Dynatrace

OCTOBER 4, 2022

While data lakehouses combine the flexibility and cost-efficiency of data lakes with the querying capabilities of data warehouses, it’s important to understand how these storage environments differ. Data warehouses. Data warehouses were the original big data storage option.

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

The Netflix TechBlog

MAY 4, 2023

Adding forking logic and complexity to the device code can create dependencies on device application release cycles that generally run at a slower cadence than service release cycles, leading to bottlenecks in the migration. There is also an increased risk that bugs in the replay logic have the potential to impact production code and metrics.

Traffic 347

Traffic Latency Tuning Systems 347

Dynatrace

APRIL 21, 2021

To do this effectively, you need a big data processing approach. First Input Delay can be improved by reducing the impact of third-party code, redoing JavaScript execution time, minimizing main thread work, and keeping requests counts low and transfer sizes small. How do you know where to focus first with failing pages?

Traffic 264

Traffic Mobile Metrics Analytics 264

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support.

Artificial Intelligence 254

Artificial Intelligence Social Media Monitoring IoT 254

The Netflix TechBlog

OCTOBER 27, 2020

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. The processed data is typically stored as data warehouse tables in AWS S3. Moving data with Bulldozer at Netflix.

Latency 252

Latency Storage Big Data Tuning 252

Dynatrace

APRIL 11, 2023

For example, the open source Java library at the heart of the Log4Shell crisis in 2021 was patched within days given the pervasiveness of the code. How vulnerabilities are evaluated – platform module Learn the mechanism that Dynatrace Application Security uses to generate third-party vulnerabilities and code-level vulnerabilities.

Cloud 246

Cloud DevOps Open Source Retail 246

DZone

APRIL 15, 2022

Since I was dealing with legacy code, I needed to understand the value assigned to each property and also analyze whether it is relevant for the present-day load or not. Since we were using Apache tomcat’s JDBC connection pool, I started reading the source code to get a better understanding.

Database 245

Database Code Big Data Performance 245

Dynatrace

JUNE 29, 2022

A hybrid cloud, however, combines public infrastructure and services with on-premises resources or a private data center to create a flexible, interconnected IT environment. Hybrid environments provide more options for storing and analyzing ever-growing volumes of big data and for deploying digital services.

Infrastructure 246

Infrastructure Cloud Azure AWS 246

The Netflix TechBlog

FEBRUARY 16, 2021

Operational Efficiency: The majority of the changes require metadata configuration files and library code changes, usually taking days of testing and service release to adopt the updates. Besides, the mixed-use of the metadata files and business logic code adds another layer of maintenance complexity.

Mobile 218

Mobile Engineering Infrastructure Scalability 218

All Things Distributed

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things.

AWS 154

AWS Cloud Artificial Intelligence IoT 154

Dynatrace

AUGUST 14, 2023

These sources can include the website or app itself, a data warehouse or a customer data platform (CDP), or social media monitoring tools. An organization may collect this data the following ways. Using application programming interfaces (APIs) to instrument a wider range of digital touchpoints.

Analytics 246

Analytics Social Media Website IoT 246

Dynatrace

FEBRUARY 16, 2023

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 246

Analytics Innovation Metrics Database 246

The Netflix TechBlog

SEPTEMBER 18, 2020

I bring my breadth of big data tools and technologies while Julie has been building statistical models for the past decade. A lot of my learning and training was self-guided until 2016, when a manager at my last company took a chance on me and helped me make the rare transfer from a role in HR to Data Science.

Analytics 230

Analytics Education Innovation Engineering 230

The Netflix TechBlog

OCTOBER 18, 2022

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 211

Java Scalability Traffic Architecture 211

Dynatrace

MARCH 11, 2021

I took a big-data-analysis approach, which started with another problem visualization. With R (or RStudio) you can efficiently perform analysis on large data sets. It’s easy to learn and with a little coding, you can get amazing results quickly! But that didn’t work for me. Visualizing problem noise.

Tuning 264

Tuning Architecture Monitoring Big Data 264

The Netflix TechBlog

JUNE 1, 2021

clinical data was often small enough to fit into memory on an average computer and only in rare cases would its computation require any technical ingenuity or massive computing power. There was not enough scope to explore the distributed and large-scale computing challenges that usually come with big data processing.

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

Dynatrace

OCTOBER 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. But before that new code can be deployed, it needs to be tested and reviewed from a security perspective.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support.

Monitoring 173

Monitoring Performance Social Media Artificial Intelligence 173

The Netflix TechBlog

NOVEMBER 20, 2023

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing. append, overwrite, etc.).

