Dynatrace

JANUARY 17, 2023

The release candidate of OpenTelemetry metrics was announced earlier this year at Kubecon in Valencia, Spain. Since then, organizations have embraced OTLP as an all-in-one protocol for observability signals, including metrics, traces, and logs, which will also gain Dynatrace support in early 2023.

Analytics 285

Analytics Metrics Open Source Java 285

Dynatrace

NOVEMBER 14, 2023

Site reliability engineering (SRE) has become increasingly important to organizations looking to keep up with the rapid pace of digital transformation. Effective site reliability engineering requires enterprise-wide transformation Without a unified understanding of SRE practices, organizational silos can quickly form between departments.

Best Practices 196

Best Practices Engineering DevOps Software Engineering 196

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 206

Analytics Metrics DevOps Storage 206

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 154

AWS Metrics Availability Lambda 154

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 204

Government Analytics Benchmarking Storage 204

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. Out of the box, Dynatrace also works with Google Cloud’s Cloud Run, BigQuery, Compute Engine, and dozens of other native Google Cloud services and offerings.

Google 224

Google Metrics Cloud Analytics 224

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 147

Metrics Open Source Analytics Engineering 147

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 206

Metrics Infrastructure Open Source Database 206

Dynatrace

SEPTEMBER 5, 2023

Predictive AI uses machine learning, data analysis, statistical models, and AI methods to predict anomalies, identify patterns, and create forecasts. Predictive AI empowers site reliability engineers (SREs) and DevOps engineers to detect anomalies and irregular patterns in their systems long before they escalate into critical incidents.

Artificial Intelligence 266

Artificial Intelligence DevOps Analytics Engineering 266

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 212

Metrics Latency Java Cache 212

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. And we can’t discount the productivity impact it causes on data platform users.

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 133

Metrics Infrastructure Database Cloud 133

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 246

Metrics Analytics Storage Monitoring 246

Dynatrace

AUGUST 26, 2020

We are proud to s hare Dynatrace has been named the winner in the “ Best Overall AI-based Analytics Company ” category, recognized for our innovation and the business-driving impact of our AI engine, Davis. . The post Dynatrace wins AI Breakthrough Award for Davis AI engine appeared first on Dynatrace blog.

Engineering 304

Engineering DevOps Innovation AWS 304

DZone

FEBRUARY 25, 2021

QA performance metrics are essential for eliminating inefficient strategies and improving internal processes. They also enable managers to track the progress of their QA team over time and make data-driven decisions about future projects.

Metrics 153

Metrics Performance Strategy Engineering 153

Dynatrace

APRIL 30, 2021

But because of the complexity involved in executing and analyzing test results of dynamic systems, performance engineering is difficult to scale — especially with lean staff or resources. Grabner also introduced four ways organizations can turbocharge their performance engineering with automation.

Engineering 204

Engineering Testing Performance Performance Testing 204

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

The Netflix TechBlog

JUNE 15, 2022

By Alex Hutter , Falguni Jhaveri , and Senthil Sayeebaba In a previous post , we described the indexing architecture of Studio Search and how we scaled the architecture by building a config-driven self-service platform that allowed teams in Content Engineering to spin up search indices easily.

Engineering 183

Engineering Architecture Availability Tuning 183

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 217

Metrics Network Monitoring Infrastructure 217

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 155

Monitoring Education Technology Technology 155

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 178

IoT Analytics Database Metrics 178

Dynatrace

DECEMBER 28, 2020

Welcome back to the blog series where we provide you with deeper dives into the latest observability awesomeness from Dynatrace , demonstrating 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 151

Metrics Open Source Monitoring Engineering 151

Dynatrace

MARCH 23, 2020

Our procurement decisions were based on trace data that was pulled from a handful of fragmented monitoring solutions. The data had to be painstakingly stitched together over the course of a few weeks, across each layer of our stack. High fidelity data, zero developer involvement. The effort was exhausting to say the least.

Google 195

Google Engineering Metrics Hardware 195

Dynatrace

APRIL 21, 2021

Metrics that offer measurable, repeatable insight into the user experience from the moment they arrive on a website from a mobile or desktop device. Great user experiences start with Core Web Vitals (CWVs) — a set of metrics defined by Google to help measure user experience at scale. When do these metrics matter?

