AGENTIC DATA AND OPS MOVE FROM SLIDES TO STACK DIAGRAMS
Google’s Agentic Data Cloud framing puts agents inside the core data stack, and ops vendors are racing to close the loop. A deep dive into [Google’s Agentic Da...
Google’s Agentic Data Cloud framing puts agents inside the core data stack, and ops vendors are racing to close the loop.
A deep dive into Google’s Agentic Data Cloud Architecture argues for agents as first-class citizens alongside governance, retrieval, and observability—shifting design from pipelines with LLM add‑ons to governed agent loops over trusted data.
That arc shows up in ops, too: HPE’s agentic approach to cloud/AI sprawl pairs closed‑loop automation with AIOps, echoing the view that AIOps isn’t optional anymore.
Two practitioner takes—on exposing trusted data to autonomous systems governance patterns and on making governance executable policy‑as‑code—plus a fresh look at the buy‑vs‑build calculus with agentic coding systems arXiv round out the picture.
If agents become first-class, data, governance, and SRE concerns shift from bolt‑ons to core architecture decisions.
Closed‑loop AIOps with policy‑as‑code can reduce toil and incident tail risk if the guardrail/latency tradeoff holds up.
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Spin up a narrow ops or analytics agent over your warehouse/lakehouse with tool use and policy‑as‑code; measure p95 latency overhead from guardrails and the real MTTR impact.
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Instrument agent loops end‑to‑end (retrieval, tool calls, approvals) with tracing/metrics; run failure injection to verify rollbacks, budget enforcement, and audit trails.
Legacy codebase integration strategies...
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Wrap existing RPA/AIOps playbooks with an agentic overseer before replacing them; keep human‑in‑the‑loop approvals for high‑risk actions.
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Externalize data access decisions (catalog, lineage, PII tags) so agents consult the same policies your services use; avoid one‑off ACLs in prompts.
Fresh architecture paradigms...
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Design for agents as clients from day one: semantic layer, retrieval APIs, tool catalogs, and unified observability per agent task.
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Adopt policy‑as‑code for AI early so guardrails ship with the pipeline (pre‑prod evals, runtime checks, and audit by default).
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