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A RAG demo answering questions correctly over ten hand-picked documents proves almost nothing about how it behaves over a real corpus. Seven concrete ways retrieval-augmented generation breaks in production, and what actually fixes each one.
Senior engineers walk into this question and either downplay a real failure into something trivial, or overshare something career-damaging. Neither answers what the interviewer is actually evaluating — and the part of the story most candidates skip is the part that matters most.
Rate limiting looks like a one-line INCR in a whiteboard interview and turns into a race-condition minefield the moment it's distributed across nodes. A tour of the four real algorithms, and the atomicity bug that ships in more Redis rate limiters than anyone admits.
HPA, VPA, and KEDA solve three different scaling problems, and running the wrong one is why 'autoscaling doesn't work' tickets keep coming back. A field guide to picking the right one — and why HPA and VPA fight each other when misconfigured together.
Unpacking DeepSeek-R1's Multi-head Latent Attention (MLA), DeepSeekMoE 210B sparse routing, and group relative policy optimization (GRPO) reinforcement learning.
How Grouped-Query Attention (GQA) and Multi-Query Attention (MQA) reduce KV-cache memory bandwidth consumption in LLM inference.
Avoid repeating $0.03 LLM queries by matching semantically similar user prompts in vector cache before hitting API endpoints.
Moving beyond naive vector lookup: building adaptive multi-agent retrieval routers that decide when to query vector databases vs SQL databases.
DPO eliminates the need for training separate reward models and complex PPO reinforcement loops by deriving the implicit reward directly from binary preference data.
How malicious instructions hidden inside scraped web pages or user uploaded PDFs can hijack your LLM agent's execution flow.
Histogram-based decision trees vs depth-wise growth: why LightGBM trains 7x faster on 10M row datasets with equal AUC-ROC scores.
Automating model lineage, hyperparameter logging, and staging-to-production promotion gates in CI/CD pipelines.
Catching covariate shift and concept drift before model accuracy degrades using PSI metrics and Evidently AI dashboards.
Streaming PostgreSQL WAL changes into StarRocks real-time analytics engine with sub-second end-to-end latency.
Comparing hidden partitioning, ACID transactions, time-travel queries, and multi-engine interoperability across Snowflake and Spark.
Why Parquet files achieve 80%+ compression ratios over CSV: inspecting columnar binary structure, footer metadata, and dictionary encoding.
Handling out-of-order event streams, tumbling vs sliding windows, and watermarking strategies for sub-second streaming analytics.
Conflict-free Replicated Data Types (CRDTs) powering low-latency multi-user canvas state synchronization.
Decoupling Command write paths from Query read projections for 100% auditable financial and enterprise domain state.
Building high-throughput asynchronous job queues handling delayed retries, rate-limiting user notifications, and multi-provider failovers.
At 14:02 UTC on a Tuesday, our search cluster stopped responding. Here is how an innocent thread pool config change killed node 3.
How to rename database columns and alter schema types on 500-million row Postgres tables without holding table locks.
Eliminating public IP exposure and bastion hosts using kernel-level WireGuard encryption and Tailscale ACL policies.
Preventing dropped HTTP connections during rolling k8s deployments by configuring terminationGracePeriodSeconds and preStop hooks.