The Netflix TechBlog

AUGUST 30, 2021

When a new hardware device is connected, the Local Registry detects and collects a set of information about it, such as networking information and ESN. Fault Tolerance If the underlying KafkaConsumer crashes due to ephemeral system or network events, it should be automatically restarted. million elements.

Latency 213

Latency Traffic Transportation Cloud 213

VoltDB

MAY 30, 2024

If you pick a data platform that can only be deployed in a set number of geographic locations, it could lead to latency issues due to increasingly stringent latency SLAs and trouble meeting those SLAs due to the limits of physics. Early RDBMS products were designed to offer SQL and ACID and not much else.

Latency 52

Latency Cloud Database Tuning 52

The Netflix TechBlog

OCTOBER 19, 2020

Now let’s look at how we designed the tracing infrastructure that powers Edgar. Reconstructing a streaming session was a tedious and time consuming process that involved tracing all interactions (requests) between the Netflix app, our Content Delivery Network (CDN), and backend microservices.

Infrastructure 233

Infrastructure Transportation Storage Open Source 233

Dynatrace

DECEMBER 22, 2019

AWS offers a broad set of global, cloud-based services including computing, storage, networking, Internet of Things (IoT), and many others. The example below visualizes average latency by API name and stage for a specific AWS API Gateway. Stay tuned for updates in Q1 2020. You can also create custom charts. Requirements.

AWS 134

AWS Metrics IoT Storage 134

Dynatrace

DECEMBER 22, 2019

AWS offers a broad set of global, cloud-based services including computing, storage, networking, Internet of Things (IoT), and many others. The example below visualizes average latency by API name and stage for a specific AWS API Gateway. Stay tuned for updates in Q1 2020. You can also create custom charts. Requirements.

AWS 132

AWS Metrics IoT Storage 132

Scalegrid

MARCH 22, 2024

They can also bolster uptime and limit latency issues or potential downtimes. Consistently evaluating and tuning resource allocations based on use patterns helps prevent overprovisioning and reduces unnecessary expenses. Scalegrid: Your Multi-Cloud Strategy Solution ScaleGrid.io

Strategy 130

Strategy Cloud Government Innovation 130

Smashing Magazine

NOVEMBER 8, 2021

As developers, we rightfully obsess about the customer experience, relentlessly working to squeeze every millisecond out of the critical rendering path, optimize input latency, and eliminate jank. Stay tuned for more in 2022! Continue reading below ↓ Meet Smart Interface Design Patterns , with Vitaly Friedman.

Cache 137

Cache Best Practices Strategy Servers 137

IO River

NOVEMBER 15, 2023

The OSI Model is like a layer cake of how data moves through networks. This means it specifically looks at the content of the data (like the writing inside our letters from the analogy) rather than just the envelope.So, what is the difference between a Firewall at the application level and network level?Network-level

Traffic 52

Traffic Network Logistics Architecture 52

The Morning Paper

JUNE 13, 2019

Making queries to an inference engine has many of the same throughput, latency, and cost considerations as making queries to a datastore, and more and more applications are coming to depend on such queries. The following figure highlights how just one of these variables, batch size, impacts throughput and latency on ResNet50.

Hardware 58

Hardware Latency Serverless Energy 58

IO River

NOVEMBER 2, 2023

The OSI Model is like a layer cake of how data moves through networks. This means it specifically looks at the content of the data (like the writing inside our letters from the analogy) rather than just the envelope.So, what is the difference between a Firewall at the application level and network level?Network-level

Traffic 40

Traffic Network Logistics Architecture 40

SQL Performance

APRIL 27, 2020

Hyperscale achieves high performance from each compute node having SSD-based caches which helps minimize the network round trips to fetch data. This way they can know that there is always a minimum compute level available, and they can always automatically scale to a designated compute level.

Azure 55

Azure Database Serverless Hardware 55

Abhishek Tiwari

JULY 12, 2018

Here are 8 fallacies of data pipeline The pipeline is reliable Topology is stateless Pipeline is infinitely scalable Processing latency is minimum Everything is observable There is no domino effect Pipeline is cost­-effective Data is homogeneous The pipeline is reliable The inconvenient truth is that pipeline is not reliable.

Latency 63

Latency Analytics Scalability Engineering 63

The Netflix TechBlog

DECEMBER 21, 2020

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. These principles reduce resource usage by being more efficient and effective while lowering the end-to-end latency in data processing. Transparency to end-users.

Storage 203

Storage Latency Efficiency Data Engineering 203

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.

Processing 229

Processing Media Latency Innovation 229

The Netflix TechBlog

SEPTEMBER 24, 2021

Uploading and downloading data always come with a penalty, namely latency. It is worth pointing out that cloud processing is always subject to variable network conditions. Doing so has the added advantage of being able to design and tune the enhancement to suit the requirements of packager and our other encoding applications.

Cloud 237

Cloud Media Storage Cache 237

The Netflix TechBlog

FEBRUARY 18, 2022

This separation allows us to tune system configuration and scaling policies independently for different event priorities and traffic patterns. This network connection heterogeneity made choosing a single delivery model difficult. This approach enables the computing power to catch up quickly when the queues grow.

Systems 334

Systems Traffic Architecture Mobile 334

SQL Server According to Bob

JANUARY 11, 2020

Many high-end disk subsystems provide high-speed cache facilities to reduce the latency of read and write operations. For specific information on I/O tuning and balancing, you will find more details in the following document. The I/O and transactional design of SQL Server ensures that the ACID properties are fully maintained.

Servers 40

Servers Cache Media Hardware 40

Smashing Magazine

AUGUST 22, 2021

As we will see, QUIC and HTTP/3 indeed have great web performance potential, but mainly for users on slow networks. If your average visitor is on a fast cabled or cellular network, they probably won’t benefit from the new protocols all that much. Two-way latency is often called round-trip time (RTT). Congestion Control.

Performance 107

Performance Network Latency Servers 107

SQL Server According to Bob

JANUARY 11, 2020

​​ With new ​​ innovations ​​ come ​​ new terms, designs, ​​ and ​​ algorithms. This is different from ​​ the reference count design ​​ that was ​​ used in SQL Server 7.0 and ​​ 2000.

Servers 40

Servers Cache Database Media 40

Smashing Magazine

AUGUST 9, 2021

You’ve probably heard things like: “HTTP/3 is much faster than HTTP/2 when there is packet loss”, or “HTTP/3 connections have less latency and take less time to set up”, and probably “HTTP/3 can send data more quickly and can send more resources in parallel”. and lower), this typically takes two network round trips.

Transportation 145

Transportation Internet Internet Network 145

All Things Distributed

OCTOBER 2, 2017

With these requirements in mind, and a willingness to question the status quo, a small group of distributed systems experts came together and designed a horizontally scalable distributed database that would scale out for both reads and writes to meet the long-term needs of our business. This was the genesis of the Amazon Dynamo database.

Internet 128

Internet Internet AWS Performance 128