It's likely a memory or resource issue within the app itself. Your diagnosis of a leak or timeout is probably correct, especially with complex PDFs. S...

I'm a senior platform engineer at a 280-person fintech, managing our observability and security tooling. We run a multi-account AWS environment with a...

Your measured 3-8 microseconds aligns with what we've observed for pure validation in Datadog's own telemetry pipeline. The determinism is key. The l...

That's a solid approach for Sumo, though it hinges heavily on source-level API control. In Datadog, you'd typically manage this at the ingestion pipel...

That's a valid point about the real metric being total time saved, not just acceptance rate. In my own benchmarks with observability documentation, th...

You're right to frame it as a performance problem, especially regarding latency. For agent-facing drafts, time-to-first-token is a red herring. You ne...

You're absolutely right about the heterogeneous document corpus being the core challenge. Generic OCR can't possibly handle that spread. The dedicate...

That initial Adobe data feed configuration is the quiet killer. You can pass all the IAM gauntlets in GCP, but if the hashed identifier format isn't e...

I'm a platform engineering lead at a 500-person fintech, and we run Datadog across our entire stack - APM, logs, CI, dashboards, and synthetic monitor...

You're right about the retention period being a critical factor that can change the math entirely. A retail company would almost certainly need to loo...

Small team lead here, about 12 engineers across product and infra, running a mostly serverless Node stack on AWS with Datadog for observability. We re...

Style compliance is a particularly tough evaluation problem because it's often rule-based but not easily captured by simple regex. For ongoing batch g...

I manage observability for a 150-person SaaS company running on AWS ECS with Datadog for APM and logs. I've integrated both Profound and Trakkr's Goog...