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class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-EehZO nRhiJb-fmcmS-oXtfBe"><h1 class="Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-ibL1re"><div class="Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-ibL1re"><span class="FewWi"></span>Using deemed SLIs to measure customer reliability</div></h1></div></div><div class="nRhiJb-fmcmS-oXtfBe dEogG">January 15, 2020</div></div></section><div class="EKklye"><div class="nRhiJb-DARUcf ZWw7T"><div class="npzWPc"><div class="dzoHJ"><div class="nRhiJb-DX2B6 nRhiJb-DX2B6-OWXEXe-h30Snd"><div class="nRhiJb-j5y3u"><ul class="nRhiJb-Qijihe phRaUe" role="list"><li class="hpHPGf"><a class="nRhiJb-ARYxNe" href="https://x.com/intent/tweet?text=Using%20deemed%20SLIs%20to%20measure%20customer%20reliability%20@googlecloud&amp;url=https://cloud.google.com/blog/products/management-tools/using-deemed-slis-to-measure-customer-reliability" track-name="x"track-type="social share"track-metadata-eventdetail="x.com/intent/tweet?text=Using deemed SLIs to measure customer 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See how CRE teams and customers at Google use deemed SLIs%0A%0Acloud.google.com/blog/products/management-tools/using-deemed-slis-to-measure-customer-reliability"track-metadata-module="social icons" target="_blank" rel="noopener"><svg class="nRhiJb-Bz112c nRhiJb-Bz112c-OWXEXe-DX2B6 nRhiJb-Bz112c-OWXEXe-nSuQf" viewBox="0 0 24 24" role="presentation" aria-hidden="true" role="presentation" aria-hidden="true"><path d="M20 4H4c-1.1 0-2 .9-2 2v12c0 1.1.9 2 2 2h16c1.1 0 2-.9 2-2V6c0-1.1-.9-2-2-2zm-.8 2L12 10.8 4.8 6h14.4zM4 18V7.87l8 5.33 8-5.33V18H4z"></path></svg></a></li></ul></div></div></div></div></div><div><section class="nRhiJb-DARUcf"><div class="nRhiJb-DbgRPb-wNfPc-ma6Yeb nRhiJb-DbgRPb-wNfPc-cGMI2b"><section class="DA9Qj nRhiJb-ObfsIf nRhiJb-fmcmS-oXtfBe"><div class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-c5RTEf"></div><div class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-qWD73c"><h5 class="cHE8Ub Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-qWD73c">Adrian Hilton</h5><p class="nRhiJb-qJTHM khCp7b">Customer Reliability Engineer, SRE</p></div></section></div></section><div class="nRhiJb-DARUcf"><div class="nRhiJb-ObfsIf nRhiJb-DbgRPb-wNfPc-ma6Yeb nRhiJb-DbgRPb-qWD73c-cGMI2b"><div class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-ibL1re dzoHJ"></div><div class="OYL9D nRhiJb-kR0ZEf-OWXEXe-GV1x9e-OiUrBf" jsname="tx2NYc"><section class="Wy08Ac nRhiJb-qJTHM-OWXEXe-hJDwNd nRhiJb-DbgRPb-II5mzb-cGMI2b"><div jsaction="rcuQ6b:npT2md" jscontroller="M0Q3Qb" data-is-cws-richtext="true" class=" "><p>Do you own and operate a software service? If so, is your service a ”platform”? In other words, does it run and manage applications of a wide range of users and/or companies? There are both simple and complex types of platforms, all of which serve customers. One example could be Google Cloud, which provides, among other things, relatively low-level infrastructure for starting and running VM images. A higher-level example of a platform might be a blogging service that allows any customer to create and contribute to a blog, design and sell merchandise featuring pithy blog quotes, and allow readers to send tips to the blog author.</p><p>If you do run a platform, it’s going to break sooner or later. Some breakages are large and easy to understand, such as no one being able to reach websites hosted on your platform while your company’s failure is frequently mentioned on social media. However, other kinds of breakage may be less obvious to you—but not to your customers. What if you’ve accidentally dropped all inbound network traffic from Kansas, for example?</p><p>At Google Cloud, we follow SRE principles to ensure reliability for our systems and also customers partnered with the Customer Reliability Engineering (CRE) team. A core SRE operating principle is the use of service-level indicators (SLIs) to detect when your users start having a bad time. In this blog post, we’ll look at how to measure your platform customers’ approximate reliability using approximate SLIs, which we term “deemed SLIs.” We use these to detect low-level outages and drive the operational response.</p><h3>Why use deemed SLIs?</h3><p><a href="https://cloud.google.com/blog/products/gcp/introducing-a-new-era-of-customer-support-google-customer-reliability-engineering">CRE founder</a> Dave Rensin noted in his SRECon 2017 talk, <a href="https://www.usenix.org/conference/srecon17americas/program/presentation/rensin" target="_blank">Reliability When Everything Is A Platform</a>, that as a platform operator, your monitoring doesn’t decide your reliability—your customers do! The best way to get direct visibility into your customers’ reliability experience is to get them to <a href="https://landing.google.com/sre/resources/practicesandprocesses/art-of-slos/" target="_blank">define their own SLIs</a>, and share those signals directly with you. That level of transparency is wonderful, but it requires active and ongoing participation from your customers. What if your customers can’t currently prioritize the time to do this?</p><p>As a platform provider, you might use any number of internal monitoring metrics related to what’s happening with customer traffic. For instance, say you’re providing an API to a storage service:</p><ul><li><p>You may be measuring the total number of queries and number of successful responses as <a href="https://cloud.google.com/blog/products/management-tools/stackdriver-tips-and-tricks-understanding-metrics-and-building-charts">cumulative numeric metrics</a>, grouped by each API function.