Dynatrace

AUGUST 10, 2021

Carrie called out how at Dynatrace we know it takes a village to achieve the extraordinary, from innovating reliable digital services at speed to learning how to adapt and thrive while managing our increasingly complex, dynamic technology environments. Investing in data is easy but using it is really hard”. She wasn’t wrong.

DevOps 246

DevOps Innovation Big Data Cloud 246

DZone

JULY 17, 2023

Apache Spark is a leading platform in the field of big data processing, known for its speed, versatility, and ease of use. Understanding Apache Spark Apache Spark is a unified computing engine designed for large-scale data processing. However, getting the most out of Spark often involves fine-tuning and optimization.

Big Data 130

Big Data Performance Open Source Tuning 130

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. And without the encumbrances of traditional databases, Grail performs fast. “In

Analytics 246

Analytics Innovation Metrics Database 246

Dynatrace

DECEMBER 15, 2022

This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. 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. Reliability. Performance. ITOps vs. AIOps.

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. VLDB’19. For the larger more production-like query analysed in §4.2.1,

Big Data 57

Big Data Analytics Latency Azure 57

Dynatrace

OCTOBER 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. A huge advantage of this approach is speed. It works without having to identify training data, then training and honing.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

Dynatrace

APRIL 11, 2023

Shifting left and shifting right also enable DevSecOps teams to create closed-loop systems that are resilient, DevSecOps teams need to shift left to speed development cycles without compromising quality. Shift left vs. shift right: A DevOps mystery solved – blog Shift-left evaluation reduces defects and speeds delivery in development.

Cloud 246

Cloud DevOps Open Source Retail 246

Dynatrace

MARCH 14, 2022

AIOps (or “AI for IT operations”) uses artificial intelligence so that big data can help IT teams work faster and more effectively. This has granted the speed and agility to accelerate innovation and bring new rewards to its members more frequently. Gartner introduced the concept of AIOps in 2016.

Healthcare 246

Healthcare Artificial Intelligence Innovation Strategy 246

Dynatrace

OCTOBER 14, 2021

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” A huge advantage of this approach is speed. It works without having to identify training data, then training and honing.

Artificial Intelligence 246

Artificial Intelligence DevOps Innovation Metrics 246

The Netflix TechBlog

MAY 26, 2020

These characteristics allow for an on-call response time that is relaxed and more in line with traditional big data analytical pipelines. Spark could look up and retrieve the data in the s3 files that the Mouthful represented. And excellent logging is needed for debugging purposes and supportability.

Network 154

Network Tuning AWS Big Data 154

All Things Distributed

SEPTEMBER 29, 2016

To support our customers’ growth, their digital transformation, and to speed up their innovation and lower the cost of running their IT, we continue to build out additional European infrastructure. Since we opened the first AWS EU Region in Ireland in November 2007, we have seen an acceleration of companies adopting the AWS Cloud.

AWS 158

AWS IoT Internet Internet 158

The Netflix TechBlog

NOVEMBER 20, 2023

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing. ETL pipelines keep all the benefits of batch workflows.

Processing 219

Processing Big Data Efficiency Engineering 219

The Netflix TechBlog

JUNE 1, 2021

His favorite TV shows: Bojack Horseman , Marco Polo , and The Witcher His favorite movies: Scarface, I Am Legend and The Old Guard Sam, what drew you to data engineering? Early in my career, I was headed full speed towards life as a clinical researcher. Furthermore, engineering velocity was often sacrificed owing to rigid processes.

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

All Things Distributed

OCTOBER 7, 2015

Today, I am excited to share with you a brand new service called Amazon QuickSight that aims to simplify the process of deriving insights from a wide variety of data sources in a fast and affordable manner. Big data challenges. We believe this is one of the critical parts of our big data offerings.

Cloud 112

Cloud Big Data AWS Analytics 112

The Netflix TechBlog

FEBRUARY 16, 2021

However, with our rapid product innovation speed, the whole approach experienced significant challenges: Business Complexity: The existing SKU management solution was designed years ago when the engagement rules were simple?

Mobile 218

Mobile Engineering Infrastructure Scalability 218

Alex Podelko

DECEMBER 19, 2019

System Performance Estimation, Evaluation, and Decision (SPEED) by Kingsum Chow, Yingying Wen, Alibaba. Solving the “Need for Speed” in the World of Continuous Integration by Vivek Koul, Mcgraw Hill. How Website Speed affects your Bottom Line and what you can do about it by Alla Gringaus, Rigor. Something we all struggle with.

Efficiency 100

Efficiency Artificial Intelligence Scalability Performance 100

Scalegrid

JUNE 28, 2024

This system allows for scalability and efficiency, demonstrating RabbitMQ’s versatility in real-world applications where speed and reliability are crucial. Can RabbitMQ handle the high-throughput needs of big data applications? For high-throughput big data applications, RabbitMQ may fall short of expectations.

IoT 130

IoT Healthcare Programming Open Source 130

ScaleOut Software

JULY 19, 2021

And it can maintain contextual information about every data source (like the medical history of a device wearer or the maintenance history of a refrigeration system) and keep it immediately at hand to enhance the analysis.

IoT 78

IoT Big Data Analytics Architecture 78

Scalegrid

FEBRUARY 11, 2025

Due to the lack of a rigid schema, MongoDB is well-suited for applications that demand real-time analytics and handle big data, providing expedient processing capabilities. Best Use Cases for MongoDB MongoDB thrives in scenarios that necessitate the management of unstructured data and rapid processing speeds.

Scalability 147

Scalability Database Storage IoT 147

All Things Distributed

MARCH 2, 2011

Japanese companies and consumers have become used to low latency and high-speed networking available between their businesses, residences, and mobile devices. Driving down the cost of Big-Data analytics. Today Amazon Web Services is expanding its world-wide coverage with the launch of a new AWS Region located in Tokyo, Japan.

