Dynatrace

MARCH 31, 2021

For quite some time already, Dynatrace has provided full observability into AWS services by ingesting CloudWatch metrics that are published by AWS services. Amazon CloudWatch gathers metric data from various services that run on AWS. Dynatrace ingests this data to perform root-cause analysis using the Dynatrace Davis® AI engine.

AWS 152

AWS Metrics Availability Lambda 152

Dynatrace

FEBRUARY 2, 2023

Should business data be part of your observability solution? Technology and business leaders express increasing interest in integrating business data into their IT observability strategies, citing the value of effective collaboration between business and IT.

Analytics 204

Analytics Metrics DevOps Storage 204

Dynatrace

NOVEMBER 3, 2023

It also requires agencies to develop digital experiences that are user-centric and data-driven. When combined, key metrics will generate an accurate CX index score. But which metrics should your agency include? But which metrics should your agency include? Abandonment rate and data.

Metrics 216

Metrics Government Website Monitoring 216

Dynatrace

NOVEMBER 16, 2021

Dynatrace has recently extended its Kubernetes operator by adding a new feature, the Prometheus OpenMetrics Ingest , which enables you to import Prometheus metrics in Dynatrace and build SLO and anomaly detection dashboards with Prometheus data. Here we’ll explore how to collect Prometheus metrics and what you can achieve with them.

Metrics 203

Metrics Infrastructure Open Source Database 203

DZone

FEBRUARY 20, 2023

The data community is striving to incorporate the core concepts of engineering rigor found in software communities but still has further to go. This talk covers ways to leverage software engineering practices for data engineering and demonstrates how measuring key performance metrics could help build more robust and reliable data pipelines.

Software Engineering 264

Software Engineering Engineering Software Software 264

Dynatrace

JANUARY 4, 2024

While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. But to be successful, data quality is critical. Teams need to ensure the data is accurate and correctly represents real-world scenarios. Consistency.

Government 202

Government Analytics Benchmarking Storage 202

The Netflix TechBlog

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. We expect complete and accurate data at the end of each run.

Data Engineering 264

Data Engineering Engineering Processing Games 264

Dynatrace

SEPTEMBER 28, 2021

The emerging concepts of working with DevOps metrics and DevOps KPIs have really come a long way. DevOps metrics to help you meet your DevOps goals. Like any IT or business project, you’ll need to track critical key metrics. Here are nine key DevOps metrics and DevOps KPIs that will help you be successful.

DevOps 203

DevOps Metrics Traffic Efficiency 203

Dynatrace

MARCH 29, 2023

With this Google Cloud Ready integration, Dynatrace ensures that AlloyDB for PostgreSQL users can now ingest metrics along with existing Google Cloud data. The post Dynatrace announces support of Google Cloud’s AlloyDB for PostgreSQL metrics ingest appeared first on Dynatrace news.

Google 222

Google Metrics Cloud Analytics 222

Dynatrace

JUNE 9, 2023

ln a world driven by macroeconomic uncertainty, businesses increasingly turn to data-driven decision-making to stay agile. They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. All of these factors challenge DevOps maturity.

DevOps 186

DevOps Analytics Storage Metrics 186

DZone

JULY 2, 2020

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.

Metrics 258

Metrics Java Architecture Monitoring 258

Dynatrace

APRIL 7, 2022

One of these solutions is Micrometer which provides 17+ pre-instrumented JVM-based frameworks for data collection and enables instrumentation code with a vendor-neutral API. Micrometer is used for instrumenting both out-of-the-box and custom metrics from Spring Boot applications. That’s a large amount of data to handle.

Metrics 210

Metrics Latency Java Cache 210

The Netflix TechBlog

MARCH 10, 2023

This platform has evolved from supporting studio applications to data science applications, machine-learning applications to discover the assets metadata, and build various data facts. Hence we built the data pipeline that can be used to extract the existing assets metadata and process it specifically to each new use case.

