DZone

JUNE 3, 2019

Using local SSDs inside of the GPU node delivers fast access to data during training, but introduces challenges that impact the overall solution in terms of scalability, data access, and data protection.

Storage 100

Storage Performance Network Scalability 100

DZone

JUNE 4, 2019

NVMe Storage Use Cases. NVMe storage's strong performance, combined with the capacity and data availability benefits of shared NVMe storage over local SSD, makes it a strong solution for AI/ML infrastructures of any size. There are several AI/ML focused use cases to highlight.

Storage 100

Storage FinTech Artificial Intelligence Performance 100

Dynatrace

FEBRUARY 16, 2023

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 182

Analytics Innovation Metrics Database 182

DZone

JULY 29, 2019

In today's world, data is generated in high volumes and to make something out of it, extracted data is needed to be transformed, stored, maintained, governed and analyzed. These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on.

Big Data 157

Big Data Government Open Source Storage 157

DZone

MAY 30, 2019

With big data on the rise and data algorithms advancing, the ways in which technology has been applied to real-world challenges have grown more automated and autonomous. Financial analysis with real-time analytics is used for predicting investments and drives the FinTech industry's needs for high-performance computing.

Artificial Intelligence 100

Artificial Intelligence Social Media FinTech Storage 100

DZone

JANUARY 20, 2023

There is a countless number of enterprises, particularly Internet giants, that have explored ways to make graph data processing scalable. It has been a norm to perceive that distributed databases use the method of adding cheap PC(s) to achieve scalability (storage and computing) and attempt to store data once and for all on demand.

Scalability 201

Scalability Big Data Hardware Internet 201

Dynatrace

OCTOBER 4, 2022

Several pain points have made it difficult for organizations to manage their data efficiently and create actual value. Limited data availability constrains value creation. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes.

Analytics 231

Analytics Artificial Intelligence Storage Serverless 231

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. Managed DBaaS solutions like ScaleGrid.io

Cache 130

Cache Storage Scalability Architecture 130

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 220

Cloud Monitoring Best Practices Infrastructure 220

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

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. However, this cannot be done without efficient, scalable data analytics.

Big Data 111

Big Data Analytics AWS Cloud 111

The Netflix TechBlog

OCTOBER 15, 2019

Part I: Overview Andreas Andreakis , Falguni Jhaveri , Ioannis Papapanagiotou , Mark Cho , Poorna Reddy , Tongliang Liu Overview It is a commonly observed pattern for applications to utilize multiple datastores where each is used to serve a specific need such as storing the canonical form of data (MySQL etc.), caching (Memcached etc.),

Transportation 192

Transportation Architecture Processing Storage 192

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. We will examine each of these elements in more detail.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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. The primary goal of ITOps is to provide a high-performing, consistent IT environment. Performance. What does IT operations do?

Artificial Intelligence 198

Artificial Intelligence DevOps Hardware Virtualization 198

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 182

Infrastructure Open Source Operating System Cloud 182

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 340

Open Source Java Operating System Programming 340

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. The first phase involves validating functional correctness, scalability, and performance concerns and ensuring the new systems’ resilience before the migration.

Traffic 339

Traffic Latency Tuning Systems 339

Percona

OCTOBER 18, 2023

release , we added support for physical backups and restores to significantly reduce Recovery Time Objective ( RTO ), especially for big data sets. However, the problem of losing data between backups – in other words, Recovery Point Objective (RPO) – for physical backups was not solved. spec: backup: enabled: true.

Best Practices 93

Best Practices Storage AWS Big Data 93

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

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 following diagram illustrates a typical workflow. What’s missing in this picture?

IoT 78

IoT Analytics Big Data Architecture 78

Highly Scalable

MARCH 1, 2012

NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. At the same time, NoSQL data modeling is not so well studied and lacks the systematic theory found in relational databases. Many techniques that are described below are perfectly applicable to this model.

Database 279

Database Ecommerce Efficiency Engineering 279

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 90

Open Source Storage Database Big Data 90

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

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

Testsigma

JULY 14, 2020

According to Wikipedia, Data-Driven Testing(DDT) is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded. Database tables.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

All Things Distributed

DECEMBER 8, 2016

AWS data centers in Canada will draw from a regional electricity grid that is 99 percent powered by hydropower. 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.

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. Late transformation.

Big Data 40

Big Data Retail Storage Google 40

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

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 243

Latency Storage Big Data Tuning 243

O'Reilly

SEPTEMBER 19, 2023

It progressed from “raw compute and storage” to “reimplementing key services in push-button fashion” to “becoming the backbone of AI work”—all under the umbrella of “renting time and storage on someone else’s computers.” Cloud computing? And Hadoop rolled in. Until it wasn’t.

Hardware 99

Hardware Storage Big Data Blockchain 99

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 Lambda 79

The Morning Paper

SEPTEMBER 19, 2019

Their dataset has about 7B edges… Meanwhile, AnalyticDB is Alibaba’s real-time OLAP RDBMS handling 10PB of data (in excess of 100 trillion rows!). Autoscaling tiered cloud storage in Anna. The authors claim a two orders-of-magnitude performance improvement. speedup over the best performing existing method.

Blockchain 46

Blockchain Hardware Google Analytics 46

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 114

AWS Latency Storage Big Data 114

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

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 104

AWS Retail Innovation Strategy 104

Testsigma

FEBRUARY 12, 2021

When more companies transition into digital-first projects, there must be an expanded number of processes and IT data departments to keep IT teams on track. The latest trend in hyperautomation – Gartner projects that by the year 2023, 25% of tasks by the organisations will be able to perform autonomously and hence reducing the cost.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92