Dynatrace

AUGUST 25, 2023

These signals ( latency, traffic, errors, and saturation ) provide a solid means of proactively monitoring operative systems via SLOs and tracking business success. Performance typically addresses response times or latency aspects and contributes to the four golden signals. This is what Dynatrace captures as response time.

Performance 182

Performance Latency Traffic Metrics 182

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 224

Cache Latency Traffic Systems 224

Dynatrace

MAY 21, 2024

With the latest advances from Dynatrace, this process is instantaneous. That’s because it does not require any pre-prepared schemas, and access to cold/hot storage is fully automatic and with zero latency. Moreover, it is fast, powered by its massively parallel processing data lakehouse.

Technology 209

Technology Technology Analytics Storage 209

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 291

Cache Latency Strategy Speed 291

Dynatrace

JUNE 1, 2023

But how do you get started, and what are some service level objective examples? In this post, I’ll lay out five foundational service level objective examples that every DevOps and SRE team should consider. Five example SLOs for faster, more reliable apps 1. Note : you might hear the term latency used instead of response time.

Latency 185

Latency Website Traffic Virtualization 185

The Netflix TechBlog

MARCH 6, 2019

—?Mounting object storage in Netflix’s media processing platform By Barak Alon (on behalf of Netflix’s Media Cloud Engineering team) MezzFS (short for “Mezzanine File System”) is a tool we’ve developed at Netflix that mounts cloud objects as local files via FUSE. Encoding is not a one-time process?—?large We have one file?—?the

Media 214

Media Storage Processing Cache 214

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. It can achieve impressive performance, handling up to 50 million operations per second.

Metrics 130

Metrics Monitoring Latency Cache 130

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. For example, a video encoding service is built of components that are scale-agnostic: API, workflow, and functions.

Serverless 228

Serverless Media Latency Social Media 228

KeyCDN

FEBRUARY 13, 2020

Push Zones are now seamlessly supporting Image Processing ! The complete feature set of Image Processing is now also available for Push Zones. This is ideal for delivering images of any size with low latency regardless of where the user is located. No commitment: Scale up and down anytime and only pay for the images processed.

Processing 78

Processing Storage Latency Servers 78

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. Our example dashboard below visualizes OpenAI token consumption. Businesses in all sectors are introducing novel approaches to innovate with generative AI in their domains.

Monitoring 171

Monitoring Latency Metrics Azure 171

The Netflix TechBlog

MAY 4, 2023

It provides a good read on the availability and latency ranges under different production conditions. The upstream service calls the existing and new replacement services concurrently to minimize any latency increase on the production path. For example, if some fields in the responses are timestamps, those will differ.

Traffic 339

Traffic Latency Tuning Systems 339

Dynatrace

SEPTEMBER 13, 2023

For example, optimizing resource utilization for greater scale and lower cost and driving insights to increase adoption of cloud-native serverless services. This process enables you to continuously evaluate software against predefined quality criteria and service level objectives (SLOs) in pre-production environments.

AWS 256

AWS Efficiency Azure Cloud 256

High Scalability

JANUARY 11, 2022

There are two major processes which gets executed when a user posts a photo on Instagram. Firstly, the synchronous process which is responsible for uploading image content on file storage, persisting the media metadata in graph data-storage, returning the confirmation message to the user and triggering the process to update the user activity.

Design 334

Design Media Storage Logistics 334

Dynatrace

MAY 19, 2022

However, many teams struggle with knowing which ones to use and how to incorporate them into the processes. Below, several Dynatrace customers shared their SLO management journey and discussed the resulting dashboards they rely on daily to manage their mission-critical business processes and applications. What are SLOs?

Automotive 277

Automotive Latency Architecture Azure 277

Dynatrace

FEBRUARY 15, 2023

Streamline development and delivery processes Nowadays, digital transformation strategies are executed by almost every organization across all industries. SREs use Service-Level Indicators (SLI) to see the complete picture of service availability, latency, performance, and capacity across various systems, especially revenue-critical systems.

DevOps 227

DevOps Latency Traffic Best Practices 227

The Netflix TechBlog

MARCH 7, 2024

In addition to Spark, we want to support last-mile data processing in Python, addressing use cases such as feature transformations, batch inference, and training. We use metaflow.Table to resolve all input shards which are distributed to Metaflow tasks which are responsible for processing terabytes of data collectively.

Systems 226

Systems Media Cache Open Source 226

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 224

DevOps Latency Metrics Traffic 224

The Netflix TechBlog

NOVEMBER 3, 2023

Democratizing Stream Processing @ Netflix By Guil Pires , Mark Cho , Mingliang Liu , Sujay Jain Data powers much of what we do at Netflix. On the Data Platform team, we build the infrastructure used across the company to process data at scale. In our last blog post, we introduced “Data Mesh” — A Data Movement and Processing Platform.

