Dynatrace

JANUARY 31, 2024

This blog post explores how AI observability enables organizations to predict and control costs, performance, and data reliability. Figure 1: Sample RAG architecture While this approach significantly improves the response quality of GenAI applications, it also introduces new challenges.

Cache 209

Cache Azure Infrastructure Monitoring 209

Dynatrace

JANUARY 14, 2022

The Akamas vision is that only an autonomous optimization approach powered by AI can effectively enable performance engineers, SREs, and architects to identify the best configurations that ensure maximum service performance and resilience, at the lowest possible cost and at business speed. below 500ms) and error rates (e.g. lower than 2%.).

Latency 210

Latency Tuning Efficiency AWS 210

Dynatrace

MAY 13, 2022

Because of its scalability and distributed architecture, thousands of companies trust it to run their cloud and hybrid-based workloads at high availability without compromising performance. With the Dynatrace Data Explorer, you can easily analyze metrics, such as client read/write latency by Cassandra nodes and disk space usage by keyspaces.

Azure 239

Azure Latency Metrics Infrastructure 239

Adrian Cockcroft

JANUARY 20, 2023

Here’s some predictions I’m making: Jack Dongarra’s efforts to highlight the low efficiency of the HPCG benchmark as an issue will influence the next generation of supercomputer architectures to optimize for sparse matrix computations. Next generation architectures will use CXL3.0 Next generation architectures will use CXL3.0

Architecture 52

Architecture Latency Benchmarking AWS 52

The Netflix TechBlog

SEPTEMBER 24, 2021

Our previous tech blog Packaging award-winning shows with award-winning technology detailed our packaging technology deployed on the streaming side. Table 1: Movie and File Size Examples Initial Architecture A simplified view of our initial cloud video processing pipeline is illustrated in the following diagram.

Cloud 237

Cloud Media Storage Cache 237

The Netflix TechBlog

NOVEMBER 17, 2022

In this tech blog, we describe how we improved Netflix video quality with neural networks, the challenges we faced and what lies ahead. 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 292

Network Media Innovation Efficiency 292

The Netflix TechBlog

NOVEMBER 3, 2022

The original assumptions and architectural choices were no longer viable. This blog post presents how our current iteration of Titus deals with high API call volumes by scaling out horizontally. Overview The figure below depicts a simplified high-level architecture of a single Titus cluster (a.k.a

Cache 224

Cache Latency Traffic Systems 224

The Netflix TechBlog

APRIL 27, 2023

Engineers want their alerting system to be realtime, reliable, and actionable. A few years ago, we were paged by our SRE team due to our Metrics Alerting System falling behind — critical application health alerts reached engineers 45 minutes late! The internals here are outside the scope of this blog post. OK, Results?

Storage 288

Storage Cache Metrics Database 288

Dynatrace

MAY 19, 2022

A service-level objective ( SLO ) is the new contract between business, DevOps, and site reliability engineers (SREs). Example 1: Architecture boundaries. First, they took a big step back and looked at their end-to-end architecture (Figure 2). SLO dashboard defined by architectural boundary. So, what did they do?

Automotive 275

Automotive Latency Architecture Azure 275

The Netflix TechBlog

FEBRUARY 18, 2022

In this blog post, we will give an overview of the Rapid Event Notification System at Netflix and share some of the learnings we gained along the way. Personalized Experience Refresh Netflix Recommendation engine continuously refreshes recommendations for every member. This messaging system is described in this blog post.

Systems 334

Systems Traffic Architecture Mobile 334

Adrian Cockcroft

MAY 6, 2023

They state in the blog that this was quick to build, which is the point. A real-time user experience analytics engine for live video, that looked at all users rather than a subsample. When you are exploring how to construct something, building a prototype in a few days or weeks is a good approach. Finally, what were they building?

Serverless 145

Serverless Lambda Best Practices Traffic 145

High Scalability

FEBRUARY 19, 2021

You can view the original article on Ably's blog. This means a system that is not merely available but is also engineered with extensive redundant measures to continue to work as its users expect. Being tolerant to non-binary failures requires a lot of thought, engineering and, sometimes, human intervention.

