Dynatrace

AUGUST 9, 2023

The massive volumes of log data over months, sometimes years, of a breach have made this a complicated and expensive problem to solve. A traditional log-based SIEM approach to security analytics may have served organizations well in simpler on-premises environments. and “was any sensitive data stolen?”

Analytics 207

Analytics Metrics Database Storage 207

Dynatrace

OCTOBER 4, 2022

For IT infrastructure managers and site reliability engineers, or SREs , logs provide a treasure trove of data. But on their own, logs present just another data silo as IT professionals attempt to troubleshoot and remediate problems. Data volume explosion in multicloud environments poses log issues.

Analytics 209

Analytics Storage Infrastructure Metrics 209

CSS Wizardry

NOVEMBER 3, 2020

When first working on a new site-speed engagement, you need to work out quickly where the slowdowns, blindspots, and inefficiencies lie. Google Analytics can show us individual slow pages, but doesn’t necessarily help us build a bigger picture of the site as a whole. Gathering Data. Visualising the Data. See entry 6.

Speed 292

Speed Ecommerce Metrics Analytics 292

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? How does a data lakehouse work?

Artificial Intelligence 197

Artificial Intelligence Storage Analytics Government 197

Dynatrace

JULY 29, 2022

What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.

Analytics 203

Analytics Storage Retail Monitoring 203

Dynatrace

OCTOBER 4, 2022

Some time ago, at a restaurant near Boston, three Dynatrace colleagues dined and discussed the growing data challenge for enterprises. At its core, this challenge involves a rapid increase in the amount—and complexity—of data collected within a company. Work with different and independent data types. Thus, Grail was born.

Artificial Intelligence 257

Artificial Intelligence Analytics Storage Architecture 257

Dynatrace

JULY 29, 2021

The complexity of such deployments has accelerated with the adoption of emerging, open-source technologies that generate telemetry data, which is exploding in terms of volume, speed, and cardinality. All this data is then consumed by Dynatrace Davis® AI for more precise answers, thereby driving AIOps for cloud-native environments.

Analytics 245

Analytics Open Source Serverless Architecture 245

Dynatrace

OCTOBER 12, 2023

To help you raise the quality of your investigation results, Dynatrace offers an easy way of structuring data using DPL Architect. The best thing: the whole process is performed on read when the query is executed, which means you have full flexibility and don’t need to define a structure when ingesting data. >>

Speed 198

Speed AWS C++ Availability 198

Dynatrace

SEPTEMBER 1, 2022

Business analytics is a growing science that’s rising to meet the demands of data-driven decision making within enterprises. Ideally, IT data can inform business-side decisions, but there’s a challenge. But what is business analytics exactly, and how can you feed it with reliable data that ties IT metrics to business outcomes?

Analytics 167

Analytics Ecommerce Metrics Innovation 167

Dynatrace

OCTOBER 6, 2023

Grail: Enterprise-ready data lakehouse Grail, the Dynatrace causational data lakehouse, was explicitly designed for observability and security data, with artificial intelligence integrated into its foundation. Tables are a physical data model, essentially the type of observability data that you can store.

Artificial Intelligence 252

Artificial Intelligence Analytics Metrics Storage 252

Dynatrace

JULY 29, 2022

What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.

Analytics 171

Analytics Storage Retail Monitoring 171

DZone

NOVEMBER 27, 2023

An open-source distributed SQL query engine, Trino is widely used for data analytics on distributed data storage. Optimizing Trino to make it faster can help organizations achieve quicker insights and better user experiences, as well as cut costs and improve infrastructure efficiency and scalability. But how do we do that?

Tuning 162

Tuning Speed Performance Open Source 162

Dynatrace

JANUARY 31, 2024

I have ingested important custom data into Dynatrace, critical to running my applications and making accurate business decisions… but can I trust the accuracy and reliability?” ” Welcome to the world of data observability. At its core, data observability is about ensuring the availability, reliability, and quality of data.