Media 237

Media Traffic Processing Design 237

DZone

JUNE 11, 2023

Application logs and metrics are vital for any application development or maintenance process. However, managing and analyzing logs and metrics can be a daunting task, especially if the application generates a large volume of data. It stores data in a document-oriented index, offering fast search and analytics capabilities.

Metrics 141

Metrics Open Source Analytics Engineering 141

Dynatrace

DECEMBER 9, 2020

Recently we simplified observability for custom metrics and opened up Dynatrace OneAgent for integration of metrics from various sources like StatsD , Telegraf , and Prometheus. We’re therefore happy to introduce the new metric browser , available as an Early Adopter release with Dynatrace version 1.207.

Metrics 148

Metrics Analytics Availability Monitoring 148

DZone

JULY 14, 2021

This article will tell some of the metrics used to evaluate the performance of the classification problems and will also tell when to use which metrics. Some of the metrics used to evaluate the performance of the classification problems are mentioned below:

Metrics 246

Metrics Performance 246

Dynatrace

MAY 17, 2023

That is, relying on metrics, logs, and traces to understand what software is doing and where it’s running into snags. OpenTelemetry, the open source observability tool, has emerged as an industry-standard solution for instrumenting application telemetry data to make it observable.

Metrics 182

Metrics Open Source Traffic Cache 182

Dynatrace

OCTOBER 7, 2020

Dynatrace recently opened up the enterprise-grade functionalities of Dynatrace OneAgent to all the data needed for observability, including metrics, events, logs, traces, and topology data. Davis topology-aware anomaly detection and alerting for your custom metrics.

Metrics 245

Metrics Analytics Storage Monitoring 245

DZone

AUGUST 20, 2022

Observability is a mindset that lets you use data to answer questions about business processes.

Metrics 358

Metrics Processing 358

DZone

OCTOBER 4, 2023

A system becomes 'observable' when it is possible to estimate the current state using only information from outputs, namely sensor data. You can use the data from Observability to identify and troubleshoot problems, optimize performance, and improve security.

Metrics 109

Metrics Systems Performance 109

Dynatrace

OCTOBER 24, 2023

The session focused on how agencies are protecting data within the context of zero trust. Reflecting on their discussion, I identified five emerging “truths” about zero trust and data. Identity is not necessarily as important as data because at the end of the day, we steal identities to get to the data,” said Williamson. “I

Government 222

Government Artificial Intelligence Best Practices Infrastructure 222

The Netflix TechBlog

JANUARY 13, 2022

By Vikram Srivastava and Marcelo Mayworm Netflix has one of the most complex data platforms in the cloud on which our data scientists and engineers run batch and streaming workloads. As our subscribers grow worldwide and Netflix enters the world of gaming , the number of batch workflows and real-time data pipelines increases rapidly.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

DZone

JANUARY 23, 2023

Since I’ve been using SQL as my primary query language for basically my entire professional career, it feels natural for me to interact with data using SQL instead of other newer proprietary query languages. In my life as a cloud engineer, I deal with time series metrics all the time.

Metrics 124

Metrics Infrastructure Database Cloud 124

Dynatrace

OCTOBER 15, 2021

Let’s take a closer look and clear up any confusion about what it is, the telemetry data it covers, and the benefits it can provide. Loosely defined, observability is the ability to understand what’s happening inside a system from the knowledge of the external data it produces, which are usually logs, metrics, and traces.

Open Source 221

Open Source Metrics Cloud Transportation 221

DZone

JANUARY 13, 2023

In this tutorial, you are going to learn about QuestDB SQL extensions which prove to be very useful with time-series data. Using some sample data sets, you will learn how designated timestamps work and how to use extended SQL syntax to write queries on time-series data.

