Simplify observability for all your custom metrics (Part 4: Prometheus)


In Part 1 we explored how you can use the Davis AI to analyze your StatsD metrics. In Part 2 we showed how you can run multidimensional analysis for external metrics that are ingested via the OneAgent Metric API. Analyzing Prometheus metrics in Kubernetes is challenging.

Simplify observability for all your custom metrics (Part 2: OneAgent metric API)


In Part 1 we explored how you can use the Davis AI to analyze your StatsD metrics. . In part 2, we’ll show you how you can run multidimensional analysis from external metrics that are ingested via the OneAgent metric API. Dynatrace news.


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Find and analyze important metrics faster with the new metric browser


Recently we simplified observability for custom metrics and opened up Dynatrace OneAgent for integration of metrics from various sources like StatsD , Telegraf , and Prometheus. Explore the metrics you’re most interested in with the new metric browser.

Simplify observability for all your custom metrics (Part 3: Scripting languages)


In Part 1 we explored how you can use the Davis AI to analyze your StatsD metrics. In Part 2 we showed how you can run multidimensional analysis for external metrics that are ingested via the OneAgent Metric API. Example use case: G et various CPU metrics per processor.

MicroProfile Metrics with Prometheus and Grafana [Video]


In this short video, Rudy de Busscher shows how to connect MicroProfile Metrics with Prometheus and Grafana to produce useful graphics and to help investigate your microservice architecture. The goal of MicroProfile Metrics is to expose monitoring data from the implementation in a unified way. java microservices microservice architecture microprofile grafana prometheus microprofile metrics

3 Performance Testing Metrics Every Tester Should Know


There are certain performance testing metrics that are essential to understand properly in order to draw the right conclusions from your tests. These metrics require some basic understanding of math and statistics, but nothing too complicated. performance data load testing metrics performance metrics quality metricsMaking sense of the average, standard deviation and percentiles in performance testing reports.

Simplify observability for all your custom metrics (Part 1: StatsD)


In this post we’ll explore how you can use the Davis AI to analyze your StatsD metrics. Making sense of StatsD metrics is challenging. Dynatrace brings AIOps to your StatsD metrics. Automatic observability into Apache Airflow apps by sending StatsD metrics to Dynatrace.

Ingesting JMeter, temperature and humidity metrics: A Dynatrace innovation day report


Dynatrace has recently enhanced its Metrics APIs, allowing everyone to send any type of metric with any set of data dimension to Davis, Dynatrace’s AI engine. In our conversation, I mentioned the new Dynatrace Metrics ingestion and off we went. ?? Dynatrace news.

Announcing enterprise-grade observability at scale for OpenTelemetry custom metrics (Part 2)


Welcome back to the second part of our blog series on how easy it is to get enterprise-grade observability at scale in Dynatrace for your OpenTelemetry custom metrics. Getting specific metrics from libraries that are pre-instrumented with OpenTelemetry (for example, database drivers).

Automate complex metric-related use cases with the Metrics API version 2


Dynatrace collects a huge number of metrics for each OneAgent-monitored host in your environment. Depending on the types of technologies you’re running on individual hosts, the average number of metrics is about 500 per computational node. Besides all the metrics that originate from your hosts, Dynatrace also collects all the important key performance metrics for services and real-user monitored applications as well as cloud platform metrics from AWS, Azure, and Cloud Foundry.

Announcing enterprise-grade observability at scale for your OpenTelemetry custom metrics


As the application owner of an e-commerce application, for example, you can enrich the source code of your application with domain-specific knowledge by adding actionable semantics to collected performance or business metrics. Seamlessly export your OpenTelemetry custom metrics to Dynatrace.

Database Metrics

SQL Shack

Summary There is a multitude of database metrics that we can collect and use to help us understand database and server resource consumption, as well as overall usage. This data can include hardware statistics, such as measures of CPU or memory consumed over time. We can also examine database metadata, including row counts, waits, and […]. Monitoring Performance

Increased focus for your teams with fine-grained access control for your Prometheus, StatsD, and Telegraf metrics


Recently, we simplified StatsD, Telegraf, and Prometheus observability by allowing you to capture and analyze all your custom metrics. Gain fine-grained access control for Prometheus, StatsD, and Telegraf metrics. What if a custom metric is sent to a host in my management zone?

Elevate your dashboards with the new Dynatrace metrics framework


We’ve introduced a new framework for metrics that provides (1) a logical tree structure, (2) globally unique metric keys that ease integration between multiple Dynatrace environments, and (3) more flexibility to extend Dynatrace so it better fits your specific business use cases. Going forward, the new metrics framework will be at the core of everything that you can do with metrics in Dynatrace. Find metrics more quickly with metric categories.

Understanding Software Quality Metrics With Manual and Automated Testing


Understanding software quality metrics, especially in automated testing, helps us identify what is working well and what needs improvement. performance automation testing software quality manual testing metrics. quality metricsLearn more about manual and automated testing! Quality is the true measure of product success. Poor user experience or application performance negates any advantages you achieve in delivery speed or production cost.

