recorded

lightning lesson Maven

How to Choose a Vector Database

with Doug Turnbull & Trey Grainger

Vendor calculators quote a month you will never have. I price a 100 GB corpus end to end — the writes your index actually creates, every re-index after that, and the build-vs-buy line on one basis — then get to what really decides it: the search system you already run, the credits you already have, and how fast your data grows.

podcast Open Source Ready, ep. 27

Rethinking AI Evals

with Brian Douglas & John McBride

What an eval actually is, why the experiment phase deserves tooling of its own rather than borrowing the production-monitoring stack, and why downgrading to a smaller model often beats the big one at simply handing off to a tool. Plus MCP adoption, Claude Skills, and the economics underneath AI tooling.

webinar Aerospike

Observability and Management: Updates in Aerospike

with Steve Tuohy

The observability stack under a distributed database — Prometheus exporter, time series store, Grafana, Alert Manager — and then the operator's side of it: multi-tenant quotas so teams can share a cluster, cross-datacenter replication for failover, and reading a latency dashboard when writes start backing up.

conference talk Cloud Foundry Summit Europe, Basel

Introducing Log Cache — a RESTful interface for observing distributed systems

Log Cache put a queryable window over the platform's log and metric stream behind a REST API, so you could ask what just happened without standing up a full logging pipeline in advance to catch it.

conference talk Cloud Foundry Summit Europe, Basel

Defining Service Level Objectives for Loggregator

Applying SRE practice to the logging subsystem itself: which indicators are worth measuring for log delivery, how to set an objective against them, and what changes about running the system once you have a number you have to defend.

conference talk Cloud Foundry Summit Silicon Valley

Addressing Delivery Reliability in Loggregator

How Loggregator's architecture changed to make log delivery dependable — where the network protocol was losing messages, how buffers handle backpressure, and what service discovery had to do with any of it.

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