Machine Learning on Kubernetes Birds of a Feather
Explore best practices for implementing and scaling machine learning solutions on Kubernetes, covering the entire pipeline from data ingestion to production deployment.
Building MLOps POCs and Sandbox Environments Using k3s and Argo
Explore building MLOps POCs using k3s and Argo. Learn to reduce implementation time and costs for data pipeline automation and ML workflows, with insights on lightweight Kubernetes and Edge Computing.
Noise Cancelling Headphones for Fluent Bit - Powered by Lua
Explore Fluent Bit's Lua filter plugin for IP address enrichment and noise reduction in log data, enhancing security and data engineering workflows.
How Spotify Leverages Flyte to Coordinate Financial Analytics Company-Wide
Explore Spotify's use of Flyte for financial analytics, covering MLOps/DataOps needs, best practices for ML/data apps, and how Flyte bridges technical gaps for users of varying proficiency.
Sparse High-resolution Histograms in the Prometheus TSDB
Explore sparse high-resolution histograms in Prometheus TSDB, covering implementation, storage savings, benchmarks, and future improvements for efficient data handling and visualization.
Bootstrapping Microservices Using Akka, Kafka, and Spark
Explore real-time data platforms using Kafka, Spark Streaming, and Akka. Learn about unified data transfer protocols, topic management, and scalable ingestion for modern microservices architecture.
Akka Streams for High Throughput Data Processing
Explore high-throughput data processing with Akka Streams, comparing it to Akka Actors. Learn best practices, optimization techniques, and when to switch to Streams for improved performance in large-scale data transfer systems.
A Story of Unification from Apache Spark to MLflow
Explore the journey of unification from Apache Spark to MLflow, highlighting key developments and innovations in big data processing and machine learning workflows.
Processing Data at Scale with Rails
Strategies for handling large datasets using Rails, covering data ingestion, transformation, and storage with tools like ActiveRecord, Sidekiq, and Postgres.
Data Indexing with RGB - Ruby, Graphs and Bitmaps
Explore data indexing using Ruby, graph databases, and bitmap stores to build a unique data engine, improving query speed and enabling cross-market analysis and harmonization.
Go, the Data Engineer's Missing Tool?
Explore Go's potential in data engineering, focusing on serialization, efficient processing, and reliability. Learn about challenges and benefits of introducing Go to this domain.
Dat - An Open Source Tool for Sharing and Collaborating on Data
Explore Dat, an open-source tool for data sharing and collaboration. Learn about its features, applications in reproducible science, and how it aims to revolutionize data management like Git did for source control.
Versioning, Syncing & Streaming Large Datasets Using DAT + Node
Explore versioning, syncing, and streaming large datasets using DAT and Node.js. Learn about open-source tools for efficient data collaboration, reproducibility, and building cross-platform data pipelines.
Not a Magic - What to Expect from Machine Learning Projects
Practical insights on implementing machine learning projects, covering data handling, algorithm selection, training, evaluation, and deployment challenges in organizational settings.
Building Advance Analytics Pipelines with Azure Databricks
Explore Azure Databricks for advanced analytics: Learn Spark basics, collaboration features, cluster management, and Azure integration through a detailed network intrusion anomaly detection pipeline walkthrough.
Serverless SQL Pipelines
Explore serverless SQL options across cloud platforms, comparing AWS and Google services. Learn architectural patterns for data lake pipelines and emerging serverless solutions.
Fundamentals of Azure IoT
Explore Azure IoT infrastructure, MXChip Kit, and connecting industrial equipment. Learn about SDKs, data ingestion, device management, and practical examples using various platforms.
Automate Your City Data With Python Using Datasette and GitHub Actions
Discover how to build automated data pipelines using Python, Datasette, and GitHub Actions to extract and analyze city planning decisions and public data for better civic engagement.
Data Pipeline Scorecard: Evaluating Python Processing Approaches
Explore data processing approaches in Python, comparing different methods and their practical applications for building efficient data pipelines and optimizing workflow performance.
Privacy Engineering: Not Just for Privacy Engineers
Explore Uber's collaborative approach to privacy engineering, blending data analysis with robust privacy measures to enhance services while ensuring regulatory compliance and user protection.
Intent Realization in Self-Serve Platforms - PlatformCon 2024
Explore intent realization's impact on reducing friction and improving developer experience in self-serve platforms, focusing on Netflix's data infrastructure and user-friendly tooling.