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Apache Kafka® is one of the most popular event streaming systems. There are many ways to compare systems in this space, but one thing everyone cares about is performance. Kafka […].
The making of Edge Gateway, the highly-available and scalable self-serve gateway to configure, manage, and monitor APIs of every business domain at Uber. Evolution of Uber’s API gateway. In October 2014, Uber had started its journey of scale in what … The post Designing Edge Gateway, Uber’s API Lifecycle Management Platform appeared first on Uber Engineering Blog.
by Aditya Mavlankar , Liwei Guo , Anush Moorthy and Anne Aaron Netflix has an ever-expanding collection of titles which customers can enjoy in 4K resolution with a suitable device and subscription plan. Netflix creates premium bitstreams for those titles in addition to the catalog-wide 8-bit stream profiles¹. Premium features comprise a title-dependent combination of 10-bit bit-depth, 4K resolution, high frame rate (HFR) and high dynamic range (HDR) and pave the way for an extraordinary viewing
You want to become a data engineer, but don't know how to set up a data engineering project? I will show you! Do not make this mistake! First of all you should not make the mistake that unfortunately many people make! Often people want to build the whole thing from the beginning. They say: "Okay I need to do a project. I need to make a big thing. I don't even know what data and what tools I want to use.
In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate
Teradata Workload Management enables Vantage to be fully optimized for cloud & hybrid deployments & to efficiently deliver the lowest cost for enterprise analytics.
2020 may well go down as the year where what seems impossible today, did become possible tomorrow. It’s been a year filled with disruption and uncertainty. One day we were all going to the office, and the next we were working from home. Businesses had to literally switch operations, and enable better collaboration and access to data in an instant — while streamlining processes to accommodate a whole new way of doing things.
As one of the world’s biggest internet-based platform companies, Tencent uses technology to enrich the lives of users and assist the digital upgrade of enterprises. An example product is the […].
As one of the world’s biggest internet-based platform companies, Tencent uses technology to enrich the lives of users and assist the digital upgrade of enterprises. An example product is the […].
Summary Data warehouse technology has been around for decades and has gone through several generational shifts in that time. The current trends in data warehousing are oriented around cloud native architectures that take advantage of dynamic scaling and the separation of compute and storage. Firebolt is taking that a step further with a core focus on speed and interactivity.
by Mariana Afonso , Anush Moorthy , Liwei Guo , Lishan Zhu , Anne Aaron Netflix has been one of the pioneers of streaming video-on-demand content?—?we announced our intention to stream video over 13 years ago, in January 2007?—?and have only increased both our device and content reach since then. Given the global nature of the service and Netflix’s commitment to creating a service that members enjoy, it is not surprising that we support a wide variety of streaming devices, from set-top-boxes and
Data Science , Artificial Intelligence and Machine Learning. These topics are currently the hype in the field of Data Science. Everyone wants to become a Data Scientist. But isn't the work being done in the field of Data Engineereing the real MVP? Isn't it important to have Data Scientists AND Data Engineers on board to make a project successful? Yes, it is!
This post presents a simulation framework that leverages several mathematical models to simulate the spread of diseases such as COVID-19 in urban environments.
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
In part 2 of the series focusing on the impact of evolving technology on the telecom industry, we sat down with Vijay Raja, Director of Industry & Solutions Marketing at Cloudera to get his views on how the sector is changing and where it goes next. Hi Vijay, thank you so much for joining us again. To continue where we left off, as industry players continue to shift toward a more 5G centric network, how is 5G impacting the industry from a data perspective?
On behalf of the Apache Kafka® community, it is my pleasure to announce the release of Apache Kafka 2.6.0. This another exciting release with many new features and improvements. We’ll […].
Summary In order to scale the use of data across an organization there are a number of challenges related to discovery, governance, and integration that need to be solved. The key to those solutions is a robust and flexible metadata management system. LinkedIn has gone through several iterations on the most maintainable and scalable approach to metadata, leading them to their current work on DataHub.
Jeffrey Wong , Colin McFarland Every Netflix data scientist, whether their background is from biology, psychology, physics, economics, math, statistics, or biostatistics, has made meaningful contributions to the way Netflix analyzes causal effects. Scientists from these fields have made many advancements in causal effects research in the past few decades, spanning instrumental variables, forest methods, heterogeneous effects, time-dynamic effects, quantile effects, and much more.
