The Netflix TechBlog

OCTOBER 28, 2021

Netflix’s unique work culture and petabyte-scale data problems are what drew me to Netflix. During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics. Moreover, its petabyte scale also brings unique engineering challenges.

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

DZone

MAY 21, 2019

The demand for more IT resource-intensive applications has significantly increased today, whether it is to process quicker transactions, gain real-time insight, crunch big data sets, or to meet customer expectations. That’s because NVMe provides 6x higher bandwidth and IOPS advantage compared to SAS/SATA SSD.

Performance 100

Performance Big Data Storage Processing 100

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

All Things Distributed

AUGUST 18, 2011

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. Driving Storage Costs Down for AWS Customers. Comments (). At werner.ly

Big Data 112

Big Data Analytics AWS Scalability 112

Dynatrace

MARCH 24, 2023

Problems include provisioning and deployment; load balancing; securing interactions between containers; configuration and allocation of resources such as networking and storage; and deprovisioning containers that are no longer needed. How does container orchestration work?

Infrastructure 187

Infrastructure Open Source Operating System Cloud 187

Dynatrace

DECEMBER 15, 2022

Besides the traditional system hardware, storage, routers, and software, ITOps also includes virtual components of the network and cloud infrastructure. The primary goal of ITOps is to provide a high-performing, consistent IT environment. Performance. What does IT operations do? ITOps vs. AIOps.

Artificial Intelligence 204

Artificial Intelligence DevOps Hardware Virtualization 204

Scalegrid

MAY 13, 2020

Greenplum uses an MPP database design that can help you develop a scalable, high performance deployment. High performance, query optimization, open source and polymorphic data storage are the major Greenplum advantages. Greenplum features a cost-based query optimizer for large-scale, big data workloads.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

The Netflix TechBlog

MAY 4, 2023

The first phase involves validating functional correctness, scalability, and performance concerns and ensuring the new systems’ resilience before the migration. These include Quality-of-Experience(QoE) measurements at the customer device level, Service-Level-Agreements (SLAs), and business-level Key-Performance-Indicators(KPIs).

Traffic 339

Traffic Latency Tuning Systems 339

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. The best they can usually do in real-time using general purpose tools is to filter and look for patterns of interest.

IoT 78

IoT Analytics Big Data Architecture 78

Dynatrace

JANUARY 16, 2023

The study analyzes factual Kubernetes production data from thousands of organizations worldwide that are using the Dynatrace Software Intelligence Platform to keep their Kubernetes clusters secure, healthy, and high performing. Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch.

Open Source 344

Open Source Java Operating System Programming 344

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 203

Storage Latency Efficiency Data Engineering 203

Percona

JANUARY 19, 2023

While the technologies have evolved and matured enough, there are still some people thinking that MySQL is only for small projects or that it can’t perform well with large tables. With disks being faster nowadays and CPU and memory resources being cheaper, we could easily say MySQL can handle TBs of data with good performance.

Open Source 87

Open Source Storage Database Big Data 87

All Things Distributed

DECEMBER 8, 2016

It adopted Amazon Redshift, Amazon EMR and AWS Lambda to power its data warehouse, big data, and data science applications, supporting the development of product features at a fraction of the cost of competing solutions. Performance. Rapid time to market. as part of its Box Zones ecosystem.

AWS 155

AWS Cloud Lambda Innovation 155

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. Then we perform frequent batch ETL from application databases to a data warehouse. Classic ETL. Stateless and elastic.

Big Data 40

Big Data Retail Storage Google 40

The Netflix TechBlog

OCTOBER 15, 2019

Delta is an eventual consistent, event driven, data synchronization and enrichment platform. Existing Solutions Dual Writes In order to keep two datastores in sync, one could perform a dual write, which is executing a write to one datastore following a second write to the other. clock drift on the partition leader).

Transportation 192

Transportation Architecture Processing Storage 192

ScaleOut Software

APRIL 3, 2020

For example, the parameters for a ventilator could include its identifier, make and model, current location, status (in use, in storage, broken), time in use, technical issues and repairs, and contact information. These questions can be answered using the latest data as it streams in from the field.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

For example, the parameters for a ventilator could include its identifier, make and model, current location, status (in use, in storage, broken), time in use, technical issues and repairs, and contact information. These questions can be answered using the latest data as it streams in from the field.

Logistics 52

Logistics Analytics Scalability Cloud 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. The test data management for the company had become a big problem and had to be solved.

Testing 60

Testing Storage Database Processing 60

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 and Memcached both provide high performance with sub-millisecond response times. This mechanism results in fast data access and effective memory utilization.

Cache 130

Cache Storage Scalability Architecture 130

All Things Distributed

AUGUST 22, 2011

There are many success stories about the effectiveness of caching in many different scenarios; next to helping applications achieving fast and predictable performance, it often protects databases from requests bursts and brownouts under overload conditions. Driving Storage Costs Down for AWS Customers. At werner.ly Syndication.

