ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . By transparently distributing stored objects across a cluster of servers (physical or virtual), it automatically scales performance for fast-growing workloads and maintains consistently low access latency. In-Memory Data Grids for Fast-Changing Data.

Analytics 52

Analytics Airlines Cache Scalability 52

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

Dynatrace

DECEMBER 2, 2021

As organizations adopt microservices-based architecture , service-level objectives (SLOs) have become a vital way for teams to set specific, measurable targets that ensure users are receiving agreed-upon service levels. For example, if your SLO guarantees 99.5% For example, if your SLO is to deliver 99.5% Dynatrace news.

Metrics 189

Metrics Best Practices DevOps Infrastructure 189

Dynatrace

JULY 6, 2020

Let’s look at the Azure DB for MariaDB overview as an example. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics. Database-service views provide all the metrics you need to set up high-performance database services.

Azure 147

Azure Cloud Big Data Virtualization 147

ACM Sigarch

MARCH 18, 2019

Analytic models—including simple ones like Amdahl’s Law —represent a third, often underused, evaluation method that can provide insight for both practice and research, albeit with less accuracy. How many buffers are needed to track pending requests as a function of needed bandwidth and expected latency? Answered in Part 2.).

Systems 60

Systems Latency Performance Analytics 60

ScaleOut Software

APRIL 6, 2021

With the ScaleOut Digital Twin Streaming Service , an Azure-hosted cloud service, ScaleOut Software introduced breakthrough capabilities for streaming analytics using the real-time digital twin concept. Scaleout StreamServer® DT was created to meet this need.

IoT 52

IoT Azure Analytics Healthcare 52

ACM Sigarch

MARCH 25, 2019

Previously, Part 1 of these two blog posts provided our thesis that analytic models can complement measurement and simulations to give quick insight, show what is not possible, provide a double-check, and suggest future directions. How many buffers are needed to track pending requests as a function of needed bandwidth and expected latency?

Systems 53

Systems Latency Performance C++ 53

Abhishek Tiwari

JULY 12, 2018

It can be used to power new analytics, insight, and product features. It can be used to power new analytics, insight, and product features. Processing latency is minimum If only you can infinitely scale your data pipeline, processing latency can be guaranteed to be minimum, but we know for sure that is not true.

Latency 63

Latency Analytics Scalability Engineering 63

ScaleOut Software

AUGUST 18, 2018

This minimizes event-handling latency and enables better management of local operations, while still providing strategic analysis and control by remote (cloud-based or on-premises) IoT applications. The digital twin provides a powerful answer to this challenge.

IoT 45

IoT Ecommerce Analytics Latency 45

ScaleOut Software

AUGUST 18, 2018

This minimizes event-handling latency and enables better management of local operations, while still providing strategic analysis and control by remote (cloud-based or on-premises) IoT applications. The digital twin provides a powerful answer to this challenge.

IoT 40

IoT Ecommerce Analytics Latency 40

Scalegrid

DECEMBER 21, 2023

With its widespread use in modern application architectures, understanding the ins and outs of Redis® monitoring is essential for any tech professional. Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. Redis®, a powerful in-memory data store, is no exception.

Strategy 130

Strategy Monitoring Latency DevOps 130

VoltDB

FEBRUARY 28, 2018

As a result, these iterations of blockchain have extremely low throughput, extremely high latency, and low capacity—none of which is acceptable for, as an example, mission-critical trading systems in financial services. With VoltDB V8, we’ve added support for CTEs and recursive CTEs for graph traversal.

Blockchain 45

Blockchain Technology Technology Database 45

The Netflix TechBlog

JANUARY 10, 2024

This architecture shift greatly reduced the processing latency and increased system resiliency. We expanded pipeline support to serve our studio/content-development use cases, which had different latency and resiliency requirements as compared to the traditional streaming use case.

Processing 229

Processing Media Latency Innovation 229

Scalegrid

FEBRUARY 8, 2024

Distributed Storage Architecture Distributed storage systems are designed with a core framework that includes the main system controller, a data repository for the system, and a database. Durability Availability Fault tolerance These combined outcomes help minimize latency experienced by clients spread across different geographical regions.

Storage 130

Storage Systems Big Data Azure 130

VoltDB

FEBRUARY 28, 2018

As a result, these iterations of blockchain have extremely low throughput, extremely high latency, and low capacity—none of which is acceptable for, as an example, mission-critical trading systems in financial services. With VoltDB V8, we’ve added support for CTEs and recursive CTEs for graph traversal.

Blockchain 40

Blockchain Technology Technology Database 40

Highly Scalable

AUGUST 20, 2013

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. A typical example of pipelining is shown below: In this example, the hash join algorithm is employed to join four relations: R1, S1, S2, and S3 using 3 processors.

Big Data 154

Big Data Processing Lambda Database 154

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 down the cost of Big-Data analytics.

Cloud 118

Cloud AWS Automotive Latency 118

The Netflix TechBlog

JULY 26, 2021

Netflix is known for its loosely coupled microservice architecture and with a global studio footprint, surfacing and connecting the data from microservices into a studio data catalog in real time has become more important than ever. See example below. Example: Filter Processor, Sink Processors Opt in to schema Evolution example 2.

Big Data 253

Big Data Government Analytics Processing 253

All Things Distributed

DECEMBER 5, 2010

A simple example is the situation with Persons and Telephones; a person has a name, a person can have one or more telephones and each phone can have one or more telephone numbers. Modern systems require much faster update propagation to for example deal with outages. Driving down the cost of Big-Data analytics. No lock-in.

