# Agentic AI Architecture

Agentic AI architecture is the structure and design of AI frameworks that enables AI agents to autonomously plan, act, observe, and collaborate within agentic AI systems.

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## A Unified Data Architecture For Sovereign Agentic AI With VMware Tanzu And VMware vSAN

DevFeed: [A Unified Data Architecture For Sovereign Agentic AI With VMware Tanzu And VMware vSAN](<https://devfeed.tech/articles/a-unified-data-architecture-for-sovereign-agentic-ai-with-vmware-tanzu-and-vmware-vsan-12812.md>)

Original publisher: [Read original article](<https://blogs.vmware.com/tanzu/a-unified-data-architecture-for-sovereign-agentic-ai-with-vmware-tanzu-and-vmware-vsan/>)

Author: arnab chakraborty

Published: 2026-09-03T23:27:50Z

Content type: article

Language: en

Sources: [VMware Blogs](<https://devfeed.tech/sources/vmware-blogs.md>)

Topics: [Agentic AI Architecture](<https://devfeed.tech/topics/agentic-ai-architecture.md>), [AI Architecture](<https://devfeed.tech/topics/ai-architecture.md>), [data-architecture](<https://devfeed.tech/topics/data-architecture.md>), [AI Agent](<https://devfeed.tech/topics/ai-agent.md>), [cloud-infrastructure](<https://devfeed.tech/topics/cloud-infrastructure.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [real-time](<https://devfeed.tech/topics/real-time.md>), [Security](<https://devfeed.tech/topics/security.md>), [data-processing](<https://devfeed.tech/topics/data-processing.md>)

Tags: [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agentic-ai-architecture](<https://devfeed.tech/tags/agentic-ai-architecture.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-architecture](<https://devfeed.tech/tags/ai-architecture.md>), [blog](<https://devfeed.tech/tags/blog.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [data-architecture](<https://devfeed.tech/tags/data-architecture.md>), [efficiency](<https://devfeed.tech/tags/efficiency.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [latency](<https://devfeed.tech/tags/latency.md>), [modern-apps](<https://devfeed.tech/tags/modern-apps.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [security](<https://devfeed.tech/tags/security.md>)

### AI overview

The article presents a unified, on-premises data architecture for sovereign agentic AI using VMware Tanzu, VMware Tanzu Greenplum, VMware Cloud Foundation, and VMware vSAN. It argues that placing AI compute close to enterprise data can improve performance and cost while reducing latency, data-transfer fees, and compliance risks.

### Source excerpt

By combining VMware Tanzu Greenplum with VMware vSAN, organizations can bring their AI compute directly to their data storage layer for improved cost and latency. The post A Unified Data Architecture For Sovereign Agentic AI With VMware Tanzu And VMware vSAN appeared first on Tanzu. The post A Unified Data Architecture For Sovereign Agentic AI With VMware Tanzu And VMware vSAN appeared first on VMware Blogs.

## The Thundering Herd Problem in Agentic AI: Why Traditional Fixes Fall Short

DevFeed: [The Thundering Herd Problem in Agentic AI: Why Traditional Fixes Fall Short](<https://devfeed.tech/articles/the-thundering-herd-problem-in-agentic-ai-why-traditional-fixes-fall-short-23739.md>)

Original publisher: [Read original article](<https://cockroachlabs.com/blog/agentic-ai-thundering-herd-problem>)

Author: Quentin Packard

Published: 2026-06-19T00:00:00Z

Content type: article

Language: en

Sources: [Cockroach Labs](<https://devfeed.tech/sources/cockroach-labs.md>)

Topics: [Agentic AI Architecture](<https://devfeed.tech/topics/agentic-ai-architecture.md>), [agent orchestration](<https://devfeed.tech/topics/agent-orchestration.md>), [AI Agent](<https://devfeed.tech/topics/ai-agent.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Concurrency](<https://devfeed.tech/topics/concurrency.md>)

Tags: [agent-orchestration](<https://devfeed.tech/tags/agent-orchestration.md>), [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [ai-architecture](<https://devfeed.tech/tags/ai-architecture.md>), [load-testing](<https://devfeed.tech/tags/load-testing.md>), [parallel](<https://devfeed.tech/tags/parallel.md>), [thundering-herd](<https://devfeed.tech/tags/thundering-herd.md>)

### AI overview

This article examines how agentic AI can create a thundering herd through intentional fan-out and parallel execution. It argues that traditional mitigations only partly transfer because agent-generated synchronization can produce a sharp saturation point that staging load tests may not reveal.

