: #666666;\">.<\/span><\/h1>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_text _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221; hover_enabled=&#8221;0&#8243;]<h1><strong>Automization by multiside traces \/ Auto-Correlation (MTAC)<\/strong><\/h1>\n<p><span>\u2026 a feature developed for SharkMon &#8211; \u00a0our solution for analyszing large number of pcap files with wireshark metrics to provide an ongoing monitoring.<\/span><\/p>\n<p><em><span>SharkMon enables users to define packet analysis scenarios for 1000s of trace files \u2013 providing a constant monitoring \u2013 and to correlate and compare both sides based on free definable metrics of packet content by using same variety and syntax as wireshark. \u00a0<\/span><\/em><\/p>\n<p><span>\u00a0<\/span><\/p>\n<p><span>If traces\/pcap files of sender (client-PC) and receiver (server-side tcpdump, datacenter capture probe) exist for same time \u2013 they can be synchronized and issues of data integrity, packet loss, timing, route changes, application performance etc. easily identified. <\/span><\/p>\n<p>&nbsp;<\/p>\n<h2><strong>Process<\/strong><\/h2>\n<p><strong><span>First check:<\/span><\/strong><span> measure service time to identify issues. <\/span><\/p>\n<p><span>This should be done on client side to understand clear the difference: how fast is the reply received on the client \u2013 and on the providing site\/server sametime. <\/span><\/p>\n<p><span>\u00a0<\/span><\/p>\n<p><span>The picture below shows the results from 2 side locations : <\/span><\/p>\n<ul>\n<li>Client side \u2013 the green line<\/li>\n<li>Server-side \u2013 the red line<\/li>\n<\/ul>\n<p><span>The gap between both lines is the network time <\/span><\/p>\n<p><span>\u00a0<\/span><\/p>\n<p><span>You can identify a spike on both lines at 1:10pm, which makes clear \u2013 that this is a server \/ backend issue &#8211; because the responsetime measured directly on the server via tcpdump shows the same outage \u2013 <strong>this is local server performance<\/strong>. <\/span><\/p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_image src=&#8221;https:\/\/www.interviewns.de\/wp-content\/uploads\/2021\/02\/MTAC1.png&#8221; title_text=&#8221;MTAC1&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_text _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;]<p><span>But people still want to understand the variance of network effects here.<\/span><\/p>\n<p><span>The following picture shows the variation of network performance on 2 sides: <\/span><\/p>\n<ul>\n<li>TTL \u2013 for measuring the number of routing hops end2end, a variation would point to rerouting and latency<\/li>\n<li>iRTT \u2013 for the average latency based on 3way handshake<\/li>\n<li>RTO \u2013 the time for retransmission effects<\/li>\n<\/ul>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_image src=&#8221;https:\/\/www.interviewns.de\/wp-content\/uploads\/2021\/02\/MATC2.png&#8221; title_text=&#8221;MATC2&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221;][et_pb_text _builder_version=&#8221;4.5.1&#8243; _module_preset=&#8221;default&#8221; hover_enabled=&#8221;0&#8243;]<p><span>The results here are clear <\/span><\/p>\n<ul>\n<li>TTL did not change \u2013 the route between both side is constant<\/li>\n<li>iRTT is on both side constant \u2013 no much variation in latency<\/li>\n<li>iRTO is at client side constant and higher than on server side \u2013 the experienced networking issue will be not on the server-side.<\/li>\n<\/ul>\n<h1><strong>Summary <\/strong><\/h1>\n<p><span>Using 2-side trace-correlation \u2013 client \/ Service effects are identified fast \u2013 and precise. <\/span><\/p>\n<p><span>Finger-pointing is clearly avoided \u2013 Downtime reduced.<\/span><\/p>\n<p><span>\u00a0<\/span><\/p>\n<p><span>It can show clear if the incident was caused on the transfer network or at the server-side \u00a0infrastructure.<\/span><\/p>\n<p><span>In case of network issues \u2013 it can clear identify the real important parameters. <\/span><\/p>\n<p><span>\u00a0<\/span><\/p>\n<h2><strong>SharkMon by interview network solutions<\/strong><\/h2>\n<p><span>SharkMon can collect packet data from multiple locations and entities: <\/span><\/p>\n<ul>\n<li>direct on the service using tcpdump\/tshark<\/li>\n<li>large capture probesy <span><\/span>via API <span>\u00a0<\/span><\/li>\n<li>manually upload of tracefiles<\/li>\n<\/ul>\n<p><span>\u00a0<\/span><\/p>\n<p><span>User can import 1000ds of tracefiles for a providing a constant monitoring history.<\/span><\/p>\n<p><span>Tracefiles are organized in scenarios which can be easily correlated \u2013 such allowing analysis <strong>scenarios<\/strong> like <\/span><\/p>\n<ul>\n<li><strong>Client<\/strong>\u00a0vers.\u00a0<strong>Server <\/strong><\/li>\n<li><strong>location A<\/strong>\u00a0ves. other <strong>location B<\/strong><\/li>\n<li><strong>User A<\/strong>\u00a0vers.\u00a0<strong>User B<\/strong><\/li>\n<li><strong>Application A<\/strong>\u00a0vers.\u00a0<strong>Application B <\/strong><\/li>\n<li><strong>Leaving country A<\/strong>\u00a0very.\u00a0<strong>entering country B<\/strong> (geo-political scenario)<\/li>\n<\/ul>\n<p><span>\u00a0<\/span><\/p>\n<p><span>It can use any metric which can be found in wireshark for monitoring &#8211; allowing deepest monitoring ability in the industry.<\/span><\/p>\n<p><span>\u00a0<\/span><\/p>\n<p><span>This allows usage in networking environments \u00a0as <\/span><\/p>\n<ul>\n<li>WAN \/ Network<\/li>\n<li>datacenter<\/li>\n<li>Cloud \u2013 IaaS\/PaaS<\/li>\n<li>WLAN<\/li>\n<li>VPN<\/li>\n<li>Industry \/ industrial ethernet<\/li>\n<li>User endpoints<\/li>\n<\/ul>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]\n","protected":false},"excerpt":{"rendered":"<p>IT Performance analysis is always a comparison task &#8211; usually between at least 2 states &#8211; an estimated, or precalculated or guesses, or before or somewhere else experienced or simply expcted &#8220;good&#8221; state &#8211; and the experience of a bad state.\u00a0 comparisons can cover a multitude of scenarios like\u00a0 yesterday good &#8211; today bad\u00a0 my [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":213789,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","content-type":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[31],"tags":[33,32,34],"class_list":["post-213778","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sharkmon-deep-packet-monitoring","tag-network-packet-monitoring","tag-sharkmon","tag-wireshark-monitoring"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Multiside traces \/ auto-correlations - Interview Network Solutions<\/title>\n<meta name=\"robots\" content=\"index, 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