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 Analytics Big Data Architecture 78

The Netflix TechBlog

MAY 4, 2023

Utilizing cloned real traffic, we can exercise the diversity of inputs from a wide range of devices and device application software versions in production. Moreover, allowing the device to execute untested server-side code paths can inadvertently expose an attack surface area for potential misuse.

Traffic 339

Traffic Latency Tuning Systems 339

The Netflix TechBlog

JUNE 1, 2021

Interview with Samuel Setegne Samuel Setegne This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Samuel Setegne is a Senior Software Engineer on the Core Data Science and Engineering team.

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

Dynatrace

AUGUST 14, 2023

Collect user behavior data Organizations typically use analytics software to collect a large volume of data on user behavior from relevant sources. These sources can include the website or app itself, a data warehouse or a customer data platform (CDP), or social media monitoring tools.

Analytics 233

Analytics Social Media Website IoT 233

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 187

Infrastructure Cloud Azure AWS 187

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. Taking AIOps to the next level.

DevOps 202

DevOps Artificial Intelligence Healthcare Innovation 202

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. The Dynatrace Software Intelligence Platform provides all-in-one advanced observability. What sets Dynatrace apart?

Artificial Intelligence 184

Artificial Intelligence Social Media Monitoring IoT 184

The Netflix TechBlog

APRIL 29, 2019

Various software systems are needed to design, build, and operate this CDN infrastructure, and a significant number of them are written in Python. One example is the Spectator Python client library, a library for instrumenting code to record dimensional time series metrics. We also use Python to detect sensitive data using Lanius.

Open Source 279

Open Source Network Infrastructure Big Data 279

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 218

Artificial Intelligence DevOps Innovation Metrics 218

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 202

Java Scalability Traffic Architecture 202

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 210

Processing Big Data Efficiency Engineering 210

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 191

Analytics Innovation Metrics Database 191

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

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. This is something Dynatrace offers users, to make sure monitoring is made easy. What sets Dynatrace apart?

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

High Scalability

APRIL 14, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). T riplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Learn to balance architecture trade-offs and design scalable enterprise-level software. Apply here.

Education 105

Education Software Engineering Scalability Engineering 105

High Scalability

MAY 12, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). T riplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Learn to balance architecture trade-offs and design scalable enterprise-level software. Apply here.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

APRIL 28, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). T riplebyte lets exceptional software engineers skip screening steps at hundreds of top tech companies like Apple, Dropbox, Mixpanel, and Instacart. Learn to balance architecture trade-offs and design scalable enterprise-level software. Apply here.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 24, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). Sisu Data is looking for machine learning engineers who are eager to deliver their features end-to-end, from Jupyter notebook to production, and provide actionable insights to businesses based on their first-party, streaming, and structured relational data.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MAY 26, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). Sisu Data is looking for machine learning engineers who are eager to deliver their features end-to-end, from Jupyter notebook to production, and provide actionable insights to businesses based on their first-party, streaming, and structured relational data.

Education 100

Education AWS Software Engineering Scalability 100

O'Reilly

AUGUST 15, 2023

To follow up on our previous survey about low-code and no-code tools, we decided to run another short survey about tools specifically for software developers—including, but not limited to, GitHub Copilot and ChatGPT. That was a surprise, since many of these tools are supposed to be low- or no-code.

Development 71

Development Programming Speed Open Source 71

High Scalability

MARCH 30, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). Sisu Data is looking for machine learning engineers who are eager to deliver their features end-to-end, from Jupyter notebook to production, and provide actionable insights to businesses based on their first-party, streaming, and structured relational data.

Education 105

Education Software Engineering Engineering Big Data 105

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 166

AWS Cloud Artificial Intelligence IoT 166

Testsigma

JULY 14, 2020

According to Wikipedia, Data-Driven Testing(DDT) is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

Alex Podelko

DECEMBER 19, 2019

How is DevOps changing the Modern Software Development Landscape? , Boris has unique expertise in that area – especially in Big Data applications. And, by the way, you may get a discount with my personal code Podelko10. System Performance Estimation, Evaluation, and Decision (SPEED) by Kingsum Chow, Yingying Wen, Alibaba.

Efficiency 100

Efficiency Artificial Intelligence Scalability Performance 100

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 207

Analytics C++ Innovation Engineering 207

ScaleOut Software

APRIL 3, 2020

What’s missing is a flexible, fast, and easy-to-use software system that can be quickly adapted to track these assets in real time and provide immediate answers for logistics managers. These questions can be answered using the latest data as it streams in from the field. What are real-time digital twins and why are they useful here?

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

What’s missing is a flexible, fast, and easy-to-use software system that can be quickly adapted to track these assets in real time and provide immediate answers for logistics managers. These questions can be answered using the latest data as it streams in from the field. What are real-time digital twins and why are they useful here?

Logistics 52

Logistics Analytics Scalability Cloud 52

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 137

Cloud Big Data AWS Analytics 137

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

NOVEMBER 24, 2020

At the same time, telemetry snapshots are stored in a data lake, such as HDFS , for offline batch analysis and visualization using big data tools like Spark. This new, object-oriented software technique provides a memory-based orchestration framework for tracking and analyzing telemetry from each data source.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

Analytics 52

Analytics IoT Lambda Big Data 52

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. What is test data? The test data required by testing team to test an application can be of two types: 1.

Testing 60

Testing Storage Database Processing 60

All Things Distributed

APRIL 27, 2011

To our shareowners: Random forests, naïve Bayesian estimators, RESTful services, gossip protocols, eventual consistency, data sharding, anti-entropy, Byzantine quorum, erasure coding, vector clocks. Look inside a current textbook on software architecture, and youll find few patterns that we dont apply at Amazon.

Technology 151

Technology Technology AWS Storage 151

Rigor

SEPTEMBER 11, 2019

Rick is a software engineer on the Google Chrome team, “leading an effort to make the web just work for developers.” Patrick is a London-based software developer who specializes in web performance and who describes himself as enjoying “working the entire stack, back-end to front-end, CDN to server.” Rick Byers.

Performance 89

Performance Education Google Website 89

All Things Distributed

MAY 21, 2018

We already have an idea of how digitalization, and above all new technologies like machine learning, big-data analytics or IoT, will change companies' business models — and are already changing them on a wide scale. The workplace of the future. A voice command creates a lot more productivity.

Artificial Intelligence 76

Artificial Intelligence Technology Technology IoT 76

All Things Distributed

NOVEMBER 30, 2016

HubSpot, a marketing and sales software leader, uses a chatbot called GrowthBot to help marketers and sales personnel be more productive by providing access to relevant data and services. Hubspot could take advantage of advanced AI and ML capabilities provided by Amazon Lex, without having to code the algorithms.

AWS 165

AWS Lambda Artificial Intelligence Mobile 165

Highly Scalable

MARCH 1, 2012

No one can expect human users to explicitly control concurrency, integrity, consistency, or data type validity. On the other hand, it turned out that software applications are not so often interested in in-database aggregation and able to control, at least in many cases, integrity and validity themselves.

Database 279

Database Ecommerce Efficiency Engineering 279