</p></li><li><p>You may also be recording the 95th percentile response latency with the same grouping, and get a good idea of how your service is doing overall by looking at the ratio of successful queries and the response latency values. If your success ratio suddenly drops from its normal value of 99% to 75%, you likely have many customers experiencing errors. Similarly, if the 95th percentile latency rises from 600ms to 1400ms, your customers are waiting much longer than normal for responses.</p></li></ul><p>The key insight to motivate the use of “deemed SLIs” is that metrics aggregated across all customers will miss edge cases—and your top customers are very likely to depend on those edge cases. Your top customers need to know about outages as soon as, or even before, they happen. Therefore, you most likely want to know when any of your top customers is likely to experience a problem, even if most of your customers are fine. </p><p>Suppose FooCorp, one of your biggest customers, uses your storage service API to store virtual machine images:</p><ul><li>They build and write three different images every 15 minutes.</li><li>The VM images are much larger than most blobs in your service. </li><li>Every time one of their 10,000 virtual machines is restarted, it reads an image from the API. </li><li>Therefore, their traffic rate is one write per five minutes and assuming a daily VM restart, one read per 8.6 seconds. </li><li>Your overall API traffic rate is one write per second and 100 reads per second.</li></ul><p>Let’s say you roll out to your service a change that has a bug, causing very large image reads and writes, which are likely to time out and not complete. You initially don’t see any noticeable effect on your API’s overall success rate and think your platform is running just fine. FooCorp, however, is <i>furious</i>. Wouldn’t you like to know what just happened?</p><h3>Implementation of deemed SLIs</h3><p>The first and foremost step is to see key metrics at the granularity of a single customer. This requires careful assessment and trade-offs. </p><p>For our storage API, assuming we were originally storing two cumulative measures (success, total) and one gauge (latency) at one-minute intervals, we can measure and store three data points per minute with no problem at all. However, if we have 20,000 customers, then storing 60,000 points per minute is a very different problem. Therefore, we need to be careful in the selection of metrics for which we provide the per-customer breakdown. In some cases, it may be sensible to have per-customer breakdowns only for a subset of customers, such as those contracting for a certain level of paid support.</p><p>Next, identify your top customers. “Top” could mean:</p><ul><li><p>invests the most money on your platform;</p></li><li><p>is expected to invest the most money on your platform in the next two years;</p></li><li><p>is strategic from the point of view of partnerships or publicity; or even</p></li><li><p>raises the most support cases and hence causes the greatest operational load on your team.</p></li></ul><p>As we mentioned, customers use your platform in different ways and as a result, have different expectations of it. To find out what your customer might regard as an outage, you need to understand in some depth what their workload really does. In some cases, the customer’s clients might automatically read data from your API every 30 minutes, and update their state if new information is available. However, even if the API is completely broken for an hour, very few customers might actually notice. </p><p>To determine your deemed SLIs, consider applying your understanding of the customer’s workload from the limited selection of metrics per customer.  Think about your observation of the volatility of the metrics over time, and if possible, observation of the metrics during a known customer outage. From this, pick the subset of metrics which you think best represent customer happiness. Identify the normal ranges of those metrics, and aggregate them into a dashboard view for that customer.</p><p>This is why we call these metrics “deemed SLIs”—you deem them to be representative of your particular customer’s happiness, in the absence of better information. </p><p>Some of the metrics you look at for your deemed SLIs of the storage service might include:</p><ul><li><p>Overall API success rate and latency</p></li><li><p>Read and write success rate for large objects (i.e., FooCorp’s main use case)</p></li><li><p>Read latency for objects below a certain size (i.e., excluding large image read bursts so there’s a clear view of API performance for its more common read use case).</p></li></ul><p>The main challenges are:</p><ul><li><p>Lack of technical transparency into the customer’s key considerations. For instance, if you only provide <a href="https://cloud.google.com/load-balancing/docs/tcp/">TCP load balancing</a> to your customer, you can’t observe HTTP response codes. </p></li><li><p>Lack of organizational transparency—you don’t have enough understanding of the customer’s workload to be able to identify what SLIs are meaningful to them.