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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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Airbnb Builds Himeji - a Scalable Centralized Authorization System
Airbnb recently described how it built Himeji, a scalable centralized authorization system. Himeji stores permissions data and performs permission checks as a central source of truth. It uses a sharded and replicated in-memory cache to improve performance and lower latencies and has served checks in production for about a year.
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Designing for Failure in the BBC's Analytics Platform
Last week at InfoQ Live, Blanca Garcia-Gil, principal systems engineer at BBC, gave a session on Evolving Analytics in the Data Platform. During this session, Garcia-Gil focused on how her team prepared and designed for two types of failure - "known unknowns" and "unknown unknowns."
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PayPal Standardizes on Apache Airflow and Apache Gobblin for Its Next-Gen Data Movement Platform
PayPal recently described how it standardized on Apache Airflow and Apache Gobblin for implementing its next-gen data movement platform. In a recent blog post, PayPal engineers detail how the existing data movement platform evolved into many tools & platforms in a complex and unmanageable ecosystem and their shift towards a new implementation.
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AWS Introduces Amazon Managed Workflows for Apache Airflow
Recently, AWS introduced Amazon Managed Workflows for Apache Airflow (MWAA), a fully-managed service simplifying running open-source versions of Apache Airflow on AWS and build workflows to execute extract-transform-load (ETL) jobs and data pipelines.