Dynatrace

MAY 2, 2024

Across the globe, privacy laws grant individuals data subject rights, such as the right to access and delete personal data processed about them. Successful compliance with privacy rights requests involves tracking and verifying requests across the entire data ecosystem, including third-party services.

Tuning 278

Tuning Scalability Efficiency Processing 278

Dynatrace

MARCH 4, 2020

It helps you identify errors, analyze areas of struggle, and provides tons of analytical data for your testing teams. We’ve developed Session Replay with data privacy regulations and laws in mind, including GDPR (in Europe), California Consumer Privacy Act (CCPA), and Brazilian General Data Protection Law (LGPD).

Tuning 306

Tuning Analytics Strategy Website 306

Dynatrace

APRIL 15, 2025

Our talk was called “Putting the Experience in UX: The Importance of Making Data Accessible.” OpenTelemetry provides us with a standard for generating, collecting, and emitting telemetry, and we have existing tooling that leverages OTel data to help us understand work processes and workflows.

Open Source 260

Open Source Energy Benchmarking Tuning 260

The Netflix TechBlog

FEBRUARY 14, 2025

Every image you hover over isnt just a visual placeholder; its a critical data point that fuels our sophisticated personalization engine. This nuanced integration of data and technology empowers us to offer bespoke content recommendations. This queue ensures we are consistently capturing raw events from our global userbase.

Tuning 166

Tuning Latency Efficiency Storage 166

Dynatrace

MARCH 15, 2024

As organizations strive for observability and data democratization, OpenTelemetry emerges as a key technology to create and transfer observability data. Understanding OpenTelemetry OpenTelemetry is an open, vendor-neutral standard for creating, collecting, and transferring telemetry data, like traces, metrics, and logs.

Open Source 306

Open Source Best Practices Infrastructure Tuning 306

The Netflix TechBlog

AUGUST 1, 2022

Data Mesh?—?A A Data Movement and Processing Platform @ Netflix By Bo Lei , Guilherme Pires , James Shao , Kasturi Chatterjee , Sujay Jain , Vlad Sydorenko Background Realtime processing technologies (A.K.A After evaluating the options , the team has decided to create Data Mesh as our next generation data pipeline solution.

Processing 273

Processing Transportation Entertainment Tuning 273

Dynatrace

MAY 21, 2024

Observing complex environments involves handling regulatory, compliance, and data governance requirements. This continuously evolving landscape requires careful management and clarity regarding how sensitive data is used. This is particularly important when dealing with large volumes of data.

Government 277

Government Storage Tuning Monitoring 277

The Netflix TechBlog

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

Latency 252

Latency Storage Big Data Tuning 252

The Netflix TechBlog

SEPTEMBER 18, 2024

Second, developers had to constantly re-learn new data modeling practices and common yet critical data access patterns. To overcome these challenges, we developed a holistic approach that builds upon our Data Gateway Platform. Data Model At its core, the KV abstraction is built around a two-level map architecture.

Latency 260

Latency Storage Cache Servers 260

The Netflix TechBlog

NOVEMBER 3, 2023

Democratizing Stream Processing @ Netflix By Guil Pires , Mark Cho , Mingliang Liu , Sujay Jain Data powers much of what we do at Netflix. On the Data Platform team, we build the infrastructure used across the company to process data at scale. The existing Data Mesh Processors have a lot of overlap with SQL.

Processing 271

Processing Engineering Infrastructure Latency 271

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.

Big Data 257

Big Data Government Processing Analytics 257

DZone

AUGUST 21, 2021

This article describes 3 different tricks that I used in dealing with big data sets (order of 10 million records) and that proved to enhance performance dramatically. Trick 1: CLOB Instead of Result Set.

Big Data 246

Big Data Performance Tuning Mobile 246

DZone

JUNE 6, 2023

When building an IoT-based service, we need to implement a messaging mechanism that transmits data collected by the IoT devices to a hub or a server. That mechanism is known as a messaging protocol. A messaging protocol is a set of rules and formats that are agreed upon among entities that want to communicate with each other.

IoT 305

IoT Tuning Storage Network 305

The Netflix TechBlog

OCTOBER 8, 2024

Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.

Latency 239

Latency Storage Traffic Tuning 239

DZone

FEBRUARY 4, 2025

Understanding Teradata Data Distribution and Performance Optimization Teradata performance optimization and database tuning are crucial for modern enterprise data warehouses.

Performance 173

Performance Tuning Analytics Strategy 173

DZone

FEBRUARY 27, 2024

Understanding the structures within a Relational Database Management System (RDBMS) is critical to optimizing performance and managing data effectively. Here's a breakdown of the concepts with examples. RDBMS Structures 1.

Database 264

Database Tuning Systems Performance 264

DZone

NOVEMBER 27, 2023

An open-source distributed SQL query engine, Trino is widely used for data analytics on distributed data storage. In this article, we will show you how to tune Trino by helping you identify performance bottlenecks and provide tuning tips that you can practice. But how do we do that?

Tuning 162

Tuning Speed Performance Open Source 162

Dynatrace

FEBRUARY 6, 2025

Welcome, data enthusiasts! Whether you’re a seasoned IT expert or a marketing professional looking to improve business performance, understanding the data available to you is essential. In this blog series, we’ll guide you through creating powerful dashboards that transform complex data into actionable insights.

