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 184

Analytics Infrastructure Storage Efficiency 184

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

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 182

Analytics Innovation Metrics Database 182

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

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 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. For example, if some fields in the responses are timestamps, those will differ.

Traffic 339

Traffic Latency Tuning Systems 339

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

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

Percona

JANUARY 19, 2023

However, there are cases where the same column is defined on multiple indexes in order to serve different query patterns, and sometimes some of the indexes created for the same column are redundant, leading to more overhead when inserting or deleting data (as indexes are updated) and increased disk space for storing the indexes for the table.

Open Source 90

Open Source Storage Database Big Data 90

All Things Distributed

DECEMBER 13, 2016

Take Peterborough City Council as an example. The council has deployed IoT Weather Stations in Schools across the City and is using the sensor information collated in a Data Lake to gain insights on whether the weather or pollution plays a part in learning outcomes.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

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

All Things Distributed

JUNE 26, 2016

Here are the benefits of a comprehensive platform, with customer examples: A connected platform to sense the business environment. Examples of continuous sensing are found in the managed cloud platform built by Rachio on AWS IoT to enable the secure interaction of its connected devices with cloud applications/other devices.

AWS 90

AWS Cloud Healthcare Blockchain 90

All Things Distributed

OCTOBER 7, 2015

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. However, the data infrastructure to collect, store and process data is geared toward developers (e.g.,

Cloud 137

Cloud Big Data AWS Analytics 137

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

Some examples of how current customers use AWS are: Cost-effective solutions. 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

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. Consider a simple example in which a message arrives signaling that a ventilator has been activated for a patient.

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. Consider a simple example in which a message arrives signaling that a ventilator has been activated for a patient.

Logistics 52

Logistics Analytics Scalability Cloud 52

All Things Distributed

AUGUST 16, 2011

For example a number of our European customers are subject to data residency requirements when it comes to PII data and they use the EU Region to meet to those requirements. 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

FEBRUARY 17, 2011

Since a few days ago this weblog serves 100% of its content directly out of the Amazon Simple Storage Service (S3) without the need for a web server to be involved. This enables Amazon S3 to know what document to serve if one isnt explicitly requested: for example [link]. Driving Storage Costs Down for AWS Customers.

AWS 134

AWS Website Storage Servers 134

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

APRIL 27, 2011

For example, to construct a product detail page for a customer visiting Amazon.com, our software calls on between 200 and 300 services to present a highly personalized experience for that customer. The storage systems weve pioneered demonstrate extreme scalability while maintaining tight control over performance, availability, and cost.

Technology 151

Technology Technology AWS Storage 151

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. Although there are some good examples that come with Cactus is still early days and there is not much of a community using it. At werner.ly Syndication.

Servers 126

Servers Social Media AWS Website 126

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

All Things Distributed

MARCH 28, 2011

The methods for accessing these objects is also rapidly changing; where in the past you needed a PC or a Laptop to access these objects, now many of our electronic devices have become capable of processing them. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. At werner.ly Syndication.

AWS 138

AWS Cloud Storage Internet 138

All Things Distributed

SEPTEMBER 6, 2013

Europe is a continent with much diversity and for each country there are great AWS customer examples to tell. Here are some great examples from different industries each with unique use cases. Shell leverages AWS for big data analytics to help achieve these goals.

Cloud 129

Cloud Energy AWS Healthcare 129

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

FEBRUARY 25, 2011

If anything goes wrong during the creation process, automatic rollback will be executed and resources created for this stack will be cleaned up. A simple scenario is for example the ability to clearly identify production from staging and development environments. Driving Storage Costs Down for AWS Customers. At werner.ly

AWS 121

AWS Cloud Scalability Storage 121

All Things Distributed

NOVEMBER 15, 2010

From financial processing and traditional oil & gas exploration HPC applications to integrating complex 3D graphics into online and mobile applications, the applications of GPU processing appear to be limitless. For example, the most fundamental abstraction trade-off has always been latency versus throughput.

AWS 136

AWS Latency Programming Architecture 136

The Netflix TechBlog

OCTOBER 27, 2020

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. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 243

Latency Storage Big Data Tuning 243

All Things Distributed

DECEMBER 3, 2009

But customers have also asked us for more flexibility and control in the way that Amazon EC2 instances are booted such that they have finer grained control over for example what software configurations and data sets are available to the instance at boot time. with new security patches installed), or add new user data.

AWS 60

AWS Storage Operating System Cloud 60

SQL Server According to Bob

JANUARY 15, 2020

​​ For example, my master-0, SQL Server, pod was getting evicted and restarted. 344] eviction manager: must evict ​​ pod(s) to reclaim ephemeral-storage kubelet[1242]: I1205 02:55:10.471522 ​​ ​​​​ 1242 eviction_manager.go:362]

Servers 40

Servers Metrics Big Data Operating System 40

All Things Distributed

JULY 13, 2010

Customers with complex computational workloads such as tightly coupled, parallel processes, or with applications that are very sensitive to network performance, can now achieve the same high compute and networking performance provided by custom-built infrastructure while benefiting from the elasticity, flexibility and cost advantages of Amazon EC2.

Cloud 118

Cloud AWS Automotive Latency 118

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. Processed 4.15 Processed 4.15 Processed 8.19 Processed 8.19 Processed 4.15 Processed 3.05

Database 40

Database Analytics Blockchain Healthcare 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

Abhishek Tiwari

DECEMBER 27, 2017

A common theme across all these trends is to remove the complexity by simplifying data management as a whole. In 2018, we anticipate that ETL will either lose relevance or the ETL process will disintegrate and be consumed by new data architectures. Unified data management architecture.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49