{"id":32356,"date":"2023-05-11T06:00:00","date_gmt":"2023-05-11T13:00:00","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=32356"},"modified":"2023-05-13T10:55:03","modified_gmt":"2023-05-13T17:55:03","slug":"why-slis-and-slos-are-essential-for-observability","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2023\/05\/11\/why-slis-and-slos-are-essential-for-observability\/","title":{"rendered":"Why SLIs and SLOs Are Essential for Observability"},"content":{"rendered":"\n<p>If you work in infrastructure technology, chances are you spend a lot of time working with IT operations teams. You\u2019ve watched them invest lots of hard work trying to meet the expectations of the business, but they\u2019ve come away with limited success. The business continually bashes IT for providing poor service, while IT struggles to meet seemingly nebulous expectations with limited resources. The major problem here is the fundamental disconnect over how IT and the business each measure success.<\/p>\n\n\n\n<p>IT is responsible for sharing limited resources (such as CPU, memory, and disk) between business functions, so they measure consumption. IT then uses those metrics to recognize when a resource is close to exhaustion to avoid problems and keep costs low. On the other hand, the business needs responsive and error-free services, so they measure success using speed and quality. The disconnect is two teams with drastically different definitions of success, resulting in lots of tension between IT and the business.&nbsp;<\/p>\n\n\n\n<p>If you want a simpler and more responsive observability practice, tighter alignment with the business, and faster paths to improvement, you should focus on service level metrics instead. In this article, I\u2019ll introduce two metrics that should matter for your observability practice \u2013 service level indicators (SLIs) and service level objectives (SLOs) \u2013 and I\u2019ll show you how to set your SLOs.<\/p>\n\n\n\n<p><strong>Service level indicators<\/strong><\/p>\n\n\n\n<p>An <strong>SLI<\/strong> is a carefully defined quantitative indicator of some aspect of the level of service that is provided. In other words, an SLI is a metric measuring one thing that shows how well your IT service is performing. An SLI must be relevant to the delivered service and should be simple and easy to understand. In other words, when an SLI goes wrong, there must be some business impact, such as an outage or poor user experience. Remember, the business expects speed and quality, so you need to choose SLIs (metrics) that measure those things, such as:<\/p>\n\n\n\n<ul>\n<li>Latency\/response time<\/li>\n\n\n\n<li>Error rate\/quality<\/li>\n\n\n\n<li>Availability&nbsp;<\/li>\n\n\n\n<li>Uptime<\/li>\n<\/ul>\n\n\n\n<p>Yes, there is a distinction between uptime (reliability) and availability (time loss).&nbsp; And here are some potential SLI choices that you shouldn\u2019t use because they don\u2019t directly correlate to business impact:<\/p>\n\n\n\n<ul>\n<li>CPU, disk, memory consumption<\/li>\n\n\n\n<li>Cache hit rate<\/li>\n\n\n\n<li>Garbage collection time<\/li>\n<\/ul>\n\n\n\n<p>Again, the main difference between a good and bad SLI is the metric\u2019s relevance to service delivery. A high error rate or slow response time affects service delivery. High CPU utilization might impact service delivery, but the relationship between CPU and service performance is harder to establish. This is why IT teams that measure resource consumption struggle.<\/p>\n\n\n\n<p>The key here is to pick a metric for your SLI that is clearly and unambiguously related to service delivery and is simple and easy to communicate to non-technical people. That will resolve the disconnect, making things easier for everyone involved.<\/p>\n\n\n\n<p><strong>Service level objectives<\/strong><\/p>\n\n\n\n<p>An SLO is simply a goal that you set for your SLIs. First, you identify your SLIs. Then, by setting thresholds for each SLI, you create your SLOs.