Metrics 243

Metrics Infrastructure Monitoring Best Practices 243

Dynatrace

NOVEMBER 6, 2023

Recently, the Parliament of India released the Digital Personal Data Protection Act 2023 , which regulates the processing of digital personal data in India and recognizes the right of individuals to protect their data in India. Dynatrace is constantly evaluating the further expansion of its regional presence of Dynatrace SaaS.

AWS 264

AWS Azure Tuning Analytics 264

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 242

Big Data Infrastructure Metrics Games 242

The Netflix TechBlog

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 212

Storage Latency Efficiency Data Engineering 212

DZone

NOVEMBER 4, 2024

In an era characterized by an exponential increase in data generation, organizations must effectively leverage this wealth of information to maintain their competitive edge. As data engineers, we are tasked with implementing these sophisticated solutions, ensuring organizations can derive actionable insights from vast datasets.

Retail 130

Retail Performance Best Practices Tuning 130

The Netflix TechBlog

DECEMBER 17, 2024

Metric definitions are often scattered across various databases, documentation sites, and code repositories, making it difficult for analysts and data scientists to find reliable information quickly. LORE: How were democratizing analytics atNetflix Apurva Kansara At Netflix, we rely on data and analytics to inform critical business decisions.

Analytics 212

Analytics Engineering Entertainment Metrics 212

Dynatrace

JULY 13, 2023

Krishan and I discuss the data privacy and security concerns associated with TikTok and its parent company, Bytedance. This two-part episode of Tech Transforms explores how the federal government is addressing artificial intelligence and data privacy, specifically as it relates to ChatGPT and TikTok.

Artificial Intelligence 245

Artificial Intelligence Social Media Media Government 245

The Netflix TechBlog

JUNE 20, 2024

A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024 The Data Engineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.

Data Engineering 206

Data Engineering Engineering Entertainment Software Engineering 206

Dynatrace

APRIL 20, 2023

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. based financial services group, discussed how the bank uses log monitoring on the Dynatrace platform with an emphasis on observability and security data.

Analytics 246

Analytics Infrastructure Storage Architecture 246

DZone

AUGUST 30, 2023

Hyperparameter tuning is an essential practice in optimizing the performance of machine learning models. This article provides an in-depth exploration of advanced hyperparameter tuning methods, including Population-Based Training (PBT), BOHB, ASHA, TPE, Optuna, DEHB, Meta-Gradient Descent, BOSS, and SNIPER. What Are Hyperparameters?

Tuning 147

Tuning Government Network Processing 147

Scalegrid

FEBRUARY 6, 2025

RabbitMQ is designed for flexible routing and message reliability, while Kafka handles high-throughput event streaming and real-time data processing. Both serve distinct purposes, from managing message queues to ingesting large data volumes.

Latency 147

Latency Analytics Architecture Storage 147

Dynatrace

FEBRUARY 16, 2023

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 246

Analytics Innovation Metrics Database 246

Dynatrace

APRIL 22, 2022

Although many companies adopt solutions such as OpenTelemetry, Prometheus, and Grafana as part of their observability strategy, they often confront a common data analysis problem: data silos. When teams, tools, and data are siloed, it’s harder for organizations to succeed. This leads to multiple tool-specific dashboards.

Open Source 244

Open Source Metrics Cloud Tuning 244

Dynatrace

FEBRUARY 25, 2025

However, its history is marked by critical security flaws leading to data breaches. Implementing File Upload with Apache Struts 2 The Struts 2 framework simplifies file uploads by automatically storing uploaded files in a temporary location and passing the file data to the action class.

Servers 214

Servers Processing Java Tuning 214

The Netflix TechBlog

MARCH 4, 2024

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. We have also noted a great potential for further improvement by model tuning (see the section of Rollout in Production).

Tuning 217

Tuning Efficiency Big Data Engineering 217

Dynatrace

MARCH 11, 2024

In recent years, technologists and business leaders have dubbed data as “the new oil.” Because both oil and data require their owners to refine them to unleash their true value. So how do you realize the vast potential of data while protecting it from threats? Is data the new oil?

Artificial Intelligence 246

Artificial Intelligence Government Games Tuning 246

The Netflix TechBlog

MARCH 4, 2025

Store the data in an optimized, highly distributed datastore. Additionally, some collectors will instead poll our kafka queue for impressions data. This data is processed from a real-time impressions stream into a Kafka queue, which our title health system regularly polls. Track real-time title impressions from the NetflixUI.

Traffic 180

Traffic Strategy Entertainment Innovation 180

DZone

FEBRUARY 22, 2024

We create custom applications in Salesforce that are built on top of customer or transactional data from Salesforce data tables. About Query Performance It is obvious that the performance of your query completely depends on the complexity of data you currently have in your production org.

Tuning 173

Tuning Efficiency Performance Development 173

DZone

MARCH 7, 2023

Apache Spark is a powerful open-source distributed computing framework that provides a variety of APIs to support big data processing. In addition, pySpark applications can be tuned to optimize performance and achieve better execution time, scalability, and resource utilization.

Big Data 173

Big Data Code Tuning Open Source 173

The Netflix TechBlog

DECEMBER 17, 2024

Metadata and assets must be correctly configured, data must flow seamlessly, microservices must process titles without error, and algorithms must function as intended. This allows us to focus on data analysis and problem-solving rather than managing complex systemchanges. This could lead to an exponential increase in logged data.

Traffic 172

Traffic Scalability Strategy Monitoring 172