Dynatrace

MAY 23, 2024

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data.

Engineering 245

Engineering Tuning Latency Open Source 245

The Netflix TechBlog

NOVEMBER 12, 2024

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

Latency 247

Latency Cache Infrastructure Strategy 247

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. It also serves as central configuration of access patterns such as consistency or latency targets.

Latency 256

Latency Storage Cache Servers 256

Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. Fault-tolerance.

Big Data 154

Big Data Processing Lambda Database 154

CSS Wizardry

OCTOBER 16, 2023

In this post, I’m going to break these processes down into each of: ? Plotted on the same horizontal axis of 1.6s, the waterfalls speak for themselves: 201ms of cumulative latency; 109ms of cumulative download. 4,362ms of cumulative latency; 240ms of cumulative download. Read the complete test methodology. It gets worse.

Cache 353

Cache Latency Strategy Speed 353

The Netflix TechBlog

SEPTEMBER 24, 2021

By Xiaomei Liu , Rosanna Lee , Cyril Concolato Introduction Behind the scenes of the beloved Netflix streaming service and content, there are many technology innovations in media processing. Packaging has always been an important step in media processing. Uploading and downloading data always come with a penalty, namely latency.

Cloud 240

Cloud Media Storage Cache 240

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.

Serverless 232

Serverless Media Latency Social Media 232

The Netflix TechBlog

FEBRUARY 18, 2022

Event Prioritization Considering the use cases were wide ranging both in terms of their sources and their importance, we built segmentation into the event processing. We thus assigned a priority to each use case and sharded event traffic by routing to priority-specific queues and the corresponding event processing clusters.

Systems 334

Systems Traffic Architecture Mobile 334

The Netflix TechBlog

MARCH 10, 2023

Hence we built the data pipeline that can be used to extract the existing assets metadata and process it specifically to each new use case. This feature support required a significant update in the data table design (which includes new tables and updating existing table columns). N, first N rows are fetched from the table.

Media 240

Media Traffic Processing Design 240

Scalegrid

FEBRUARY 6, 2025

RabbitMQ is designed for flexible routing and message reliability, while Kafka handles high-throughput event streaming and real-time data processing. RabbitMQ follows a message broker model with advanced routing, while Kafkas event streaming architecture uses partitioned logs for distributed processing. What is Apache Kafka?

Latency 147

Latency Analytics Architecture Storage 147

Dynatrace

FEBRUARY 24, 2021

DevOps is focused on optimizing software development and delivery, and SRE is focused on operations processes. DevOps is not a specific process, but rather a general collection of flexible software creation and delivery practices that looks to close the gap between software development and IT operations. Reduced latency.

DevOps 267

DevOps Software Engineering Speed Google 267

The Netflix TechBlog

NOVEMBER 3, 2022

We introduce a caching mechanism in the API gateway layer, allowing us to offload processing from singleton leader elected controllers without giving up strict data consistency and guarantees clients observe. cell): Titus Job Coordinator is a leader elected process managing the active state of the system.

Cache 228

Cache Latency Traffic Systems 228

Dynatrace

APRIL 5, 2021

AWS Lambda is a serverless compute service that can run code in response to predetermined events or conditions and automatically manage all the computing resources required for those processes. Real-time file processing, for quickly indexing files, processing logs, and validating content.

Lambda 257

Lambda AWS Serverless Hardware 257

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. Its goal is to assign running processes to time slices of the CPU in a “fair” way. So why mess with it?

Cache 255

Cache Latency Airlines Logistics 255

Dynatrace

MARCH 16, 2023

Monitors signals The first attribute of a good SLO is the ability to monitor the four “golden signals”: latency, traffic, error rates, and resource saturation. Includes the end user While SLOs for back-end silos and processes help eliminate internal issues, back-end-based objectives tell only half the story.

DevOps 264

DevOps Latency Metrics Traffic 264

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.

Latency 235

Latency Storage Traffic Infrastructure 235

Dynatrace

JUNE 7, 2023

Advanced AI applications using OpenAI services don’t just forward user input to OpenAI models; they also require client-side pre- and post-processing. 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.

Monitoring 241

Monitoring Latency Metrics Azure 241

The Netflix TechBlog

SEPTEMBER 10, 2024

The voice service then constructs a message for the device and places it on the message queue, which is then processed and sent to Pushy to deliver to the device. 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.

Latency 230

Latency Cache Tuning Efficiency 230

Dynatrace

AUGUST 27, 2019

Welcome back to the blog series in which we share how you can easily solve three common problem scenarios by using Dynatrace and xMatters Flow Designer. In Part 1 we explored how DevOps teams can prevent a process crash from taking down services across an organization in five easy steps. xMatters creates and updates Jira issues.

Systems 199

Systems DevOps Latency Azure 199

Dynatrace

JUNE 25, 2020

The network latency between cluster nodes should be around 10 ms or less. For Premium HA, this has been extended from 10 ms latency (in the same network region) to around 100 ms network latency due to asynchronous data replication between regions. In the image below, three downed nodes make an entire cluster unavailable.

