Scalegrid

FEBRUARY 24, 2025

This guide will cover how to distribute workloads across multiple nodes, set up efficient clustering, and implement robust load-balancing techniques. While clustering across wide-area networks (WANs) is discouraged due to latency issues, leased links can mitigate some connectivity challenges.

Best Practices 147

Best Practices Traffic Strategy Efficiency 147

The Netflix TechBlog

DECEMBER 17, 2024

The Challenge of Title Launch Observability As engineers, were wired to track system metrics like error rates, latencies, and CPU utilizationbut what about metrics that matter to a titlessuccess? Additionally, the time-sensitive nature of these investigations precludes the use of cold storage, which cannot meet the stringent SLAs required.

Traffic 168

Traffic Scalability Strategy Monitoring 168

The Netflix TechBlog

OCTOBER 8, 2024

Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.

Latency 235

Latency Storage Traffic Infrastructure 235

Scalegrid

JUNE 22, 2020

Compare Latency. On average, ScaleGrid achieves almost 30% lower latency over DigitalOcean for the same deployment configurations. ScaleGrid provides 30% more storage on average vs. DigitalOcean for MySQL at the same affordable price. Read-Intensive Latency Benchmark. Balanced Workload Latency Benchmark.

Database 217

Database Benchmarking Latency Performance 217

DZone

JUNE 15, 2023

In order to gain insight into these problems, we gather a range of metrics and logs to monitor the utilization of system resources such as CPU, memory, and application-specific latencies. It is worth noting that this data collection process does not impact the performance of the application.

Latency 253

Latency Storage Strategy Metrics 253

The Netflix TechBlog

SEPTEMBER 24, 2021

Figure 1: A Simplified Video Processing Pipeline With this architecture, chunk encoding is very efficient and processed in distributed cloud computing instances. From chunk encoding to assembly and packaging, the result of each previous processing step must be uploaded to cloud storage and then downloaded by the next processing step.

Cloud 240

Cloud Media Storage Cache 240

Dynatrace

JANUARY 17, 2024

As organizations turn to artificial intelligence for operational efficiency and product innovation in multicloud environments, they have to balance the benefits with skyrocketing costs associated with AI. The good news is AI-augmented applications can make organizations massively more productive and efficient. Use containerization.

Strategy 288

Strategy Artificial Intelligence Storage Cloud 288

DZone

AUGUST 16, 2023

Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing. Bandwidth optimization: Caching reduces the amount of data transferred over the network, minimizing bandwidth usage and improving efficiency.

Cache 246

Cache Scalability Performance Latency 246

Dynatrace

JANUARY 15, 2020

Citrix is a sophisticated, efficient, and highly scalable application delivery platform that is itself comprised of anywhere from hundreds to thousands of servers. Dynatrace automation and AI-powered monitoring of your entire IT landscape help you to engage your Citrix management tools where they are most efficient. Citrix VDA.

Latency 52

Latency Performance Virtualization Infrastructure 52

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. Unlike data warehouses, however, data is not transformed before landing in storage.

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

Scalegrid

MAY 11, 2024

MongoDB offers several storage engines that cater to various use cases. The default storage engine in earlier versions was MMAPv1, which utilized memory-mapped files and document-level locking. The newer, pluggable storage engine, WiredTiger, addresses this by using prefix compression, collection-level locking, and row-based storage.

Storage 130

Storage Engineering Cache Database 130

The Netflix TechBlog

OCTOBER 27, 2020

The data warehouse is not designed to serve point requests from microservices with low latency. Therefore, we must efficiently move data from the data warehouse to a global, low-latency and highly-reliable key-value store. It leverages Netflix Scheduler for scheduling the Bulldozer Jobs. Moving data with Bulldozer at Netflix.

Latency 248

Latency Storage Big Data Tuning 248

Dynatrace

SEPTEMBER 13, 2023

This is a set of best practices and guidelines that help you design and operate reliable, secure, efficient, cost-effective, and sustainable systems in the cloud. The framework comprises six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.

AWS 305

AWS Efficiency Azure Cloud 305

Dynatrace

NOVEMBER 9, 2023

Dynatrace, in tandem with the Nutanix extension, simplifies performance monitoring and makes issue identification and resolution more efficient. Performance monitoring Dynatrace can collect performance metrics from Nutanix clusters, including latency, IOPS (Input/Output Operations Per Second), and network throughput.

Virtualization 246

Virtualization Storage Metrics Monitoring 246

The Netflix TechBlog

SEPTEMBER 2, 2020

Edgar helps Netflix teams troubleshoot distributed systems efficiently with the help of a summarized presentation of request tracing, logs, analysis, and metadata. Telltale provides Edgar with latency benchmarks that indicate if the individual trace’s latency is abnormal for this given service. What is Edgar?

Latency 297

Latency Transportation Engineering Traffic 297

High Scalability

SEPTEMBER 8, 2018

Anna is not only incredibly fast, it’s incredibly efficient and elastic too: an autoscaling, multi-tier, selectively-replicating cloud service. The issue is that Anna is now orders of magnitude more efficient than competing systems, in addition to being orders of magnitude faster. What's changed ?

Storage 199

Storage Performance AWS Cloud 199

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 236

Infrastructure Transportation Storage Open Source 236

The Netflix TechBlog

SEPTEMBER 10, 2024

With these clear benefits, we continued to build out this functionality for more devices, enabling the same efficiency wins. It was very efficient, but it had a set job size, requiring manual intervention if we wanted to horizontally scale it, and it required manual intervention when rolling out a new version.

