Dynatrace

DECEMBER 13, 2023

This includes how quickly the application loads, how much load it is putting on the device, how much storage is being used, and how frequently it crashes. Here are some ways observability data is important to mobile app performance monitoring. Load time and network latency metrics. Issue remediation. Proactive monitoring.

Best Practices 198

Best Practices Mobile Metrics Performance 198

The Morning Paper

SEPTEMBER 10, 2019

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., Anchored in the primary use case of supporting Google’s YouTube business, what we’re looking at here could well be the future of data processing at Google. Because they had too many data processing systems! ;). VLDB’19. are divided.

Analytics 75

Analytics Latency Cache Google 75

High Scalability

JANUARY 11, 2022

from a client it performs two parallel operations: i) persisting the action in the data store ii) publish the action in a streaming data store for a pub-sub model. User Feed Service, Media Counter Service) read the actions from the streaming data store and performs their specific tasks. Data Models. Graph Data Models.

Design 334

Design Media Storage Logistics 334

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130

Cache Storage Scalability Architecture 130

ScaleOut Software

JULY 14, 2021

Whether it’s health-tracking watches, long-haul trucks, or security sensors, extracting value from these devices requires streaming analytics that can quickly make sense of the telemetry and intelligently react to handle an emerging issue or capture a new opportunity.

IoT 52

IoT Azure Analytics Serverless 52

Scalegrid

JANUARY 8, 2024

The partnership between AI and cloud computing brings about transformative trends like enhanced security through intelligent threat detection, real-time analytics, personalization, and the implementation of edge computing for quicker on-site decision-making.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

Scalegrid

MARCH 14, 2024

Implementing a hybrid cloud solution involves careful decision-making regarding application and data placement, migration strategies, and choosing compatible cloud service providers while ensuring seamless integration and addressing security and compliance challenges. We will examine each of these elements in more detail.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Scalegrid

JANUARY 12, 2024

Key Takeaways A cloud workload encompasses any application or service running on a cloud infrastructure, facilitating tasks ranging from basic functions to advanced data analysis with the help of resources like databases, collaboration tools, and disaster recovery systems. This applies to both virtual machines and container-based deployments.

Cloud 130

Cloud Virtualization Storage Efficiency 130

The Netflix TechBlog

OCTOBER 19, 2020

If we had an ID for each streaming session then distributed tracing could easily reconstruct session failure by providing service topology, retry and error tags, and latency measurements for all service calls. Our distributed tracing infrastructure is grouped into three sections: tracer library instrumentation, stream processing, and storage.

Infrastructure 233

Infrastructure Transportation Storage Open Source 233

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

Dynatrace

SEPTEMBER 13, 2023

This is where unified observability and Dynatrace Automations can help by leveraging causal AI and analytics to drive intelligent automation across your multicloud ecosystem. Storing frequently accessed data in faster storage, usually in-memory caching, improves data retrieval speed and overall system performance. Beyond

AWS 247

AWS Efficiency Azure Cloud 247

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . In-Memory Data Grids for Fast-Changing Data. For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache.

Analytics 52

Analytics Airlines Cache Scalability 52

Dynatrace

DECEMBER 15, 2022

Complex cloud computing environments are increasingly replacing traditional data centers. In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. Why is IT operations important?

Artificial Intelligence 202

Artificial Intelligence DevOps Hardware Virtualization 202

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . In-Memory Data Grids for Fast-Changing Data. For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache.

Analytics 52

Analytics Airlines Cache Scalability 52

All Things Distributed

JUNE 7, 2017

Unlocking the value of data is a primary goal that AWS helps our customers to pursue. In recent years, an explosion of intelligent devices have created oceans of new data across many industries. This is because data gets more valuable when it can be processed together with other data. Law of Economics. Law of the Land.

AWS 118

AWS IoT Lambda Storage 118

Dynatrace

APRIL 26, 2022

Digital experience monitoring enables companies to respond to issues more efficiently in real time, and, through enrichment with the right business data, understand how end-user experience of their digital products significantly affects business key performance indicators (KPIs). Endpoint monitoring (EM). Endpoints can be physical (i.e.,

Monitoring 203

Monitoring Social Media IoT Metrics 203

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

Percona

JUNE 22, 2023

Database uptime and availability Monitoring database uptime and availability is crucial as it directly impacts the availability of critical data and the performance of applications or websites that rely on the MySQL database. Disk space usage Monitor the disk space usage of MySQL data files, log files, and temporary files.

Performance 107

Performance Monitoring Traffic Database 107

Dynatrace

DECEMBER 22, 2019

AWS offers a broad set of global, cloud-based services including computing, storage, networking, Internet of Things (IoT), and many others. Amazon Kinesis Data Analytics. Amazon Kinesis Data Firehose. Amazon Kinesis Data Streams (KDS). Amazon Simple Storage Service (S3). Dynatrace news. Amazon Redshift.