<\/p>\n\n\n\n<p>SLOs should be easy for even non-technical stakeholders to understand. Stand-alone resource consumption metrics, such as CPU utilization, don\u2019t tell you if something is performing well or not\u2014they require interpretation by an SME. Identifying business-impacting SLIs, setting SLOs, and properly presenting them means that the consumers of those SLOs don\u2019t have to ask if the number is good or bad. Interpretation is intuitive\u2014the answer is \u201cgood\u201d or \u201cnot good.\u201d As a bonus, it\u2019s easy to use SLOs to measure improvement.<\/p>\n\n\n\n<p><strong>Setting your SLOs<\/strong><\/p>\n\n\n\n<p>If the business or IT management has already set SLOs for you, then you\u2019ll want to use those. If they haven\u2019t, I recommend using an iterative approach as follows:<\/p>\n\n\n\n<ol>\n<li>Identify the service you want to set SLOs for.<\/li>\n\n\n\n<li>Identify the service\u2019s key transactions. Many services have transactions, such as health checks, that should not contribute to performance SLOs.<\/li>\n\n\n\n<li>Identify service and transaction SLIs.<\/li>\n\n\n\n<li>For each SLI, create a baseline SLO using the 95th percentile. Don\u2019t use averages, as they hide outliers, and you\u2019ll end up with noisy alerts.<\/li>\n\n\n\n<li>Set SLO violation alerts.<\/li>\n\n\n\n<li>Periodically review alert KPIs and service performance to ensure that your SLOs are relevant and help drive improvement.<\/li>\n<\/ol>\n\n\n\n<p>Establishing SLIs and SLOs will result in a simpler and more responsive observability practice, tighter alignment with the business, and a faster path to improvement. It\u2019s simple and easy to get started, practice this on one service and see how well it works.&nbsp;<\/p>\n\n\n\n<p><strong>About the Author<\/strong><\/p>\n\n\n\n<p>Jemiah Sius, Director, Developer Relations, <a href=\"https:\/\/newrelic.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">New Relic<\/a><\/p>\n\n\n\n<p><em>Sign up for the free insideBIGDATA&nbsp;<a href=\"http:\/\/inside-bigdata.com\/newsletter\/\" target=\"_blank\" rel=\"noreferrer noopener\">newsletter<\/a>.<\/em><\/p>\n\n\n\n<p><em>Join us on Twitter:&nbsp;<a href=\"https:\/\/twitter.com\/InsideBigData1\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/twitter.com\/InsideBigData1<\/a><\/em><\/p>\n\n\n\n<p><em>Join us on LinkedIn:&nbsp;<a href=\"https:\/\/www.linkedin.com\/company\/insidebigdata\/\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/www.linkedin.com\/company\/insidebigdata\/<\/a><\/em><\/p>\n\n\n\n<p><em>Join us on Facebook:&nbsp;<a href=\"https:\/\/www.facebook.com\/insideBIGDATANOW\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/www.facebook.com\/insideBIGDATANOW<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this contributed article, Jemiah Sius, Director, Product Management, New Relic, discusses the difference between good and bad SLIs \u2014 and how that can inform creating the best SLOs to measure improvement. Establishing SLIs and SLOs will result in a simpler and more responsive observability practice, tighter alignment with the business, and a faster path to improvement. It\u2019s simple and easy to get started, practice this on one service and see how well it works.\u00a0<\/p>\n","protected":false},"author":10513,"featured_media":30424,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[115,180,61,268,56,1],"tags":[280,1200,1067,96],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Why SLIs and SLOs Are Essential for Observability - insideBIGDATA<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/insidebigdata.com\/2023\/05\/11\/why-slis-and-slos-are-essential-for-observability\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Why SLIs and SLOs Are Essential for Observability - insideBIGDATA\" \/>\n<meta property=\"og:description\" content=\"In this contributed article, Jemiah Sius, Director, Product Management, New Relic, discusses the difference between good and bad SLIs \u2014 and how that can inform creating the best SLOs to measure improvement. Establishing SLIs and SLOs will result in a simpler and more responsive observability practice, tighter alignment with the business, and a faster path to improvement. 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