Processing 219

Processing Big Data Efficiency Engineering 219

The Morning Paper

OCTOBER 26, 2020

Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. What follows is a discussion of where big data systems might be heading, heavily inspired by the remarks in this paper, but with several of my own thoughts mixed in.

Cloud 104

Cloud Big Data Latency Architecture 104

Dynatrace

OCTOBER 14, 2021

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” This means data sources typically come from disparate infrastructure monitoring tools and second-generation APM solutions.

Artificial Intelligence 246

Artificial Intelligence DevOps Innovation Metrics 246

Highly Scalable

MAY 1, 2012

Let us start with a simple example that illustrates capabilities of probabilistic data structures: Let us have a data set that is simply a heap of ten million random integer values and we know that it contains not more than one million distinct values (there are many duplicates). what is the cardinality of the data set)?

Analytics 191

Analytics Traffic Big Data Efficiency 191

ScaleOut Software

JULY 19, 2021

What makes in-memory computing unique and powerful is its two-fold ability to host fast-changing data in memory and run analytics code within a few milliseconds after new data arrives. Unlike manual or automatic log queries, in-memory computing can continuously run analytics code on all incoming data and instantly find issues.

IoT 78

IoT Big Data Analytics Architecture 78

All Things Distributed

OCTOBER 7, 2015

Today, I am excited to share with you a brand new service called Amazon QuickSight that aims to simplify the process of deriving insights from a wide variety of data sources in a fast and affordable manner. Big data challenges. We believe this is one of the critical parts of our big data offerings.

Cloud 112

Cloud Big Data AWS Analytics 112

O'Reilly

JANUARY 13, 2020

The experimental DSL for code contracts gives developers the ability to provide guarantees about the ways that code behaves. Code contracts allow you to make these promises, and the compiler can use them to loosen compile-time checks. Does your function have side effects? Is it guaranteed to return a non-null value?

Programming 144

Programming Java Google C++ 144

Scalegrid

JUNE 28, 2024

This allows developers to adopt RabbitMQ without learning new coding languages or making substantial changes to their workflows. Can RabbitMQ handle the high-throughput needs of big data applications? For high-throughput big data applications, RabbitMQ may fall short of expectations.

IoT 130

IoT Healthcare Programming Open Source 130

The Netflix TechBlog

MARCH 2, 2021

I started working at a local payment processing company after graduation, where I built survival models to calculate lifetime value and experimented with them on our brand new big data stack. I was doing data science without realizing it. Coding with statistical software and SQL are my most widely used technical skills.

Analytics 216

Analytics C++ Innovation Engineering 216

O'Reilly

SEPTEMBER 19, 2023

” Each step has been a twist on “what if we could write code to interact with a tamper-resistant ledger in real-time?” ” I’ve called out the data field’s rebranding efforts before; but even then, I acknowledged that these weren’t just new coats of paint. And, often, to giving up.

Hardware 135

Hardware Storage Big Data Blockchain 135

O'Reilly

FEBRUARY 4, 2025

They were succeeded by programmers writing machine instructions as binary code to be input one bit at a time by flipping switches on the front of a computer. It lets a programmer use a human-like language to tell the computer to move data to locations in memory and perform calculations on it. No code became a buzzword.

Programming 145

Programming Google Infrastructure Internet 145

Highly Scalable

MARCH 1, 2012

An important feature of a Geohash is its ability to estimate distance between regions using bit-wise code proximity, as is shown in the figure. Geohash encoding allows one to store geographical information using plain data models, like sorted key values preserving spatial relationships.

Database 279

Database Ecommerce Efficiency Engineering 279

High Scalability

MARCH 24, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

APRIL 14, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Scalability Engineering 105

High Scalability

MAY 12, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

APRIL 28, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 102

Education Software Engineering Scalability Engineering 102

All Things Distributed

JUNE 26, 2016

AdiMap uses Amazon Kinesis to process real-time streaming online ad data and job feeds, and processes them for storage in petabyte-scale Amazon Redshift. Advanced problem solving that connects big data with machine learning. warehouses to glean business insights for jobs, ad spend, or financials for mobile apps.

AWS 77

AWS Cloud Healthcare Blockchain 77

High Scalability

MARCH 30, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Engineering Big Data 105

Scalegrid

MARCH 14, 2024

Effective hybrid cloud management requires robust tools and techniques for centralized administration, policy enforcement, cost management, and modern infrastructure practices like Infrastructure-as-Code (IaC) and containers. It results in consistently configured environments and allows for swift deployment.

Strategy 130

Strategy Cloud Infrastructure Artificial Intelligence 130