IoT 174

IoT Analytics Database Metrics 174

Dynatrace

FEBRUARY 3, 2021

In Part 1 we explored how you can use the Davis AI to analyze your StatsD metrics. Part 2 showed how to run multidimensional analysis for external metrics that are ingested via the OneAgent Metric API. In Part 3 we discussed how the Davis AI can analyze your metrics from scripting languages like Bash or PowerShell.

Metrics 165

Metrics Open Source Monitoring Technology 165

Dynatrace

APRIL 28, 2023

Optimize cost and availability while staying compliant Observability data like logs and metrics provide automated answers, root cause detection, and security issues. Customer decisions about data retention are often determined by important security, privacy, and legal issues.

Analytics 216

Analytics Storage Infrastructure Metrics 216

Dynatrace

SEPTEMBER 5, 2023

Predictive AI uses machine learning, data analysis, statistical models, and AI methods to predict anomalies, identify patterns, and create forecasts. Through predictive analytics, SREs and DevOps engineers can accurately forecast resource needs based on historical data. Proactive resource allocation. Capacity planning.

Artificial Intelligence 265

Artificial Intelligence DevOps Analytics Engineering 265

DZone

APRIL 3, 2020

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 Testing 226

Performance Testing Metrics Testing Performance 226

Dynatrace

APRIL 7, 2022

One of these solutions is Micrometer which provides 17+ pre-instrumented JVM-based frameworks for data collection and enables instrumentation code with a vendor-neutral API. Micrometer is used for instrumenting both out-of-the-box and custom metrics from Spring Boot applications. That’s a large amount of data to handle.

Metrics 130

Metrics Latency Java Cache 130

Dynatrace

APRIL 7, 2022

One of these solutions is Micrometer which provides 17+ pre-instrumented JVM-based frameworks for data collection and enables instrumentation code with a vendor-neutral API. Micrometer is used for instrumenting both out-of-the-box and custom metrics from Spring Boot applications. That’s a large amount of data to handle.

Metrics 130

Metrics Latency Java Cache 130

Dynatrace

JANUARY 12, 2021

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. In Part 3 we discussed how the Davis AI can analyze your metrics from scripting languages like Bash or PowerShell.

Metrics 180

Metrics Open Source Monitoring Analytics 180

Dynatrace

APRIL 13, 2023

The massive volumes of log data associated with a breach have made cybersecurity forensics a complicated, costly problem to solve. As organizations adopt more cloud-native technologies, observability data—telemetry from applications and infrastructure, including logs, metrics, and traces—and security data are converging.

Analytics 187

Analytics Java Infrastructure Cloud 187

Dynatrace

NOVEMBER 3, 2020

Welcome to the blog series where we give you a deeper dive into the latest awesomeness around Dynatrace : how we bring scale, zero configuration, automatic AI driven alerting, and root cause analysis to all your custom metrics, including open source observability frameworks like StatsD, Telegraf, and Prometheus.

Metrics 159

Metrics Open Source Monitoring Traffic 159

Dynatrace

MARCH 5, 2021

In today’s complex IT environments, the sheer volume of data created makes it impossible for humans to monitor, comprehend, or troubleshoot problems before they impact the experience of your end users. Still, you might have use cases that rely on important custom data streams. Now you can: Alert on the outage of a custom data source.

Metrics 215

Metrics Network Monitoring Infrastructure 215

Gtmetrix

APRIL 5, 2024

We explain the key differences between field and lab data and how you should interpret them. Overview Web performance metrics can be broadly classified into two distinct groups – field data and lab (synthetic data). where the data comes from), and is gathered using different methodologies. In […]

Metrics 75

Metrics Performance 75

Dynatrace

FEBRUARY 20, 2024

Today’s organizations are drowning in data. So, it’s no surprise that data volumes have grown beyond humans’ ability to manage. But the data deluge isn’t the only problem facing enterprises, as many struggle with tool sprawl. Modern observability necessitates a holistic approach to collecting, processing, and analyzing data.

Monitoring 154

Monitoring Education Technology Technology 154