AWS 136

AWS Metrics IoT Storage 136

Dynatrace

DECEMBER 22, 2019

AWS offers a broad set of global, cloud-based services including computing, storage, networking, Internet of Things (IoT), and many others. Amazon Kinesis Data Analytics. Amazon Kinesis Data Firehose. Amazon Kinesis Data Streams (KDS). Amazon Simple Storage Service (S3). Dynatrace news. Amazon Redshift.

AWS 133

AWS Metrics IoT Storage 133

All Things Distributed

OCTOBER 16, 2019

These places might have important data that could help us better understand earth and its history, as well as life on other planets. For some applications, a trip to the cloud and back isn't possible because of latency requirements (for example, an autonomous car interpreting its environment in real time).

IoT 126

IoT Healthcare Internet Internet 126

Abhishek Tiwari

JULY 12, 2018

Building data pipelines can offer strategic advantages to the business. It can be used to power new analytics, insight, and product features. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines. Data pipeline initiatives are generally unfinished projects.

Latency 63

Latency Analytics Scalability Engineering 63

Percona

JULY 17, 2023

Instead of the table-based structure of relational databases, MongoDB stores data in documents and collections, a design for handling large amounts of unstructured data and for real-time web applications. More specifically, DBAs and developers like that MongoDB stores data in JSON-like documents with optional schemas.

Open Source 79

Open Source Database Scalability Software 79

Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154

Big Data Processing Lambda Database 154

n0derunner

SEPTEMBER 17, 2018

As with traditional storage, applications are writing to a shared storage environment which is necessary to support VM movement. It is the shared storage that often causes performance issues for data bases which are otherwise separated across nodes. 4 “Data” Disks. X-Ray Workload specification.

Performance Testing 40

Performance Testing Benchmarking Testing Performance 40

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. Each of these categories opens up challenging problems in AI/visual algorithms, high-density computing, bandwidth/latency, distributed systems. Analyzing visual data is predominantly accomplished using deep learning.

Wireless 54

Wireless IoT Analytics Architecture 54

Dotcom-Montior

MAY 12, 2020

Websites are now more than just the storage and retrieval of information to present content to users. Network latency. Network Latency. With the evolution of cloud technologies, such as Single Page Applications (SPAs), Web APIs, and Model View Controller (MVC), network latency has become a crucial factor to be monitored.

Monitoring 63

Monitoring Entertainment Hardware Latency 63

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. The advanced Asia Pacific network infrastructure also makes the AWS Tokyo Region a viable low-latency option for customers from South Korea. At werner.ly Syndication.

AWS 112

AWS Cloud Games Latency 112

The Netflix TechBlog

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. 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.

Latency 243

Latency Storage Big Data Tuning 243

All Things Distributed

DECEMBER 14, 2011

This new Region has been highly requested by companies worldwide, and it provides low-latency access to AWS services for those who target customers in South America. The new Sao Paulo Region provides better latency to South America, which enables AWS customers to deliver higher performance services to their South American end-users.

AWS 114

AWS Latency Storage Big Data 114

All Things Distributed

AUGUST 16, 2011

There are different considerations when deciding where to allocate resources with latency and cost being the two obvious ones, but compliance sometimes plays an important role as well. 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

Alex Russell

MARCH 6, 2021

A then-representative $200USD device had 4-8 slow (in-order, low-cache) cores, ~2GiB of RAM, and relatively slow MLC NAND flash storage. In 2016, Jio swept over the subcontinent like a monsoon dropping a torrent of 4G infrastructure and free data rather than rain. The Moto G4 , for example. A 2021 Global Baseline.

Performance 124

Performance Network Cache Metrics 124

Testsigma

FEBRUARY 12, 2021

When more companies transition into digital-first projects, there must be an expanded number of processes and IT data departments to keep IT teams on track. of companies invest over US$ 50 million in initiatives such as Artificial Intelligence (AI) and Big Data in 2020, up from 39.7% Automation to Enhance AI Security Defence.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

All Things Distributed

JULY 13, 2010

Further computationally intensive, highly parallel workloads have found their way to Amazon EC2 as businesses have explored using HPC types of algorithms for other application categories, for example to to process very large unstructured data sets for Business Intelligence applications. Driving Storage Costs Down for AWS Customers.

Cloud 118

Cloud AWS Automotive Latency 118

All Things Distributed

DECEMBER 3, 2009

This new Region consists of multiple Availability Zones and provides low-latency access to the AWS services from for example the Bay Area. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics. blog comments powered by Disqus.

AWS 60

AWS Cloud Latency Storage 60

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. At werner.ly

AWS 85

AWS Storage Cloud Big Data 85

ScaleOut Software

MAY 4, 2014

Usually this means moving to a server with more CPU cores, greater memory capacity, and higher-end networking and storage options. Now CPU, memory, and storage resources can grow without predefined limits. We often host data sets in the terabytes in our in-memory data grid.) Finding the Right Balance.

Network 40

Network Servers Analytics Storage 40