The Netflix TechBlog

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management.

Infrastructure 225

Infrastructure Big Data Transportation Architecture 225

Dynatrace

MARCH 11, 2021

In the fourth part of the series, I’ll show you how I used Dynatrace’s raw problem and event data to find the best fit for optimized anomaly detection settings. I took a big-data-analysis approach, which started with another problem visualization. Statistically analyzing Dynatrace’s event and problem data.

Tuning 264

Tuning Architecture Big Data Monitoring 264

Dynatrace

JANUARY 16, 2023

Messaging : RabbitMQ and Kafka are the two main messaging and event streaming systems used. Specifically, they provide asynchronous communications within microservices architectures and high-throughput distributed systems. Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch.

Open Source 358

Open Source Java Operating System Programming 358

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. Performance.

Big Data 63

Big Data Storage Benchmarking Hardware 63

The Netflix TechBlog

MAY 4, 2023

When undertaking system migrations, one of the main challenges is establishing confidence and seamlessly transitioning the traffic to the upgraded architecture without adversely impacting the customer experience. This blog series will examine the tools, techniques, and strategies we have utilized to achieve this goal.

Traffic 347

Traffic Latency Tuning Systems 347

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.” Typically, only the aggregated events will be accessible to ML and will often exclude additional details. What is AIOps?

Artificial Intelligence 246

Artificial Intelligence DevOps Innovation Metrics 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. CloudOps includes processes such as incident management and event management. CloudOps: Applying AIOps to multicloud operations.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 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. Logs on Grail Log data is foundational for any IT analytics.

Analytics 246

Analytics Innovation Metrics Database 246

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. There are two main approaches to AIOps: Traditional AIOps: Machine learning models identify correlations between IT events. Gartner introduced the concept of AIOps in 2016.

Healthcare 246

Healthcare Artificial Intelligence Innovation Strategy 246

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. How to modernize ITOps with AIOps.

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

The Netflix TechBlog

MAY 26, 2020

It is easier to tune a large Spark job for a consistent volume of data. As you may know, S3 can emit messages when events (such as a file creation events) occur which can be directed into an AWS SQS queue. These events represent a specific cut of data from the table.

Network 154

Network Tuning AWS Big Data 154

The Netflix TechBlog

JUNE 20, 2024

To address this, we propose developing an intelligent agent that can automatically discover, map, and query all data within an enterprise. This “Enterprise Data Model/Architect Agent” employs generative AI techniques for autonomous enterprise data modeling and architecture. Until next time!

Data Engineering 206

Data Engineering Engineering Entertainment Software Engineering 206

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

APRIL 11, 2023

Cloud application security remains challenging because organizations lack end-to-end visibility into cloud architecture. As organizations migrate applications to the cloud, they must balance the agility that microservices architecture brings with the complexity and lack of transparency that can also come with it.

Cloud 246

Cloud DevOps Open Source Retail 246

Dynatrace

APRIL 25, 2023

Exploratory analytics with collaborative analytics capabilities can be a lifeline for CloudOps, ITOps, site reliability engineering, and other teams struggling to access, analyze, and conquer the never-ending deluge of big data. These analytics can help teams understand the stories hidden within the data and share valuable insights.

Analytics 246

Analytics Big Data Media Operating System 246

Dynatrace

MARCH 24, 2023

Using Marathon, its data center operating system (DC/OS) plugin, Mesos becomes a full container orchestration environment that, like Kubernetes and Docker Swarm, discovers services, balances loads, and manages application containers. Mesos also supports other orchestration engines, including Kubernetes and Docker Swarm.

Infrastructure 246

Infrastructure Open Source Operating System Cloud 246

The Morning Paper

OCTOBER 26, 2020

As a production system within Microsoft capturing around a quadrillion events and indexing 16 trillion search keys per day it would be interesting in its own right, but there’s a lot more to it than that. These two narratives of reference architecture and ingestion/indexing system are interwoven throughout the paper.

Cloud 104

Cloud Big Data Latency Architecture 104

Scalegrid

JUNE 28, 2024

Integrating such a backend service system supported by RabbitMQ into a web application’s architecture can drastically alter its operational dynamics. It enables the smooth processing of various actions like uploading user content, sending notifications, or performing heavy-duty data operations.

