Dynatrace

FEBRUARY 14, 2022

Building on its advanced analytics capabilities for Prometheus data , Dynatrace now enables you to create extensions based on Prometheus metrics. Without any coding, these extensions make it easy to ingest data from these technologies and provide tailor-made analysis views and zero-config alerting. Specialized Unified Analysis page.

Technology 219

Technology Technology Metrics Infrastructure 219

Dynatrace

JULY 10, 2023

Here is what a few of these customers say about Dynatrace: “ Dynatrace has been a game changer in our ability to respond to incidents, identify areas for performance tuning, and gain meaningful data from user behavior analysis.” Director of infrastructure, software sector “ Strong technology and stronger people.

Monitoring 222

Monitoring Retail Performance Government 222

Dynatrace

JULY 6, 2022

AIOps brings an additional level of analysis to observability, as well as the ability to respond to events that warrant it. With ever-evolving infrastructure, services, and business objectives, IT teams can’t keep up with routine tasks that require human intervention. IT automation, DevOps, and DevSecOps go together.

Artificial Intelligence 191

Artificial Intelligence Tuning Strategy Big Data 191

Dynatrace

APRIL 25, 2023

These functions are executed by a serverless platform or provider (such as AWS Lambda, Azure Functions or Google Cloud Functions) that manages the underlying infrastructure, scaling and billing. Enable faster development and deployment cycles by abstracting away the infrastructure complexity.

Serverless 210

Serverless Lambda Azure AWS 210

Dynatrace

DECEMBER 5, 2023

Legacy data center infrastructure and software support have kept all the benefits of ARM at, well… arm’s length. Now you have the additional value of log data informing your Dynatrace root cause analysis should a problem arise on this host. Still, we at Dynatrace speak to customers who recognize this value and want to implement it.

Efficiency 268

Efficiency Architecture Energy Monitoring 268

Dynatrace

OCTOBER 7, 2020

Open-source metric sources automatically map to our Smartscape model for AI analytics. Stay tuned for an upcoming blog series where we’ll give you a more hands-on walkthrough of how to ingest any kind of data from StatsD, Telegraf, Prometheus, scripting languages, or our integrated REST API. Davis AI analyzes your StatsD metrics.

Open Source 256

Open Source Metrics Analytics Tuning 256

Dynatrace

FEBRUARY 8, 2021

Putting logs into context with metrics, traces, and the broader application topology enables and improves how companies manage their cloud architectures, platforms and infrastructure, optimizing applications and remediate incidents in a highly efficient way. AI-powered answers and additional context for apps and infrastructure, at scale.

Cloud 260

Cloud Azure Analytics Open Source 260

Dynatrace

SEPTEMBER 29, 2021

Think of containers as the packaging for microservices that separate the content from its environment – the underlying operating system and infrastructure. For a deeper look into how to gain end-to-end observability into Kubernetes environments, tune into the on-demand webinar Harness the Power of Kubernetes Observability.

Open Source 304

Open Source Traffic DevOps Cloud 304

Dynatrace

APRIL 26, 2022

Gartner estimates that by 2025, 70% of digital business initiatives will require infrastructure and operations (I&O) leaders to include digital experience metrics in their business reporting. With DEM solutions, organizations can operate over on-premise network infrastructure or private or public cloud SaaS or IaaS offerings.

Monitoring 206

Monitoring Social Media IoT Metrics 206

Scalegrid

JANUARY 11, 2024

This article strips away the complexities, walking you through best practices, top tools, and strategies you’ll need for a well-defended cloud infrastructure. Cloud security monitoring is key—identifying threats in real-time and mitigating risks before they escalate.

Best Practices 130

Best Practices Cloud Monitoring Strategy 130

Dynatrace

JULY 24, 2023

It enables them to adapt to user feedback swiftly, fine-tune feature releases, and deliver exceptional user experiences, all while maintaining control and minimizing disruption. Change impact analysis is an indispensable process for effectively managing changes within an organization’s infrastructure and applications.

DevOps 222

DevOps Traffic Efficiency Servers 222

Dynatrace

APRIL 21, 2022

To stay tuned, keep an eye on our release notes. Log data analysis. Problem detection and analysis. Generic root cause analysis rules now also consider closed events as they might explain the root cause of a problem. (APM-360327). This will happen with Dynatrace version 1.242 or later. New features and enhancements.

Azure 218

Azure Metrics AWS Monitoring 218

Dynatrace

MAY 15, 2020

This is especially true when we consider the explosive growth of cloud and container environments, where containers are orchestrated and infrastructure is software defined, meaning even the simplest of environments move at speeds beyond manual control, and beyond the speed of legacy Security practices. And this poses a significant risk.

Government 228

Government DevOps Infrastructure Network 228

Dynatrace

JANUARY 19, 2021

Actionable analytics across the?entire Serverless architectures help developers innovate more efficiently and effectively by removing the burden of managing underlying infrastructure. Actionable analytics across the?entire AI-powered answers, provided by?Dynatrace Dynatrace Davis AI. entire stack,?including other services,?regardless

Lambda 211

Lambda Serverless AWS Mobile 211

Dynatrace

MAY 17, 2023

The next level of observability: OneAgent In the first two parts of our series, we used OpenTelemetry to manually instrument our application and send the telemetry data straight to the Dynatrace analytics back end. Let’s take a look at what kind of additional telemetry data we will have at our fingertips with OneAgent.