</p></li><li><p>Missing per-customer metrics. You might find that you need to know whether an API call is made internally or externally because the latter is the key representative of availability. However, this distinction isn’t captured in the existing metrics.</p></li></ul><p>It’s important to remember that we don’t expect these metrics to be perfect at first— these metrics are often quite inconsistent with the customer’s experience in the beginning. So how do we fix this? Simple—we iterate.</p><h3>Iteration when choosing deemed SLIs</h3><p>Now sit back and wait for a significant outage of your platform. There’s a good chance that you won’t have to wait too long, particularly if you deploy <a href="https://conferences.oreilly.com/velocity/vl-eu/public/schedule/detail/78800" target="_blank">configuration changes</a> or binary releases often.</p><p>When your outage happens:</p><ul><li>Do an initial impact analysis. Look at each of your deemed SLIs, see if they indicate an outage for that customer, and feed that information to your platform leadership.</li><li>Feed quantitative data into the postmortem being written for the incident. For example, “Top customer X first showed impact at 10:30 EST, reached a maximum of 30% outage at 10:50 EST, and had effectively recovered by 11:10 EST.”</li><li>Reach out to those customers via your account management teams, to discover what their actual impact was.</li></ul><p>Here’s a quick reference table for what you need to do for each customer:</p></div></section><section class="QzPuud"><div><section><figure class="NEBdNd"><section class="PBkdHd DhGbH" jscontroller="SCGBie" jsaction="rcuQ6b:npT2md"><img class="JcsBte mZzdH ZOnyjc" src="https://storage.googleapis.com/gweb-cloudblog-publish/images/reference_table.max-1100x1100.png" alt="https://storage.googleapis.com/gweb-cloudblog-publish/images/reference_table.max-1100x1100.png" jsname='P3Vluc' jsaction="click:HTIlC" loading="lazy"/><section class="glue-modal glue-modal--dark QHdDac" role="dialog" aria-modal="true"><img class="JcsBte mZzdH ZOnyjc" src="https://storage.googleapis.com/gweb-cloudblog-publish/images/reference_table.max-1100x1100.png" alt="https://storage.googleapis.com/gweb-cloudblog-publish/images/reference_table.max-1100x1100.png" jsname='P3Vluc' jsaction="click:HTIlC" loading="lazy"/><button class="glue-modal__close-btn" tabindex="0" aria-label="Close this modal"></button></section></section></figure></section></div></section><section class="Wy08Ac nRhiJb-qJTHM-OWXEXe-hJDwNd nRhiJb-DbgRPb-II5mzb-cGMI2b"><div jsaction="rcuQ6b:npT2md" jscontroller="M0Q3Qb" data-is-cws-richtext="true" class=" "><p>As you gain confidence in some of the deemed SLIs, you may start to set alerts for your platform’s on-call engineers based on those SLIs going out of bounds. For each such alert, see whether it represents a material customer outage, and adjust the bounds accordingly. </p><p>It’s important to note that customers can also shoot themselves in the foot and cause SLIs to go out of bounds. For example, they might cause themselves a high error rate in the API by providing an out-of-date decryption key for the blob. In this case, it’s a real outage, and your on-caller might want to know about it. There’s nothing for the on-caller to do, however—the customer has to fix it themselves. At a higher level, your product team may also be interested in these signals because there may be opportunities to design the product to guard against customers making such mistakes—or at least advise the customer when they are about to do so.</p><p>If a top customer has too many “it was us, not the platform” alerts, that’s a signal to turn off the alerts until things improve. This may also indicate that your engineers should collaborate with the customer to improve their reliability on your platform.</p><p>When your on-call engineer gets deemed SLI alerts from multiple customers, on the other hand, they can have a high confidence that the proximate cause is likely on the platform side.</p><h3>Getting started with your own deemed SLIs</h3><p>In Google Cloud, some of these metrics are exposed to customers directly through project-related, <a href="https://cloud.google.com/blog/products/gcp/transparent-slis-see-google-cloud-the-way-your-application-experiences-it">Transparent SLIs</a>.</p><p>If you run a platform, you need to know what your customers are experiencing.</p><ul><li><p>Knowing that a top customer has started having a problem before they phone your support hotline shrinks incident detection by many minutes, reduces the overall impact of the outage, and improves relationships with that customer. </p></li><li><p>Knowing that several top customers have started to have problems can even be used to signal that a recent deployment should presumptively be rolled back, just in case.</p></li><li><p>Knowing roughly how many customers are affected by an outage is a very helpful signal for incident triage—is this outage minor, significant, or huge? </p></li></ul></div></section><section class="Wy08Ac nRhiJb-qJTHM-OWXEXe-hJDwNd nRhiJb-DbgRPb-II5mzb-cGMI2b"><div jsaction="rcuQ6b:npT2md" jscontroller="M0Q3Qb" data-is-cws-richtext="true" class=" "><p>Whatever your business, you know who your most important customers are. This week, go and look at the monitoring of your top three customers. Identify a “deemed SLI” for each of them, measure it in your monitoring system, and set up an automated alert for when those SLIs go squirrelly. You can tune your SLI selection and alert thresholds over the next few weeks, but right now, you are in tune with your top three customers’ experience on your platform. Isn’t that great? <br></p><p>Learn more about SLIs and other SRE practices from <a href="https://cloud.google.com/blog/products/devops-sre">previous blog posts</a> and the <a href="https://landing.google.com/sre/workbook/toc/" target="_blank">online Site Reliability Workbook</a>.