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. We have also noted a great potential for further improvement by model tuning (see the section of Rollout in Production).

Tuning 210

Tuning Efficiency Big Data Engineering 210

DZone

FEBRUARY 27, 2024

Caching is a critical technique for optimizing application performance by temporarily storing frequently accessed data, allowing for faster retrieval during subsequent requests. Multi-layered caching involves using multiple levels of cache to store and retrieve data.

Cache 161

Cache Efficiency Architecture Design 161

DZone

FEBRUARY 2, 2024

In the rapidly evolving landscape of the Internet of Things (IoT), edge computing has emerged as a critical paradigm to process data closer to the source—IoT devices. This proximity to data generation reduces latency, conserves bandwidth and enables real-time decision-making.

IoT 195

IoT Artificial Intelligence Latency Internet 195

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.

Metrics 130

Metrics Monitoring Latency Cache 130

Dynatrace

DECEMBER 13, 2023

User demographics , such as app version, operating system, location, and device type, can help tailor an app to better meet users’ needs and preferences. Here are some ways observability data is important to mobile app performance monitoring. Load time and network latency metrics. Issue remediation. Proactive monitoring.

Best Practices 203

Best Practices Mobile Metrics Performance 203

Dynatrace

SEPTEMBER 23, 2020

Recent improvements in OneAgent runtime-data handling. Operating Systems are not always set up in the same way. Storage mount points in a system might be larger or smaller, local or remote, with high or low latency, and various speeds. Customizable location of large runtime files. See details below. See details below.

Storage 150

Storage Latency Operating System Network 150

Dynatrace

AUGUST 27, 2019

Step 2 – xMatters passes Dynatrace data to alerts that provide actionable responses. In this alert, xMatters includes all the important incident information from Dynatrace, so there’s no need for you to visit additional system dashboards. Dynatrace data in an xMatters alert (left), with actionable responses (right).

Systems 176

Systems DevOps Latency Azure 176

Dynatrace

FEBRUARY 21, 2024

Quality gates to validate the “four golden signals” The “four golden signals” represent the most crucial metrics of a customer-facing system’s performance. These metrics are latency, traffic, errors, and saturation, all of which must be key considerations when curating user experience. The failure threshold is anything above 60ms.

Speed 212

Speed Software Software Latency 212

DZone

JUNE 15, 2023

In order to gain insight into these problems, we gather a range of metrics and logs to monitor the utilization of system resources such as CPU, memory, and application-specific latencies. It is worth noting that this data collection process does not impact the performance of the application.

Latency 246

Latency Storage Strategy Metrics 246

DZone

SEPTEMBER 4, 2022

It is important to highlight that most older monitoring systems were considered inefficient due to their operational overhead. Pixie offers monitoring, telemetry, metrics, and more with less than 5% CPU overhead and latency degradation during data collection.

Monitoring 241

Monitoring Latency Metrics Cloud 241

Dynatrace

MARCH 29, 2024

As organizations continue to modernize their technology stacks, many turn to Kubernetes , an open source container orchestration system for automating software deployment, scaling, and management. Providing at-a-glance data makes it possible for teams to quickly identify high-level issues and then drill down into the details.

Engineering 231

Engineering DevOps Operating System Open Source 231

Dynatrace

DECEMBER 27, 2022

SLOs can be a great way for DevOps and infrastructure teams to use data and performance expectations to make decisions, such as whether to release and where engineers should focus their time. This telemetry data serves as the basis for establishing meaningful SLOs. SLOs aid decision making. SLOs promote automation. Reliability.

Software 269

Software Software Benchmarking Latency 269

The Morning Paper

OCTOBER 11, 2020

Orbital edge computing: nanosatellite constellations as a new class of computer system , Denby & Lucia, ASPLOS’20. Only space system architects don’t call it request-response, they call it a ‘ bent-pipe architecture.’. The old ground-initiated command-and-control style systems aren’t going to work for these finer-grained systems.

