Let's learn about Metrics via these 83 free blog posts. They are ordered by HackerNoon reader engagement data. Visit the Learn Repo or LearnRepo.com to find the most read blog posts about any technology.Metrics are quantifiable measures used to track and assess the status of a specific business process, project, or activity. They matter for decision-making, performance evaluation, identifying trends, and ensuring accountability in various domains.1. My Notes on MAE vs MSE Error Metrics 🚀We will focus on MSE and MAE metrics, which are frequently used model evaluation metrics in regression models.2. Rethinking Programming: Automated ObservabilityIntroduction3. Measuring Traffic Quality in Mobile Applications: Standards and Best PracticesIn today's world, mobile devices have become indispensable companions, connecting us to mass media, entertainment, and essential information.4. A Deep Dive Into Semantic Segmentation Evaluation MetricsSemantic segmentation is an area of computer vision that specialises in dividing an image into regions based on pixel characteristics.5. Key Product Metrics and Where They Come FromWhy do we need different types of metrics - topline, supporting, guardrail - and how are they defined by the product mission and lifecycle stages?6. Beyond Recall and Precision: Rethinking Metrics in Fraud PreventionUnderstanding fraud prevention demands a balance between classic metrics and business outcomes. Opt for a comprehensive set of metrics beyond Recall and Precisi7. Size Does Matter: Global Control Group for a BankLearn how to approach data-driven measurement properly. See what unexpected results we got in a bank and get insights for your own data analytics journey.8. 7 Rules to Track Software Engineering Metrics Correctly How to Use  -  and NOT Abuse  -  Software Engineering Metrics9. Creating the Perfect Dashboard: Visualizing Your MetricsA well-designed dashboard can become a key element in forecasting trends and anticipating outcomes, impacting the efficiency and motivation of the team.10. Answering Metric Questions in Product Manager InterviewsProduct manager interviews usually include a section on metrics. As a data scientist at Uber, I’ve often given or helped friends prepare for these interviews. The difference between candidates who crush the metric questions and those who struggle turns, as far as I can tell, on whether they have a framework that they can apply.11. Top 10 Software Engineering Metrics To Track If You Lead An Agile TeamEvery conversation I have with CTOs, Engineering Managers, and Tech Leaders eventually gets to the “Which Metrics Should We Measure?” discussion.12. How To Set Custom Metrics for Autoscaling in AWSIn many cases, custom metrics may be useful to make more ad-hoc configuration of autoscaling in AWS. For example, a custom metric can allow an autoscaling group to react more rapidly on spikes or to take into account the health state of hosts for concurrency based metrics. Let's see how to set up a custom metric and autoscaling policy for an autoscaling group with an application load balancer and target group using AWS Console.13. How To Raise Capital from Venture FundsVenture capitalists get pitched hundreds of times a year. And, even though countless articles have been written on the topic of how to present a startup to professional investors, entrepreneurs consistently fail to address check points needed by the investor to come to a decision.14. App Metrics 101: What You Should be MeasuringWhether you’re serving your colleagues with an internal company app or you’re dreaming of topping the charts, some would say the hard work is only just about to start. No matter how much testing and research you’ve done, nothing compares to real world usage.15. Picking the Right Metrics: The Ultimate Guide for Product ManagersThis article provides definitions on what key metrics are, a framework for categorizing them, and recommendations of four basic rules to set useful metrics, using real-life examples.16. Paying Attention to Every Detail: How to Work With the Metrics to Increase Your RevenueEvery significant business result consists of micro-level metrics that one can and should manage daily. Learn how to increase your revenue with small steps.17. What the Pandemic Taught Me About Product/Market FitThe question is not, “Does the company have product/market fit or not?”. The more appropriate question is, “What’s the strength of the company’s product/market fit?”18. What is API Observability?APIs are the blood vessels of digital business.19. How to Monitor Apache Flink with OpenTelemetryApache Flink monitoring support is now available in the open source OpenTelemetry collector.20. Should Likes Exist ?There has been some debate around the importance of public 'likes' on social media platforms. Let's discuss this further with sociological insights.21. How to Monitor Serverless Applications With AWS CloudWatch AlarmsRunning any application in production assumes reliable monitoring to be in place and serverless applications are no exception.22. Are You Focusing on the Right Product Metrics?In this article, we'll delve into seven common mistakes that people often make when it comes to selecting and tracking product metrics.23. Unleashing VM histograms for Ruby: Migrating from Prometheus to VictoriaMetrics with vm-clientExample migration of rails app from Prometheus to VictoriaMetrics to unlock the advantages of VM histograms with vm-client gem.24. 