DevOps 187

DevOps Analytics Airlines Metrics 187

Dynatrace

MAY 23, 2024

The jobs executing such workloads are usually required to operate indefinitely on unbounded streams of continuous data and exhibit heterogeneous modes of failure as they run over long periods. Performance is usually a primary concern when using stream processing frameworks.

Engineering 171

Engineering Tuning Latency Open Source 171

Dynatrace

NOVEMBER 15, 2021

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Logs can include data about user inputs, system processes, and hardware states. What is log analytics? Log monitoring vs log analytics.

Analytics 198

Analytics Monitoring Artificial Intelligence DevOps 198

Dynatrace

JUNE 28, 2022

Mobile analytics can help organizations optimize their mobile application performance, earning customer accolades and increasing revenue in the process. Learn how one Dynatrace customer leveraged mobile analytics to ensure a crash-free, five-star mobile application. Add instrumentation and validate incoming mobile analytics data.

Mobile 200

Mobile Analytics Best Practices Software Engineering 200

Dynatrace

JANUARY 23, 2024

AI data analysis can help development teams release software faster and at higher quality. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights? And how can they take advantage of AI without incurring skyrocketing costs to store, manage, and query data?

Performance 176

Performance DevOps Innovation Artificial Intelligence 176

Scalegrid

MAY 13, 2020

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

DZone

OCTOBER 24, 2023

The exponential growth of data presents both immense opportunities and challenges for organizations. Valuable insights are often buried across massive, complex datasets too large and unwieldy for traditional analytics tools to handle.

Analytics 290

Analytics Speed 290

Dynatrace

FEBRUARY 14, 2022

Mobile app monitoring and mobile analytics make this possible. By providing insight into how apps are operating and why they crash, mobile analytics lets you know what’s happening with your apps and what steps you can take to solve potential problems. What is mobile analytics? Why use mobile analytics and app monitoring?

Mobile 170

Mobile Analytics Monitoring Best Practices 170

Dynatrace

SEPTEMBER 23, 2022

But IT teams need to embrace IT automation and new data storage models to benefit from modern clouds. As they enlist cloud models, organizations now confront increasing complexity and a data explosion. Log management and analytics have become a particular challenge. Data explosion hinders better data insight.

Cloud 168

Cloud Artificial Intelligence Innovation Architecture 168

The Netflix TechBlog

JULY 15, 2021

Data Engineers of Netflix?—?Interview Interview with Kevin Wylie This post is part of our “Data Engineers of Netflix” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Kevin Wylie is a Data Engineer on the Content Data Science and Engineering team.

Data Engineering 189

Data Engineering Engineering Entertainment Big Data 189

DZone

NOVEMBER 16, 2023

As live streaming emerges as a way of doing business, the need for data analysis follows up. What's Different About Data Analytics in Live Streaming? Live streaming is one typical use case for real-time data analysis because it stresses speed.

Analytics 124

Analytics Speed Efficiency Processing 124

The Netflix TechBlog

DECEMBER 3, 2022

by Jasmine Omeke , Obi-Ike Nwoke , Olek Gorajek Intro This post is for all data practitioners, who are interested in learning about bootstrapping, standardization and automation of batch data pipelines at Netflix. You may remember Dataflow from the post we wrote last year titled Data pipeline asset management with Dataflow.

Best Practices 358

Best Practices Code Testing Data Engineering 358

Dynatrace

MAY 24, 2024

These criteria include operational excellence, security and data privacy, speed to market, and disruptive innovation. With the insights they gained, the team expanded into developing workflow automations using log management and analytics powered by the Grail data lakehouse.

Technology 205

Technology Technology Analytics Innovation 205

DZone

NOVEMBER 25, 2023

Factors like read and write speed, latency, and data distribution methods are essential. For instance, rapid read and write operations are crucial for applications requiring real-time data analytics. Yet, they are often evaluated in isolation, removed from the business context.

