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

DZone

JANUARY 19, 2023

Because with the advent of cloud providers, we are less worried about managing data centers. This leads to an increase in the size of data as well. Big data is generated and transported using various mediums in single requests. Though we are not worried about computing resources, the latency becomes an overhead.

Best Practices 262

Best Practices Transportation Big Data Latency 262

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. We have also noted a great potential for further improvement by model tuning (see the section of Rollout in Production).

Tuning 214

Tuning Efficiency Big Data Engineering 214

The Netflix TechBlog

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 209

Storage Latency Efficiency Data Engineering 209

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. Five queries improve substantially on both latency and total compute hours.

Big Data 57

Big Data Analytics Latency Azure 57

The Netflix TechBlog

MAY 4, 2023

It can happen on an edge API system servicing customer devices, between the edge and mid-tier services, or from mid-tiers to data stores. It provides a good read on the availability and latency ranges under different production conditions. For instance, envision a response payload that delivers media streams for a playback session.

Traffic 344

Traffic Latency Tuning Systems 344

The Netflix TechBlog

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

Processing 215

Processing Big Data Efficiency Engineering 215

The Netflix TechBlog

JULY 21, 2022

We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform. With large data, comes the opportunity to leverage the data for predictive and classification based analysis.

Big Data 184

Big Data Cache Engineering Data Engineering 184

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., on end-to-end latency) and less than 0.15% on throughput. This tracing system is similar to Dapper and Zipkin and records per-microservice latencies and number of outstanding requests. ASPLOS’19.

Big Data 45

Big Data Cloud Performance Hardware 45

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

InfoQ

APRIL 15, 2024

He specifically delved into Venice DB, the NoSQL data store used for feature persistence. At the QCon London 2024 conference, Félix GV from LinkedIn discussed the AI/ML platform powering the company’s products. By Rafal Gancarz

Artificial Intelligence 109

Artificial Intelligence Big Data Data Engineering Latency 109

Dynatrace

DECEMBER 15, 2022

Complex cloud computing environments are increasingly replacing traditional data centers. In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. Why is IT operations important?

Artificial Intelligence 215

Artificial Intelligence DevOps Hardware Virtualization 215

The Morning Paper

OCTOBER 26, 2020

On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. PVLDB’20. Emphasis mine ).

Cloud 104

Cloud Big Data Latency Architecture 104

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130

Cache Storage Architecture Scalability 130

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 153

Azure Cloud Big Data Virtualization 153

VoltDB

OCTOBER 17, 2024

The automotive industry is more reliant than ever on real-time data – and not just the manufacturers but also the dealers. Some industry experts are even seeing the automotive industry’s use of real-time data as a pioneering chapter for real-time data in general that will soon spread to other industries.

Automotive 52

Automotive IoT Energy Artificial Intelligence 52

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

ScaleOut Software

JULY 19, 2021

Incoming data is saved into data storage (historian database or log store) for query by operational managers who must attempt to find the highest priority issues that require their attention. 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

Scalegrid

MARCH 14, 2024

Implementing a hybrid cloud solution involves careful decision-making regarding application and data placement, migration strategies, and choosing compatible cloud service providers while ensuring seamless integration and addressing security and compliance challenges.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

All Things Distributed

NOVEMBER 5, 2015

This region will provide even lower latency and strong data sovereignty to local users. The AWS UK region will be our third in the European Union (EU), and we're shooting to have it ready by the end of 2016 (or early 2017). Public Sector & Not-for-Profit – UCAS , Makewaves , JustGiving.

AWS 167

AWS Retail Entertainment IoT 167

Abhishek Tiwari

DECEMBER 27, 2017

ETL refers to extract, transform, load and it is generally used for data warehousing and data integration. There are several emerging data trends that will define the future of ETL in 2018. A common theme across all these trends is to remove the complexity by simplifying data management as a whole.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

All Things Distributed

SEPTEMBER 5, 2013

Over the past few years, two important trends that have been disrupting the database industry are mobile applications and big data. The explosive growth in mobile devices and mobile apps is generating a huge amount of data, which has fueled the demand for big data services and for high scale databases.

Big Data 87

Big Data Mobile Latency Database 87

ACM Sigarch

MAY 31, 2023

Heterogeneous and Composable Memory (HCM) offers a feasible solution for terabyte- or petabyte-scale systems, addressing the performance and efficiency demands of emerging big-data applications. even lowered the latency by introducing a multi-headed device that collapses switches and memory controllers.

Latency 52

Latency Hardware Cache Architecture 52

Adrian Cockcroft

NOVEMBER 18, 2024

In this lightning talk, learn how customers are using AWS to perform millions of calculations on real-time grid data to execute the scenario analysis, simulations, and operational planning necessary to operate a dynamic power grid. This presentation is brought to you by Capgemini, an AWS Partner.