Metrics 173

Metrics Monitoring Database Network 173

Dynatrace

JUNE 6, 2019

The CNCF introduced the dedicated category Observability and Analysis to their project landscape to cover all things related to the monitoring of cloud-native stacks. The real-time dependency model of your whole environment drives the core of Davis—the Dynatrace full-stack root-cause analytics engine. So stay tuned.

Monitoring 165

Monitoring Tuning Metrics Analytics 165

Dynatrace

DECEMBER 2, 2021

SLOs can be a great way for DevOps and infrastructure teams to use data and performance expectations to make decisions, such as whether to release, and where engineers should focus their time. Dashboards and manual metric collection sheets make remediation processes slow and don’t provide root cause analysis. Promote automation.

Metrics 193

Metrics Best Practices DevOps Infrastructure 193

Dynatrace

JULY 22, 2019

They gather information infrastructure data such as CPU, memory and log files. More information can be found here: /support/help/how-to-use-dynatrace/problem-detection-and-analysis/problem-detection/detection-of-frequent-issues/. It doesn’t apply to infrastructure metrics such as CPU or memory. This is called a frequent issue.

Best Practices 164

Best Practices Artificial Intelligence Monitoring Tuning 164

Dynatrace

DECEMBER 8, 2020

Dynatrace combines RASP and observability for automatic and continuous analysis of applications, libraries, and code runtime in production and pre-production to detect, assess and manage vulnerabilities. Stay tuned – this is only the start. Automatic “crown jewel” protection and comprehensive CISO reporting.

Cloud 292

Cloud Open Source Internet Internet 292

Dynatrace

DECEMBER 9, 2020

Confidence for a safe release is provided by more validation of how the changes impact quality, for example, before deploying to production or with impact analysis during blue/green deployments. We are moving from static to very dynamic infrastructure and applications.

Metrics 152

Metrics Engineering Google Monitoring 152

Dynatrace

JUNE 13, 2019

Data analysis within large and highly dynamic microservices environments is the biggest challenge that Application Performance Monitoring (APM) vendors face today. The real challenge is robust and effective analysis of such data. Why are we doing this? What Dynatrace will contribute.

IoT 46

IoT C++ Analytics Java 46

O'Reilly Software

APRIL 4, 2018

Those were the days when “connected” meant having some web presence, “interactions” were measured in number of clicks, and the analysis happened in batch overnight processes. The data shape will dictate capacity planning, tuning of the backbone, and scalability analysis for individual components. At least once? At most once?

Architecture 80

Architecture Scalability Google Operating System 80

Rigor

SEPTEMBER 3, 2019

RUM or analytics data (funnel analysis) can help you determine the user flows that drive the majority of your business and that will be most critical on high-load days. Traffic patterns outside of normal [RUM or Analytics]. Drop in cart completions, increase in abandonment or other key conversion events [RUM or Analytics].

Website 74

Website Cache Ecommerce Traffic 74

The Netflix TechBlog

APRIL 29, 2019

An easy, though imprecise, way of thinking about Netflix infrastructure is that everything that happens before you press Play on your remote control (e.g., Various software systems are needed to design, build, and operate this CDN infrastructure, and a significant number of them are written in Python. are you logged in?

Open Source 279

Open Source Network Infrastructure Big Data 279

O'Reilly

NOVEMBER 28, 2023

AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. Even with cloud-based foundation models like GPT-4, which eliminate the need to develop your own model or provide your own infrastructure, fine-tuning a model for any particular use case is still a major undertaking. of nonusers, 5.4%

Open Source 108

Open Source Artificial Intelligence Google Infrastructure 108

The Netflix TechBlog

JANUARY 10, 2024

Reloaded was created as a single monolithic system, where developers from various media teams in ET and our platform partner team Content Infrastructure and Solutions (CIS)¹ worked on the same codebase, building a single system that handled all media assets. The service also provides options that allow fine-tuning latency, throughput, etc.,

Processing 229

Processing Media Latency Innovation 229

The Netflix TechBlog

JULY 26, 2021

Such a paradigm aspires to assist front-line operations personnel and stakeholders in “running the business”²; performing their tasks through means such as ad hoc analysis, decision-support, and tracking (of tasks, assets, schedules, etc). Data Mesh leverages Iceberg tables as data warehouse sinks for downstream analytics use cases.

Big Data 253

Big Data Government Analytics Processing 253

The Netflix TechBlog

MARCH 7, 2019

To unlock these innovations we are making a strategic choice that our focus should be geared towards developing the surrounding infrastructure so that scientists’ work can be easily absorbed into the wider Netflix Experimentation Platform. In the democratization of the experimentation platform we also want to allow custom analysis.

Engineering 174

Engineering Design Innovation Java 174

High Scalability

NOVEMBER 25, 2019

Infrastructure Optimization. What Infrastructure Do You Use? Eventually, we resorted to caching the events in memory for a short duration and also tuning the GC settings on those nodes as we are doing a lot of young generation collections. Nagios, Grafana and New Relic and some internal proactive exception analysis are used.

Architecture 52

Architecture Cache Azure Storage 52