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
There are a huge number of tools and platforms for data engineers. It's this enormous selection that makes it difficult for newcomers to filter out the really important tools. In the course of the Data Engineer Coaching I was able to gain important experience in this regard and would like to tell you the most important tools on this basis today! During the coaching sessions I saw that a lot of tools keep coming up all the time: Kafka, Spark and AWS.
A modern analytic ecosystem embraces a hybrid approach and leverages the right technologies to meet the needs at the right cost/value ratio. Read more.
There’s no doubt that cloud has become ubiquitous, and thank goodness for that in 2020. We wouldn’t have survived the challenges of this year without cloud. It’s supported everything, from the sudden changes in the way we work to the way we access healthcare and even shop for vital goods. While cloud is the vehicle, it’s what sits on it that makes it so valuable — data.
Tools for automated testing of Kafka Streams applications have been available to developers ever since the technology’s genesis. Although these tools are very useful in practice, this blog post will […].
Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri
Summary Most databases are designed to work with textual data, with some special purpose engines that support domain specific formats. TileDB is a data engine that was built to support every type of data by using multi-dimensional arrays as the foundational primitive. In this episode the creator and founder of TileDB shares how he first started working on the underlying technology and the benefits of using a single engine for efficiently storing and querying any form of data.
By Andrei U., Seth Katz , Janak Ramachandran , Jeff Butsch , Peter Lau , Ram Vaithilingam , and Greg Burrell Our Telltale Vision An alert fires and you get paged in the middle of the night. A metric crossed a threshold. You’re half awake and wondering, “Is there really a problem or is this just an alert that needs tuning? When was the last time somebody adjusted our alert thresholds?
No operator ever made, or ever will make, a single cent or penny from purely digitizing and then storing data – they need to do something with it! Find out how.
Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
From leading banks, and insurance organizations to some of the largest telcos, manufacturers, retailers, healthcare and pharma, organizations across diverse verticals lead the way with real-time data and streaming analytics. These businesses use data-fueled insights to enhance the customer experience, reduce costs, and increase revenues. And Cloudera is at the heart of enabling these real-time data driven transformations. .
Whether you are a developer working on a cool new real-time application or an architect formulating the plan to reap the benefits of event streaming for the organisation, the subject […].
Summary Event based data is a rich source of information for analytics, unless none of the event structures are consistent. The team at Iteratively are building a platform to manage the end to end flow of collaboration around what events are needed, how to structure the attributes, and how they are captured. In this episode founders Patrick Thompson and Ondrej Hrebicek discuss the problems that they have experienced as a result of inconsistent event schemas, how the Iteratively platform integrat
So, what is a Power BI Template App? A Power BI Template App is a published Power BI solution that can be used by any company that has the data platform for which the Template App was created. Can you imagine picking your entire Power BI Solution off the shelf - one crafted for your specific business needs and your specific data structure. Power BI Template Apps are designed to be such an out-of-the-box solution and this blog post is an example of such for a Power BI Solution for Stripe.
Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
Explore the intriguing world of eta-expansion: Discover how methods and functions interact in Scala, revealing insights that can elevate your coding game
Agile practices in the retail sector can deliver fast & compelling returns, but they can also lead to fragmentation, data silos, & unnecessary complexity. Learn more.
One of the key challenges of building an enterprise-class robust scalable storage system is to validate the system under duress and failing system components. This includes, but is not limited to: failed networks, failed or failing disks, arbitrary delays in the network or IO path, network partitions, and unresponsive systems. Apache Ozone fault injection framework is designed to validate Ozone under heavy stress and failed or failing system components.
If you know me, you know two things: first, that I am committed to remote work as an effective way to build a company; I’ve been a remote employee for […].
With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer. This eBook provides a comprehensive overview of DAG writing features with plenty of example code. You’ll learn how to: Understand the building blocks DAGs, combine them in complex pipelines, and schedule your DAG to run exactly when you want it to Write DAGs that adapt to your data at runtime and set up alerts and notifications Scale you
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