Metrics 134

Metrics Google Website Speed 134

Dynatrace

JUNE 3, 2022

At the heart of Dynatrace Digital Experience Monitoring (DEM) is Davis, the state-of-the-art AI engine that accurately prioritizes the severity of each detected performance anomaly in terms of its potential impact on real users and business KPIs. This ensures greater agility and reduces the time to resolution.

Metrics 228

Metrics Mobile IoT Monitoring 228

The Netflix TechBlog

SEPTEMBER 18, 2020

and what the role entails by Julie Beckley & Chris Pham This Q&A provides insights into the diverse set of skills, projects, and culture within Data Science and Engineering (DSE) at Netflix through the eyes of two team members: Chris Pham and Julie Beckley. What was your path to working in data? There’s us to the right!

Analytics 223

Analytics Education Innovation Engineering 223

Dynatrace

MAY 7, 2024

Fluent Bit is a telemetry agent designed to receive data (logs, traces, and metrics), process or modify it, and export it to a destination. Fluent Bit can serve as a proxy before you send data to Dynatrace or similar. However, you can also use Fluent Bit as a processor because you can perform various actions on the data.

Best Practices 248

Best Practices IoT Metrics Storage 248

DZone

APRIL 23, 2019

One of the essential tasks every QA engineer should master is how to log bug reports properly. 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.

Metrics 100

Metrics Strategy Testing Engineering 100

Dynatrace

FEBRUARY 28, 2024

Doing so reduces the risk of production disruptions and instills confidence in both SREs (Site Reliability Engineers) and end-users. Foremost among these is the complexity associated with data gathering and analysis. The main goal of this stage is to identify and address any issues or problems that were detected.

DevOps 208

DevOps Metrics Engineering Analytics 208

Dynatrace

MARCH 18, 2024

Following FinOps practices, engineering, finance, and business teams take responsibility for their cloud usage, making data-driven spending decisions in a scalable and sustainable manner. Empowering teams to manage their FinOps practices, however, requires teams to have access to reliable multicloud monitoring and analysis data.

Best Practices 237

Best Practices Strategy Cloud AWS 237

DZone

MAY 15, 2020

Now that you’ve deployed your code, it’s time to monitor it, collect data, and analyze your metrics. The first step to gather this type of data is application monitoring. The first step to gather this type of data is application monitoring. Once you have data though, it’s important to analyze it correctly.

Metrics 246

Metrics Performance Development Monitoring 246

Dynatrace

JUNE 28, 2019

Dynatrace leverages high-fidelity data to fuel Davis, our AI-driven causation engine for automatic monitoring insights. 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. Dynatrace news.

Metrics 142

Metrics Monitoring Efficiency Availability 142

Dynatrace

DECEMBER 4, 2023

“Engineers today lack an easy way to track the tokens and prompt usage of their LLM applications in production. Data quality and drift: Monitoring the quality and characteristics of training and runtime data to detect significant changes that might impact model accuracy. Maintained under the Apache 2.0

Open Source 262

Open Source Latency Metrics Java 262

Dynatrace

MAY 31, 2023

As a result, site reliability has emerged as a critical success metric for many organizations. Site reliability engineering (SRE) has recently become a critical discipline in recent years as the world has shifted in favor of web-based interactions. Mobile retail e-commerce spending in the U. Service-level objectives (SLOs).

Best Practices 227

Best Practices DevOps Latency Metrics 227

Percona

APRIL 14, 2023

A shared characteristic in most (if not all) databases, be them traditional relational databases like Oracle, MySQL, and PostgreSQL or some kind of NoSQL-style database like MongoDB, is the use of a caching mechanism to keep (a copy of) part of the data in memory. So, how do you know if your hot data is in memory? MySQL does.

Cache 89

Cache Efficiency Database Monitoring 89

Tasktop

JANUARY 5, 2022

Flow Metrics are a major pillar of how we measure improvement in value streams. . As organizations begin to adopt Flow Metrics , our natural tendencies emerge to massage the newfound visibility to make the metrics “look good”. Flow Metrics anti-pattern: Excluding part of the value stream.

Metrics 98

Metrics Speed Analytics Azure 98