From e38eafe0520d46ece17b047e80aa77abc6ecf5df Mon Sep 17 00:00:00 2001 From: Colleen McGinnis Date: Fri, 30 Aug 2024 11:51:31 -0500 Subject: [PATCH] [apm] Add examples using `trace_continuation_strategy` to sampling docs (#4167) * first attempt * update diagrams * reframe, restructure * address feedback * add titles to images, reference in text (cherry picked from commit 363af381dc2de59051fcf4af78937c8f47bf202a) --- ...sampling-continuation-strategy-restart.png | Bin 0 -> 142787 bytes ...continuation-strategy-restart_external.png | Bin 0 -> 138720 bytes .../apm/images/dt-sampling-example-1.png | Bin 83070 -> 91712 bytes .../apm/images/dt-sampling-example-2.png | Bin 82942 -> 96382 bytes .../apm/images/dt-sampling-example-3.png | Bin 87071 -> 102403 bytes docs/en/observability/apm/sampling.asciidoc | 71 +++++++++++++++--- 6 files changed, 60 insertions(+), 11 deletions(-) create mode 100644 docs/en/observability/apm/images/dt-sampling-continuation-strategy-restart.png create mode 100644 docs/en/observability/apm/images/dt-sampling-continuation-strategy-restart_external.png diff --git a/docs/en/observability/apm/images/dt-sampling-continuation-strategy-restart.png b/docs/en/observability/apm/images/dt-sampling-continuation-strategy-restart.png new file mode 100644 index 0000000000000000000000000000000000000000..e68e43caf7ccbb7d53e2e39a0f3cf32db75db7db GIT binary patch literal 142787 zcmeFZWl&sA*ER|S0tpEkJV?;s!2^Q@cL-!~3k>e=?k))yEVx5(XK;6S65QPe{Wf{t z_tg3IJ@>y;r|Pbnsy)@UrMuVaUTarB8qTu&wJtE5ROrv z11&rn$Lzob-cC_m2(EPa?G79q8JwiZr!UUh`>8Jyl{PLON9y~2g?QJkh6c;{Hnvjc zkNQX|>?vx@OcUQKnU#R|6cZYLI+RVTYj7==lr&B$QxPPFO0foiDWPQZRo@Fl&FuZL zp7!`?*c-jET+e04#@5%o!YiMiCpX-fGQ!nj`Co*BIe{dU0T__wPt4aXT@IQI2Aek`Qzc2l-Gw}cYoPLoZbGwLeqA4s+6A|)! zM=&s$jKKU))CR>q!8_Q!t1~PZg6Z=8mimB&dU>hgbYKp*ciCkt)pKClrIdX2ELfsI zBu@ePAH8uM8zUpU-TvNtFp<7HYU?{OPYqH<0$xp5Qhu8pjRG#BAl!fdF<=GD&lm9< zk15X##tUAa5*@H5Zg4sBcvt+Bl|!aL?L$v}0QNFSGT<3%WQ=aUJF0n(OZRc>v&e&- z3>PH-5u|iEZ{y+w3b6f0FZ^Ki=eC2l$`OyeB{&4FpN2e?)$)`C1RW!mTEgw!WRh8y z?xfk`xVg)2-bLR5hWY%zj}e%M2J++6_8PAbV^<&xk;9a#+N1MBg}oYJ!0qcrGEMTO zpOwFd+#ZzM6@yX*2{7Q`|NCz{w3Xhfh3E}9wYE)6o%&!Sd7RkP5wQYChWF#lHip6W zZ@$Y}Qv)X+AJ%^~@=+Y0nPu3@@n8d3XJd{bwMyk)c`0Ms!pHouowLvC_)*7y`k%dor!r;F;w@c+rp zI@rL?Gnj(6|3re#Qg8@rWvgQP|Kw&5S>R?JakvA&e7G8UAT{&Ix_WBp{e9%;Yh*xuoS@O*86Z!ej~?h#v%$UA#y6Ft*hY5=q_S znN7>S0)NatI&br!%+h$n#`uLNe=8sqX%q9sfcZm$@5tHX2}V?i2~F#e5Srx#{af^M zMMbK5h3$2ql1G=@XBsmokSM-OIp`5DsSXwS7E9&$UW}+8AkQgLK}w3jnLH%mpJKkF&@J)kft9O^mvGZ=sR&6O}uOUB7F(rg3TK!3l z6a)p|^WO)Xd{Tgiuf=M;+n(<2u)_H8&KrhFyJ`!JRx1t8niMe{_>zcaT}o?Vf>R_L zc3N2jFZyqOlygq_ccJJ%&Ml*Op$-AS{PwA_C2n&y6Mw8i2Hs7Cn0Ouf4IN!aji_0a z`O{C^rx}f;GDU!=dHPgmemf04(4?M$NQ7a{3=H)!qIrQ&=l)cVEf|Ma$H9%f)eB>r z4Z*gnRWgkJ;cof_VUAB8I{PzUs*O8N=-df?>~-d3v)w6r9>Y;(V&+#2I3H~)>y-(+ z!15pSRKoU{*u-CE>x>r9JCc{Tr_eH3Ft&w(G2LSD|9I|0N8t@C??>=GJf{Ud?GZ{E z;U@^j1ZElhN6_ddv9%$=$-MVh?Qa+zI)VH$qn8A)t{eG?n8%_pJFvz4#z#nsqcr2s zJ~xt&DOOeZ9WM^ig!YBe-~8=nv;1&FLa^K+CGF|mImM+wC(Dax;!k!$^!GB2;k{pC zOS;PS@J^6Cs97T}0|RA}4Cn&~KD#{uqN@)eU~TVk>cStupF%Wr9%KX$F}O4R^bGM1 zu#oP>;@B0I&DI&%VB7ih(Ag&L9Bm1(C)RX6ld(mT%5S#6I-#YUTZ*Qy@aT}at>&nN zxTI^wemLm_B+--dgZ&s4QLvTJ=Qb@IF#w{SSFJE`PLV5Hu1u&*rf`dR*mb9R`^g`f zZ1fo*noGDZU(}RDw zPc1h6-2{4i_wW$DGqC?FpuvZuZ;bkuOrVfGrs96SeufZ7;eC=}%kWw008{W`Mtg8n zA7h&l0iV=0jD5a9454W2P!kyXN}4=apKFW;7&kJO>eUe`jx&e#cq7h~6InF(2b14e zKrc8DRDY|kA<`RR2|j?>N{?S6(tUzk6Q+8f8L3X?eOETso3TPRdWQIc|D0F9N}(CB zG+-<9Q8o-~9>AP&QiPL!;Dpcoi1INJt{WK{8Lu=6cu_LBFFZbY-@i4kw&fe0b_?&MiFwcs0Mcx3F>>)*eBw{s{V^m-|Ye1L}j#AiaRe_hEWk<*s!