
ARMs at Uber Scale, Hyper Parameters Tuning, and how celebrations shape the Internet.
🛡️ Tolerating Full Cloud Outages with Monzo Stand-in
What happened – Monzo launched Stand-in: a pared-down banking platform on GCP that can instantly replace their AWS primary during a full-cloud outage.
Why it matters – Shows engineers how dual-cloud failover with minimal services and zero shared dependencies raises availability without doubling complexity.
🚀 Adopting Arm at Scale: Bootstrapping Infrastructure
What happened – Uber built multi-arch build, deploy and scheduling tools to roll out Arm64 hosts across its fleet, pivoting off costly x86 servers.
Why it matters – Blueprint for migrating huge microservice fleets to Arm, slashing power and hardware spend while retaining seamless x86 fallback.
🎬 Tracking Millions of Heartbeats on ZEE’s Streaming Platform
What happened – ZEE5 migrated its 100-billion-a-day heartbeat API to ScyllaDB, redesigning data model and pipeline, cutting database costs five-fold.
Why it matters – Shows how NoSQL switch plus schema rethink delivers single-digit-ms P99 latency and big savings for massive real-time streaming workloads.
🤖 Tune Smarter, Not Harder: Hyperparameter Tuning in Payment Fraud at Booking.com
What happened – Booking.com parallelized hyperparameter tuning with Spark and adopted Bayesian TPE, trimming fraud-model training time 95 % and improving PR-AUC.
Why it matters – Fresher, stronger models arrive faster; engineers can copy Spark+Hyperopt recipe to save compute and boost business outcomes.
🎄 Offline Celebrations: How Christmas, NYE, and Lunar New Year Shape Traffic
What happened – Cloudflare Radar analyzed internet traffic across 50+ countries, seeing up-to-70 % drops as users disconnected for Christmas, NYE, and Lunar New Year.
Why it matters – Holiday traffic troughs give ops teams predictable windows for upgrades, scaling, or cost optimization across geographically diverse workloads.
🔍 Improving Pinterest Search Relevance Using Large Language Models
What happened – Pinterest deployed a cross-encoder language model fine-tuned on human labels to re-rank Pin–query pairs, boosting search relevance metrics.
Why it matters – Illustrates lightweight LLM distillation that lifts engagement without expensive reranking latency, applicable to many search ranking stacks.
🌀 Disaster Recovery with Physical Cluster Replication in CockroachDB
What happened – CockroachDB introduced Physical Cluster Replication, streaming low-level key-value snapshots to a standby cluster for near-zero-data-loss disaster recovery.
Why it matters – Brings enterprise-grade DR to open-source SQL; failover is fast, data is consistent, and logical migrations aren’t required.
Got a link that belongs here, or any feedback? Reach out to me on LinkedIn, and I’ll check it out. Until next time – stay scalable! ✌️