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

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

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. What is your favorite project?

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

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. Dynatrace discovers logs automatically at scale.

Analytics 234

Analytics Artificial Intelligence Storage Serverless 234

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

Scalegrid

MARCH 28, 2024

With these goals in mind, two in-memory data stores, Redis and Memcached, have emerged as the top contenders. This article will explore how they handle data storage and scalability, perform in different scenarios, and, most importantly, how these factors influence your choice. Data transfer technology. 3d render.

Cache 130

Cache Storage Scalability Architecture 130

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. Website monitoring examines a cloud-hosted website’s processes, traffic, availability, and resource use. Cloud storage monitoring.

Cloud 222

Cloud Monitoring Best Practices Infrastructure 222

Dynatrace

APRIL 20, 2023

-based financial services group, discussed how the bank uses log monitoring on the Dynatrace platform with an emphasis on observability and security data. To grasp the challenges of multifeatured, cross-team cooperation dealing with observability data, consider the content of the logs generated. Dissolving data silos.

Analytics 187

Analytics Infrastructure Storage Efficiency 187

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

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. This consistency aids not only in application deployment but also simplifies scaling processes. We will examine each of these elements in more detail.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

MARCH 24, 2023

Container orchestration is a process that automates the deployment and management of containerized applications and services at scale. Container orchestration enables organizations to manage and automate the many processes and services that comprise workflows. How does container orchestration work?

Infrastructure 186

Infrastructure Open Source Operating System Cloud 186

Dynatrace

DECEMBER 15, 2022

In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. This transition to public, private, and hybrid cloud is driving organizations to automate and virtualize IT operations to lower costs and optimize cloud processes and systems. So, what is ITOps? ITOps vs. AIOps.

Artificial Intelligence 202

Artificial Intelligence DevOps Hardware Virtualization 202

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

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 186

Analytics Innovation Metrics Database 186

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

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. What follows is a discussion of where big data systems might be heading, heavily inspired by the remarks in this paper, but with several of my own thoughts mixed in.

Cloud 104

Cloud Big Data Latency Architecture 104

Dynatrace

JANUARY 16, 2023

Redis is an in-memory key-value store and cache that simplifies processing, storage, and interaction with data in Kubernetes environments. Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch. Databases : Among databases, Redis is the most used at 60%.

Open Source 343

Open Source Java Operating System Programming 343

The Netflix TechBlog

MAY 4, 2023

Traffic Duplication and Correlation: The initial step requires the implementation of a mechanism to clone and fork production traffic to the newly established pathway, along with a process to record and correlate responses from the original and alternative routes.

Traffic 339

Traffic Latency Tuning Systems 339

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. Thus, ensuring the atomicity of writes across different storage technologies remains a challenging problem for applications [3].

Transportation 192

Transportation Architecture Processing Storage 192

The Netflix TechBlog

DECEMBER 21, 2020

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. On the other hand, these optimizations themselves need to be sufficiently inexpensive to justify their own processing cost over the gains they bring.

Storage 203

Storage Latency Efficiency Data Engineering 203

Percona

JANUARY 19, 2023

Compression: Compression is the process of restructuring the data by changing its encoding in order to store it in fewer bytes. There are many compression tools and algorithms for data out there. It can help us to save costs on storage and backup times. 1 mysql mysql 592K Dec 30 02:48 tb1.ibd ibd -rw-r --. ibd -rw-r --.

Open Source 91

Open Source Storage Database Big Data 91

All Things Distributed

JUNE 26, 2016

(previously known as Emdeon) uses Amazon SNS to handle millions of confidential client transactions daily to process claims and pharmacy requests serving over 340K physicians and 60K pharmacies in full compliance with healthcare industry regulations. . Seamless ingestion of large volumes of sensed data.

AWS 90

AWS Cloud Healthcare Blockchain 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

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. Kik Interactive is a Canadian chat platform with hundreds of millions of users around the globe.

AWS 155

AWS Cloud Lambda Innovation 155

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. Excel files.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

All Things Distributed

AUGUST 16, 2011

ITAR is the International Traffic in Arms Regulatory framework which stipulates for example that data must be stored in an environment where physical and logical access is restricted to US Persons. Government and Big Data. One particular early use case for AWS GovCloud (US) will be massive data processing and analytics.

AWS 111

AWS Government Big Data Cloud 111

All Things Distributed

AUGUST 17, 2011

As some of you may remember I was pretty excited when Amazon Simple Storage Service (S3) released its website feature such that I could serve this weblog completely from S3. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics.

Servers 126

Servers Social Media AWS Website 126

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. This allows quick answers to questions such as: “Show me the percentage shortfall in ventilators by state.”.

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. This allows quick answers to questions such as: “Show me the percentage shortfall in ventilators by state.”.

Logistics 52

Logistics Analytics Scalability Cloud 52

Testsigma

FEBRUARY 12, 2021

The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. With all of these processes in place, cost optimization is also a high concern for organizations worldwide. Dominance of Robotic Process Automation. Hyperautomation. The most recent 2021 trend.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

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

The Morning Paper

SEPTEMBER 19, 2019

Autoscaling tiered cloud storage in Anna. It handles an order of magnitude more throughput than a prototype built on a stream processing engine. Could it be Analyzing efficient stream processing on modern hardware ? Research papers. (In In random order!). for machine generated emails sent to humans). What’s their secret???

Blockchain 46

Blockchain Hardware Google Analytics 46

Highly Scalable

MARCH 1, 2012

And this was where a new evolution of data models began: Key-Value storage is a very simplistic, but very powerful model. One of the most significant shortcomings of the Key-Value model is a poor applicability to cases that require processing of key ranges. Data duplication and denormalization are first-class citizens.

Database 279

Database Ecommerce Efficiency Engineering 279

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 Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics.

AWS 85

AWS Storage Cloud Big Data 85

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

All Things Distributed

SEPTEMBER 6, 2013

Shell leverages AWS for big data analytics to help achieve these goals. Due to the exponential growth of the biology and informatics fields, Unilever needs to maintain this new program within a highly-scalable environment that supports parallel computation and heavy data storage demands.

Cloud 129

Cloud Energy AWS Healthcare 129

All Things Distributed

DECEMBER 3, 2009

In the traditional boot process, the root partition of the image will be the local disk, which is created and populated at boot time. In the new Amazon EBS boot process, the root partition is an Amazon EBS volume, which is created at boot time from an Amazon EBS snapshot. with new security patches installed), or add new user data.

AWS 60

AWS Storage Operating System Cloud 60