DZone

FEBRUARY 20, 2024

In the landscape of computer architecture, two prominent paradigms shape the realm of parallel processing: SIMD (Single Instruction, Multiple Data) and MIMD (Multiple Instruction, Multiple Data) architectures.

Architecture 296

Architecture Processing Efficiency Design 296

DZone

JANUARY 2, 2024

Sharding, a database architecture pattern, involves partitioning a database into smaller, faster, more manageable parts called shards. Key Characteristics Data Distribution: Shards can be distributed across multiple servers, reducing the load on any single server and improving response times. What Is Sharding?

Architecture 270

Architecture Database Scalability Servers 270

DZone

JULY 13, 2023

In today's data-driven world, organizations need efficient and scalable data pipelines to process and analyze large volumes of data. Medallion Architecture provides a framework for organizing data processing workflows into different zones, enabling optimized batch and stream processing.

Azure 246

Azure Architecture Efficiency Processing 246

DZone

NOVEMBER 2, 2023

It’s an underlying web application architecture that makes this process possible. In this blog, you’ll discover what a web app architecture is, how a web application architecture diagram looks, and how you can design the right architecture for web apps.

Architecture 272

Architecture Mobile Website Servers 272

DZone

FEBRUARY 28, 2025

We can then parse structured log data to be formatted for our customized analysis needs. Created by Grafana Labs in 2018, Loki has rapidly emerged as a compelling alternative to traditional logging systems, particularly for cloud-native and Kubernetes environments. Loki can provide a comprehensive log journey.

Architecture 130

Architecture Scalability Efficiency Cloud 130

Dynatrace

MAY 23, 2022

As a result, organizations are weighing microservices vs. monolithic architecture to improve software delivery speed and quality. Traditional monolithic architectures are built around the concept of large applications that are self-contained, independent, and incorporate myriad capabilities. What is monolithic architecture?

Architecture 263

Architecture DevOps Monitoring Programming 263

DZone

FEBRUARY 28, 2024

Mainframe architecture refers to the design and structure of a mainframe computer system, which is a powerful and reliable computing platform used for large-scale data processing, transaction processing, and enterprise applications.

Architecture 263

Architecture Design Processing Systems 263

Dynatrace

DECEMBER 5, 2023

Without observability, the benefits of ARM are lost Over the last decade and a half, a new wave of computer architecture has overtaken the world. ARM architecture, based on a processor type optimized for cloud and hyperscale computing, has become the most prevalent on the planet, with billions of ARM devices currently in use.

Architecture 290

Architecture Efficiency Energy Monitoring 290

DZone

NOVEMBER 7, 2023

In the rapidly evolving digital landscape, the role of data has shifted from being merely a byproduct of business to becoming its lifeblood. With businesses constantly in the race to stay ahead, the process of integrating this data becomes crucial. However, it's no longer enough to assimilate data in isolated, batch-oriented processes.

Systems 292

Systems Analytics Architecture Engineering 292

DZone

OCTOBER 8, 2024

Snowflake is a powerful cloud-based data warehousing platform known for its scalability and flexibility. To fully leverage its capabilities and improve efficient data processing, it's crucial to optimize query performance. Snowflake’s architecture consists of three main layers:

Best Practices 282

Best Practices Performance Architecture Scalability 282

Dynatrace

OCTOBER 4, 2022

For IT infrastructure managers and site reliability engineers, or SREs , logs provide a treasure trove of data. But on their own, logs present just another data silo as IT professionals attempt to troubleshoot and remediate problems. Data volume explosion in multicloud environments poses log issues.

Analytics 264

Analytics Storage Infrastructure Metrics 264

DZone

AUGUST 13, 2024

As our data grew, we had problems with AWS Redshift which was slow and expensive. But this also caused storage challenges like disk failures and data recovery. We innovatively use its snapshot feature to implement a primary-replica architecture for ClickHouse.