4 Key Observability Metrics for Distributed ApplicationsA common architectural design pattern these days is to break up an application monolith into smaller microservices. Each microservice is then responsible for a specific aspect or feature of your app. For example, one microservice might be responsible for serving external API requests, while another might handle data fetching for your frontend.25. Application Monitoring: Closing Observability Gaps with Custom MetricsWhich application metrics should you collect for your microservices?26. Software Quality: The Top 10 metrics to build confidenceHow do you measure quality in software engineering? I guess this is the question there will always be a debate on. There are so many approaches to this question that finding only one answer is just impossible. In this article, we will be listing the quality-related metrics that the top engineering teams have been keeping track of, and see when and how you should use them.27. No More Dark Patterns: New Laws Are Forcing Streaming and Apps to Play FairMany common growth hacks used by Subscription-based businesses are under regulatory fire worldwide.28. Microservice Observability Patterns [Part 2]In my previous article, I talked about the importance of logs and the differences between structured and unstructured logging. Logs are easy to integrate into your application and provide the ability to represent any type of data in the form of strings.29. The Beginner's Guide to The Google HEART FrameworkIn this post, we will dig into the Google HEART framework: a simple way to ensure you take into consideration every aspect of the user journey.30. Measuring the ROI of Generative AI Projects in Enterprise SettingsExplore how to effectively measure the ROI of generative AI projects in enterprises, focusing on impact assessment and value generation.31. Mastering Prioritization: Strategies for Effective Product ManagementIn this article, we'll explore proven prioritization techniques that can help product managers and teams make informed decisions.32. Facebook Takes Action On 19.2 million Posts of Violence Using AIFacebook AI researchers have leveraged advancing technologies and Machine Learning to develop a system with a level of intelligence on par with humans. AI enables and equips Facebook with various tools, including interactive chat modules, chatbots, polls, surveys, and more.33. Is Bitcoin’s Bull Market Closer to the End Than You Think?Analysts have come up with all sorts of data models and metrics to predict lofty prices and long bull markets. One metric suggests they might be wrong.34. 17 Metrics for Measuring DevOps SuccessThe metrics we choose can expose problems. But it can also hide them behind irrelevant data.35. How to Use Dora Metrics to Become an Elite TeamTradeoff between speed and quality is a myth.36. Applying First Principles Thinking to your Startup Idea to Enhance ImpactOne thing that surprises me over and over is how many startup founders don’t use models and equations in their business. I always get strange looks when invariably I ask my favorite business questions: “So, what is the equation here? What variable are you hoping to affect by doing this?”37. Setup Monitoring Using Apache Zookeeper and OpenTelemetryIn this article, I’ll show you a simplified way to configure a critical open-source component, Zookeeper.38. The Biases in Fitness TrackersIf you have darker skin, shuffle when you walk, or regularly push a stroller, it can throw off the data39. Proven Metrics and Important KPIs for Startups to Measure SuccessWhat are the most important KPIs for startups to measure success? Find your answer in this article and learn what key product metrics to track to enable growth.40. Find a Hard Metric From the StartTo succeed at sales, you need to know the value of your product.41. The Most Infuriating And Outrageous Fiverr Scam of All TimeThe Fiverr scam is offering a service that promises to increase your website’s domain authority using MOZ, a third-party SEO metric.42. Cases When Concurrency Based Autoscaling May be UsefulEvery time facing a task of configuring how the system should scale out and scale in, we decide what metrics and policies will be more effective. I have already described CPU based policies and what challenges they may have. But what if this is not an option, i.e. the service is represented by legacy application, written years ago, not well documented, etc. and we still want to run it in Cloud and autoscale?43. Podcast Analytics: How to Accurately Measure Content PerformanceThe podcast industry is booming. Each week the number of Americans who listen to podcasts tops the number of those who have Netflix accounts.44. Growth Marketing Hacks: 9 Effective Strategies to Increase Your MetricsIf you're looking to increase your website's metrics, growth marketing is the process for you.45. Teams Without Vision Are Just Busywork FactoriesWithout a clear, evolving vision, autonomous teams risk becoming busywork machines.46. Confusion Matrix Explained: The Real Foundation of Model EvaluationConfusion Matrix is one of the core foundations of evaluating AI model performance. Accuracy is the simplest metric built on top of it.47. Becoming a Manager of Engineers: How to Focus on Visibility and PredictabilityBecoming a manager is usually one of the biggest challenges of an engineer’s career. We are usually used to algorithms and state machines, which are predictable and have specific outputs depending on the input.48. 