Toward a Better Quality Metric for the Video Community

The Netflix TechBlog

VMAF is a video quality metric that Netflix jointly developed with a number of university collaborators and open-sourced on Github. In the rest of this blog, we highlight three other areas of recent development, as our efforts toward making VMAF a better quality metric for the community.

DYOC: Agentless RUM, OpenKit, Metric ingest, and Business Analytics


Agentless RUM, OpenKit, and Metric ingest to the rescue! What insights can we gain from usage metrics that we can feed-back to our product management teams? Doing so is as simple as a click on the Create Metric button and then Pin to Dashboard. Dynatrace news.

Multidimensional analysis 2.0: Analyze, chart, and report on microservices-based metrics without code changes


In an existing application landscape, however, it can be difficult to get to those metrics. A larger financial institution is using the analysis to report business metrics on dashboards and make them accessible via the Dynatrace API. Optimize your application and business performance by analyzing request- and service-based metrics. To take the multidimensional analysis feature to the next level, we seamlessly combined it with our Calculated metrics capability.

How to Publish Spring Boot Actuator Metrics to Dynatrace


Learn more about publishing Spring boot actuator metrics! The metrics generated by the Spring Boot Actuator module of Spring Boot can be easily published to a Dynatrace cloud instance. java tutorial performance spring boot dynatrace micrometer spring actuator metrics monitoringThis article will give you a step-by-step guide for obtaining that.

Dynatrace partners with AWS to provide enterprise-grade, intelligent observability for custom OpenTelemetry metrics


OpenTelemetry metrics are useful for augmenting the fully automatic observability that can be achieved with Dynatrace OneAgent. OpenTelemetry metrics add domain specific data such as business KPIs and license relevant consumption details. Dynatrace news.

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Integrate Dynatrace more easily using the new Metrics REST API


As a full stack monitoring platform, Dynatrace collects a huge number of metrics for each OneAgent monitored host in your environment. Depending on the types of technologies you’re running on your individual hosts, the average number of metrics is about 500 per computational node. All told, there are thousands of metric types that can be charted and that Davis automatically analyzes and alerts on within your Dynatrace environment. New metric identifiers and structure.

Cumulative Layout Shift, The Layout Instability Metric


Cumulative Layout Shift … Continue reading Cumulative Layout Shift, The Layout Instability Metric → Web best PracticesHave you ever started reading an exciting news article but then lose your line because all the text shifted downwards?

Modern UX metrics on WebPageTest

Addy Osmani

This tip covers how to measure modern UX metrics on WebPageTest using the Custom Metrics feature

How to Use Software Productivity Metrics The Right Way


Software engineering productivity or velocity metrics have always been a very debated topic. In this article, I want to list the different velocity metrics and see how and when you can use them, and sometimes perhaps not at all. Let’s start with a review of what software engineering metrics are, and are not. tutorial performance management productivity developer agile development metrics engineer

Dynatrace innovates again with the release of topology-driven auto-adaptive metric baselines


With the advent and ingestion of thousands of custom metrics into Dynatrace, we’ve once again pushed the boundaries of automatic, AI-based root cause analysis with the introduction of auto-adaptive baselines as a foundational concept for Dynatrace topology-driven timeseries measurements.

The “Best” Performance Metrics? Start With These Six


It’s true that what might be considered the “most important” or “best” web performance metrics can vary by industry. Whether you’re new to web performance or you’re an expert working with the business side of your organization to gain buy-in on performance culture, we suggest starting with six specific metrics: Time to Interactive , First Contentful Paint , Visually Complete , Speed Index , Time to First Byte , and Total Content Size. The post The “Best” Performance Metrics?

Metrics from 1M sites

Speed Curve

The number of performance metrics is large and increases every year. It's important to understand what the different metrics represent and pick metrics that are important for your site. Our Evaluating rendering metrics post was a popular (and fun) way to compare and choose rendering metrics. Recently I created this timeline of performance metric medians from the HTTP Archive for the world's top ~1.3 An analysis of Chromium's paint timing metrics.

Displaying Page Load Metrics on Your Site


I was browsing Tim Kadlec’s website and I noticed he had added page load time metrics in the footer. If your browser supports the Paint Timing API you will see a couple of extra metrics: First Paint and First Contentful Paint. First Paint and First Contentful Paint Page load time is a metric that tells us part of the story. I have written before about user perceived performance and metrics that tell how long it takes to render something on the page.

New web performance insights with additional metrics and enhanced Visually complete for synthetic monitors


Recently introduced improvements to Visually complete and new web performance metrics for Real User Monitoring are now available for Synthetic Monitoring as well. Ensure better user experience with paint-focused performance metrics. Track specific performance metrics over a long term.

Analyzing API Call Performance From Different Global Locations Based on cURL Metrics


The cURL component timings are: performance api metrics curl api performance curl metricsMy previous post presented “A Graphical View of API Performance Based on Call Location.” In that post, we analyzed the performance of a week of calls to the World Bank Countries API (which is served from Washington DC) from four different locations around the globe: Washington DC, USA; Oregon, USA; Ireland; and Tokyo, Japan. The API performance across the week showed remarkable consistency.