Engineering 215

Engineering Systems Scalability Availability 215

The Netflix TechBlog

NOVEMBER 3, 2023

In our last blog post, we introduced “Data Mesh” — A Data Movement and Processing Platform. By leveraging Flink SQL within a Data Mesh Processor, we were able to support the streaming SQL functionality without changing the architecture of Data Mesh.

Processing 265

Processing Engineering Infrastructure Latency 265

The Netflix TechBlog

SEPTEMBER 2, 2020

For engineers, instead of whodunit, the question is often “what failed and why?” An engineer can find herself digging through logs, poring over traces, and staring at dozens of dashboards. While this abundance of dashboards and information is by no means unique to Netflix, it certainly holds true within our microservices architecture.

Latency 296

Latency Transportation Engineering Traffic 296

The Netflix TechBlog

JUNE 13, 2023

Our previous blog post presented replay traffic testing — a crucial instrument in our toolkit that allows us to implement these transformations with precision and reliability. This blog post will delve into the techniques leveraged at Netflix to introduce these changes to production.

Traffic 279

Traffic Metrics Systems Strategy 279

The Netflix TechBlog

NOVEMBER 20, 2023

It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. In this blog post, we talk about the landscape and the challenges in workflows at Netflix. Note that the backfill support is skipped in this blog. There are three common issues that the dataset owners usually face.

Processing 210

Processing Big Data Efficiency Engineering 210

Dynatrace

SEPTEMBER 18, 2020

Cloud-based application architectures commonly leverage microservices. By leveraging the Dynatrace Davis AI causation engine to watch for unforeseen changes in underlying API responsiveness, Dynatrace automatically identifies slowdowns in the performance of your API manager and points you to their root cause.

Infrastructure 192

Infrastructure Latency Metrics Analytics 192

The Netflix TechBlog

FEBRUARY 20, 2019

by Jason Koch , with Martin Spier , Brendan Gregg , Ed Hunter Improving the tools available to our engineers to help them diagnose, triage, and work through software performance challenges in the cloud is a key goal for the cloud performance engineering team at Netflix. Vector is open source and in use by multiple companies.

Performance 211

Performance Latency Open Source Metrics 211

The Netflix TechBlog

MARCH 4, 2024

In this blog post, we present our project on Auto Remediation, which integrates the currently used rule-based classifier with an ML service and aims to automatically remediate failed jobs without human intervention. 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

SEPTEMBER 13, 2023

Because Google offers its own Google Cloud Architecture Framework and Microsoft its Azure Well-Architected Framework , organizations that use a combination of these platforms triple the challenge of integrating their performance frameworks into a cohesive strategy. One of the powerful workflows to leverage is continuous release validation.

AWS 252

AWS Efficiency Azure Cloud 252

The Netflix TechBlog

SEPTEMBER 8, 2020

This allowed Android engineers to have much more control and observability over how we get our data. Image taken from a previously published blog post As you can see, our code was just a part (#2 in the diagram) of this monolithic service. It was a Node.js The context around why the Node.js

Latency 233

Latency Cache Java Traffic 233

Dynatrace

NOVEMBER 3, 2021

Organizations are depending more and more on distributed architectures to provide application services. For example, when monitoring a database, you’ll want to know about any latency when writing data to a disk or average query response time. appeared first on Dynatrace blog. Dynatrace news.

Monitoring 226

Monitoring Metrics DevOps Scalability 226

O'Reilly Software

DECEMBER 11, 2017

A message-based microservices architecture offers many advantages, making solutions easier to scale and expand with new services. The asynchronous nature of interservice interactions inherent to this architecture, however, poses challenges for user-initiated actions such as create-read-update-delete (CRUD) requests on an object.

Architecture 68

Architecture Government Latency Efficiency 68

The Netflix TechBlog

NOVEMBER 2, 2021

The Reloaded system is a well-matured and scalable system, but its monolithic architecture can slow down rapid innovation. Cosmos offers several benefits as highlighted in the linked blog, such as separation of concerns, independent deployments, observability, rapid prototyping and productization. via bug fixes).

Media 171

Media Innovation Metrics Latency 171

Dynatrace

APRIL 5, 2021

Lambda’s highly efficient, on-demand computing environment aligns with today’s microservices-centric architectures, and readily integrates with other popular AWS offerings that an organization may already be using. AWS continues to improve how it handles latency issues. appeared first on Dynatrace blog.