Systems 125

Systems Latency Architecture Energy 125

Dynatrace

MAY 31, 2023

Uptime Institute’s 2022 Outage Analysis report found that over 60% of system outages resulted in at least $100,000 in total losses, up from 39% in 2019. Maintaining reliable uptime and consistent service quality has become more complex as organizations expand their computing footprints across multiple data centers and in the cloud.

Best Practices 227

Best Practices DevOps Latency Metrics 227

DZone

AUGUST 16, 2023

From a data engineer's point of view, financial risk management is a series of data analysis activities on financial data. The financial sector imposes its unique requirements on data engineering. Data Must Be Combined The financial data landscape is evolving from standalone to distributed, heterogeneous systems.

FinTech 130

FinTech Engineering Latency Data Engineering 130

Dynatrace

APRIL 8, 2024

If system failures occur, teams must resolve them quickly and resolutely. Maximizing a strong foundation of IT infrastructure performance and security means effectively utilizing all the data that these systems produce to drive risk management processes and decision-making. Automated issue resolution.

Analytics 206

Analytics Infrastructure Efficiency Technology 206

Dynatrace

JANUARY 31, 2024

This blog post explores how AI observability enables organizations to predict and control costs, performance, and data reliability. It also shows how data observability relates to business outcomes as organizations embrace generative AI. GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues.

Cache 209

Cache Azure Infrastructure Monitoring 209

Dynatrace

OCTOBER 23, 2023

Hyper-V plays a vital role in ensuring the reliable operations of data centers that are based on Microsoft platforms. Microsoft Hyper-V is a virtualization platform that manages virtual machines (VMs) on Windows-based systems. Optimize resource allocation, identify bottlenecks, and improve overall system performance.

Efficiency 219

Efficiency Virtualization Hardware Performance 219

Dynatrace

DECEMBER 4, 2023

By using OpenLLMetry and Dynatrace, anyone can get complete visibility into their system, including gen-AI parts with 5 minutes of work.” Data quality and drift: Monitoring the quality and characteristics of training and runtime data to detect significant changes that might impact model accuracy. Maintained under the Apache 2.0

Open Source 262

Open Source Latency Metrics Java 262

DZone

MAY 1, 2023

It is a transversal component that applies to all the tech areas and architecture layers such as operating systems, data platforms, backend, frontend, and other components. It is a transparent layer for the data consumer in terms of user usability except to improve performance. What Is a Cache?

Cache 141

Cache Strategy Latency Operating System 141

Dynatrace

NOVEMBER 6, 2023

Cloud complexity and data proliferation are two of the most significant challenges that IT teams are facing today. Computing environments are scaling to new heights, resulting in more data that makes pinpointing root causes and vulnerabilities even more challenging. But not all teams use the same observability data in the same way.

Development 267

Development DevOps Programming Cloud 267

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. These workflows also utilize Davis® , the Dynatrace causal AI engine, and all your observability and security data across all platforms, in context, at scale, and in real-time.

AWS 252

AWS Efficiency Azure Cloud 252

High Scalability

JANUARY 11, 2022

from a client it performs two parallel operations: i) persisting the action in the data store ii) publish the action in a streaming data store for a pub-sub model. User Feed Service, Media Counter Service) read the actions from the streaming data store and performs their specific tasks. System Components. Data Models.

Design 334

Design Media Storage Logistics 334

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! In other words, false positives are bad but false negatives are the absolute worst!

Storage 288

Storage Cache Metrics Database 288

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. By providing data relevant to both parties — such as user adoption metrics for CEOs and application crash data for CTOs — organizations can find common ground.

DevOps 220

DevOps Latency Metrics Traffic 220

Dynatrace

APRIL 7, 2022

One of these solutions is Micrometer which provides 17+ pre-instrumented JVM-based frameworks for data collection and enables instrumentation code with a vendor-neutral API. That’s a large amount of data to handle. This creates a lot of complexity given different data sources, components, and tools. Here’s how it works.

