The Netflix TechBlog

MARCH 25, 2019

Now, imagine yourself in the role of a software engineer responsible for a micro-service which publishes data consumed by few critical customer facing services (e.g. You are about to make structural changes to the data and want to know who and what downstream to your service will be impacted.

Infrastructure 225

Infrastructure Big Data Transportation Architecture 225

Dynatrace

JUNE 26, 2023

Software analytics offers the ability to gain and share insights from data emitted by software systems and related operational processes to develop higher-quality software faster while operating it efficiently and securely. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI.

Software 246

Software Software Analytics Big Data 246

The Netflix TechBlog

JUNE 1, 2021

Data Engineers of Netflix?—?Interview 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. What drew you to Netflix?

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

Dynatrace

APRIL 20, 2023

Causal AI—which brings AI-enabled actionable insights to IT operations—and a data lakehouse, such as Dynatrace Grail , can help break down silos among ITOps, DevSecOps, site reliability engineering, and business analytics teams. Logs are automatically produced and time-stamped documentation of events relevant to cloud architectures.

Analytics 246

Analytics Infrastructure Storage Architecture 246

Dynatrace

OCTOBER 4, 2022

Limited data availability constrains value creation. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes. Grail addresses today’s challenges of big data and cloud everywhere: Grail is highly scalable, cost-effective, and super-fast.

Analytics 264

Analytics Artificial Intelligence Storage Serverless 264

Dynatrace

JUNE 29, 2022

To drive better outcomes using hybrid cloud architectures, it helps to understand their benefits—and how to orchestrate them seamlessly. What is hybrid cloud architecture? Hybrid cloud architecture is a computing environment that shares data and applications on a combination of public clouds and on-premises private clouds.

Infrastructure 246

Infrastructure Cloud Azure AWS 246

DZone

JULY 29, 2019

These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on. One of the top trending open-source data storage that responds to most of the use cases is Elasticsearch.

Big Data 162

Big Data Government Open Source Storage 162

Dynatrace

JULY 6, 2022

As organizations continue to adopt multicloud strategies, the complexity of these environments grows, increasing the need to automate cloud engineering operations to ensure organizations can enforce their policies and architecture principles. Big data automation tools. Batch process automation.

Artificial Intelligence 246

Artificial Intelligence Tuning Strategy Big Data 246

The Netflix TechBlog

JUNE 7, 2021

Flow Exporter The Flow Exporter is a sidecar that uses eBPF tracepoints to capture TCP flows at near real time on instances that power the Netflix microservices architecture. After several iterations of the architecture and some tuning, the solution has proven to be able to scale. What is BPF?

Network 327

Network Transportation AWS Cloud 327

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges.

Big Data 63

Big Data Storage Benchmarking Hardware 63

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

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. See the health of your big data resources at a glance. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 227

Azure Cloud Big Data Virtualization 227

Dynatrace

MARCH 24, 2023

Docker Swarm First introduced in 2014 by Docker, Docker Swarm is an orchestration engine that popularized the use of containers with developers. The Docker file format is used broadly for orchestration engines, and Docker Engine ships with Docker Swarm and Kubernetes frameworks included. The post What is container orchestration?

Infrastructure 246

Infrastructure Open Source Operating System Cloud 246

Uber Engineering

JANUARY 15, 2020

Uber leverages real-time analytics on aggregate data to improve the user experience across our products, from fighting fraudulent behavior on Uber Eats to forecasting demand on our platform. .

Engineering 141

Engineering Analytics Big Data Database 141

Dynatrace

JANUARY 16, 2023

Most Kubernetes clusters in the cloud (73%) are built on top of managed distributions from the hyperscalers like AWS Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE). Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch.

Open Source 358

Open Source Java Operating System Programming 358

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

DECEMBER 15, 2022

AIOps (artificial intelligence for IT operations) combines big data, AI algorithms, and machine learning for actionable, real-time insights that help ITOps continuously improve operations. ITOps vs. AIOps. The three core components of an AIOps solution are the following: 1. ” The post What is ITOps?

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

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. Rule Execution Engine is responsible for matching the collected logs against a set of predefined rules.

Tuning 217

Tuning Efficiency Big Data Engineering 217

The Netflix TechBlog

NOVEMBER 20, 2023

It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. 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. past 3 hours or 10 days).

