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. This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

MAY 23, 2024

The jobs executing such workloads are usually required to operate indefinitely on unbounded streams of continuous data and exhibit heterogeneous modes of failure as they run over long periods. Fault tolerance stands as a critical requirement for continuously operating production systems. Recovery time of the latency p90.

Engineering 185

Engineering Tuning Latency Open Source 185

DZone

FEBRUARY 27, 2024

Caching is a critical technique for optimizing application performance by temporarily storing frequently accessed data, allowing for faster retrieval during subsequent requests. Multi-layered caching involves using multiple levels of cache to store and retrieve data.

Cache 161

Cache Efficiency Architecture Design 161

The Netflix TechBlog

MARCH 10, 2020

We had an interesting challenge on our hands: we needed to build the core of our app from scratch, but we also needed data that existed in many different systems. Existing data was crucial to the behavior and business logic of our application. Existing data was crucial to the behavior and business logic of our application.

Architecture 345

Architecture Transportation Java Strategy 345

Dynatrace

JANUARY 4, 2024

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. 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.

Government 205

Government Analytics Benchmarking Storage 205

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 226

Analytics Storage Infrastructure Metrics 226

DZone

NOVEMBER 7, 2023

In the labyrinth of data-driven architectures, the challenge of data integration—fusing data from disparate sources into a coherent, usable form — stands as one of the cornerstones. As businesses amass data at an unprecedented pace, the question of how to integrate this data effectively comes to the fore.

Processing 177

Processing Architecture Technology Technology 177

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 264

Data Engineering Engineering Processing Games 264

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 206

Architecture Serverless Azure Programming 206

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 200

Architecture DevOps Monitoring Programming 200

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 272

Processing Transportation Entertainment Tuning 272

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. We do that by excluding the following from all queries in our system.

Media 264

Media Latency Architecture Database 264

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 197

Design Storage Programming Analytics 197

Scalegrid

MAY 13, 2020

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

AUGUST 17, 2021

This method of structuring, developing, and operating complex, multi-function software as a collection of smaller independent services is known as microservice architecture. Easy to leverage API interfaces connect services with core functionality, allowing applications to communicate and share data.

Architecture 246

Architecture Software Software Development 246

Dynatrace

AUGUST 17, 2021

This method of structuring, developing, and operating complex, multi-function software as a collection of smaller independent services is known as microservice architecture. Easy to leverage API interfaces connect services with core functionality, allowing applications to communicate and share data.

Architecture 245

Architecture Software Software Development 245

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 272

Artificial Intelligence Analytics Storage Architecture 272

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 189

DevOps Analytics Storage Metrics 189

The Netflix TechBlog

OCTOBER 18, 2022

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 202

Java Scalability Traffic Architecture 202

Dynatrace

NOVEMBER 10, 2022

Lifting and shifting applications from the data center to the cloud delivers only marginal benefits. To take full advantage of the scalability, flexibility, and resilience of cloud platforms, organizations need to build or rearchitect applications around a cloud-native architecture. So, what is cloud-native architecture, exactly?

Cloud 162

Cloud Architecture Serverless Infrastructure 162

The Netflix TechBlog

JANUARY 13, 2022

By Vikram Srivastava and Marcelo Mayworm Netflix has one of the most complex data platforms in the cloud on which our data scientists and engineers run batch and streaming workloads. As our subscribers grow worldwide and Netflix enters the world of gaming , the number of batch workflows and real-time data pipelines increases rapidly.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

Dynatrace

NOVEMBER 22, 2022

The nirvana state of system uptime at peak loads is known as “five-nines availability.” In its pursuit, IT teams hover over system performance dashboards hoping their preparations will deliver five nines—or even four nines—availability. How can IT teams deliver system availability under peak loads that will satisfy customers?

Infrastructure 188

Infrastructure Availability Systems Retail 188

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making.

Big Data 253

Big Data Government Analytics Processing 253

Scalegrid

JANUARY 5, 2024

Enhanced data security, better data integrity, and efficient access to information. If you’re considering a database management system, understanding these benefits is crucial. Understanding Database Management Systems (DBMS) A Database Management System (DBMS) assists users in creating and managing databases.

Efficiency 147

Efficiency Storage Database Scalability 147

Dynatrace

MAY 1, 2023

IT operations analytics is the process of unifying, storing, and contextually analyzing operational data to understand the health of applications, infrastructure, and environments and streamline everyday operations. ITOA collects operational data to identify patterns and anomalies for faster incident management and near-real-time insights.

Analytics 193

Analytics Artificial Intelligence Big Data Open Source 193

DZone

FEBRUARY 10, 2023

In today's data-driven era, it's critical to design data platforms to help business to foster innovation and compete in the market. Selecting a robust, future-proof set of tools and architecture requires an act of balance between purely technological concerns and the wider constraints of the project.

Architecture 130

Architecture Innovation Scalability Technology 130

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 235

Analytics Social Media Metrics Efficiency 235

The Netflix TechBlog

SEPTEMBER 29, 2022

Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support for Non-Parallelizable Workloads by Kostas Christidis Introduction Timestone is a high-throughput, low-latency priority queueing system we built in-house to support the needs of Cosmos , our media encoding platform. Over the past 2.5

Latency 212

Latency Systems Media Serverless 212

Dynatrace

OCTOBER 6, 2023

Grail: Enterprise-ready data lakehouse Grail, the Dynatrace causational data lakehouse, was explicitly designed for observability and security data, with artificial intelligence integrated into its foundation. Tables are a physical data model, essentially the type of observability data that you can store.

Artificial Intelligence 266

Artificial Intelligence Analytics Metrics Storage 266

Dynatrace

OCTOBER 4, 2022

Software and data are a company’s competitive advantage. But for software to work perfectly, organizations need to use data to optimize every phase of the software lifecycle. The only way to address these challenges is through observability data — logs, metrics, and traces. Teams interact with myriad data types.

Analytics 196

Analytics Software Software Storage 196

Dynatrace

JANUARY 23, 2024

AI data analysis can help development teams release software faster and at higher quality. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights? And how can they take advantage of AI without incurring skyrocketing costs to store, manage, and query data?

Performance 191

Performance DevOps Innovation Artificial Intelligence 191

Dynatrace

JUNE 15, 2021

The fact is, Reliability and Resiliency must be rooted in the architecture of a distributed system. The email walked through how our Dynatrace self-monitoring notified users of the outage but automatically remediated the problem thanks to our platform’s architecture. Fact #2: No significant impact on Dynatrace Users.

AWS 195

AWS Traffic Architecture Azure 195

The Netflix TechBlog

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

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

Dynatrace

JUNE 20, 2023

Modern IT organizations are generating more data from more tools and technologies than ever. Data is proliferating in separate silos from containers and Kubernetes to open source APIs and software to serverless compute services, such as AWS and Azure. However, they had numerous custom applications with separate APIs.

Open Source 199

Open Source Google Serverless Azure 199

ACM Sigarch

DECEMBER 19, 2022

If data movement were faster, more work could be done on the same processors. We look here at a Gedankenexperiment: move 16 bytes per cycle , addressing not just the CPU movement, but also the surrounding system design. The new instructions just need control logic to detect zero data movement, and control logic to zero-extend 0.15

Design 145

Design Systems Cache Network 145

The Netflix TechBlog

MARCH 4, 2024

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. We have also noted a great potential for further improvement by model tuning (see the section of Rollout in Production).

Tuning 210

Tuning Efficiency Big Data Engineering 210