InfoQ Homepage Data Pipelines Content on InfoQ
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Yelp Overhauls Its Streaming Architecture with Apache Beam and Apache Flink
Yelp reworked its data streaming architecture by employing Apache Beam and Apache Flink. The company replaced a fragmented set of data pipelines for streaming transactional data into its analytical systems, like Amazon Redshift and in-house data lake, using Apache data streaming projects to create a unified and flexible solution.
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Netflix Creates Incremental Processing Solution Using Maestro and Apache Iceberg
Netflix created a new solution for incremental processing in its data platform. The incremental approach reduces the cost of computing resources and execution time significantly as it avoids processing complete datasets. The company used its Maestro workflow engine and Apache Iceberg to improve data freshness and accuracy and plans to provide managed backfill capabilities.
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Goldsky’s Streaming-First Architecture for Blockchain Data with Flink, Redpanda and Kubernetes
Goldsky created a platform for the real-time processing of blockchain data. The platform allows clients to extract data from blockchains into their own databases to support product features, but without running the data pipeline infrastructure. The event-driven architecture (EDA) of Goldsky leverages Apache Flink, Redpanda, Kubernetes, and cloud provider services.
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A Modern Compute Stack for Scaling Large AI, ML, & LLM Workloads at QCon SF
Jules Damji, a lead developer advocate at Anyscale Inc., discussed the difficulties data scientists encounter when managing infrastructure for machine learning models. He emphasized the necessity for a framework that supports the latest machine learning libraries, is easily manageable, and can scale to accommodate large datasets and models. Damji introduced Ray as a potential solution.
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Confluent Announces Apache Flink on Confluent Cloud in Open Preview
Confluent recently announced the open preview of Apache Flink on Confluent Cloud as a fully-managed service for stream processing. The company claims that the managed service will make it easier for companies to filter, join, and enrich data streams with Flink.
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Running Apache Flink Applications on AWS KDA: Lessons Learnt at Deliveroo
Deliveroo introduced Apache Flink into its technology stack for enriching and merging events consumed from Apache Kafka or Kinesis Streams. The company opted to use AWS Kinesis Data Analytics (KDA) service to manage Apache Flink clusters on AWS and shared its experiences from running Flink applications on KDA.
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Pfizer Uses Serverless Architecture on AWS to Scale Processing of Digital Biomarkers
Pfizer upgraded the serverless architecture for processing digital biomarker data at scale to make it more flexible and configurable. They created a framework that uses a file processing pipeline built with AWS Step Functions and other serverless services, as well as a custom Python package for data ingestion and processing.
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Yelp Rebuilds Corrupted Cassandra Cluster Using Its Data Streaming Architecture
Yelp created a solution to sanitize data from the corrupted Apache Cassandra cluster utilizing its data streaming architecture. The team explored many potential options to address the data corruption issue, however, ultimately had to move the data into a new cluster to remove corrupted records in the process.
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Instacart Creates a Self-Serve Apache Flink Platform on Kubernetes
Instacart moved their Apache Flink workloads from AWS EMR to Kubernetes to meet the high demand for data processing use cases using Flink within the organization, as using EMR became problematic for many teams with different requirements. As a result, they made the platform easier to use and reduced their operational and infrastructure costs.
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Strategies and Principles to Scale and Evolve MLOps - at QCon London
At the QCon London conference, Hien Luu, senior engineering manager for the Machine Learning Platform at DoorDash, discussed strategies and principles for scaling and evolving MLOps. With 85% of ML projects failing, understanding MLOps at an engineering level is crucial. Luu shared three core principles: "Dream Big, Start Small," "1% Better Every Day," and "Customer Obsession."
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AWS Publishes Reference Architecture and Implementations for Deployment Pipelines
AWS recently released a reference architecture and a set of reference implementations for deployment pipelines. The recommended architectural patterns are based on best practices and lessons collected at Amazon and customer projects.
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AWS Glue Now Supports Crawler History
AWS recently launched support for histories of AWS Glue Crawlers, which allows the interrogation of Crawler executions and associated schema changes for the last 12 months.
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Shopify’s Practical Guidelines from Running Airflow for ML and Data Workflows at Scale
Shopify engineering shared its experience in the company's blog post on how to scale and optimize Apache Airflow for running ML and data workflows. They shared practical solutions for the challenges they faced like slow file access, insufficient control over DAG, irregular level of traffic, resource contention among workloads, and more.
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Data Collection, Standardization and Usage at Scale in the Uber Rider App
Uber Engineering recently published how it collects, standardises and uses data from the Uber Rider app. Rider data comprises all the rider's interactions with the Uber app. This data accounts for billions of events from Uber's online systems every day. Uber uses this data to deal with top problem areas such as increasing funnel conversion, user engagement, etc.
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QCon Plus November 2021 is Now Hybrid. Attend Online and In-Person (NY & SF)
The QCon Plus software development conference will be back November 1-5, 2021 - online and in-person. Get the chance to engage and network with professionals driving change and innovation inside the world’s most innovative software organizations.