5 Metrics for a Startup, and How to Choose YoursAh, business metrics… To me, it’s the best illustration of how information overload can do more harm than good. A brief online search will provide you with dozens of “key, important, essential business metrics that every company should know”.49. How To Avoid Manipulating Data Subconsciously: A P-Hacking StoryP value is the probability that the results we are seeing are real and not by random chance. P-Hacking is a term used to describe the scientific manipulation of data to get the desired P value. All of us do this with our experiments, consciously or not.50. How to Measure Product-Market FitCan product-market fit be measured? And if so, how? What are the most important things to keep an eye on during your journey towards the holy grail of startups?51. What's Your Cycle Time?If you can’t answer it, don’t worry, you’re not alone. Many engineering leaders couldn’t tell you without some significant number-crunching. Gaining visibility into performance is only half the battle though. Knowing how to interpret metrics and how to apply them to improving performance is where the magic happens. Many CEOs do not know how to align engineering metrics to business KPIs (revenue, customer retention, etc.). Bringing metrics to your board or non-technical CEO for the first time may be challenging if you are unable to help them bridge the gap.52. Dashboards Lie. Payloads Don’t. So I Built a Tool to Catch the DriftWe had observability tools. Logs, metrics, dashboards. But they weren’t built for this.53. Not A Single Trace: The True Story of Java PerformanceObservability is an orchestra, not a single instrument. By combining multiple data points we form an accurate production narrative to resolve issues.54. Beyond Numbers: Embracing Contextual Intelligence in Engineering LeadershipThis article explores the gap between engineering teams and their leaders, highlighting the importance of cohesion and alignment55. This One Prometheus Feature Could Save You Hours of DebuggingWhether you're using Go, Python, or another language, the investment in implementing exemplars will pay dividends in your observability journey.56. Engineering Metrics: The Moneyball ApproachEngineering managers often rely on subjective clues to assess how their team is doing. But decisions made based on gut feel and imperfect measurements are less than ideal — sometimes they result in team success; other times they result in disappointment.57. How Goji Investments Enhances Developer Experience via ObservabilityThis post was written by Dean Record, Engineer at Goji Investments.58. Scaling PHP Symfony Metrics at 200k RPM: 50+ Servers, Zero Overhead with UDP + TelegrafFix PHP monitoring bottlenecks: learn how UDP + Telegraf replaced Prometheus pull, scaling to 50+ servers with zero timeouts.59. 5 Tips to Effectively Monitor Heroku ApplicationsHeroku differentiates itself from other cloud providers, by offering a complete, cohesive environment. Where AWS and GCP present a decoupled toolkit, Heroku strives for a seamless, UI-driven experience for the user. This philosophy is clearly embodied in its metrics functionality, which is often a single click or basic configuration file away.60. DevOps: I Measure The Metrics A Bit Differently. Here's WhyThe four key DevOps metrics are an exciting set of measurements. They’re getting more and more relevant since the book Accelerate has been published. I firmly believe they’re essential for engineering teams seeking effectiveness and efficiency.61. Beyond Numbers: Making Metrics Make SenseWe often treat metrics like answers. But they’re really questions about what we value, what we’re trying to change, and where we believe the leverage is.62. Technical Metrics Integration Flow: Observability and MonitoringThere is no universal standard for which metrics should be used in specific cases.63. 5 Important Metrics to Measure your SuccessNo matter how big or small your business is, you need to have certain metrics that tell you how much growth it has achieved.64. The Unusual Product Strategies That Scaled an EdTech GiantThis is the story of how we turned community, competition, and cartoon mascots into one of the most powerful products and go-to-market engines in K–12 education65. 