The Netflix TechBlog

OCTOBER 28, 2021

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

DZone

JANUARY 9, 2024

In the data-driven landscape of today, automation has become indispensable across industries, not just to maximize efficiency but, more importantly, to ensure quality. This holds true for the critical field of data engineering as well. Automated testing methodologies are now imperative to deliver speed, accuracy, and integrity.

Data Engineering 130

Data Engineering Efficiency Engineering Testing 130

Dynatrace

APRIL 18, 2024

DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. Observability of applications and infrastructure serves as a critical foundation for DevOps and platform engineering, offering a comprehensive view into system performance and behavior.

DevOps 190

DevOps Engineering Artificial Intelligence Infrastructure 190

Dynatrace

MARCH 29, 2024

Five of the most common include cluster instability, resource and cost management, security, observability, and stress on engineering teams. Engineering teams are overwhelmed with stuff to do.” Providing at-a-glance data makes it possible for teams to quickly identify high-level issues and then drill down into the details.

Engineering 226

Engineering DevOps Operating System Open Source 226

DZone

JANUARY 6, 2024

Meetings are a crucial aspect of software engineering , serving as a collaboration, communication, and decision-making platform. In this article, we will delve deeper into the issues associated with meetings in software engineering and explore the available data.

Software Engineering 284

Software Engineering Efficiency Engineering Software 284

DZone

JANUARY 30, 2024

The evolution of enterprise software engineering has been marked by a series of "less" shifts — from client-server to web and mobile ("client-less"), data center to cloud ("data-center-less"), and app server to serverless.

Software Engineering 266

Software Engineering Engineering Software Software 266

Dynatrace

OCTOBER 30, 2023

Today, speed and DevOps automation are critical to innovating faster, and platform engineering has emerged as an answer to some of the most significant challenges DevOps teams are facing. Data proliferation and the increased complexity of modern multicloud environments are nearly impossible to manage without automation.

Engineering 246

Engineering DevOps Innovation Storage 246

DZone

JULY 3, 2023

Data engineering projects often require the setup and management of complex infrastructures that support data processing, storage, and analysis. In this article, we will explore the benefits of leveraging IaC for data engineering projects and provide detailed implementation steps to get started.

Data Engineering 141

Data Engineering Infrastructure Engineering Code 141

Dynatrace

FEBRUARY 12, 2024

When it comes to platform engineering, not only does observability play a vital role in the success of organizations’ transformation journeys—it’s key to successful platform engineering initiatives. The various presenters in this session aligned platform engineering use cases with the software development lifecycle.

Engineering 182

Engineering Development Infrastructure Cloud 182

Dynatrace

NOVEMBER 7, 2023

Platform engineering is on the rise. According to leading analyst firm Gartner, “80% of software engineering organizations will establish platform teams as internal providers of reusable services, components, and tools for application delivery…” by 2026.

Engineering 274

Engineering DevOps Best Practices Infrastructure 274

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 281

Systems Analytics Architecture Engineering 281

The Netflix TechBlog

JUNE 1, 2021

Data Engineers of Netflix?—?Interview Interview with Dhevi Rajendran Dhevi Rajendran This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix.

Data Engineering 138

Data Engineering Engineering Software Engineering Big Data 138

Dynatrace

MAY 3, 2024

Log data—the most verbose form of observability data, complementing other standardized signals like metrics and traces—is especially critical. As cloud complexity grows, it brings more volume, velocity, and variety of log data. When trying to address this challenge, your cloud architects will likely choose Amazon Data Firehose.

Cloud 218

Cloud Lambda AWS Analytics 218

The Netflix TechBlog

JUNE 1, 2021

Data Engineers of Netflix?—?Interview Interview with Samuel Setegne Samuel Setegne This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. For example?—?clinical

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

DZone

MARCH 14, 2023

Site Reliability Engineering (SRE) is a systematic and data-driven approach to improving the reliability, scalability, and efficiency of systems. It combines principles of software engineering, operations, and quality assurance to ensure that systems meet performance goals and business objectives.

Engineering 246

Engineering Software Engineering Scalability Efficiency 246

Dynatrace

OCTOBER 10, 2023

Planned effort Site Reliability Engineering (SRE) effort and time allocation planning typically fall into two domains: Operations Management (50%) Operations Management includes on-call responsibilities, post-mortem assessments, addressing other interruptions, and buffer time. These practices are commonly known as “ chaos engineering. ”

Engineering 227

Engineering DevOps Innovation Strategy 227

Dynatrace

OCTOBER 28, 2021

Chaos engineering answers this need so organizations can deliver robust, resilient cloud-native applications that can stand up under any conditions. What is chaos engineering? Chaos engineers ask why. As chaos engineers grow confident in their testing, they change more variables and broaden the scope of the disaster.

Engineering 226

Engineering Entertainment Cloud Infrastructure 226

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 221

Analytics Storage Infrastructure Metrics 221

Dynatrace

NOVEMBER 14, 2023

Site reliability engineering (SRE) has become increasingly important to organizations looking to keep up with the rapid pace of digital transformation. Effective site reliability engineering requires enterprise-wide transformation Without a unified understanding of SRE practices, organizational silos can quickly form between departments.

