The Netflix TechBlog

JANUARY 13, 2022

This blog will explore these two systems and how they perform auto-diagnosis and remediation across our Big Data Platform and Real-time infrastructure. This has led to a dramatic reduction in the time it takes to detect issues in hardware or bugs in recently rolled out data platform software.

Big Data 241

Big Data Infrastructure Metrics Games 241

DZone

JANUARY 20, 2023

Having a distributed and scalable graph database system is highly sought after in many enterprise scenarios.

Scalability 199

Scalability Big Data Hardware Internet 199

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? Data warehouses.

Artificial Intelligence 222

Artificial Intelligence Storage Analytics Government 222

Scalegrid

FEBRUARY 8, 2024

Their design emphasizes increasing availability by spreading out files among different nodes or servers — this approach significantly reduces risks associated with losing or corrupting data due to node failure. These distributed storage services also play a pivotal role in big data and analytics operations.

Storage 130

Storage Systems Big Data Azure 130

Scalegrid

JUNE 28, 2024

Integrating such a backend service system supported by RabbitMQ into a web application’s architecture can drastically alter its operational dynamics. It enables the smooth processing of various actions like uploading user content, sending notifications, or performing heavy-duty data operations.

IoT 130

IoT Healthcare Programming Open Source 130

Dynatrace

OCTOBER 4, 2022

Limited data availability constrains value creation. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes. Grail addresses today’s challenges of big data and cloud everywhere: Grail is highly scalable, cost-effective, and super-fast.

Analytics 246

Analytics Artificial Intelligence Storage Serverless 246

DZone

JULY 29, 2019

In today's world, data is generated in high volumes and to make something out of it, extracted data is needed to be transformed, stored, maintained, governed and analyzed. These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on.

Big Data 162

Big Data Government Open Source Storage 162

Dynatrace

JUNE 29, 2022

To drive better outcomes using hybrid cloud architectures, it helps to understand their benefits—and how to orchestrate them seamlessly. What is hybrid cloud architecture? Hybrid cloud architecture is a computing environment that shares data and applications on a combination of public clouds and on-premises private clouds.

Infrastructure 195

Infrastructure Cloud Azure AWS 195

The Netflix TechBlog

JUNE 20, 2024

To address this, we propose developing an intelligent agent that can automatically discover, map, and query all data within an enterprise. This “Enterprise Data Model/Architect Agent” employs generative AI techniques for autonomous enterprise data modeling and architecture.

Data Engineering 204

Data Engineering Engineering Entertainment Software Engineering 204

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., We’re not told how Seer figures out that a major architectural change has happened. ASPLOS’19. This was deployed for a two-month period and had 582 registered users with 165 daily actives.

Big Data 45

Big Data Cloud Performance Hardware 45

Dynatrace

APRIL 20, 2023

Logs highlight observability challenges Ingesting, storing, and processing the unprecedented explosion of data from sources such as software as a service, multicloud environments, containers, and serverless architectures can be overwhelming for today’s organizations.

Analytics 201

Analytics Infrastructure Storage Architecture 201

The Netflix TechBlog

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management.

Infrastructure 223

Infrastructure Big Data Transportation Architecture 223

Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

The Morning Paper

OCTOBER 26, 2020

Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. These two narratives of reference architecture and ingestion/indexing system are interwoven throughout the paper. Why do we need a new reference architecture?

Cloud 104

Cloud Big Data Latency Architecture 104

Dynatrace

JULY 6, 2022

As organizations continue to adopt multicloud strategies, the complexity of these environments grows, increasing the need to automate cloud engineering operations to ensure organizations can enforce their policies and architecture principles. Big data automation tools. How organizations benefit from automating IT practices.

Artificial Intelligence 202

Artificial Intelligence Tuning Strategy Big Data 202

Dynatrace

FEBRUARY 16, 2023

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022. Logs on Grail Log data is foundational for any IT analytics. .

Analytics 199

Analytics Innovation Metrics Database 199

Scalegrid

MARCH 28, 2024

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Memcached shines in scenarios where a simple, fast, and efficient caching solution is required without data persistence.

Cache 130

Cache Storage Architecture Scalability 130

ScaleOut Software

JULY 19, 2021

Today’s streaming analytics architectures are not equipped to make sense of this rapidly changing information and react to it as it arrives. This data is also periodically uploaded to a data lake for offline batch analysis that calculates key statistics and looks for big trends that can help optimize operations.

IoT 78

IoT Big Data Analytics Architecture 78

Dynatrace

JANUARY 11, 2023

As cloud and big data complexity scales beyond the ability of traditional monitoring tools to handle, next-generation cloud monitoring and observability are becoming necessities for IT teams. Hybrid cloud combines an on-premises or private data center with public cloud infrastructure. What is cloud monitoring?

