Dynatrace

DECEMBER 15, 2022

Besides the traditional system hardware, storage, routers, and software, ITOps also includes virtual components of the network and cloud infrastructure. AIOps (artificial intelligence for IT operations) combines big data, AI algorithms, and machine learning for actionable, real-time insights that help ITOps continuously improve operations.

Artificial Intelligence 202

Artificial Intelligence DevOps Hardware Virtualization 202

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. This report reflects Kubernetes adoption statistics based on the analysis of 4.1

Open Source 342

Open Source Java Operating System Programming 342

Uber Engineering

APRIL 5, 2018

Three years ago, Uber Engineering adopted Hadoop as the storage ( HDFS ) and compute ( YARN ) infrastructure for our organization’s big data analysis.

Systems 109

Systems Big Data Storage Infrastructure 109

Dynatrace

FEBRUARY 16, 2023

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 185

Analytics Innovation Metrics Database 185

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.

IoT 78

IoT Analytics Big Data Architecture 78

All Things Distributed

JUNE 26, 2016

AdiMap uses Amazon Kinesis to process real-time streaming online ad data and job feeds, and processes them for storage in petabyte-scale Amazon Redshift. Advanced problem solving that connects big data with machine learning. At-scale computing and visual analysis. We are at the cusp of a dramatic age of technology.

AWS 90

AWS Cloud Healthcare Blockchain 90

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. If the majority of your data is unstructured such as text, images, documents, etc. 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

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

The Morning Paper

SEPTEMBER 19, 2019

Autoscaling tiered cloud storage in Anna. Hyper Dimension Shuffle describes how Microsoft improved the cost of data shuffling, one of the most costly operations, in their petabyte-scale internal big data analytics platform, SCOPE. Research papers. (In In random order!).

Blockchain 46

Blockchain Hardware Google Analytics 46

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 87

AWS Storage Cloud Big Data 87

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

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

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

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.” ” (It will be easier to fit in the overhead storage.)

Hardware 99

Hardware Storage Big Data Blockchain 99

All Things Distributed

DECEMBER 13, 2009

These can be incidental tasks, such as the analysis of a particular dataset, or tasks where the amount of work to be done is almost never finished, such as media conversion from a Hollywoods studios movie vault, or web crawling for a search indexing company. Driving Storage Costs Down for AWS Customers. At werner.ly Syndication.

Cloud 63

Cloud AWS Storage Innovation 63

ACM Sigarch

NOVEMBER 1, 2019

Alongside more traditional sessions such as Real-World Deployed Systems and Big Data Programming Frameworks, there were many papers focusing on emerging hardware architectures, including embedded multi-accelerator SoCs, in-network and in-storage computing, FPGAs, GPUs, and low-power devices. Heterogeneous ISA. Final words.

Architecture 12

Architecture Hardware Cache Storage 12

All Things Distributed

OCTOBER 7, 2015

We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps. In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data.

Cloud 138

Cloud Big Data AWS Analytics 138

The Agile Manager

FEBRUARY 27, 2012

The Financial Times recently ran analysis and guest op-eds that sought to explain value in and from IT. The rise of Big Data - the ability to store and analyze large volumes of structured and unstructured, internal and external data - promises to let companies react more nimbly than ever before. Nor is cloud computing.

Ecommerce 45

Ecommerce Social Media Retail Airlines 45

Percona

JANUARY 14, 2019

In a partitioned massively parallel database system, the storage format and sorting algorithm may not be optimized for that operation as we are reading multiple partitions in parallel. Text analysis. database: reddit table: rc_2017 mutation_id: mutation_858.txt

Database 40

Database Analytics Blockchain Healthcare 40

All Things Distributed

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

DECEMBER 9, 2010

By supporting such large object sizes, Amazon S3 better enables a variety of interesting big data use cases. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics. For example, a 2-hour movie on Blu-ray can be 50 gigabytes.

AWS 82

AWS Big Data Scalability Storage 82

All Things Distributed

NOVEMBER 15, 2010

Starting today Amazon EMR can take advantage of the Cluster Compute and Cluster GPU instances, giving customers ever more powerful components to base the large scale data processing and analysis on. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. At werner.ly Syndication.

AWS 136

AWS Latency Programming Architecture 136