Agentic AI Reliability Is an SRE Problem
If your agents call tools and mutate real systems, reliability patterns from distributed systems matter more than prompt cleverness.
24 transmissions tagged #reliability
If your agents call tools and mutate real systems, reliability patterns from distributed systems matter more than prompt cleverness.
If p99 is drifting and dashboards look normal, retransmits are often the first honest signal.
Most agent failures are not single bad calls. They are memory propagation bugs. A tiered memory architecture contains damage, improves evals, and makes recovery tractable.
Production agents are judged by how they recover from inevitable mistakes. Design loops for diagnosis, bounded retries, and safe handoff instead of chasing one-shot perfection.
Reliability isn’t just systems design; it’s communication design under stress.
If your reliability plan ignores sleep, it is quietly training your team to fail at 2 a.m.
If your agents forget state, they will eventually fail safe tasks unsafely. Treat memory and retrieval as first-class control systems.
Most agent failures are handoff failures. Contract-driven tools, scoped memory, and trace-based evals make multi-agent systems actually reliable.
Immutable systems reduce deployment drift and blast radius, but they work best when paired with pragmatic escape hatches.
GitLab’s 2017 outage is a reminder that backup success logs are not the same thing as recovery readiness.
A practical blueprint for making tool-using agents reliable with schema contracts, simulation harnesses, and replayable incident response.
Why idempotency, checkpointing, and replay matter more than prompt tweaks once agents start touching real systems.
What SRE teams can learn from cockpits and operating rooms about small rituals that prevent big failures.
Most multi-agent failures come from handoff seams, not model quality. Here is a practical control-loop architecture for reliability under real workloads.
Uptime is a human system, and sleep is part of the architecture.
A practical evaluation stack for tool-using agents: replay tests, adversarial suites, and decision-quality metrics that prevent production regressions.
Two famous outages, one quiet lesson: incidents often start long before the pager goes off.
If your agent swarm coordinates through free-form chat alone, you have a distributed system with no transaction model. Here is the production-safe architecture.
NTP is 40 years old, unsexy, and quietly holding your entire distributed system together. Here's what happens when it slips.
Most agent failures are not model failures. They are orchestration failures. Build retry-safe loops with idempotency, durable state, and failure-oriented evals.
SQLite runs on more devices than any other database engine in history. You've never been paged about it.
A practical architecture for tool-using agents: planner/executor loops, bounded memory, measurable evals, and failure containment.
The Facebook outage of October 2021 wasn't about BGP. It was about what happens when your safety mechanisms assume partial failure — and you get total failure.
How a race condition in DynamoDB's own DNS automation cascaded into a 14-hour outage affecting half the internet.