}z++tEq%D4eD}XIC{3hVpI*S;*O7>e9n1Z)&HR}we z;9ypvD9_1$s{<{XM6Msvd|q)s1wwx>4L}dxu>i_`^Aw^aua~#hzQE}E)Y=A&^5e%k z>!I&(rz>wTUkSEW11)u&=hkl#2yCBx$-fuiVPxRp!oLsyX+>E1XT1le3mAmAVBlL| zG33)BVDy>?K0|d+hWq>$@vRKpnxCH^>Ws__vPW6WHaJ90X`sbS7`^A+f4=sgkN&3{ zKMPR=$tnrZ7>+FvL~JmuKLGlHhQ_4H1_+Ex6!95`H6zec`kL=;(0{)6pO5~}Bo>mx z`3xF<{Ppjk|CRK=>izGU{{R0*wgP8;yL7n#`Q7RRqKzdG3Ei47D1v>tchC=1 z0v^pz2)&O&i5gKvT*is4ke={N^9%^DPO)a=?i%`v=f>Vka&a(NMt6U0-6U*`br3YlW`9(9(;KK2vs1@poc32e2dx{cS2Sx6 zVdddA)igGS^8Ao(*LVZFGh`*{Z&qsuCu# zn0mU2tg85Q3k`f&Hc`G=X>VePQtjt2^2OO}q3#0Q%r}lh+>p_)I>HmVo%VF)ww%~F zC8Qx$Mkti-DpDI734`eu0(sXKUFhNH%J18{3!Y+I56F?5IU3*H`9M4mtNq%iswv!# zUg$*4o3thn%yGV3k(-7v1clghUiN$_6pVDJ<=p+1-C~?X&VJ5@{}W&<6>A^7=Ujv) z-babU_^^rfaK2s!mG*DZAmy~xzqbgDz?WJa(fT{1O&pSY%*2HB9>IJ|Z}( z{|JgQB-c$LTfO^j+DeD4%0Efmp$GY$>+glh3O0VVUq7wEQ>p!?Kf{xIf(TL28)iEY z7gHYRE#En;HP9#SsBGxsW+u-ROKM%TK{etNluD<~d*l);!kn8PX%C&mz%;eBoFgS1 zUgtL&q$s3$ANU|sc%OG-A!h4@MVHl=5ttSdSYZigcCel)D9XyCM;;e38!9`>

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0f43627743..33172f4dc9 100644 --- a/docs/en/observability/apm/sampling.asciidoc +++ b/docs/en/observability/apm/sampling.asciidoc @@ -29,23 +29,69 @@ data might be discarded purely due to chance. See <> to get started. -**Distributed tracing with head-based sampling** +[float] +[[distributed-tracing-examples]] +===== Distributed tracing In a distributed trace, the sampling decision is still made when the trace is initiated. Each subsequent service respects the initial service's sampling decision, regardless of its configured sample rate; the result is a sampling percentage that matches the initiating service. -In this example, `Service A` initiates four transactions and has sample rate of `.5` (`50%`). -The sample rates of `Service B` and `Service C` are ignored. +In the example in _Figure 1_, `Service A` initiates four transactions and has sample rate of `.5` (`50%`). +The upstream sampling decision is respected, so even if the sample rate is defined and is a different +value in `Service B` and `Service C`, the sample rate will be `.5` (`50%`) for all services. +.Upstream sampling decision is respected image::./images/dt-sampling-example-1.png[Distributed tracing and head based sampling example one] -In this example, `Service A` initiates four transactions and has a sample rate of `1` (`100%`). -Again, the sample rates of `Service B` and `Service C` are ignored. +In the example in _Figure 2_, `Service A` initiates four transactions and has a sample rate of `1` (`100%`). +Again, the upstream sampling decision is respected, so the sample rate for all services will +be `1` (`100%`). +.Upstream sampling decision is respected image::./images/dt-sampling-example-2.png[Distributed tracing and head based sampling example two] -**OpenTelemetry with head-based sampling** +[float] +===== Trace continuation strategies with distributed tracing + +In addition to setting the sample rate, you can also specify which _trace continuation strategy_ to use. +There are three trace continuation strategies: `continue`, `restart`, and `restart_external`. + +The *`continue`* trace continuation strategy is the default and will behave similar to the examples in +the <>. + +Use the *`restart_external`* trace continuation strategy on an Elastic-monitored service to start +a new trace if the previous service did not have a `traceparent` header with `es` vendor data. +This can be helpful if a transaction includes an Elastic-monitored service that is receiving requests +from an unmonitored service. + +In the example in _Figure 3_, `Service A` is an Elastic-monitored service that initiates four transactions +with a sample rate of `.25` (`25%`). Because `Service B` is unmonitored, the traces started in +`Service A` will end there. `Service C` is an Elastic-monitored service that initiates four transactions +that start new traces with a new sample rate of `.5` (`50%`). Because `Service D` is also +Elastic-monitored service, the upstream sampling decision defined in `Service C` is respected. +The end result will be three sampled traces. + +.Using the `restart_external` trace continuation strategy +image::./images/dt-sampling-continuation-strategy-restart_external.png[Distributed tracing and head based sampling with restart_external continuation strategy] + +Use the *`restart`* trace continuation strategy on an Elastic-monitored service to start +a new trace regardless of whether the previous service had a `traceparent` header. +This can be helpful if an Elastic-monitored service is publicly exposed, and you do not +want tracing data to possibly be spoofed by user requests. + +In the example in _Figure 4_, `Service A` and `Service B` are Elastic-monitored services that use the +default trace continuation strategy. `Service A` has a sample rate of `.25` (`25%`), and that +sampling decision is respected in `Service B`. `Service C` is an Elastic-monitored service that +uses the `restart` trace continuation strategy and has a sample rate of `1` (`100%`). +Because it uses `restart`, the upstream sample rate is _not_ respected in `Service C` and all four +traces will be sampled as new traces in `Service C`. The end result will be five sampled traces. + +.Using the `restart` trace continuation strategy +image::./images/dt-sampling-continuation-strategy-restart.png[Distributed tracing and head based sampling with restart continuation strategy] + +[float] +===== OpenTelemetry Head-based sampling is implemented directly in the APM agents and SDKs. The sample rate must be propagated between services and the managed intake service in order to produce accurate metrics. @@ -54,13 +100,16 @@ OpenTelemetry offers multiple samplers. However, most samplers do not propagate This results in inaccurate span-based metrics, like APM throughput, latency, and error metrics. For accurate span-based metrics when using head-based sampling with OpenTelemetry, you must use -a [consistent probability sampler](https://opentelemetry.io/docs/specs/otel/trace/tracestate-probability-sampling/). +a https://opentelemetry.io/docs/specs/otel/trace/tracestate-probability-sampling/[consistent probability sampler]. These samplers propagate the sample rate between services and the managed intake service, resulting in accurate metrics. -NOTE: OpenTelemetry does not offer consistent probability samplers in all languages. +[NOTE] +==== +OpenTelemetry does not offer consistent probability samplers in all languages. OpenTelemetry users should consider using tail-based sampling instead. -+ + Refer to the documentation of your favorite OpenTelemetry agent or SDK for more information on the availability of consistent probability samplers. +==== [float] [[apm-tail-based-sampling]] @@ -99,7 +148,7 @@ and will work with traces sent by either Elastic APM agents or OpenTelemetry SDK Due to <> when using https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/processor/tailsamplingprocessor[tailsamplingprocessor], we recommend using APM Server tail-based sampling instead. [float] -=== Sampled data and visualizations +==== Sampled data and visualizations A sampled trace retains all data associated with it. A non-sampled trace drops all <> and <> data^1^. @@ -125,7 +174,7 @@ The {kib} apps that utilize RUM data depend on transaction events, so non-sampled RUM traces retain transaction data -- only span data is dropped. [float] -=== Sample rates +==== Sample rates What's the best sampling rate? Unfortunately, there isn't one. Sampling is dependent on your data, the throughput of your application, data retention policies, and other factors.