Processing 265

Processing Engineering Infrastructure Latency 265

DZone

AUGUST 16, 2023

For example, in this use case scenario, the fintech service provider needs to connect the various transaction processing (TP) systems (MySQL, Oracle, and PostgreSQL) of its partnering banks. The ever-enlarging data size at the source end was pushing the system toward latency and instability.

FinTech 130

FinTech Engineering Latency Data Engineering 130

Dynatrace

JANUARY 31, 2024

For example, a Stanford University and UC Berkeley team noted in a research study that ChatGPT behavior deteriorates over time. Using the example of a chatbot, once the user submits a natural language prompt, RAG summarizes that prompt using semantic data. Consequently, AI model drift and hallucinations emerge as primary concerns.

Cache 212

Cache Azure Infrastructure Monitoring 212

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. How Dynatrace uses Site Reliability Guardian In each of these Dynatrace examples, insight is made in a production-like environment.

DevOps 195

DevOps Traffic Latency Best Practices 195

Dynatrace

MAY 13, 2022

For example, the Dynatrace Data Explorer enables you to do the following: Analyze multidimensional metrics , whether built into Dynatrace or ingested from other sources like Azure Monitor. 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 241

Azure Latency Metrics Infrastructure 241

Dynatrace

MAY 31, 2023

By automating and accelerating the service-level objective (SLO) validation process and quickly reacting to regressions in service-level indicators (SLIs), SREs can speed up software delivery and innovation. The growing amount of data processed at the network edge, where failures are more difficult to prevent, magnifies complexity.

Best Practices 230

Best Practices DevOps Latency Metrics 230

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 237

Cloud Media Storage Cache 237

Scalegrid

DECEMBER 21, 2023

Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold. Setting Up RedisInsight Getting RedisInsight up and running is a simple process.

Strategy 130

Strategy Monitoring Latency DevOps 130

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 243

Latency Storage Big Data Tuning 243

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

Dynatrace

JANUARY 26, 2021

REST APIs, authentication, databases, email, and video processing all have a home on serverless platforms. The Serverless Process. AWS Lambda functions are an example of how a serverless framework works: Developers write a function in a supported language or platform. Building APIs (for example, Amazon API Gateway ).

Serverless 245

Serverless Efficiency Lambda Azure 245

Dynatrace

JULY 18, 2023

As software development grows more complex, managing components using an automated onboarding process becomes increasingly important. While developers edit files, a simple CLI command applies configurations to Dynatrace and, for example, automates the setup of a quality gate, including workflows and Site Reliability Guardians.

Best Practices 198

Best Practices Code Infrastructure Latency 198

Dynatrace

NOVEMBER 6, 2023

In this example, Grabner saw that the adservice workload was running on EKS and could see the relevant metrics, logs, services, events, error logs, and more. In Grabner’s example, he could see there was a JavaScript error increase and could understand the impact of the error. “I Laifenfeld used a to-do list app as an example. “I

Development 270

Development DevOps Programming Cloud 270

The Netflix TechBlog

JULY 26, 2021

Operational Reporting is a reporting paradigm specialized in covering high-resolution, low-latency data sets, serving detailed day-to-day activities¹ and processes of a business domain. See example below. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.

Big Data 253

Big Data Government Analytics Processing 253

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 279

Traffic Metrics Systems Strategy 279

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. Data Sharding strategy in elasticsearch is updated to provide low search latency (as described in blog post) Design of new Cassandra reverse indices to support different sets of queries.

Media 237

Media Traffic Processing Design 237

Dynatrace

JULY 24, 2023

We will also explore the evolution of DevOps automation and the significance of data-driven answers in unlocking streamlined, automated DevOps and SRE processes. Business process automation Business process automation is the foundation for improving operational efficiency. This is what answer-driven automation is all about.

DevOps 228

DevOps Traffic Efficiency Servers 228

Dynatrace

MAY 17, 2023

Think about items such as general system metrics (for example, CPU utilization, free memory, number of services), the connectivity status, details of our web server, or even more granular in-application tasks like database queries. Let’s take our previous screenshot as an example.

Metrics 179

Metrics Monitoring Database Network 179

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 251

Cache Latency Airlines Logistics 251

Dynatrace

JANUARY 31, 2024

The rise of data observability in DevOps Data forms the foundation of decision-making processes in companies across the globe. For DevOps teams that inform deployment strategies, optimize processes, and drive continuous improvement, the integrity and timeliness of data are of significant importance.

DevOps 200

DevOps Analytics Airlines Metrics 200