Lambda 184

Lambda AWS Serverless Hardware 184

The Netflix TechBlog

MAY 5, 2021

In the future posts, we will do an architectural deep dive into the several components of Netflix Drive. Netflix Drive contains an abstraction layer below FUSE which allows different metadata and data stores to be plugged into the architecture by having their corresponding adapters implement the interface. A sample manifest file.

Media 174

Media Storage Architecture Cloud 174

John McCalpin

APRIL 25, 2023

Some I will address today, and some in the next blog entry. Details in the next blog entry.) To understand what is happening here, we need to understand the way memory bandwidth interacts with memory latency and the concurrency (parallelism) of memory accesses. These observations naturally give rise to a variety of questions.

Benchmarking 97

Benchmarking Cache Latency Tuning 97

Dynatrace

DECEMBER 2, 2021

As organizations adopt microservices-based architecture , service-level objectives (SLOs) have become a vital way for teams to set specific, measurable targets that ensure users are receiving agreed-upon service levels. You can set SLOs based on individual indicators, such as batch throughput, request latency, and failures-per-second.

Metrics 196

Metrics Best Practices DevOps Infrastructure 196

Uber Engineering

MAY 14, 2019

To deliver the real-time performance expected from Uber’s users, our mobile apps require low-latency and highly … The post Employing QUIC Protocol to Optimize Uber’s App Performance appeared first on Uber Engineering Blog.

Wireless 111

Wireless Performance Mobile Latency 111

All Things Distributed

JULY 20, 2015

Today, I want to explore the Amazon ECS architecture and what this architecture enables. This architecture affords Amazon ECS high availability, low latency, and high throughput because the data store is never pessimistically locked. Below is a diagram of the basic components of Amazon ECS: How we coordinate the cluster.

Latency 166

Latency Architecture AWS Open Source 166

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. Sometimes Data Engineers write downstream ETLs on ingested data to optimize the data/metadata layouts to make other ETL processes cheaper and faster.

Storage 203

Storage Latency Efficiency Data Engineering 203

The Netflix TechBlog

AUGUST 13, 2020

Over the years we’ve learned from on-call engineers about the pain points of application monitoring: too many alerts, too many dashboards to scroll through, and too much configuration and maintenance. For example, a latency increase is less critical than error rate increase and some error codes are less critical than others.

Monitoring 210

Monitoring Tuning Traffic Metrics 210

Dynatrace

JUNE 25, 2021

I lead a dedicated Dynatrace engineering team which has contributed to the OpenTelemetry project since its inception. Following is a list of questions that I hear frequently; I will answer these questions in this blog post. The post Open Observability – Part 1: Distributed tracing and observability appeared first on Dynatrace blog.

Open Source 202

Open Source Monitoring Google Systems 202

Percona

JULY 17, 2023

In this blog, we’ll examine the reasons why people would seek an alternative to MongoDB Enterprise, and we’ll identify some of the most popular NoSQL alternatives. First, some stage-setting for this blog article. 1 among non-relational/document-based systems ( DB-Engines, July 2023 ). It ranks No.

Open Source 73

Open Source Database Scalability Software 73

The Netflix TechBlog

SEPTEMBER 3, 2021

Remote calls are never free; they impose extra latency, increase probability of an error, and consume network bandwidth. The solution we use within the Netflix Studio Engineering is protobuf FieldMask. This blog post covered how and why it is used at Netflix Studio Engineering for APIs that read the data.

Design 245

Design Java Efficiency Code 245

Dynatrace

JULY 6, 2020

All this comes with the Dynatrace zero-configuration approach, automatic service detection, continuous data capture in context, and answers, not just data, from the Dynatrace Davis AI engine, making you ready for large-scale Azure deployments. Gain enhanced visibility into your Azure environment.

Azure 150

Azure Cloud Big Data Virtualization 150

Dotcom-Montior

NOVEMBER 24, 2021

Gone are the days of monolithic architecture. Within an organization, the responsibility of monitoring these large distributed systems typically falls on site reliability engineering (SRE) teams. Today, there are a variety of architectures and systems in use. Types of Distributed Systems. Multi-Tier.

Systems 74

Systems Monitoring Hardware Network 74