3 Business Lessons We (Re)Learned (Re)Watching Moneyball at WaydevTo help soothe the shock of returning to work after the holidays, we've started a new tradition over at Waydev and kick off the year with a good movie or two. Since it had to be something both entertaining and inspiring, we chose to go with a classic: Moneyball, the 2011 film starring Brad Pitt.66. Evidence-Based Management in Business: Will it make a difference?Discover the benefits of evidence-based management in business, understand its impact, challenges, and how to transition to evidence-based decision-making.67. Evidence-Based Management: When the Path Is MissingDiscover how evidence-based management can guide organizations through uncertainty and help set clear missions and goals for product development.68. Better Performance and Security by Monitoring Logs, Metrics, and MoreMonitoring is a crucial part of observability. Learn how monitoring can specifically improve security, performance, and reliability.69. Cloud-Native Autoscaling in AWSImagine the situation, you have a legacy system partially migrated to multiple services and used by the relatively small amount of concurrent users. And one day stakeholders want to create an open API and expose the system to external clients with the load significantly higher than the existing system can handle, and it should be scalable to handle in the future even more.70. Why You Should Use Lead Time Instead of Cycle TimeOur concepts of Lead Time and Cycle Time came from the field of Operations Management and Production Engineering. As such, I think it’s beneficial to all of us to maintain coherent with them and use the same semantics in Software Engineering Management as well.71. I Defined the Same Business Metric in 4 Semantic Layers. 3 of Them Disagreed.Define the metric once, in one place, and every tool (and every AI agent) that queries it gets the same answer.72. On Discussing Engineering Metrics to Direct Your Team's Focus, DailySoftware engineering metrics help daily stand-up meetings to be more productive for the team. They can become tedious or irrelevant for many developers when they frequently exceed the fifteen minutes time box or even sound like a work report.73. How Metrics Lead to Effective Sprint RetrospectivesIn the Atlassian playbook, it states that Sprint Retrospective’s goal is to identify how to improve teamwork by reflecting on what worked, what didn’t, and why. Usually, the meeting consists of brainstorming what the team did well and what the team needs to do better.74. Financial Modeling: Key Importance Tips to Build Your Winning ModelFinancial modeling is a critical tool for informed decision-making and strategic planning for any business.75. How Engineering Managers Benefit from Synthetic MetricsEngineering managers are in charge of tech teams. It means there are tens or maybe hundreds of people supporting them. Generally, they need to ensure the best practices around software development, hire and train engineering staff, align and motivate the team towards the company’s goal, manage the team’s performance, and be accountable for all technical decisions.76. Rework Costs Your Company Millions — How to Cut Back?On average, a software development team reworks about 26% of its code prior to release. Even after accounting for necessary changes, those wasted hours can cost a medium-sized business upwards of $4.7M a year.Still, when engineering leaders look to cut costs, they often look at departmental spending. Software licenses, discretionary expenses, and even salaries may come under scrutiny.But not all costs come with such a clear price tag — inefficiencies in the software development process are harder to quantify, but much more expensive.According to a 2017 DORA white paper, Forecasting the Value of DevOps Transformations, the cost of Rework in software development is staggering, setting businesses of all sizes back millions of dollars a year.77. How Engineering Teams Can Leverage the Power of MetricsEver wondered what key metrics other engineering teams are tracking? The short answer: it varies completely. Even within the same organization, different teams78. Monitoring Observability — or What the Heck Is It Anyway?Observability is more than just sexy dashboards with colorful graphs. It's about predicting the problem before it becomes one.79. Consensus 2021: Understanding LatAm Blockchain States and Protocol Usage MetricsConsensus 2021 panel discussions around crypto states in Latin America and layer one and layer two blockchain protocols. Tokenomics metrics and usage growth.80. Exporting Data to Fit Your NeedsA lot of the work we do at ChartMogul centers around how we display and present your data in a clear and transparent way.81. Tracking Metrics as a BootstrapperI’m a ChartMogul customer, and I’m a bootstrapper. I’m the founder of Feature Upvote, a bootstrapped and profitable SaaS.82. Why Accuracy Metrics Break Down When Humans Are Part of the SystemHigh accuracy doesn’t mean reliable AI. This story explains why real-world systems fail—and how predictable behavior drives adoption.83. Worry if The CPU based Policy Does Not Cut It For YouImagine you are in the process of migration of a legacy system from the data center to the cloud to make the system scalable. If containerization is not an option you will try cloud-native autoscaling. One of the most commonly used metric to perform autoscaling is CPU utilisation. If your application does not scale well based on this metric this is pretty likely because of more serious issues. Let's see why.Thank you for checking out the 83 most read blog posts about Metrics on HackerNoon.Visit the /Learn Repo to find the most read blog posts about any technology.