Best Practices 191

Best Practices Engineering DevOps Software Engineering 191

Dynatrace

DECEMBER 18, 2023

For busy site reliability engineers, ensuring system reliability, scalability, and overall health is an imperative that’s getting harder to achieve in ever-expanding, cloud-native, container-based environments. To get a more granular look into telemetry data, many analysts rely on custom metrics using Prometheus. What is Prometheus?

Metrics 178

Metrics Engineering Energy Tuning 178

Dynatrace

FEBRUARY 28, 2024

In a digital-first world, site reliability engineers and IT data analysts face numerous challenges with data quality and reliability in their quest for cloud control. Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices.

Analytics 210

Analytics Metrics Media Monitoring 210

Dynatrace

MARCH 15, 2024

As organizations strive for observability and data democratization, OpenTelemetry emerges as a key technology to create and transfer observability data. Understanding OpenTelemetry OpenTelemetry is an open, vendor-neutral standard for creating, collecting, and transferring telemetry data, like traces, metrics, and logs.

Open Source 284

Open Source Best Practices Infrastructure Tuning 284

Dynatrace

APRIL 29, 2021

Whilst our traditional Dynatrace website predominantly showcases Dynatrace content and product information for visitors, the idea behind the creation of our new Engineering website – engineering.dynatrace.com – was to set up a space to feature the results of our research and innovation efforts and aims to be a site made by engineers for engineers.

Engineering 261

Engineering Open Source Website Innovation 261

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 186

Performance DevOps Innovation Artificial Intelligence 186

DZone

SEPTEMBER 11, 2023

This article delves into a specialized approach for anomaly detection that makes extensive use of a rule-based engine. Overview of the System Architecture Data Stream This is the continuous flow of data that the engine reviews.

Engineering 161

Engineering Healthcare Architecture Monitoring 161

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. Rule Execution Engine is responsible for matching the collected logs against a set of predefined rules.

Tuning 210

Tuning Efficiency Big Data Engineering 210

Dynatrace

DECEMBER 8, 2022

As cloud-native, distributed architectures proliferate, the need for DevOps technologies and DevOps platform engineers has increased as well. DevOps engineer tools can help ease the pressure as environment complexity grows. ” What does a DevOps platform engineer do? .” What are DevOps engineer tools and platforms.

DevOps 191

DevOps Engineering Testing Open Source 191

The Netflix TechBlog

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.

Processing 226

Processing Data Engineering Efficiency Analytics 226

Dynatrace

SEPTEMBER 5, 2023

Predictive AI uses machine learning, data analysis, statistical models, and AI methods to predict anomalies, identify patterns, and create forecasts. Predictive AI empowers site reliability engineers (SREs) and DevOps engineers to detect anomalies and irregular patterns in their systems long before they escalate into critical incidents.

Artificial Intelligence 264

Artificial Intelligence DevOps Analytics Engineering 264

DZone

FEBRUARY 27, 2023

It's midnight in the dim and cluttered office of The New York Times, currently serving as the "situation room." A powerful surge of traffic is inevitable. During every major election, the wave would crest and crash against our overwhelmed systems before receding, allowing us to assess the damage.

Data Engineering 169

Data Engineering Engineering Traffic Systems 169

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 200

Government Analytics Benchmarking Storage 200

The Netflix TechBlog

DECEMBER 14, 2020

Life of a Netflix Partner Engineer?—?The The case of the extra 40 ms By: John Blair , Netflix Partner Engineering The Netflix application runs on hundreds of smart TVs, streaming sticks and pay TV set top boxes. The role of a Partner Engineer at Netflix is to help device manufacturers launch the Netflix application on their devices.

Engineering 352

Engineering Code Hardware Open Source 352

The Netflix TechBlog

JUNE 30, 2020

Our mission in Studio Engineering is to build a unified, global, and digital studio that powers the effective production of amazing content. link] Why Does Studio Engineering Exist? Business negotiations: Empower the Netflix Legal team with data to help with deal negotiations and acquisition of rights to produce and stream the content.

Engineering 238

Engineering Entertainment Logistics Innovation 238

DZone

MARCH 29, 2023

Data migration is the process of moving data from one location to another, which is an essential aspect of cloud migration. Data migration involves transferring data from on-premise storage to the cloud. With the rapid adoption of cloud computing , businesses are moving their IT infrastructure to the cloud.

Best Practices 304

Best Practices Cloud Storage Data Engineering 304

The Netflix TechBlog

FEBRUARY 1, 2022

By Karen Casella, Director of Engineering, Access & Identity Management Have you ever experienced one of the following scenarios while looking for your next role? Most backend engineering teams follow a process very similar to what is shown below. If so, we invite you to begin the interview process.

Engineering 199

Engineering Games Entertainment Innovation 199

Dynatrace

MARCH 11, 2024

In recent years, technologists and business leaders have dubbed data as “the new oil.” Because both oil and data require their owners to refine them to unleash their true value. So how do you realize the vast potential of data while protecting it from threats? Is data the new oil? Look, I’m an engineer,” Williamson said.

Artificial Intelligence 193

Artificial Intelligence Government Games Tuning 193

DZone

AUGUST 16, 2023

From a data engineer's point of view, financial risk management is a series of data analysis activities on financial data. The financial sector imposes its unique requirements on data engineering. Before they adopted an OLAP engine, they were using Kettle to collect data.

FinTech 130

FinTech Engineering Latency Data Engineering 130