Latency 230

Latency Cache Tuning Efficiency 230

Dynatrace

JUNE 1, 2023

Note : you might hear the term latency used instead of response time. Both latency and response time are critical to ensure reliability. Latency typically refers to the time it takes for a single request to travel from its source to its destination. Latency primarily focuses on the time spent in transit.

Website 245

Website Latency Traffic DevOps 245

Dynatrace

APRIL 8, 2024

This blog explores how vertically integrated risk management solutions that use AI and automation enable unparalleled visibility, control, and efficiency for risk management in banking. They can accomplish this all while delivering transformation efficiency and economies of scale for IT functions that maintain risk management infrastructure.

Analytics 246

Analytics Infrastructure Efficiency Technology 246

VoltDB

DECEMBER 11, 2024

By bringing computation closer to the data source, edge-based deployments reduce latency, enhance real-time capabilities, and optimize network bandwidth. Data Overload and Storage Limitations As IoT and especially industrial IoT -based devices proliferate, the volume of data generated at the edge has skyrocketed.

IoT 52

IoT Energy Logistics Latency 52

VoltDB

NOVEMBER 20, 2024

Advances in the Industrial Internet of Things (IIoT) and edge computing have rapidly reshaped the manufacturing landscape, creating more efficient, data-driven, and interconnected factories. This proximity reduces latency and enables real-time decision-making.

IoT 52

IoT Energy Latency Automotive 52

The Morning Paper

JANUARY 28, 2020

Narrowing the gap between serverless and its state with storage functions , Zhang et al., Shredder is " a low-latency multi-tenant cloud store that allows small units of computation to be performed directly within storage nodes. " SoCC’19. "Narrowing Shredder’s implementation is built on top of Seastar.

Serverless 99

Serverless Storage Latency Cloud 99

Highly Scalable

SEPTEMBER 18, 2012

These developments gradually highlight a system of relevant database building blocks with proven practical efficiency. Historically, NoSQL paid a lot of attention to tradeoffs between consistency, fault-tolerance and performance to serve geographically distributed systems, low-latency or highly available applications. Data Placement.

Database 213

Database Latency C++ Scalability 213

Dynatrace

DECEMBER 15, 2022

Besides the traditional system hardware, storage, routers, and software, ITOps also includes virtual components of the network and cloud infrastructure. This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. The primary goal of ITOps is to provide a high-performing, consistent IT environment.

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

Dynatrace

SEPTEMBER 25, 2019

Citrix is a sophisticated, efficient, and highly scalable application delivery platform that is itself comprised of anywhere from hundreds to thousands of servers. Dynatrace automation and AI-powered monitoring of your entire IT landscape help you to engage your Citrix management tools where they are most efficient. Dynatrace news.

Latency 164

Latency Performance Virtualization Infrastructure 164

The Netflix TechBlog

APRIL 26, 2022

The first version of our logger library optimized for storage by deduplicating facts and optimized for network i/o using different compression methods for each fact. Since we were optimizing at the logging level for storage and performance, we had less data and metadata to play with to optimize the query performance.

Storage 191

Storage Design Scalability Latency 191

The Netflix TechBlog

JUNE 13, 2023

By collecting and analyzing key performance metrics of the service over time, we can assess the impact of the new changes and determine if they meet the availability, latency, and performance requirements. One can perform this comparison live on the request path or offline based on the latency requirements of the particular use case.

Traffic 282

Traffic Metrics Systems Strategy 282

The Netflix TechBlog

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. This talk explores the journey, learnings, and improvements to performance analysis, efficiency, reliability, and security.

AWS 38

AWS Entertainment Open Source Benchmarking 38

All Things Distributed

JANUARY 18, 2012

Amazon DynamoDB offers low, predictable latencies at any scale. In response, we began to develop a collection of storage and database technologies to address the demanding scalability and reliability requirements of the Amazon.com ecommerce platform. s read latency, particularly as dataset sizes grow. The growth of Amazonâ??s

Scalability 162

Scalability Database Ecommerce Latency 162

Percona

MARCH 29, 2023

Compression in any database is necessary as it has many advantages, like storage reduction, data transmission time, etc. Storage reduction alone results in significant cost savings, and we can save more data in the same space. By default, MongoDB provides a snappy block compression method for storage and network communication.

Storage 130

Storage Network Open Source Latency 130

Scalegrid

JANUARY 21, 2025

Identifying key Redis metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. To monitor Redis instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold.

Strategy 130

Strategy Monitoring Latency DevOps 130

DZone

AUGUST 18, 2023

You may also know that this has led to an increase in the demand for efficient and secure data storage solutions that won’t break the bank. By processing data at the edge of the network, latency can be minimized, which means that data can be processed and analyzed faster.

IoT 130

IoT Media Latency Storage 130

Dynatrace

JUNE 1, 2023

Note : you might hear the term latency used instead of response time. Both latency and response time are critical to ensure reliability. Latency typically refers to the time it takes for a single request to travel from its source to its destination. Latency primarily focuses on the time spent in transit.

Traffic 173

Traffic Website Latency DevOps 173

Scalegrid

MARCH 28, 2024

This article will explore how they handle data storage and scalability, perform in different scenarios, and, most importantly, how these factors influence your choice. Snapshots provide point-in-time captures of the dataset, which are efficient for recovery on startup.

Cache 130

Cache Storage Architecture Scalability 130

Scalegrid

JANUARY 25, 2024

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. These essential data points heavily influence both stability and efficiency within the system.

Metrics 130

Metrics Monitoring Latency Cache 130