The Netflix TechBlog

OCTOBER 15, 2019

Another thread or process is constantly polling events from the log table and writes them to one or multiple datastores, optionally removing events from the log table after acknowledged by all datastores. In Netflix the microservice architecture is widely adopted and each microservice typically handles only one type of data.

Transportation 192

Transportation Architecture Processing Storage 192

ScaleOut Software

NOVEMBER 24, 2020

However, telematics architectures face challenges in responding to telemetry in real time. Current Telematics Architecture. The volume of incoming telemetry challenges current telematics systems to keep up and quickly make sense of all the data. Challenges for Current Architectures.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Percona

JANUARY 19, 2023

Some startups adopted MySQL in its early days such as Facebook, Uber, Pinterest, and many more, which are now big and successful companies that prove that MySQL can run on large databases and on heavily used sites. There are many compression tools and algorithms for data out there. 1 mysql mysql 592K Dec 30 02:48 tb1.ibd

Open Source 90

Open Source Storage Database Big Data 90

Scalegrid

FEBRUARY 8, 2024

At its core, a distributed storage system comprises three main components: a controller for managing the system’s operations, an internal datastore where information is held, and databases geared towards ensuring scalability, partitioning capabilities, and high availability for all types of data.

Storage 130

Storage Systems Big Data Azure 130

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

Dynatrace

MAY 1, 2023

IT operations analytics is the process of unifying, storing, and contextually analyzing operational data to understand the health of applications, infrastructure, and environments and streamline everyday operations. ITOA automates repetitive cloud operations tasks and streamlines the flow of analytics into decision-making processes.

Analytics 198

Analytics Artificial Intelligence Big Data Open Source 198

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 Artificial Intelligence Infrastructure 130

The Netflix TechBlog

JULY 26, 2021

Netflix is known for its loosely coupled microservice architecture and with a global studio footprint, surfacing and connecting the data from microservices into a studio data catalog in real time has become more important than ever. In the initial stage, data consumers set up ETL pipelines directly pulling data from databases.

Big Data 253

Big Data Government Analytics Processing 253

Dynatrace

APRIL 20, 2023

Logs highlight observability challenges Ingesting, storing, and processing the unprecedented explosion of data from sources such as software as a service, multicloud environments, containers, and serverless architectures can be overwhelming for today’s organizations. But what about value versus cost?

Analytics 197

Analytics Infrastructure Storage Efficiency 197

Dynatrace

FEBRUARY 16, 2023

The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes. Grail data lakehouse delivers massively parallel processing for answers at scale Modern cloud-native computing is constantly upping the ante on data volume, variety, and velocity.

Analytics 196

Analytics Innovation Metrics Database 196

SQL Server According to Bob

FEBRUARY 15, 2018

Microsoft engineering is actually sending quite a few folks over the Atlantic to come talk about SQL Server 2017, SQL Server on Linux, GDPR, Performance, Security, Azure Data Lake, Azure SQL Database, Azure SQL Data Warehouse, and Azure CosmosDB. Best practices on Building a Big Data Analytics Solution – Michael Rys.

Engineering 40

Engineering Azure Best Practices Servers 40

Dynatrace

JANUARY 11, 2023

As cloud and big data complexity scales beyond the ability of traditional monitoring tools to handle, next-generation cloud monitoring and observability are becoming necessities for IT teams. Database monitoring. This ensures the database queries are performant, while also identifying host problems. Website monitoring.

Cloud 231

Cloud Monitoring Best Practices Infrastructure 231

All Things Distributed

JULY 13, 2010

Customers with complex computational workloads such as tightly coupled, parallel processes, or with applications that are very sensitive to network performance, can now achieve the same high compute and networking performance provided by custom-built infrastructure while benefiting from the elasticity, flexibility and cost advantages of Amazon EC2.

Cloud 118

Cloud AWS Automotive Latency 118

ScaleOut Software

APRIL 3, 2020

These questions can be answered using the latest data as it streams in from the field. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins. Besides just tracking assets, real-time digital twins also can track needs.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

These questions can be answered using the latest data as it streams in from the field. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins. Besides just tracking assets, real-time digital twins also can track needs.

Logistics 52

Logistics Analytics Scalability Cloud 52

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 219

Infrastructure Big Data Transportation Architecture 219

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 191

Infrastructure Cloud Azure AWS 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. 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

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.

Latency 243

Latency Storage Big Data Tuning 243

The Netflix TechBlog

DECEMBER 21, 2020

There are several benefits of such optimizations like saving on storage, faster query time, cheaper downstream processing, and an increase in developer productivity by removing additional ETLs written only for query performance improvement. Some of the optimizations are prerequisites for a high-performance data warehouse.

Storage 203

Storage Latency Efficiency Data Engineering 203

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

Dynatrace

MARCH 11, 2021

I took a big-data-analysis approach, which started with another problem visualization. If during the ticket handling another alert is raised this process repeats – but maybe with a different set of people who are working in parallel. The raw event and problem data from Dynatrace for analysis stored in InfluxDB.

Tuning 264

Tuning Architecture Monitoring Big Data 264

Abhishek Tiwari

DECEMBER 27, 2017

ETL refers to extract, transform, load and it is generally used for data warehousing and data integration. ETL is a product of the relational database era and it has not evolved much in last decade. There are several emerging data trends that will define the future of ETL in 2018. Unified data management architecture.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

The Morning Paper

JUNE 23, 2019

Factor VI in the 12-factor app manifesto , “Execute the app as one or more stateless processes,” to be dropped and replaced with “Execute the app as one or more stateful processes.” session state that you want to survive an application process crash), and to keep the application server/services layer stateless.

Cache 79

Cache Latency Google Lambda 79

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

All Things Distributed

NOVEMBER 15, 2010

From financial processing and traditional oil & gas exploration HPC applications to integrating complex 3D graphics into online and mobile applications, the applications of GPU processing appear to be limitless. Because of its focus on latency, the generic CPU yielded rather inefficient system for graphics processing.

AWS 136

AWS Latency Programming Architecture 136

All Things Distributed

MARCH 28, 2011

The methods for accessing these objects is also rapidly changing; where in the past you needed a PC or a Laptop to access these objects, now many of our electronic devices have become capable of processing them. a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. Countdown to What is Next in AWS.

AWS 138

AWS Cloud Storage Internet 138

Highly Scalable

MARCH 10, 2015

More specialized data mining applications like supply chain optimization and fraud detection are out of scope, as well as the implementation details of the data mining process (such as evaluation of model quality). Outputs of this tier can be used to configure downstream processes.

Retail 152

Retail C++ Analytics Metrics 152

All Things Distributed

NOVEMBER 15, 2016

Previously, I wrote about Amazon QuickSight , a new service targeted at business users that aims to simplify the process of deriving insights from a wide variety of data sources quickly, easily, and at a low cost. Put simply, data is not always readily available and accessible to organizational end users.

Analytics 152

Analytics Availability Media Social Media 152