Cloud 117

Cloud Internet Internet AWS 117

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

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. At Netflix, we also heavily embrace a microservice architecture that emphasizes separation of concerns.

Latency 243

Latency Storage Big Data Tuning 243

The Netflix TechBlog

SEPTEMBER 2, 2020

While this abundance of dashboards and information is by no means unique to Netflix, it certainly holds true within our microservices architecture. Example call graph in Edgar In some cases, the question we’re answering is, “What’s happening right now??” The downside is that we have so many dashboards.

Latency 296

Latency Transportation Engineering Traffic 296

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. cameras) in many usages ranging from digital security/surveillance and automated retail (e.g.

Wireless 54

Wireless IoT Analytics Architecture 54

The Netflix TechBlog

NOVEMBER 20, 2023

As our business scales globally, the demand for data is growing and the needs for scalable low latency incremental processing begin to emerge. 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.

Processing 210

Processing Big Data Efficiency Engineering 210

Dynatrace

NOVEMBER 3, 2021

Organizations are depending more and more on distributed architectures to provide application services. For example, we can actively watch a single metric for changes that indicate a problem — this is monitoring. Examples include a spike in memory utilization, a decrease in cache hit ratio, or an increase in CPU utilization.

Monitoring 219

Monitoring Metrics DevOps Scalability 219

Dynatrace

JUNE 25, 2021

Already in the 2000s, service-oriented architectures (SOA) became popular, and operations teams discovered the need to understand how transactions traverse through all tiers and how these tiers contributed to the execution time and latency. Let me give you an example. In both cases, a broken trace will be the result.

Open Source 198

Open Source Monitoring Google Systems 198

Smashing Magazine

SEPTEMBER 24, 2021

It can be hosted on a CDN like Vercel or Netlify, which results in lower latency. When you run npx create-next-app , you will have a folder structure like the following (this is also how most examples are structured): /public logo.gif /src /lib /hooks useForm.js /api content.js /components Header.js Challenges. Developing with Next.js

Website 114

Website Code Servers Analytics 114

All Things Distributed

JULY 14, 2015

In this blog post, I will explain how these three new capabilities empower you to build applications with distributed systems architecture and create responsive, reliable, and high-performance applications using DynamoDB that work at any scale. DynamoDB Cross-region Replication.

Database 167

Database Lambda AWS IoT 167

Dotcom-Montior

NOVEMBER 24, 2021

Ok, so maybe that is an oversimplified example, but you get the point. Gone are the days of monolithic architecture. Today, there are a variety of architectures and systems in use. Today, there are a variety of architectures and systems in use. Blockchain is a good example of this. Onto the next project.

Systems 74

Systems Monitoring Hardware Network 74

Smashing Magazine

AUGUST 3, 2023

But once we had a good understanding, we knew exactly what to look for and began analyzing the analytics of our user data to identify areas that could be improved. We can then forward this data to a custom analytics service. Here are some examples: Looker Studio filter. One of the key Next.js Time to First Byte over time.

Performance 74

Performance Cache Traffic Metrics 74

IO River

NOVEMBER 15, 2023

For example, if a request activates a rule designed to block SQL injection attempts, the WAF might automatically block that request, preventing it from reaching your web application.‍Security Two of them are particularly gnarly: fine-tuning rules to perfection and managing a WAF over a multi-CDN architecture.

Traffic 52

Traffic Network Logistics Architecture 52

IO River

NOVEMBER 2, 2023

Let us look at some notable examples of industries that place a high priority on availability:‍E-commerce and RetailThe increasing digitization of commerce means consumers expect seamless, around-the-clock shopping experiences. Therefore the availability of this system is 99.77%.Contrasting

Availability 52

Availability Social Media Traffic Games 52

IO River

NOVEMBER 2, 2023

Let us look at some notable examples of industries that place a high priority on availability:‍E-commerce and RetailThe increasing digitization of commerce means consumers expect seamless, around-the-clock shopping experiences. Therefore the availability of this system is 99.77%.Contrasting

Availability 52

Availability Social Media Traffic Games 52

Alex Russell

JANUARY 30, 2024

Put another way, the performance gap between what devices the wealthy carry and what budget shoppers carry grew more this year (252 points) than the year-over-year gains from process and architecture at the volume price point (174 points). That's where the good news ends. But that's not the whole story! target="_new"> the U.K.

Performance 90

Performance Network Mobile Speed 90

IO River

NOVEMBER 2, 2023

For example, if a request activates a rule designed to block SQL injection attempts, the WAF might automatically block that request, preventing it from reaching your web application.‍Security Flywheel‍‍When it comes to fortifying web applications, think of security as a flywheel—an ever-revolving cycle that gains momentum with each turn.

Traffic 40

Traffic Network Logistics Architecture 40

All Things Distributed

NOVEMBER 15, 2010

Building general purpose architectures has always been hard; there are often so many conflicting requirements that you cannot derive an architecture that will serve all, so we have often ended up focusing on one side of the requirements that allow you to serve that area really well.

AWS 136

AWS Latency Programming Architecture 136

All Things Distributed

JANUARY 18, 2012

Amazon DynamoDB offers low, predictable latencies at any scale. This architectural pattern was a response to the scaling challenges that had challenged Amazon.com through its first 5 years, when direct database access was one of the major bottlenecks in scaling and operating the business. This impacts the predictability of a Domainâ??s

Scalability 167

Scalability Database Ecommerce Latency 167