AWS 90

AWS Cloud Games Latency 90

Scalegrid

MARCH 28, 2024

However, its limited feature set compared to Redis might be a disadvantage for applications that require more advanced data structures and persistence. Introduction Caching serves a dual purpose in web development – speeding up client requests and reducing server load. Data transfer technology. 3d render.

Cache 130

Cache Storage Architecture Scalability 130

Scalegrid

JANUARY 10, 2025

They keep the features that developers like but can handle much more data, similar to NoSQL systems. Notably, they simplify handling big data flows, offer consistent transactions, and sustain high performance even when they’re used for real-time data analysis and complex queries.

Database 130

Database Scalability Best Practices Blockchain 130

All Things Distributed

DECEMBER 12, 2018

The first platform is a real time, big data platform being used for analyzing traffic usage patterns to identify congestion and connectivity issues. The second platform is a managed IoT cloud with customer-facing applications and data management, which went live in 2016. Telenor Connexion is all-in on AWS.

AWS 119

AWS Cloud Games Serverless 119

Rigor

JANUARY 13, 2020

Take, for example, The Web Almanac , the golden collection of Big Data combined with the collective intelligence from most of the authors listed below, brilliantly spearheaded by Google’s @rick_viscomi. Site speed & SEO go hand in hand. Speed Up Your Site. Web Performance In Action. Designing for Performance.

Performance 75

Performance Social Media Website Website Performance 75

All Things Distributed

JULY 7, 2011

AWS Import/Export transfers data off of storage devices using Amazons high-speed internal network and bypassing the Internet. With this new functionality AWS Import/Export now supports importing data directly into Amazon EBS snapshots. Driving down the cost of Big-Data analytics. Spot Instances - Increased Control.

AWS 75

AWS Cloud Storage Internet 75

Scalegrid

MARCH 14, 2024

It provides significant advantages that include: Offering scalability to support business expansion Speeding up the execution of business plans Stimulating innovation throughout the company Boosting organizational flexibility, enabling quick adaptation to changing market conditions and competitive pressures.

Strategy 130

Strategy Cloud Infrastructure Artificial Intelligence 130

Abhishek Tiwari

DECEMBER 27, 2017

In 2018, we will see new data integration patterns those rely either on a shared high-performance distributed storage interface ( Alluxio ) or a common data format ( Apache Arrow ) sitting between compute and storage. For instance, Alluxio, originally known as Tachyon, can potentially use Arrow as its in-memory data structure.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

O'Reilly

AUGUST 15, 2023

Few professional software developers will find it surprising that software development teams are respondents said that productivity is the biggest challenge their organization faced, and another 19% said that time to market and deployment speed are the biggest challenges.

Development 98

Development Programming Speed Open Source 98

All Things Distributed

JULY 13, 2010

During my academic career, I spent many years working on HPC technologies such as user-level networking interfaces, large scale high-speed interconnects, HPC software stacks, etc. Driving down the cost of Big-Data analytics. Introducing the AWS South America (Sao Paulo) Region. No Server Required - Jekyll & Amazon S3.

Cloud 96

Cloud AWS Automotive Latency 96

Smashing Magazine

JULY 29, 2019

The speed of mobile networks, too, varies considerably between countries. Perhaps surprisingly, users experience faster speeds over a mobile network than WiFi in at least 30 countries worldwide, including Australia and France. South Korea has the fastest mobile download speed , averaging 52.4 per GB respectively. Mbps upload.

Cache 99

Cache Mobile Google Network 99

All Things Distributed

DECEMBER 20, 2017

Marketers use big data and artificial intelligence to find out more about the future needs of their customers. Breuninger uses modern templates for software development, such as Self-Contained Systems (SCS), so that it can increase the speed of software development with agile and autonomous teams and quickly test new features.

Artificial Intelligence 70

Artificial Intelligence Social Media Logistics AWS 70

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. ATC ’19 was refreshingly different.

Architecture 12

Architecture Hardware Cache Storage 12

Testsigma

MAY 14, 2021

Provides better testing speed, since it can run 24*7. Examples are DevOps, AWS, Big Data, Testing as Service, testing environments. Let us explore the advantages and disadvantages of cloud-based and traditional testing. Cloud-based testing advantages. The environment is dynamic and scalable.

Cloud 67

Cloud Testing Testing Tools Internet 67

The Morning Paper

SEPTEMBER 19, 2019

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. Some cool algorithms: Pigeonring speeds up thresholded similarity searches. Do we want that? Yes please!

Blockchain 46

Blockchain Hardware Google Network 46

CSS - Tricks

OCTOBER 7, 2021

These components tackle the hardest interactivity problems in UI/UX, and do it with grace, speed, and accessibility in mind. Let’s take a look at their React Data Grid component. Filtering Data. And I’d say the looks aren’t even the important part.

Big Data 60

Big Data C++ Virtualization Design 60

Testsigma

JULY 14, 2020

The redundant work of manually entering the test data is monotonous and time-consuming. Human skills can be used for better purposes like exploratory testing when data-driven automation testing is in place. A proper understanding of the AUT and a very good domain knowledge prepares the background for a great test data set.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

ScaleOut Software

NOVEMBER 24, 2020

Here’s a typical telematics architecture for processing telemetry from a fleet of trucks: Each truck today has a microprocessor-based sensor hub which collects key telemetry, such as vehicle speed and acceleration, engine parameters, trailer parameters, and more. Lastly, all telemetry is archived for future use (not shown here).

Analytics 52

Analytics Architecture Scalability Software Architecture 52