Artificial Intelligence 243

Artificial Intelligence Architecture AWS Storage 243

Dynatrace

JULY 7, 2022

Many organizations are taking a microservices approach to IT architecture. However, in some cases, an organization may be better suited to another architecture approach. Therefore, it’s critical to weigh the advantages of microservices against its potential issues, other architecture approaches, and your unique business needs.

Architecture 246

Architecture Serverless Azure Programming 246

Dynatrace

OCTOBER 4, 2022

Some time ago, at a restaurant near Boston, three Dynatrace colleagues dined and discussed the growing data challenge for enterprises. At its core, this challenge involves a rapid increase in the amount—and complexity—of data collected within a company. Work with different and independent data types. Grail architectural basics.

Artificial Intelligence 290

Artificial Intelligence Analytics Storage Architecture 290

DZone

NOVEMBER 16, 2023

This article is intended for data scientists, AI researchers, machine learning engineers, and advanced practitioners in the field of artificial intelligence who have a solid grounding in machine learning concepts, natural language processing , and deep learning architectures.

Artificial Intelligence 264

Artificial Intelligence Architecture Network Engineering 264

The Netflix TechBlog

MARCH 7, 2023

These media focused machine learning algorithms as well as other teams generate a lot of data from the media files, which we described in our previous blog , are stored as annotations in Marken. Marken Architecture Marken’s architecture diagram is as follows. in a video file.

Media 272

Media Latency Architecture Database 272

DZone

FEBRUARY 14, 2025

In the realm of modern software architecture, middleware plays a pivotal role in connecting various components of distributed systems. This is crucial because middleware often serves as the bridge between client applications and backend databases, handling a high volume of requests and data processing tasks.

Database 222

Database Performance Software Architecture Latency 222

Dynatrace

OCTOBER 3, 2024

Considering the latest State of Observability 2024 report, it’s evident that multicloud environments not only come with an explosion of data beyond humans’ ability to manage it. It’s increasingly difficult to ingest, manage, store, and sort through this amount of data. You can find the list of use cases here.

Performance 290

Performance Architecture Innovation Latency 290

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. What is a data lakehouse?

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

The Netflix TechBlog

AUGUST 1, 2022

Data Mesh?—?A A Data Movement and Processing Platform @ Netflix By Bo Lei , Guilherme Pires , James Shao , Kasturi Chatterjee , Sujay Jain , Vlad Sydorenko Background Realtime processing technologies (A.K.A After evaluating the options , the team has decided to create Data Mesh as our next generation data pipeline solution.

Processing 273

Processing Transportation Entertainment Tuning 273

The Netflix TechBlog

NOVEMBER 3, 2023

Democratizing Stream Processing @ Netflix By Guil Pires , Mark Cho , Mingliang Liu , Sujay Jain Data powers much of what we do at Netflix. On the Data Platform team, we build the infrastructure used across the company to process data at scale. The existing Data Mesh Processors have a lot of overlap with SQL.

Processing 271

Processing Engineering Infrastructure Latency 271

DZone

NOVEMBER 20, 2023

In fact, this is really no different than the challenges that are inherit within a single on-premises data center implementation. For more: Read the Report Employing cloud services can incur a great deal of risk if not planned and designed correctly.

Cloud 298

Cloud Architecture Systems Network 298

Dynatrace

APRIL 19, 2023

Creating an ecosystem that facilitates data security and data privacy by design can be difficult, but it’s critical to securing information. When organizations focus on data privacy by design, they build security considerations into cloud systems upfront rather than as a bolt-on consideration.

Design 246

Design Storage Programming Analytics 246

Dynatrace

DECEMBER 12, 2024

Move beyond logs-only security: Embrace a comprehensive, end-to-end approach that integrates all data from observability and security. More technology, more complexity The benefits of cloud-native architecture for IT systems come with the complexity of maintaining real-time visibility into security compliance and risk posture.