Metrics 213

Metrics Latency Java Cache 213

Scalegrid

OCTOBER 24, 2019

As organizations continue to migrate to the cloud, it’s important to get in front of performance issues, such as high latency, low throughput, and replication lag with higher distances between your users and cloud infrastructure. AWS High Performance XLarge (see system details below). MySQL on AWS Performance Test. Amazon RDS.

AWS 183

AWS Latency Performance Benchmarking 183

The Morning Paper

NOVEMBER 24, 2019

Mergeable replicated data types Kaki et al., This paper was published at OOPSLA, but perhaps it’s amongst the distributed systems community that I expect there to be the greatest interest. Mergeable Replicated Data Types (MRDTs) are in the same spirit as CRDTs but with the very interesting property that they compose.

Strategy 104

Strategy Latency Systems Processing 104

Dynatrace

DECEMBER 15, 2022

Complex cloud computing environments are increasingly replacing traditional data centers. In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. The IT help desk creates a ticketing system and resolves service request issues. So, what is ITOps? Why is IT operations important?

Artificial Intelligence 208

Artificial Intelligence DevOps Hardware Virtualization 208

Smashing Magazine

SEPTEMBER 28, 2022

Five Data-Loading Patterns To Improve Frontend Performance. Five Data-Loading Patterns To Improve Frontend Performance. Data loading patterns are an essential part of your application as they will determine which parts of your application are directly usable by visitors. But isn’t waiting for the data the point?

Cache 125

Cache Performance Servers Social Media 125

Randon ASCII

SEPTEMBER 8, 2019

The fact that this shows up as CPU time suggests that the reads were all hitting in the system cache and the CPU time was the kernel overhead (note ntoskrnl.exe on the first sampled call stack) of grabbing data from the cache. Remember that these are calls to the operating system – kernel calls. Think about that for a moment.

Latency 79

Latency Cache Programming Operating System 79

Dynatrace

NOVEMBER 9, 2023

Nutanix overview dashboard The extension automatically gathers real-time performance data from your Nutanix clusters to monitor resource usage, cluster health, and more, all in one place. Disk metrics Monitor the performance of disks to ensure efficient data storage and retrieval. (Select Hub from the dock in the Dynatrace web UI.

Virtualization 198

Virtualization Storage Metrics Monitoring 198

Dynatrace

MAY 19, 2022

Every organization’s goal is to keep its systems available and resilient to support business demands. Lastly, error budgets, as the difference between a current state and the target, represent the maximum amount of time a system can fail per the contractual agreement without repercussions. Dynatrace news. A world of misunderstandings.

Automotive 274

Automotive Latency Architecture Azure 274

All Things Distributed

MARCH 12, 2018

The interfaces to our digital system have been dictated by the capabilities of our computer systems—keyboards, mice, graphical interfaces, remotes, and touch screens. As a result, they fail to deliver a truly seamless and customer-centric experience that integrates our digital systems into our analog lives.

Systems 110

Systems AWS Games Transportation 110

All Things Distributed

JUNE 7, 2017

Unlocking the value of data is a primary goal that AWS helps our customers to pursue. In recent years, an explosion of intelligent devices have created oceans of new data across many industries. This is because data gets more valuable when it can be processed together with other data. Law of Economics. Law of the Land.

AWS 120

AWS IoT Lambda Storage 120

Dynatrace

APRIL 25, 2023

Observability is essential to ensure the reliability, security and quality of any software system. Higher latency and cold start issues due to the initialization time of the functions. Observability is typically achieved by collecting three types of data from a system, metrics, logs and traces.

Serverless 213

Serverless Lambda Azure AWS 213

Dynatrace

APRIL 5, 2021

AWS Lambda enables organizations to access many types of functions from AWS’ cloud-based services, such as: Data processing, to execute code based on triggers, system states, or user actions. Real-time stream processing to perform live activity tracking, data cleansing, metrics generation, and more. Data entering a stream.

Lambda 183

Lambda AWS Serverless Hardware 183