Cloud 117

Cloud Cache AWS Storage 117

All Things Distributed

DECEMBER 14, 2011

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. Additionally, it allows them to keep their data inside of Brazil. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway.

AWS 115

AWS Latency Storage Big Data 115

All Things Distributed

JUNE 29, 2011

In Amazon Web Services there are similar dimensions that are forever important to our customers; scale, reliability, security, performance, ease of use, and of course pricing. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics.

AWS 106

AWS Retail Innovation Strategy 106

Testsigma

JULY 14, 2020

Read the input data from the data source, using parameterised variables in the automation test script. Fill in the input test data in the AUT(application under test). Perform the action according to the test script. Continue the above steps with the next input test data from the data source. Excel files.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

Dynatrace

JANUARY 11, 2023

With more organizations taking the multicloud plunge, monitoring cloud infrastructure is critical to ensure all components of the cloud computing stack are available, high-performing, and secure. These next-generation cloud monitoring tools present reports — including metrics, performance, and incident detection — visually via dashboards.

Cloud 224

Cloud Monitoring Best Practices Infrastructure 224

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. “The weakness of a data lake is they fail when you need to access them fast,” Pawlowski said.

Analytics 189

Analytics Infrastructure Storage Efficiency 189

Dynatrace

OCTOBER 4, 2022

A data lakehouse features the flexibility and cost-efficiency of a data lake with the contextual and high-speed querying capabilities of a data warehouse. Data warehouses offer a single storage repository for structured data and provide a source of truth for organizations. How does a data lakehouse work?

Artificial Intelligence 210

Artificial Intelligence Storage Analytics Government 210

All Things Distributed

JULY 13, 2010

Cluster Computer Instances for Amazon EC2 are a new instance type specifically designed for High Performance Computing applications. In those days, my main goal was to take the advances in building the highly dedicated High Performance Cluster environments and turn them into commodity technologies for the enterprise to use.

Cloud 119

Cloud AWS Automotive Latency 119

Brendan Gregg

APRIL 30, 2018

LISA originally stood for "Large Installation System Administration," where "large" meant systems with more than a gigabyte of storage, or with more than 100 users. In fact, we’d link to the first LISA conference website for reference, but this conference not only predates the Wayback Machine – it also predates the World Wide Web!

DevOps 43

DevOps Network Best Practices Programming 43

Scalegrid

MARCH 14, 2024

Public Cloud Infrastructure Third-party providers run public cloud services, delivering a broad array of offerings like computing power, storage solutions, and network capabilities that enhance the functionality of a hybrid cloud architecture. We will examine each of these elements in more detail.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

OCTOBER 4, 2022

Teams have introduced workarounds to reduce storage costs. Additionally, efforts such as lowered data retention times, two-tiered storage systems, shaky index management, sampled data, and data pipelines reduce the overall amount of stored data. Turn log data into value and activate Grail.

Analytics 236

Analytics Artificial Intelligence Storage Serverless 236

Brendan Gregg

APRIL 29, 2018

LISA originally stood for "Large Installation System Administration," where "large" meant systems with more than a gigabyte of storage, or with more than 100 users. In fact, we’d link to the first LISA conference website for reference, but this conference not only predates the Wayback Machine – it also predates the World Wide Web!

DevOps 40

DevOps Network Best Practices Programming 40

All Things Distributed

DECEMBER 5, 2010

I am very excited that today we have launched Amazon Route 53, a high-performance and highly-available Domain Name System (DNS) service. This achieves very low-latency for queries which is crucial for the overall performance of internet applications. Driving Storage Costs Down for AWS Customers. Comments (). No lock-in.

Cloud 117

Cloud Internet Internet AWS 117

All Things Distributed

DECEMBER 3, 2009

In addition, the EU (Ireland) Region is available to customers who want local access to services from Europe to address their performance or jurisdiction requirements. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics.

AWS 60

AWS Cloud Latency Storage 60

SQL Server According to Bob

JANUARY 15, 2020

344] eviction manager: must evict ​​ pod(s) to reclaim ephemeral-storage kubelet[1242]: I1205 02:55:10.471522 ​​ ​​​​ 1242 eviction_manager.go:362] kubelet[1242]: I1205 02:55:10.469831 ​​ ​​​​ 1242 eviction_manager.go:344]

Servers 40

Servers Metrics Big Data Operating System 40

The Netflix TechBlog

OCTOBER 27, 2020

Usually Data scientists and engineers write Extract-Transform-Load (ETL) jobs and pipelines using big data compute technologies, like Spark or Presto , to process this data and periodically compute key information for a member or a video. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 243

Latency Storage Big Data Tuning 243

Dynatrace

FEBRUARY 16, 2023

As observability and security data converge in modern multicloud environments, there’s more data than ever to orchestrate and analyze. The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes.

Analytics 187

Analytics Innovation Metrics Database 187

All Things Distributed

APRIL 28, 2010

There are four main reasons to do so: Performance - For many applications and services, data access latency to end users is important. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics. At werner.ly Syndication.

AWS 61

AWS Cloud Latency Storage 61