Global

This post walks through an end-to-end MLOps pipeline built on PAASUP DIP — combining KFP v2, MLflow, MinIO, and KServe — covering data ingestion, challenger/champion promotion, zero-downtime KServe deployment, and production considerations.

RAG re-reads every time — costs accumulate, nothing sticks. OpenKB understands documents once and builds a Wiki that compounds. No vector DB, opens in Obsidian. If internal documents should be an asset, start here.

Misconfigured Kubernetes resource settings either waste cluster capacity or terminate pods in production. Goldilocks surfaces VPA's internally calculated recommendations into a readable dashboard — practical for squeezing more out of fixed on-premise hardware.

Benchmarking three PostgreSQL → Iceberg CDC pathways against 960 million records. In terms of balancing pipeline simplicity with real-time processing, Flink CDC emerges as the most compelling option. Initial load can be supplemented with a hybrid strategy combining Spark Batch.

Benchmarking the DIP platform at TPC-DS SF-1000 (1 TB, 6.3B rows): Batch ELT at 1,451K rows/sec, StarRocks query GeoMean of 2.2s, CN scaling analysis, and Trino comparison — all on S3 object storage.

Based on experience with a FastAPI RAG server, this post walks through the difference between the Embedded pattern (MCP lives inside your app) and the Bridge pattern (MCP runs as a separate process), how to choose the right Transport, and how to write Tool descriptions that actually guide the LLM.

Can a data platform prove its performance before you commit? We put DIP through the TPC-DS SF-100 standard benchmark. From batch ELT throughput to analytical query response times and concurrency limits—here are the numbers that speak for themselves.

A test plan for quantitatively measuring the DIP platform's batch ELT, real-time CDC, and analytical query performance using the TPC-DS standard benchmark. It compares and validates Spark, StarRocks, OLake, and Kafka CDC pipelines.

This document summarizes a PoC process of setting up OLake — a lightweight tool that performs CDC directly from PostgreSQL to Apache Iceberg without Kafka — in a local Docker environment, and testing its performance, stability, and ease of use in comparison with Debezium.

This article provides a comprehensive guide on implementing Cilium as the CNI for RKE2, replacing the default provider. It highlights the transition from legacy iptables to eBPF-based networking to achieve superior performance, security, and deep observability.