<br></p><hr><p><i>Thanks to additional contributions from Anna Emmerson, Matt Brown, Christine Cignoli and Jessie Yang.</i></p></div></section><section class="nRhiJb-kR0ZEf-OWXEXe-GV1x9e-uQSCkd nRhiJb-DbgRPb-II5mzb-cGMI2b"><div class="u2M0Kb"><a href="https://cloud.google.com/blog/products/devops-sre/sre-fundamentals-slis-slas-and-slos" class="w7DBpd" track-name="sre fundamentals: slis slas and slos"track-type="articlefeedblock"track-metadata-eventdetail="cloud.google.com/blog/products/devops-sre/sre-fundamentals-slis-slas-and-slos"><div class="odmDff "><div class="exDIId"><div class="Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-qWD73c nRhiJb-BFbNVe-r8s4j-bMElCd EQ9W8e nRhiJb-fmcmS-oXtfBe" track-name="google cloud"track-type="tag">Google Cloud</div><h5 class="Qwf2Db-MnozTc qPW6X nRhiJb-DbgRPb-R6PoUb-ma6Yeb Qwf2Db-MnozTc-OWXEXe-MnozTc-II5mzb">SRE fundamentals: SLIs, SLAs and SLOs</h5><p class="nRhiJb-qJTHM MQpQf">A big part of SRE is establishing and monitoring service-level metrics like SLOs, SLAs and SLIs. This post gives you an overview of what each of these acronyms are, what they mean, and how to use them.</p><p class="nRhiJb-cHYyed gh5m8">By Jay Judkowitz • 5-minute read</p></div><div class="OzOXWb"><section class="PBkdHd "><img class=" YwUks" src="https://storage.googleapis.com/gweb-cloudblog-publish/images/15_-_Google_Cloud_2fKuG6b.max-900x900.jpg" alt="https://storage.googleapis.com/gweb-cloudblog-publish/images/15_-_Google_Cloud_2fKuG6b.max-900x900.jpg" loading="lazy"/></section></div></div></a></div></section><section class="kcBhad"><section class="Fabbec"><span class="WrMNjb">Posted in</span><ul class="FzXI4e"><li class="I4B51b"><a href="https://cloud.google.com/blog/products/management-tools" track-metadata-position="body"track-metadata-eventdetail="cloud.google.com/blog/products/management-tools"track-metadata-module="tag list"track-metadata-module_headline="posted in">Management Tools</a></li><li class="I4B51b"><a href="https://cloud.google.com/blog/products/devops-sre" track-metadata-position="body"track-metadata-eventdetail="cloud.google.com/blog/products/devops-sre"track-metadata-module="tag list"track-metadata-module_headline="posted in">DevOps &amp; SRE</a></li><li class="I4B51b"><a href="https://cloud.google.com/blog/products/gcp" track-metadata-position="body"track-metadata-eventdetail="cloud.google.com/blog/products/gcp"track-metadata-module="tag list"track-metadata-module_headline="posted in">Google Cloud</a></li></ul></section></section></div></div></div></div></div><section class="nRhiJb-DARUcf " track-metadata-module="related articles" track-metadata-module_headline="related articles"><div class="nRhiJb-DbgRPb-c5RTEf-ma6Yeb nRhiJb-DbgRPb-wNfPc-cGMI2b"><h5 class="Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-wNfPc nRhiJb-DbgRPb-II5mzb-cGMI2b">Related articles</h5><section class="m9cUGf HGev3 nJD2Qe nRhiJb-ObfsIf"><div class=" QaGyvd nRhiJb-kR0ZEf-OWXEXe-GV1x9e-c5RTEf nRhiJb-kR0ZEf-OWXEXe-GV1x9e-qWD73c-V2iZpe"><div class="mA0uBe"><a 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read</p></div></div></a></div></div><div class=" QaGyvd nRhiJb-kR0ZEf-OWXEXe-GV1x9e-c5RTEf nRhiJb-kR0ZEf-OWXEXe-GV1x9e-qWD73c-V2iZpe"><div class="mA0uBe"><a href="https://cloud.google.com/blog/products/management-tools/alert-with-sql-in-cloud-monitoring-observability-analytics" class="lD2oe" track-name="from query to action: introducing sql alerting in cloud monitoring observability analytics"track-type="card"track-metadata-eventdetail="cloud.google.com/blog/products/management-tools/alert-with-sql-in-cloud-monitoring-observability-analytics"><div class="AhkbS "><div class="hqnDEf"><section class="PBkdHd "><img class=" D5RK8d" src="https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-700x700.jpg" alt="https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-700x700.jpg" loading="lazy"/></section></div><div class="JUOx5b"><div class="Qwf2Db-MnozTc Qwf2Db-MnozTc-OWXEXe-MnozTc-qWD73c 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metrics like SLOs and SLIs. See how CRE teams and customers at Google use deemed SLIs",[1579136400],"https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-2600x2600.jpg","https://cloud.google.com/blog/products/management-tools/using-deemed-slis-to-measure-customer-reliability",[1579136400,329586000],"blog.articlepage",null,"/api/w_v2/pages/40672/","using-deemed-slis-to-measure-customer-reliability",40672],[["Adrian Hilton","Customer Reliability Engineer, SRE"]],[null,"\u003cscript type\u003d\"application/ld+json\"\u003e{\"@context\":\"https://schema.org\",\"@type\":\"BlogPosting\",\"@id\":\"https://cloud.google.com/blog/products/management-tools/using-deemed-slis-to-measure-customer-reliability\",\"headline\":\"Deemed SLIs to put SRE into practice\",\"description\":\"Following SRE principles involves reliability metrics like SLOs and SLIs. See how CRE teams and customers at Google use deemed SLIs\",\"image\":\"https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-2600x2600.jpg\",\"author\":[{\"@type\":\"Person\",\"name\":\"Adrian