IoT 130

IoT Healthcare Programming Open Source 130

The Netflix TechBlog

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. 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.

Storage 212

Storage Latency Efficiency Data Engineering 212

The Netflix TechBlog

NOVEMBER 3, 2023

The Data Mesh SQL Processor is a platform-managed, parameterized Flink Job that takes schematized sources and a Flink SQL query that will be executed against those sources. By leveraging Flink SQL within a Data Mesh Processor, we were able to support the streaming SQL functionality without changing the architecture of Data Mesh.

Processing 271

Processing Engineering Infrastructure Latency 271

All Things Distributed

SEPTEMBER 26, 2014

We’re at 925 Market Street and our doors will be open 10AM to 6PM on weekdays, with select events running until 8PM on weeknights. Be sure to check the calendar regularly as new evening events will be added regularly. What’s Happening at the AWS Loft. And don’t be shy—walk-ins are welcome too. AWS Technical Bootcamps.

AWS 93

AWS Games Education Innovation 93

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

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

Scalegrid

MARCH 28, 2024

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Memcached shines in scenarios where a simple, fast, and efficient caching solution is required without data persistence.

Cache 130

Cache Storage Scalability Architecture 130

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

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., We’re not told how Seer figures out that a major architectural change has happened. ASPLOS’19. Seer also works best when making prediction 10-100ms into the future.

Big Data 45

Big Data Cloud Performance Hardware 45

All Things Distributed

JULY 16, 2012

It is shaping up to be a great event with many Amazonians, partners and customers presenting in well over 150 sessions. The first annual AWS user and partner conference will be held November 27-29 at The Venetian in Las Vega.

AWS 69

AWS Big Data Media Storage 69

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

High Scalability

MAY 26, 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 100

Education AWS Software Engineering Scalability 100

All Things Distributed

MAY 27, 2015

Bring your questions about AWS architecture, cost optimization, services and features, and anything else AWS related. Technical Presentations: AWS solution architects, product managers, and evangelists deliver technical presentations covering some of the highest-rated and best-attended sessions from recent AWS events.

AWS 76

AWS Education Big Data Games 76

Abhishek Tiwari

DECEMBER 27, 2017

A common theme across all these trends is to remove the complexity by simplifying data management as a whole. In 2018, we anticipate that ETL will either lose relevance or the ETL process will disintegrate and be consumed by new data architectures. Unified data management architecture.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

All Things Distributed

SEPTEMBER 30, 2010

Visiting future customers is equally exiting as you get a change to understand their current architecture, if it is a migration, and how they plan to exploit cloud services in their new setup. AWS Startup Event in Tel Aviv on October 12 with customers Porticor , SemantiNet , Live Definition. Driving down the cost of Big-Data analytics.

AWS 66

AWS Cloud Storage Best Practices 66

Highly Scalable

MARCH 10, 2015

The demand on a given product depends on many factors including a product’s own properties such as price or brand, prices of competing products in the category, sales events, and even the weather. This model can be adjusted to a retailer’s business use cases by adding more explanatory variables such as marketing events. Sale events.

Retail 152

Retail C++ Analytics Metrics 152

The Morning Paper

JUNE 23, 2019

The stateless + RInk (S+RInK) architecture attempts to provide the best of both worlds: to simultaneously offer both the implementation and operational simplicity of stateless application servers and the performance benefits of servers caching state in RAM. We’ve seen similar high marshalling overheads in big data systems too.)

Cache 79

Cache Latency Google Network 79

Abhishek Tiwari

DECEMBER 22, 2017

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. In addition, this approach is more tailored for both structured as well unstructured data sets. Classic ETL.

Big Data 40

Big Data Retail Storage Google 40

Brendan Gregg

APRIL 30, 2018

USENIX’s LISA conference is the premier event for topics in production system engineering. LISA is a vendor-neutral event known for technical depth and rigor, and continues to attract an audience of seasoned professionals. Join us for 3 days in Nashville at LISA'18. Post by Brendan Gregg and Rikki Endsley. Hope to see you in Nashville!

DevOps 41

DevOps Network Best Practices Programming 41