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Architecture & Design

Building & Operating High-Fidelity Data Streams

At QCon Plus 2021 last November, Sid Anand, chief architect at Datazoom and PMC Member at Apache Airflow, presented on building high-fidelity nearline data streams as a service within a lean team. In this talk, Anand provides a master class on building high-fidelity data streams from the ground up.

Sid Anand
on Sep 30, 2022
AI, ML & Data Engineering

Streaming-First Infrastructure for Real-Time Machine Learning

This article covers the benefits of streaming-first infrastructure for two scenarios of real-time ML: online prediction, where a model can receive a request and make predictions as soon as the request arrives, and continual learning, when machine learning models are capable of continually adapting to change in data distributions in production.

Chip Huyen
on Aug 22, 2022
Cloud

Designing IoT Solutions with Microsoft Azure

In this article, we will learn how the IoT solutions can work with Microsoft Azure and what services are available to perform different operations across multiple domains. Furthermore, it covers a few case studies to gain hands-on experience on Azure IoT that are common and provide a good starting point for utilizing cloud-based IoT services.

Kush Mishra
on Mar 02, 2022
Development

How to Create a Network Proxy Using Stream Processor Pipy

In this article we are going to introduce Pipy, an open-source cloud-native network stream processor. After describing its modular design, we will see how to rapidly build a high-performance network proxy to serve our specific needs. Pipy has been battle-tested and is already in use by multiple commercial clients.

Ali Naqvi
on Jan 31, 2022
Cloud

Indestructible Storage in the Cloud with Apache Bookkeeper

At Salesforce, we required a storage system that could work with two kinds of streams, one stream for write-ahead logs and one for data. But we have competing requirements from both of the streams. Being the pioneers in cloud computing, we also required our storage system to be cloud-aware as the requirements of availability and durability are ever more increasing.

Anup Ghatage
on Apr 28, 2021
AI, ML & Data Engineering

The Future of Data Engineering

Chris Riccomini examines the current and future states of the art in data pipelines, data streaming, and data warehousing. He presents a six-stage evolution that data ecosystems follow, from a simple monolith to a complex data-microwarehouse architecture as the data engineers who manage them solve problems and clarify their roles as infrastructure engineers, rather than data stewards.

Chris Riccomini
on Feb 16, 2021 1
AI, ML & Data Engineering

How Apache Pulsar is Helping Iterable Scale its Customer Engagement Platform

In this article, author Greg Methvin discusses his experience implementing a distributed messaging platform based on Apache Pulsar.

Greg Methvin
on Nov 30, 2020
AI, ML & Data Engineering

Beyond the Database, and beyond the Stream Processor: What's the Next Step for Data Management?

Databases have been around forever with the same shape: you make a request to your data and then you receive an answer. Now, stream processors came along with a different approach: data isn’t locked up, it is in motion. Understand how stream processors and databases relate and why there is an emerging new category of databases that focus on data that stays in place as well as data that moves.

Ben Stopford
on Nov 16, 2020 1
Architecture & Design

Real Time APIs in the Context of Apache Kafka

Events offer a Goldilocks-style approach in which real-time APIs can be used as the foundation for applications which is flexible yet performant; loosely-coupled yet efficient. Apache Kafka offers a scalable event streaming platform with which you can build applications around the powerful concept of events.

Robin Moffatt
on Oct 16, 2020
Architecture & Design

The Challenges of Building a Reliable Real-Time Event-Driven Ecosystem

Globally, there is an increasing appetite for data delivered in real time; we are witnessing the emergence of the real time API. When it comes to event-driven APIs engineers can choose between multiple different protocols. In addition to choosing a protocol, engineers also have to think about subscription models, too: server-initiated (push-based) or client-initiated (pull-based).

Matthew O'Riordan
on Jul 30, 2020
AI, ML & Data Engineering

Applied Probability - Counting Large Set of Unstructured Events with Theta Sketches

In this article, author Ronen Cohen discusses the solution to processing the event data using Theta Sketches and technologies like HBase and Kafka.

Ronen Cohen
on Jun 29, 2020
Cloud

Is Edge Computing a Thing?

Edge Computing is definitely a thing, but the computing need not occur at the edge. Instead what is needed is an ability to compute (anywhere) on streaming data from large numbers of dynamically changing devices, in the edge environment. This in turn demands an architectural pattern for stateful, distributed computing.

Simon Crosby
on Apr 17, 2020

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