Hilton\",\"url\":\"\"}],\"datePublished\":\"2020-01-16\",\"publisher\":{\"@type\":\"Organization\",\"name\":\"Google Cloud\",\"logo\":{\"@type\":\"ImageObject\",\"url\":\"https://www.gstatic.com/cgc/google-cloud-logo.svg\"}},\"url\":\"https://cloud.google.com/blog/products/management-tools/using-deemed-slis-to-measure-customer-reliability\",\"keywords\":[\"Management Tools\",\"DevOps \\u0026 SRE\",\"Google Cloud\"],\"timeRequired\":\"PT8M\"}\u003c/script\u003e"],["Using deemed SLIs to measure customer reliability"],null,null,[[null,null,[null,[null,"\u003cp\u003eDo you own and operate a software service? If so, is your service a ”platform”? In other words, does it run and manage applications of a wide range of users and/or companies? There are both simple and complex types of platforms, all of which serve customers. One example could be Google Cloud, which provides, among other things, relatively low-level infrastructure for starting and running VM images. A higher-level example of a platform might be a blogging service that allows any customer to create and contribute to a blog, design and sell merchandise featuring pithy blog quotes, and allow readers to send tips to the blog author.\u003c/p\u003e\u003cp\u003eIf you do run a platform, it’s going to break sooner or later. Some breakages are large and easy to understand, such as no one being able to reach websites hosted on your platform while your company’s failure is frequently mentioned on social media. However, other kinds of breakage may be less obvious to you—but not to your customers. What if you’ve accidentally dropped all inbound network traffic from Kansas, for example?\u003c/p\u003e\u003cp\u003eAt Google Cloud, we follow SRE principles to ensure reliability for our systems and also customers partnered with the Customer Reliability Engineering (CRE) team. A core SRE operating principle is the use of service-level indicators (SLIs) to detect when your users start having a bad time. In this blog post, we’ll look at how to measure your platform customers’ approximate reliability using approximate SLIs, which we term “deemed SLIs.” We use these to detect low-level outages and drive the operational response.\u003c/p\u003e\u003ch3\u003eWhy use deemed SLIs?\u003c/h3\u003e\u003cp\u003e\u003ca href\u003d\"https://cloud.google.com/blog/products/gcp/introducing-a-new-era-of-customer-support-google-customer-reliability-engineering\"\u003eCRE founder\u003c/a\u003e Dave Rensin noted in his SRECon 2017 talk, \u003ca href\u003d\"https://www.usenix.org/conference/srecon17americas/program/presentation/rensin\" target\u003d\"_blank\"\u003eReliability When Everything Is A Platform\u003c/a\u003e, that as a platform operator, your monitoring doesn’t decide your reliability—your customers do! The best way to get direct visibility into your customers’ reliability experience is to get them to \u003ca href\u003d\"https://landing.google.com/sre/resources/practicesandprocesses/art-of-slos/\" target\u003d\"_blank\"\u003edefine their own SLIs\u003c/a\u003e, and share those signals directly with you. That level of transparency is wonderful, but it requires active and ongoing participation from your customers. What if your customers can’t currently prioritize the time to do this?\u003c/p\u003e\u003cp\u003eAs a platform provider, you might use any number of internal monitoring metrics related to what’s happening with customer traffic. For instance, say you’re providing an API to a storage service:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eYou may be measuring the total number of queries and number of successful responses as \u003ca href\u003d\"https://cloud.google.com/blog/products/management-tools/stackdriver-tips-and-tricks-understanding-metrics-and-building-charts\"\u003ecumulative numeric metrics\u003c/a\u003e, grouped by each API function.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eYou may also be recording the 95th percentile response latency with the same grouping, and get a good idea of how your service is doing overall by looking at the ratio of successful queries and the response latency values. If your success ratio suddenly drops from its normal value of 99% to 75%, you likely have many customers experiencing errors. Similarly, if the 95th percentile latency rises from 600ms to 1400ms, your customers are waiting much longer than normal for responses.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eThe key insight to motivate the use of “deemed SLIs” is that metrics aggregated across all customers will miss edge cases—and your top customers are very likely to depend on those edge cases. Your top customers need to know about outages as soon as, or even before, they happen. Therefore, you most likely want to know when any of your top customers is likely to experience a problem, even if most of your customers are fine. \u003c/p\u003e\u003cp\u003eSuppose FooCorp, one of your biggest customers, uses your storage service API to store virtual machine images:\u003c/p\u003e\u003cul\u003e\u003cli\u003eThey build and write three different images every 15 minutes.\u003c/li\u003e\u003cli\u003eThe VM images are much larger than most blobs in your service. \u003c/li\u003e\u003cli\u003eEvery time one of their 10,000 virtual machines is restarted, it reads an image from the API. \u003c/li\u003e\u003cli\u003eTherefore, their traffic rate is one write per five minutes and assuming a daily VM restart, one read per 8.6 seconds. \u003c/li\u003e\u003cli\u003eYour overall API traffic rate is one write per second and 100 reads per second.