Cloud 234

Cloud Monitoring Best Practices Infrastructure 234

The Netflix TechBlog

MAY 4, 2023

When undertaking system migrations, one of the main challenges is establishing confidence and seamlessly transitioning the traffic to the upgraded architecture without adversely impacting the customer experience. This blog series will examine the tools, techniques, and strategies we have utilized to achieve this goal.

Traffic 344

Traffic Latency Tuning Systems 344

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 208

Java Scalability Traffic Architecture 208

Dynatrace

APRIL 11, 2023

Cloud application security remains challenging because organizations lack end-to-end visibility into cloud architecture. As organizations migrate applications to the cloud, they must balance the agility that microservices architecture brings with the complexity and lack of transparency that can also come with it.

Cloud 200

Cloud DevOps Open Source Retail 200

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. See the health of your big data resources at a glance. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 153

Azure Cloud Big Data Virtualization 153

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. For unclassified errors, the job may be retried multiple times with the default retry policy.

Tuning 214

Tuning Efficiency Big Data Engineering 214

Adrian Cockcroft

NOVEMBER 18, 2024

Discover data sources to gain insights into your resource efficiency and environmental impact, including the AWS Customer Carbon Footprint Tool and proxy metrics from the AWS Cost & Usage Reports. This lightning talk explores how companies can cut costs and carbon emissions through architectural best practices and workload optimization.

AWS 98

AWS Energy Lambda Government 98

The Netflix TechBlog

MAY 26, 2020

These characteristics allow for an on-call response time that is relaxed and more in line with traditional big data analytical pipelines. Summary Providing Network Insight into the Cloud Network Infrastructure using VPC Flow Logs at hyper scale is made possible with the Sqooby architecture.

Network 152

Network Tuning AWS Traffic 152

Dynatrace

DECEMBER 15, 2022

AIOps (artificial intelligence for IT operations) combines big data, AI algorithms, and machine learning for actionable, real-time insights that help ITOps continuously improve operations. ITOps vs. AIOps. The three core components of an AIOps solution are the following: 1.

Artificial Intelligence 216

Artificial Intelligence DevOps Hardware Virtualization 216

Dynatrace

JANUARY 16, 2023

Specifically, they provide asynchronous communications within microservices architectures and high-throughput distributed systems. Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch.

Open Source 351

Open Source Java Operating System Programming 351

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. The audits check for equality (i.e.

Big Data 256

Big Data Government Processing Analytics 256

The Netflix TechBlog

JUNE 7, 2021

By collecting, accessing and analyzing network data from a variety of sources like VPC Flow Logs , ELB Access Logs, eBPF flow logs on the instances, etc, we can provide network insight to users and central teams through multiple data visualization techniques like Lumen , Atlas , etc. What is BPF?

Network 326

Network Transportation AWS Cloud 326

Dynatrace

MARCH 24, 2023

Using Marathon, its data center operating system (DC/OS) plugin, Mesos becomes a full container orchestration environment that, like Kubernetes and Docker Swarm, discovers services, balances loads, and manages application containers. Mesos also supports other orchestration engines, including Kubernetes and Docker Swarm.

Infrastructure 199

Infrastructure Open Source Operating System Cloud 199

The Netflix TechBlog

JUNE 1, 2021

clinical data was often small enough to fit into memory on an average computer and only in rare cases would its computation require any technical ingenuity or massive computing power. There was not enough scope to explore the distributed and large-scale computing challenges that usually come with big data processing.

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

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. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 249

Latency Storage Big Data Tuning 249

The Netflix TechBlog

NOVEMBER 20, 2023

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. Backfill: Backfilling datasets is a common operation in big data processing. append, overwrite, etc.).

Processing 215

Processing Big Data Efficiency Engineering 215

Dynatrace

MARCH 14, 2022

AIOps (or “AI for IT operations”) uses artificial intelligence so that big data can help IT teams work faster and more effectively. Over the past few years, the company has undergone a digital transformation, migrating to a hybrid, cloud-native environment built on Amazon Web Services and a microservices architecture.

Healthcare 237

Healthcare Artificial Intelligence Innovation Strategy 237

ACM Sigarch

MAY 31, 2023

Introduction Memory systems are evolving into heterogeneous and composable architectures. Heterogeneous and Composable Memory (HCM) offers a feasible solution for terabyte- or petabyte-scale systems, addressing the performance and efficiency demands of emerging big-data applications.

Latency 52

Latency Hardware Cache Architecture 52

Abhishek Tiwari

DECEMBER 27, 2017

A common theme across all these trends is to remove the complexity by simplifying data management as a whole. In 2018, we anticipate that ETL will either lose relevance or the ETL process will disintegrate and be consumed by new data architectures. Unified data management architecture.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49