Availability 264

Availability Hardware Latency Traffic 264

Dynatrace

MAY 17, 2023

To ensure high standards, it’s essential that your organization establish automated validations in an early phase of the software development process—ideally when code is written. In this case, the four golden signals (latency, traffic, errors, and saturation) are derived from span attributes and DQL metric queries via Dynatrace Grail™.

DevOps 246

DevOps Traffic Latency Best Practices 246

Dynatrace

JANUARY 31, 2024

The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources. RAG augments user prompts with relevant data retrieved from outside the LLM.

Cache 276

Cache Azure Infrastructure Monitoring 276

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. This process enables you to continuously evaluate software against predefined quality criteria and service level objectives (SLOs) in pre-production environments.

AWS 305

AWS Efficiency Azure Cloud 305

The Netflix TechBlog

OCTOBER 27, 2020

Usually Data scientists and engineers write Extract-Transform-Load (ETL) jobs and pipelines using big data compute technologies, like Spark or Presto , to process this data and periodically compute key information for a member or a video. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 248

Latency Storage Big Data Tuning 248

The Netflix TechBlog

DECEMBER 21, 2020

There are several benefits of such optimizations like saving on storage, faster query time, cheaper downstream processing, and an increase in developer productivity by removing additional ETLs written only for query performance improvement. Then deep dive into the merging use case of AutoOptimize and share some results and benefits.

Storage 208

Storage Latency Efficiency Data Engineering 208

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

Latency Cache Java Traffic 237

The Netflix TechBlog

NOVEMBER 17, 2022

A distinct, NN-based, video processing block can evolve independently, be used beyond video downscaling and be combined with different codecs. Our approach to NN-based video downscaling The deep downscaler is a neural network architecture designed to improve the end-to-end video quality by learning a higher-quality video downscaler.

Network 296

Network Media Innovation Serverless 296

The Netflix TechBlog

JUNE 13, 2023

Replay traffic testing gives us the initial foundation of validation, but as our migration process unfolds, we are met with the need for a carefully controlled migration process. A process that doesn’t just minimize risk, but also facilitates a continuous evaluation of the rollout’s impact.

Traffic 282

Traffic Metrics Systems Strategy 282

The Netflix TechBlog

AUGUST 30, 2021

The challenge, then, is to be able to ingest and process these events in a scalable manner, i.e., scaling with the number of devices, which will be the focus of this blog post. In-Order Processing The semantics of correct device information updates ingestion requires that messages be consumed in the order that they are produced.

Latency 218

Latency Traffic Transportation Cloud 218

Dynatrace

OCTOBER 1, 2021

As more organizations adopt cloud-native architectures, they are also looking for ways to implement AIOps, harnessing AI as a way to automate more processes throughout the DevSecOps life cycle. An advanced observability solution can also be used to automate more processes, increasing efficiency and innovation among Ops and Apps teams.

Metrics 363

Metrics Open Source Monitoring Cloud 363

Dynatrace

FEBRUARY 2, 2022

service availability with <50ms latency for an application with no revenue impact. A broken SLO with no owner can take longer to remediate and is more likely to recur compared to an SLO with an owner and a well-defined remediation process. To avoid this, start the SLO discussion early in the design process.

DevOps 246

DevOps Metrics Best Practices Latency 246

Dynatrace

DECEMBER 15, 2022

This transition to public, private, and hybrid cloud is driving organizations to automate and virtualize IT operations to lower costs and optimize cloud processes and systems. This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. So, what is ITOps? How does ITOps create business value?

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

Scalegrid

FEBRUARY 24, 2025

The architecture of RabbitMQ is meticulously designed for complex message routing, enabling dynamic and flexible interactions between producers and consumers. While clustering across wide-area networks (WANs) is discouraged due to latency issues, leased links can mitigate some connectivity challenges.

Best Practices 147

Best Practices Traffic Strategy Scalability 147

Dynatrace

JANUARY 13, 2022

Real user monitoring (RUM) is a performance monitoring process that collects detailed data about a user’s interaction with an application. Providing insight into the service latency to help developers identify poorly performing code. Modern digital services are complex and will sometimes fail—that’s unavoidable.

Monitoring 245

Monitoring Mobile Latency Best Practices 245

DZone

SEPTEMBER 14, 2022

Typically in low-latency development, a trade-off must be made between minimizing latency and avoiding excessive CPU utilization. In a typical application stack, multiple threads are used for servicing events, processing data, pipelining, and so on. Description of the Problem.

Latency 130

Latency Open Source Strategy Design 130

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 236

Infrastructure Transportation Storage Open Source 236

Dynatrace

DECEMBER 2, 2021

And why have SLOs and SLIs become so important as teams automate processes to consistently meet SLAs and error budgets? As defined by Gartner , service-level objectives are an agreed-upon target within an SLA that must be achieved for each activity, function, and process to provide the best opportunity for customer success.

Metrics 246

Metrics Best Practices DevOps Infrastructure 246