\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eLet’s say you roll out to your service a change that has a bug, causing very large image reads and writes, which are likely to time out and not complete. You initially don’t see any noticeable effect on your API’s overall success rate and think your platform is running just fine. FooCorp, however, is \u003ci\u003efurious\u003c/i\u003e. Wouldn’t you like to know what just happened?\u003c/p\u003e\u003ch3\u003eImplementation of deemed SLIs\u003c/h3\u003e\u003cp\u003eThe first and foremost step is to see key metrics at the granularity of a single customer. This requires careful assessment and trade-offs. \u003c/p\u003e\u003cp\u003eFor our storage API, assuming we were originally storing two cumulative measures (success, total) and one gauge (latency) at one-minute intervals, we can measure and store three data points per minute with no problem at all. However, if we have 20,000 customers, then storing 60,000 points per minute is a very different problem. Therefore, we need to be careful in the selection of metrics for which we provide the per-customer breakdown. In some cases, it may be sensible to have per-customer breakdowns only for a subset of customers, such as those contracting for a certain level of paid support.\u003c/p\u003e\u003cp\u003eNext, identify your top customers. “Top” could mean:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003einvests the most money on your platform;\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eis expected to invest the most money on your platform in the next two years;\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eis strategic from the point of view of partnerships or publicity; or even\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eraises the most support cases and hence causes the greatest operational load on your team.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eAs we mentioned, customers use your platform in different ways and as a result, have different expectations of it. To find out what your customer might regard as an outage, you need to understand in some depth what their workload really does. In some cases, the customer’s clients might automatically read data from your API every 30 minutes, and update their state if new information is available. However, even if the API is completely broken for an hour, very few customers might actually notice. \u003c/p\u003e\u003cp\u003eTo determine your deemed SLIs, consider applying your understanding of the customer’s workload from the limited selection of metrics per customer.  Think about your observation of the volatility of the metrics over time, and if possible, observation of the metrics during a known customer outage. From this, pick the subset of metrics which you think best represent customer happiness. Identify the normal ranges of those metrics, and aggregate them into a dashboard view for that customer.\u003c/p\u003e\u003cp\u003eThis is why we call these metrics “deemed SLIs”—you deem them to be representative of your particular customer’s happiness, in the absence of better information. \u003c/p\u003e\u003cp\u003eSome of the metrics you look at for your deemed SLIs of the storage service might include:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eOverall API success rate and latency\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eRead and write success rate for large objects (i.e., FooCorp’s main use case)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eRead latency for objects below a certain size (i.e., excluding large image read bursts so there’s a clear view of API performance for its more common read use case).\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eThe main challenges are:\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eLack of technical transparency into the customer’s key considerations. For instance, if you only provide \u003ca href\u003d\"https://cloud.google.com/load-balancing/docs/tcp/\"\u003eTCP load balancing\u003c/a\u003e to your customer, you can’t observe HTTP response codes. \u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eLack of organizational transparency—you don’t have enough understanding of the customer’s workload to be able to identify what SLIs are meaningful to them.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eMissing per-customer metrics. You might find that you need to know whether an API call is made internally or externally because the latter is the key representative of availability. However, this distinction isn’t captured in the existing metrics.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eIt’s important to remember that we don’t expect these metrics to be perfect at first— these metrics are often quite inconsistent with the customer’s experience in the beginning. So how do we fix this? Simple—we iterate.\u003c/p\u003e\u003ch3\u003eIteration when choosing deemed SLIs\u003c/h3\u003e\u003cp\u003eNow sit back and wait for a significant outage of your platform. There’s a good chance that you won’t have to wait too long, particularly if you deploy \u003ca href\u003d\"https://conferences.oreilly.com/velocity/vl-eu/public/schedule/detail/78800\" target\u003d\"_blank\"\u003econfiguration changes\u003c/a\u003e or binary releases often.