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? How can we design systems that recognize these nuances and empower every title to shine and bring joy to ourmembers?

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The Netflix TechBlog

SEPTEMBER 18, 2024

These include challenges with tail latency and idempotency, managing “wide” partitions with many rows, handling single large “fat” columns, and slow response pagination. This model supports both simple and complex data models, balancing flexibility and efficiency.

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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.

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Dynatrace

MAY 23, 2024

Such frameworks support software engineers in building highly scalable and efficient applications that process continuous data streams of massive volume. Stream processing systems, designed for continuous, low-latency processing, demand swift recovery mechanisms to tolerate and mitigate failures effectively.

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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.

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The Netflix TechBlog

NOVEMBER 17, 2022

While conventional video codecs remain prevalent, NN-based video encoding tools are flourishing and closing the performance gap in terms of compression efficiency. We employed an adaptive network design that is applicable to the wide variety of resolutions we use for encoding. How do we apply neural networks at scale efficiently?

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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. Uploading and downloading data always come with a penalty, namely latency.

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Dynatrace

JUNE 7, 2023

A typical design pattern is the use of a semantic search over a domain-specific knowledge base, like internal documentation, to provide the required context in the prompt. With these latency, reliability, and cost measurements in place, your operations team can now define their own OpenAI dashboards and SLOs.

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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. To support this growth, we’ve revisited Pushy’s past assumptions and design decisions with an eye towards both Pushy’s future role and future stability. It served Pushy’s needs well for many years.

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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.

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Dynatrace

JANUARY 31, 2024

Model observability provides visibility into resource consumption and operation costs, aiding in optimization and ensuring the most efficient use of available resources. Observing AI models Running AI models at scale can be resource-intensive. However, organizations must consider which use cases will bring them the biggest ROI.

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Dynatrace

APRIL 5, 2021

The 2014 launch of AWS Lambda marked a milestone in how organizations use cloud services to deliver their applications more efficiently, by running functions at the edge of the cloud without the cost and operational overhead of on-premises servers. AWS continues to improve how it handles latency issues. Dynatrace news.

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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. As most key-value storage engines support efficiently deleting a namespace (e.g.

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The Netflix TechBlog

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

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Dynatrace

FEBRUARY 24, 2021

As Google’s Ben Treynor explains , “Fundamentally, it’s what happens when you ask a software engineer to design an operations function.” Designating and managing Service Level Objectives (SLOs) as availability targets for a service. Reduced latency. Efficiency. Streamlined change management.

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The Netflix TechBlog

JUNE 4, 2019

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. This avoids thrashing caches too much for B and evens out the pressure on the L3 caches of the machine.

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The Netflix TechBlog

MARCH 1, 2021

It supports both high throughput services that consume hundreds of thousands of CPUs at a time, and latency-sensitive workloads where humans are waiting for the results of a computation. The subsystems all communicate with each other asynchronously via Timestone, a high-scale, low-latency priority queuing system. Warm capacity.

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The Netflix TechBlog

JANUARY 10, 2024

This architecture shift greatly reduced the processing latency and increased system resiliency. We expanded pipeline support to serve our studio/content-development use cases, which had different latency and resiliency requirements as compared to the traditional streaming use case. divide the input video into small chunks 2.

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Processing Media Latency Innovation 233

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. Data lakehouses deliver the query response with minimal latency. Data warehouses.

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Artificial Intelligence Storage Analytics Government 246

The Netflix TechBlog

SEPTEMBER 8, 2020

For each route we migrated, we wanted to make sure we were not introducing any regressions: either in the form of missing (or worse, wrong) data, or by increasing the latency of each endpoint. Being able to canary a new route let us verify latency and error rates were within acceptable limits. This meant that data that was static (e.g.

Latency 237

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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. As data streams grow in complexity, processing efficiency can decline. Increased latency during peak loads. Balancing efficiency with carbon footprint reduction goals.

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IoT Energy Logistics Latency 52

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 ?

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Dynatrace

JANUARY 13, 2022

Analyzing a clinician’s clickstream when using an electronic medical record system to better improve the efficiency of data entry. Providing insight into the service latency to help developers identify poorly performing code. Tracking users’ paths through the conversion funnel and using that data for attributing revenue.

Monitoring 245

Monitoring Mobile Latency Best Practices 245

All Things Distributed

JANUARY 18, 2012

a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. Today is a very exciting day as we release Amazon DynamoDB , a fast, highly reliable and cost-effective NoSQL database service designed for internet scale applications. Amazon DynamoDB offers low, predictable latencies at any scale. Comments ().

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Scalability Database Ecommerce Latency 162

Dynatrace

JULY 24, 2023

In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. This evolution in automation, referred to as answer-driven automation, empowers teams to address complex issues in real time, optimize workflows, and enhance overall operational efficiency.

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The Netflix TechBlog

NOVEMBER 22, 2019

This entertaining romp through the tech stack serves as an introduction to how we think about and design systems, the Netflix approach to operational challenges, and how other organizations can apply our thought processes and technologies. In 2019, Netflix moved thousands of container hosts to bare metal.

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Dynatrace

OCTOBER 1, 2021

The goal of observability is to understand what’s happening across all these environments and among the technologies, so you can detect and resolve issues to keep your systems efficient and reliable and your customers happy. The architects and developers who create the software must design it to be observed.

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Metrics Open Source Monitoring Cloud 363

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.

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Database Latency C++ Scalability 213

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.

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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.

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Traffic Metrics Systems Strategy 282

The Netflix TechBlog

NOVEMBER 20, 2023

We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. As our business scales globally, the demand for data is growing and the needs for scalable low latency incremental processing begin to emerge. past 3 hours or 10 days).

Processing 214

Processing Big Data Efficiency Engineering 214

The Netflix TechBlog

OCTOBER 26, 2021

False negatives are closely related to the statistical concept of power , which gives the probability of a true positive given the experimental design and a true effect of a specific size. As a result, if the test treatment results in a small reduction in the latency metric, it’s hard to successfully identify?

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Testing Metrics Latency Design 206

The Netflix TechBlog

APRIL 26, 2022

We will share how its design has evolved over the years and the lessons learned while building it. To understand Axion’s design, we need to know the various components that interact with it. The motivation has not changed since then; the design has. Design evolution Axion fact store has four components?—?fact

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Storage Design Scalability Latency 191

Dynatrace

DECEMBER 15, 2022

ITOps refers to the process of acquiring, designing, deploying, configuring, and maintaining equipment and services that support an organization’s desired business outcomes. This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. Performance. What does IT operations do?

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

Dynatrace

FEBRUARY 2, 2022

service availability with <50ms latency for an application with no revenue impact. To avoid this, start the SLO discussion early in the design process. This can create an unnecessary distraction and steal time away from critical tasks. For example, the IT team of a bank wants to ensure that for a trailing 30-day period there is 99.9%

DevOps 246

DevOps Metrics Best Practices Latency 246

The Netflix TechBlog

MARCH 4, 2024

We have deployed Auto Remediation in production for handling memory configuration errors and unclassified errors of Spark jobs and observed its efficiency and effectiveness (e.g., For efficient error handling, Netflix developed an error classification service, called Pensive, which leverages a rule-based classifier for error classification.

Tuning 213

Tuning Efficiency Big Data Engineering 213

The Netflix TechBlog

OCTOBER 19, 2020

Now let’s look at how we designed the tracing infrastructure that powers Edgar. 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. Storage: don’t break the bank!

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