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. With agent monitoring, third-party software collects data and reports from the component that’s attached to the agent.

Cloud 222

Cloud Monitoring Best Practices Infrastructure 222

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

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

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

The Morning Paper

SEPTEMBER 19, 2019

Autoscaling tiered cloud storage in Anna. I don’t think so in this case, but this paper will take you down into the nitty-gritty of getting the best out of modern processors and networks, with up to two orders of magnitude single node throughput gains to be had. What if the network was no longer the bottleneck?

Blockchain 46

Blockchain Hardware Google Analytics 46

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

DECEMBER 9, 2010

By supporting such large object sizes, Amazon S3 better enables a variety of interesting big data use cases. You can create parallel uploads to better utilize your available bandwidth and even stream data into Amazon S3 as its being created. Driving Storage Costs Down for AWS Customers. At werner.ly Syndication.

AWS 80

AWS Big Data Scalability Storage 80

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. Where to go from here?

AWS 136

AWS Latency Programming Architecture 136

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.

Architecture 12

Architecture Hardware Cache Storage 12

Percona

JANUARY 14, 2019

Public API as -a-service has become a good business model: examples include social networks like Facebook/Twitter, messaging as a service like Twilio, and even credit card authorization platforms like Marqeta. Text analysis. So can we use it as our main datastore? database: reddit table: rc_2017 mutation_id: mutation_858.txt

Database 40

Database Analytics Blockchain Healthcare 40