\u003c/p\u003e\u003cp\u003eWhen your outage happens:\u003c/p\u003e\u003cul\u003e\u003cli\u003eDo an initial impact analysis. Look at each of your deemed SLIs, see if they indicate an outage for that customer, and feed that information to your platform leadership.\u003c/li\u003e\u003cli\u003eFeed quantitative data into the postmortem being written for the incident. For example, “Top customer X first showed impact at 10:30 EST, reached a maximum of 30% outage at 10:50 EST, and had effectively recovered by 11:10 EST.”\u003c/li\u003e\u003cli\u003eReach out to those customers via your account management teams, to discover what their actual impact was.\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eHere’s a quick reference table for what you need to do for each customer:\u003c/p\u003e"]]],[null,null,null,null,null,null,null,null,[[[null,""],["https://storage.googleapis.com/gweb-cloudblog-publish/images/reference_table.max-1100x1100.png","https://storage.googleapis.com/gweb-cloudblog-publish/images/reference_table.max-1100x1100.png 1017w, https://storage.googleapis.com/gweb-cloudblog-publish/images/reference_table.max-1100x1100.png 1017w"," 1017px, 1017px","https://storage.googleapis.com/gweb-cloudblog-publish/images/reference_table.max-1100x1100.png"],null,3]]],[null,null,[null,[null,"\u003cp\u003eAs you gain confidence in some of the deemed SLIs, you may start to set alerts for your platform’s on-call engineers based on those SLIs going out of bounds. For each such alert, see whether it represents a material customer outage, and adjust the bounds accordingly. \u003c/p\u003e\u003cp\u003eIt’s important to note that customers can also shoot themselves in the foot and cause SLIs to go out of bounds. For example, they might cause themselves a high error rate in the API by providing an out-of-date decryption key for the blob. In this case, it’s a real outage, and your on-caller might want to know about it. There’s nothing for the on-caller to do, however—the customer has to fix it themselves. At a higher level, your product team may also be interested in these signals because there may be opportunities to design the product to guard against customers making such mistakes—or at least advise the customer when they are about to do so.\u003c/p\u003e\u003cp\u003eIf a top customer has too many “it was us, not the platform” alerts, that’s a signal to turn off the alerts until things improve. This may also indicate that your engineers should collaborate with the customer to improve their reliability on your platform.\u003c/p\u003e\u003cp\u003eWhen your on-call engineer gets deemed SLI alerts from multiple customers, on the other hand, they can have a high confidence that the proximate cause is likely on the platform side.\u003c/p\u003e\u003ch3\u003eGetting started with your own deemed SLIs\u003c/h3\u003e\u003cp\u003eIn Google Cloud, some of these metrics are exposed to customers directly through project-related, \u003ca href\u003d\"https://cloud.google.com/blog/products/gcp/transparent-slis-see-google-cloud-the-way-your-application-experiences-it\"\u003eTransparent SLIs\u003c/a\u003e.\u003c/p\u003e\u003cp\u003eIf you run a platform, you need to know what your customers are experiencing.\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eKnowing that a top customer has started having a problem before they phone your support hotline shrinks incident detection by many minutes, reduces the overall impact of the outage, and improves relationships with that customer. \u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eKnowing that several top customers have started to have problems can even be used to signal that a recent deployment should presumptively be rolled back, just in case.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eKnowing roughly how many customers are affected by an outage is a very helpful signal for incident triage—is this outage minor, significant, or huge? \u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e"]]],[null,null,[null,[null,"\u003cp\u003eWhatever your business, you know who your most important customers are. This week, go and look at the monitoring of your top three customers. Identify a “deemed SLI” for each of them, measure it in your monitoring system, and set up an automated alert for when those SLIs go squirrelly. You can tune your SLI selection and alert thresholds over the next few weeks, but right now, you are in tune with your top three customers’ experience on your platform. Isn’t that great? \u003cbr\u003e\u003c/p\u003e\u003cp\u003eLearn more about SLIs and other SRE practices from \u003ca href\u003d\"https://cloud.google.com/blog/products/devops-sre\"\u003eprevious blog posts\u003c/a\u003e and the \u003ca href\u003d\"https://landing.google.com/sre/workbook/toc/\" target\u003d\"_blank\"\u003eonline Site Reliability Workbook\u003c/a\u003e.\u003cbr\u003e\u003c/p\u003e\u003chr\u003e\u003cp\u003e\u003ci\u003eThanks to additional contributions from Anna Emmerson, Matt Brown, Christine Cignoli and Jessie Yang.