Evaluating rendering metrics

Speed Curve

Network metrics have been around for decades, but rendering metrics are newer. These are a few of the rendering metrics that currently exist. A brief history of performance metrics. Metrics quantify behavior. In the case of performance metrics, we're trying to capture the behavior of a website in terms of speed and construction. Often, construction metrics are useful for diagnosing the cause of changes in speed metrics.

Introducing Davis data units (DDUs) for increased flexibility with custom metrics


Metrics are an essential functionality provided by the Dynatrace Software Intelligence Platform. Dynatrace OneAgent and ActiveGate extensions provide you with a multitude of metrics. With this in mind, we’ve been looking for a new way of measuring the usage of custom metrics.

Collecting Prometheus Metrics With Azure Monitor


This preview allows for the collection of Prometheus metrics in Azure Monitor. This pod will pull in metrics from your cluster and nodes and make this available to you in Azure Monitor. So far, this has been limited to collecting standard metrics about the nodes, cluster, and pods, so things like CPU, memory usage, etc. Microsoft announced a new preview this week, which I think is a pretty big deal.

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AI-powered custom log metrics for faster troubleshooting


But sometimes you might have a scenario where simple access to log file content is not enough—you need to create a metric for log entries that contain “Error,” for instance, or something more complex like “Error and not Warning.” In such cases, you need the ability to turn log data into custom metrics. Improved monitoring insights with AI-powered custom log metrics. Moreover, you also have the ability to chart these log metrics and pin them to your favorite dashboards.

Beyond Speed: Why You Should Be Tracking Interactive Metrics


In the past, the answer would be based on the load time of a page, but over the years, we have evolved our approach to site speed to incorporate new metrics, alone or in combination with existing metrics. To build fast sites and stay competitive, it is critical for people passionate about performance to stay informed about new metrics and the methodology behind them. The next evolution of performance brought in paint metrics. Modern Interactivity Metrics.

Cutting Through Performance Metrics Fog with the Lighthouse Score


With so many different metrics available to measure dozens of different aspects of a web page, it can be a struggle to know how best to quantify that page’s overall web performance. In this post, we discuss why there are so many metrics, explore what is “the best” metric, and discuss how you can use the Lighthouse Score to better your own performance. Metrics – Thick as Pea Soup. Web Performance lighthouse score performance metrics performance score

New LUX metrics

Speed Curve

Over the winter holiday we added a bunch of new metrics to LUX: First Contentful Paint. You can see all these Long Task and CPU metrics in the LUX Performance dashboard. The Chrome team aggregates the Long Task data into a metric called First CPU Idle. When your site reaches First CPU Idle it's an indication that rendering isn't blocked and the user can interact without experiencing jank, so it's important to keep this metric as low as possible.

User-centric Metrics Matter to Ecommerce. Start with These Five.


Additionally, teams are measuring and tracking key business metrics – conversion rates, cart abandonment rates, customer lifetime value, revenue by traffic source, and so on. Why Are User-centric Metrics Essential for Ecommerce? What we don’t always keep top of mind is that many performance metrics, at their core, are user-centric metrics that are critical for all businesses – and ecommerce businesses in particular – to track.

Key Application Performance Metrics From the Viewpoint of a Statistician-Turned-Developer


Now that you’ve deployed your code, it’s time to monitor it, collect data, and analyze your metrics. You’ve just released your new app into the wild, live in production. Success! Now what? Your job is done, right? Wrong. Without application performance monitoring in place, you can’t accurately determine how well things are going. Are people using your app? Is the app performant? Do the pages load quickly? Are your users experiencing any errors? If so, where? How often?

Using Database Metrics to Predict Application Problems

SQL Shack

Summary Database metrics can be collected, maintained, and used to help predict when processes go awry so problems can be resolved before they become severe. Understanding when an application or process misbehaves is not always easy. We are often left waiting until a server, application, or service breaks or enters an undesirable state before we […]. Alerting Monitoring Performance

We need more inclusive web performance metrics

CSS - Tricks

Scott Jehl argues that performance metrics such as First Contentful Paint and Largest Contentful Paint don’t really capture the full picture of everyone’s experience with websites: These metrics are often touted as measures of usability or meaning, but they are not necessarily meaningful for everyone. Direct Link to Article — Permalink The post We need more inclusive web performance metrics appeared first on CSS-Tricks.

How to Write Good Bug Reports and Gather Quality Metrics Data


Also, you will find information about bug taxonomy fields, which can help you to calculate later various quality metrics that can be used to improve the QA process in the future. I will write a dedicated article about quality metrics and how to calculate and visualize them. performance data metrics bugs data collection blocking bug reportOne of the essential tasks every QA engineer should master is how to log bug reports properly.

User experience score—the one metric to rule them all


Defining a comprehensive user-experience metric gives rise to questions such as: How do we compare the user experience of one session to another? Which metric can be used for the purpose of reporting user experience and tracking it over a period of time? Which metric can be used to drill deeper and analyze the reasons that cause frustrated users to leave your application? A single metric for user experience segmentation. Error metrics. Usability metrics.