Analytics 289

Analytics Government Efficiency Innovation 289

Dynatrace

SEPTEMBER 23, 2022

Organizations continue to turn to multicloud architecture to deliver better, more secure software faster. But IT teams need to embrace IT automation and new data storage models to benefit from modern clouds. As they enlist cloud models, organizations now confront increasing complexity and a data explosion.

Cloud 245

Cloud Artificial Intelligence Innovation Architecture 245

The Netflix TechBlog

SEPTEMBER 18, 2024

Second, developers had to constantly re-learn new data modeling practices and common yet critical data access patterns. To overcome these challenges, we developed a holistic approach that builds upon our Data Gateway Platform. Data Model At its core, the KV abstraction is built around a two-level map architecture.

Latency 260

Latency Storage Cache Servers 260

Dynatrace

JANUARY 4, 2024

While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. But to be successful, data quality is critical. Teams need to ensure the data is accurate and correctly represents real-world scenarios. Consistency.

Government 263

Government Analytics Benchmarking Storage 263

The Netflix TechBlog

MARCH 4, 2025

Part 3: System Strategies and Architecture By: VarunKhaitan With special thanks to my stunning colleagues: Mallika Rao , Esmir Mesic , HugoMarques This blog post is a continuation of Part 2 , where we cleared the ambiguity around title launch observability at Netflix. Store the data in an optimized, highly distributed datastore.

Traffic 180

Traffic Strategy Entertainment Innovation 180

DZone

MARCH 6, 2025

As organizations scale their data operations in the cloud, optimizing Snowflake performance on AWS becomes crucial for maintaining efficiency and controlling costs. This comprehensive guide explores advanced techniques and best practices for maximizing Snowflake performance, backed by practical examples and implementation strategies.

AWS 165

AWS Performance Best Practices Architecture 165

Dynatrace

JUNE 9, 2023

ln a world driven by macroeconomic uncertainty, businesses increasingly turn to data-driven decision-making to stay agile. They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. All of these factors challenge DevOps maturity.

DevOps 246

DevOps Analytics Storage Metrics 246

The Netflix TechBlog

MARCH 28, 2025

Furthermore, it was difficult to transfer innovations from one model to another, given that most are independently trained despite using common data sources. This scenario underscored the need for a new recommender system architecture where member preference learning is centralized, enhancing accessibility and utility across different models.

Tuning 200

Tuning Efficiency Latency Strategy 200

Dynatrace

APRIL 20, 2023

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. based financial services group, discussed how the bank uses log monitoring on the Dynatrace platform with an emphasis on observability and security data.

Analytics 246

Analytics Infrastructure Storage Architecture 246

Scalegrid

FEBRUARY 6, 2025

RabbitMQ is designed for flexible routing and message reliability, while Kafka handles high-throughput event streaming and real-time data processing. Both serve distinct purposes, from managing message queues to ingesting large data volumes.

Latency 147

Latency Analytics Architecture Storage 147

DZone

FEBRUARY 26, 2025

With the evolution of modern applications serving increasing needs for real-time data processing and retrieval, scalability does, too. One such open-source, distributed search and analytics engine is Elasticsearch, which is very efficient at handling data in large sets and high-velocity queries.

Scalability 147

Scalability Open Source Latency Architecture 147

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 239

Latency Storage Traffic Tuning 239

Dynatrace

FEBRUARY 15, 2023

Now we’re adding Smartscape to DQL and two new data sources to Grail: Metrics on Grail and Traces on Grail. Introducing Metrics on Grail Despite their many advantages, modern cloud-native architectures can result in scalability and fragmentation challenges. You no longer need to split, distribute, or pre-aggregate your data.

Analytics 264

Analytics Social Media Metrics Design 264

The Netflix TechBlog

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. We expect complete and accurate data at the end of each run.

Data Engineering 271

Data Engineering Engineering Processing Games 271