\u003c/i\u003e\u003c/p\u003e"]]],[null,null,null,null,null,null,null,[["Google Cloud","SRE fundamentals: SLIs, SLAs and SLOs","A big part of SRE is establishing and monitoring service-level metrics like SLOs, SLAs and SLIs. This post gives you an overview of what each of these acronyms are, what they mean, and how to use them.",["https://storage.googleapis.com/gweb-cloudblog-publish/images/15_-_Google_Cloud_2fKuG6b.max-900x900.jpg","https://storage.googleapis.com/gweb-cloudblog-publish/images/15_-_Google_Cloud_2fKuG6b.max-500x500.jpg 410w, https://storage.googleapis.com/gweb-cloudblog-publish/images/15_-_Google_Cloud_2fKuG6b.max-900x900.jpg 820w"," 410px, 820px","https://storage.googleapis.com/gweb-cloudblog-publish/images/15_-_Google_Cloud_2fKuG6b.max-900x900.jpg"],null,5,null,"https://cloud.google.com/blog/products/devops-sre/sre-fundamentals-slis-slas-and-slos",null,1,[["Jay Judkowitz","Senior Product Manager"],["Mark Carter","Group Product Manager"]],null,"37509"]]]],[["Infrastructure Modernization","New AI-powered quick assessments in Migration Center turbocharge modernization","New, AI-powered Quick Assessments in Migration Center deliver near-instant TCO modeling and automated service mapping.",["https://storage.googleapis.com/gweb-cloudblog-publish/images/19_-_Infrastructure_Modernization_o5CKMmf.max-700x700.jpg","https://storage.googleapis.com/gweb-cloudblog-publish/images/19_-_Infrastructure_Modernization_o5CKMmf.max-400x400.jpg 324w, https://storage.googleapis.com/gweb-cloudblog-publish/images/19_-_Infrastructure_Modernization_o5CKMmf.max-700x700.jpg 648w"," 324px, 648px","https://storage.googleapis.com/gweb-cloudblog-publish/images/19_-_Infrastructure_Modernization_o5CKMmf.max-700x700.jpg"],null,2,null,"https://cloud.google.com/blog/products/infrastructure-modernization/ai-powered-quick-assessments-in-migration-center",null,1,[["Jeff Welsch","Principal, Product Management, Enterprise Migration \u0026 Growth"],["Rajesh Rathod","Lead Group Product Manager"]],null,"59326"],["Databases","Introducing Database Operations Agents: The future of autonomous database management","A closer look at AI-powered database operations agents for setting up and onboarding AlloyDB, Bigtable, Cloud SQL, Spanner, as well as managing them.",["https://storage.googleapis.com/gweb-cloudblog-publish/images/10_-_Databases.max-700x700.jpg","https://storage.googleapis.com/gweb-cloudblog-publish/images/10_-_Databases.max-400x400.jpg 324w, https://storage.googleapis.com/gweb-cloudblog-publish/images/10_-_Databases.max-700x700.jpg 648w"," 324px, 648px","https://storage.googleapis.com/gweb-cloudblog-publish/images/10_-_Databases.max-700x700.jpg"],null,6,null,"https://cloud.google.com/blog/products/databases/deep-dive-on-new-ai-powered-database-agents",null,1,[["Niranjan Shivprasad","Group Product Manager"],["Nitesh Mehta","Senior Product Manager"]],null,"59140"],["Management Tools","Anomaly detection using dynamic thresholds and two-year-long alerts in Cloud Monitoring","Long-lookback alert policies for PromQL cover up to two years of metrics in Cloud Monitoring for year-over-year and quarter-over-quarter analysis.",["https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-700x700.jpg","https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-400x400.jpg 324w, https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-700x700.jpg 648w"," 324px, 648px","https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-700x700.jpg"],null,6,null,"https://cloud.google.com/blog/products/management-tools/cloud-monitoring-adds-long-lookback-alert-policies-for-promql",null,1,[["Lee Yanco","Senior Product Manager"],["Daniel Koss","Staff Software Engineer"]],null,"59049"],["Management Tools","From query to action: Introducing SQL alerting in Cloud Monitoring Observability Analytics","Cloud Monitoring Observability Analytics lets you create alerts from (and get alerted about) analytical SQL queries of logs and traces.",["https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-700x700.jpg","https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-400x400.jpg 324w, https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-700x700.jpg 648w"," 324px, 648px","https://storage.googleapis.com/gweb-cloudblog-publish/images/21_-_Management_Tools_EI9iqlb.max-700x700.jpg"],null,4,null,"https://cloud.google.com/blog/products/management-tools/alert-with-sql-in-cloud-monitoring-observability-analytics",null,1,[["Joy Wang","Senior Product Manager"],["Mark Stahl","Staff software engineer"]],null,"59038"]],null,"Management Tools",null,[["Management Tools","https://cloud.google.com/blog/products/management-tools","management-tools",[],["en"],"Products"],["DevOps \u0026 SRE","https://cloud.google.com/blog/products/devops-sre","devops-sre",[],["en"],"Products"],["Google Cloud","https://cloud.google.com/blog/products/gcp","gcp",[],["en"],"Products"]],null,null,8,null,40672], sideChannel: {}});</script><script id="wiz_jd" nonce="GUnH09PHlOGONHB3qEtlZQ">if (window['_wjdc']) {const wjd = {}; window['_wjdc'](wjd); delete window['_wjdc'];}</script><script aria-hidden="true" id="WIZ-footer" nonce="GUnH09PHlOGONHB3qEtlZQ">window.wiz_progress&&window.wiz_progress();window.stopScanForCss&&window.stopScanForCss(); ccTick('bl');</script></body></html><footer id="ZCHFDb"><footer class="nRhiJb-RWrDld nRhiJb-yePe5c QJnbF" jscontroller="NsSboe" track-metadata-module="footer"><h3 class="nRhiJb-VqCwd-L6cTce">Footer Links</h3><section class="nRhiJb-haF9Wb r2W5Od"><section class="nRhiJb-DX2B6"><div class="nRhiJb-j5y3u"><h4 class="nRhiJb-BkAck nRhiJb-BkAck-OWXEXe-TzA9Ye">Follow us</h4><ul class="nRhiJb-Qijihe c3Uqdd" role="list"><li class="nRhiJb-KKXgde"><a class="nRhiJb-ARYxNe" href="https://www.x.com/googlecloud" target="_blank" rel="noopener" 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