AWS 98

AWS Energy Lambda Government 98

VoltDB

MARCH 13, 2024

In the age of big-data-turned-massive-data, maintaining high availability , aka ultra-reliability, aka ‘uptime’, has become “paramount”, to use a ChatGPT word. In a sense, yes, especially if it runs on applications that can’t afford to lose data or go down. Are we saying your business depends on high availability?

Availability 52

Availability Latency DevOps Systems 52

InfoQ

JULY 3, 2023

The new solution achieved over 99% hit rate, helped reduce tail latencies by more than 60% and costs by 10% annually. LinkedIn introduced Couchbase as a centralized caching tier for scaling member profile reads to handle increasing traffic that has outgrown their existing database cluster. By Rafal Gancarz

Cache 85

Cache Latency Traffic Database 85

The Morning Paper

JUNE 23, 2019

Coupled with stateless application servers to execute business logic and a database-like system to provide persistent storage, they form a core component of popular data center service archictectures. If you want to store time-expiring data that should be shared across application processes, used Memcached or Redis.

Cache 79

Cache Latency Google Network 79

All Things Distributed

JANUARY 6, 2016

A region in South Korea has been highly requested by companies around the world who want to take full advantage of Korea’s world-leading Internet connectivity and provide their customers with quick, low-latency access to websites, mobile applications, games, SaaS applications, and more.

AWS 105

AWS Cloud Games Latency 105

All Things Distributed

NOVEMBER 12, 2012

This new Asia Pacific (Sydney) Region has been highly requested by companies worldwide, and it provides low latency access to AWS services for those who target customers in Australia and New Zealand. Today, Amazon Web Services has greater worldwide coverage with the launch of a new AWS Region in Sydney, Australia.

Cloud 106

Cloud AWS Ecommerce Latency 106

All Things Distributed

DECEMBER 12, 2018

They can run applications in Sweden, serve end users across the Nordics with lower latency, and leverage advanced technologies such as containers, serverless computing, and more. The first platform is a real time, big data platform being used for analyzing traffic usage patterns to identify congestion and connectivity issues.

AWS 121

AWS Cloud Games Serverless 121

All Things Distributed

MARCH 2, 2011

Japanese companies and consumers have become used to low latency and high-speed networking available between their businesses, residences, and mobile devices. The advanced Asia Pacific network infrastructure also makes the AWS Tokyo Region a viable low-latency option for customers from South Korea. Spot Instances - Increased Control.

AWS 104

AWS Cloud Games Latency 104

All Things Distributed

DECEMBER 14, 2011

This new Region has been highly requested by companies worldwide, and it provides low-latency access to AWS services for those who target customers in South America. The new Sao Paulo Region provides better latency to South America, which enables AWS customers to deliver higher performance services to their South American end-users.

AWS 112

AWS Latency Storage Cloud 112

All Things Distributed

AUGUST 16, 2011

There are different considerations when deciding where to allocate resources with latency and cost being the two obvious ones, but compliance sometimes plays an important role as well. Government and Big Data. One particular early use case for AWS GovCloud (US) will be massive data processing and analytics.

AWS 102

AWS Government Big Data Cloud 102

All Things Distributed

NOVEMBER 15, 2010

For example, the most fundamental abstraction trade-off has always been latency versus throughput. Modern CPUs strongly favor lower latency of operations with clock cycles in the nanoseconds and we have built general purpose software architectures that can exploit these low latencies very well. General Purpose GPU programming.

AWS 130

AWS Programming Latency Architecture 130

All Things Distributed

DECEMBER 3, 2009

This new Region consists of multiple Availability Zones and provides low-latency access to the AWS services from for example the Bay Area. Driving down the cost of Big-Data analytics. We have expanded the AWS footprint in the US and starting today a new AWS Region is available for use: US-West (Northern California).

AWS 60

AWS Cloud Latency Storage 60

All Things Distributed

JULY 13, 2010

Further computationally intensive, highly parallel workloads have found their way to Amazon EC2 as businesses have explored using HPC types of algorithms for other application categories, for example to to process very large unstructured data sets for Business Intelligence applications. Driving down the cost of Big-Data analytics.

Cloud 110

Cloud AWS Automotive Latency 110

All Things Distributed

JULY 11, 2011

Spot Instances are ideal for use cases like web and data crawling, financial analysis, grid computing, media transcoding, scientific research, and batch processing. Driving down the cost of Big-Data analytics. However, customers with these use cases need a way to more easily and reliably target Availability Zones.

AWS 77

AWS Storage Cloud Big Data 77