Processing 219

Processing Big Data Efficiency Engineering 219

Uber Engineering

AUGUST 14, 2019

Once identified, … The post Less is More: Engineering Data Warehouse Efficiency with Minimalist Design appeared first on Uber Engineering Blog. In our experience, optimizing for operational efficiency requires answering one key question: for which tables does the maintenance cost supersede utility?

Efficiency 110

Efficiency Engineering Design Storage 110

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.” But what is AIOps, exactly? And how can it support your organization? What is AIOps? Challenges of traditional AIOps. AIOps use cases.

Artificial Intelligence 246

Artificial Intelligence DevOps Innovation Metrics 246

The Netflix TechBlog

MAY 26, 2020

As with any sustainable engineering design, focusing on simplicity is very important. These characteristics allow for an on-call response time that is relaxed and more in line with traditional big data analytical pipelines. After several iterations of this architecture and some tuning, Sqooby has proven to be able to scale.

Network 154

Network Tuning AWS Traffic 154

Uber Engineering

APRIL 5, 2018

Three years ago, Uber Engineering adopted Hadoop as the storage ( HDFS ) and compute ( YARN ) infrastructure for our organization’s big data analysis.

Systems 109

Systems Big Data Storage Infrastructure 109

Dynatrace

MARCH 14, 2022

AIOps (or “AI for IT operations”) uses artificial intelligence so that big data can help IT teams work faster and more effectively. Over the past few years, the company has undergone a digital transformation, migrating to a hybrid, cloud-native environment built on Amazon Web Services and a microservices architecture.

Healthcare 246

Healthcare Artificial Intelligence Innovation Strategy 246

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. The four stages of data processing. AIOps supports that with the ability to assess applications during development, delivery, and deployment.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

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. These two narratives of reference architecture and ingestion/indexing system are interwoven throughout the paper. Why do we need a new reference architecture?

Cloud 104

Cloud Big Data Latency Architecture 104

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 127

Technology Technology AWS Storage 127

ACM Sigarch

NOVEMBER 1, 2019

This blog post gives a glimpse of the computer systems research papers presented at the USENIX Annual Technical Conference (ATC) 2019, with an emphasis on systems that use new hardware architectures. As a consequence, the vast majority of the papers in the past has usually focused on conventional X86 or GPU-accelerated architectures.

Architecture 12

Architecture Hardware Cache Storage 12

The Netflix TechBlog

DECEMBER 21, 2020

This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture. Some of the optimizations are prerequisites for a high-performance data warehouse.

Storage 212

Storage Latency Efficiency Data Engineering 212

Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution.

Strategy 130

Strategy Cloud Infrastructure Artificial Intelligence 130

All Things Distributed

NOVEMBER 15, 2010

Building general purpose architectures has always been hard; there are often so many conflicting requirements that you cannot derive an architecture that will serve all, so we have often ended up focusing on one side of the requirements that allow you to serve that area really well. From CPU to GPU.

AWS 125

AWS Programming Latency Architecture 125

ScaleOut Software

JULY 19, 2021

Today’s streaming analytics architectures are not equipped to make sense of this rapidly changing information and react to it as it arrives. This data is also periodically uploaded to a data lake for offline batch analysis that calculates key statistics and looks for big trends that can help optimize operations.

IoT 78

IoT Big Data Analytics Architecture 78

High Scalability

APRIL 14, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! this is going to be a challenging journey for any backend engineer! Learn to balance architecture trade-offs and design scalable enterprise-level software. Please 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). this is going to be a challenging journey for any backend engineer! this is going to be a challenging journey for any backend engineer! Learn to balance architecture trade-offs and design scalable enterprise-level software. Please 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). this is going to be a challenging journey for any backend engineer! this is going to be a challenging journey for any backend engineer! Learn to balance architecture trade-offs and design scalable enterprise-level software. Please apply here.

Education 102

Education Software Engineering Scalability Engineering 102

Scalegrid

FEBRUARY 11, 2025

Key Takeaways MySQL is a relational database management system ideal for structured data and complex relationships, ensuring data integrity and reliability. MongoDB stores data as JSON documents, presenting a flexible approach compared to the structured tabular format used by MySQL.

Scalability 147

Scalability Database Storage IoT 147

High Scalability

MAY 26, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! this is going to be a challenging journey for any backend engineer! Created by former senior-level AWS engineers of 15 years. Try out their platform. Please apply here.

Education 100

Education AWS Software Engineering Scalability 100