Database 278

Database Latency Speed Metrics 278

Dynatrace

SEPTEMBER 23, 2022

But IT teams need to embrace IT automation and new data storage models to benefit from modern clouds. As they enlist cloud models, organizations now confront increasing complexity and a data explosion. Log management and log analytics have become a particular challenge. Data explosion hinders better data insight.

Cloud 147

Cloud Artificial Intelligence Innovation Architecture 147

Dynatrace

FEBRUARY 9, 2021

New technologies like Xamarin or React Native are accelerating the speed at which organizations release new features and unlock market reach. How do I solve issues quickly while meeting every regional data privacy regulation? Most monitoring tools lack stringent data privacy controls, which could impact the data privacy of end-users.

Analytics 198

Analytics Mobile Performance Monitoring 198

Smashing Magazine

OCTOBER 31, 2023

Answering Common Questions About Interpreting Page Speed Reports Answering Common Questions About Interpreting Page Speed Reports Geoff Graham 2023-10-31T16:00:00+00:00 2023-10-31T17:06:18+00:00 This article is sponsored by DebugBear Running a performance check on your site isn’t too terribly difficult.

Speed 99

Speed Google Website Metrics 99

Dynatrace

FEBRUARY 15, 2023

They need to create new products and maintain existing ones to deliver customer value at speed and scale while managing risk. Teams can now use an observability platform to unify operations, business, and development data to gain automatic, precise answers about cloud environments and user experience.

Analytics 130

Analytics Storage Cloud Code 130

Dynatrace

AUGUST 2, 2021

As objective measurements, they allow us to make data-driven decisions. But without complex analytics to make sense of them in context, metrics are often too raw to be useful on their own. The Data explorer. Custom threshold colors can make charted metrics more glanceable, while table data or lists can speed drilldown analysis.

Metrics 243

Metrics Analytics Google Code 243

Dynatrace

APRIL 8, 2024

Deploy risk-based estimates and models with confidence, accuracy, transparency, and speed. Dynatrace Grail harnesses all this data into an efficient, flexible, powerful, low-maintenance data lakehouse that enables IT leaders and risk managers to get the data they need, in real-time and aggregated in the desired context.

Analytics 189

Analytics Infrastructure Efficiency Technology 189

Dynatrace

FEBRUARY 10, 2023

Data proliferation—as well as a growing need for data analysis—has accelerated. According to recent Dynatrace data, 59% of CIOs say the increasing complexity of their technology stack could soon overload their teams without a more automated approach to IT operations. Digital transformation shows no signs of slowing down.

Efficiency 264

Efficiency Performance Analytics DevOps 264

Dynatrace

JUNE 26, 2023

In what follows, we define software automation as well as software analytics and outline their importance. What is software analytics? This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI. We also discuss the role of AI for IT operations (AIOps) and more.

Software 177

Software Software Analytics Big Data 177

Dynatrace

DECEMBER 5, 2023

Streamline privacy requirements with flexible retention periods Data retention is a critical aspect of data handling, and it’s not just about privacy compliance—it’s about having the flexibility to optimize data storage times in Grail for your Dynatrace use cases. Grail buckets function like folders in a file system.

Storage 159

Storage Healthcare Best Practices Speed 159

DZone

NOVEMBER 20, 2023

ETL—Extract, Transform, Load—is far more than a set of operations; it's a complex dance that transforms raw data into valuable insights, serving as the critical backbone for a range of applications, from data analytics and business intelligence to real-time decision-making platforms.

Processing 124

Processing Performance Analytics Speed 124

Dynatrace

OCTOBER 17, 2023

Data, AI, analytics, and automation are key enablers for efficient IT operations Data is the foundation for AI and IT automation. IT organizations have access to massive volumes of data to troubleshoot, optimize, and secure application environments. 5) in the Gartner report.

Monitoring 215

Monitoring Artificial Intelligence Performance Analytics 215