### Source excerpt

The thundering herd of the past was externally triggered.

## Agentic AI Architecture: How CockroachDB Supports Memory, Context, and Control

DevFeed: [Agentic AI Architecture: How CockroachDB Supports Memory, Context, and Control](<https://devfeed.tech/articles/agentic-ai-architecture-how-cockroachdb-supports-memory-context-and-control-23734.md>)

Original publisher: [Read original article](<https://cockroachlabs.com/blog/agentic-ai-architecture-memory-control>)

Author: Alejandro Infanzon

Published: 2026-06-11T00:00:00Z

Content type: article

Language: en

Sources: [Cockroach Labs](<https://devfeed.tech/sources/cockroach-labs.md>)

Topics: [Agentic AI Architecture](<https://devfeed.tech/topics/agentic-ai-architecture.md>), [CockroachDB](<https://devfeed.tech/topics/cockroachdb.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [AI Architecture](<https://devfeed.tech/topics/ai-architecture.md>), [context](<https://devfeed.tech/topics/context.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [data](<https://devfeed.tech/topics/data.md>), [Resilience](<https://devfeed.tech/topics/resilience.md>), [audit](<https://devfeed.tech/topics/audit.md>), [SQL](<https://devfeed.tech/topics/sql.md>), [Back end](<https://devfeed.tech/topics/backend.md>), [Cockroach Labs](<https://devfeed.tech/topics/cockroach-labs.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agentic-ai-architecture](<https://devfeed.tech/tags/agentic-ai-architecture.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [ai-architecture](<https://devfeed.tech/tags/ai-architecture.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [audit](<https://devfeed.tech/tags/audit.md>), [backend](<https://devfeed.tech/tags/backend.md>), [cockroachdb](<https://devfeed.tech/tags/cockroachdb.md>), [context](<https://devfeed.tech/tags/context.md>), [data](<https://devfeed.tech/tags/data.md>), [database](<https://devfeed.tech/tags/database.md>), [databases](<https://devfeed.tech/tags/databases.md>), [durability](<https://devfeed.tech/tags/durability.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [latency](<https://devfeed.tech/tags/latency.md>), [low-latency](<https://devfeed.tech/tags/low-latency.md>), [memory](<https://devfeed.tech/tags/memory.md>)

### AI overview

This article explains how CockroachDB can support enterprise agentic AI architectures by storing durable agent state, long-term memory, retrieval metadata, schema context, permissions, execution metadata, cost information, latency telemetry, and SQL audit trails. It presents the database as an operational layer for observing, governing, and improving autonomous agent behavior.

### Source excerpt

What happens when you connect a fleet of autonomous AI agents to your enterprise data stack? You quickly discover...

## AI Agents Need Context to Reason, Not Just Data

DevFeed: [AI Agents Need Context to Reason, Not Just Data](<https://devfeed.tech/articles/ai-agents-need-context-to-reason-not-just-data-23742.md>)

Original publisher: [Read original article](<https://cockroachlabs.com/blog/ai-agent-context-management>)

Author: Quentin Packard

Published: 2026-05-28T00:00:00Z

Content type: article

Language: en

Sources: [Cockroach Labs](<https://devfeed.tech/sources/cockroach-labs.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [context](<https://devfeed.tech/topics/context.md>), [AI Agent](<https://devfeed.tech/topics/ai-agent.md>), [Agentic AI Architecture](<https://devfeed.tech/topics/agentic-ai-architecture.md>), [Data Infrastructure](<https://devfeed.tech/topics/data-infrastructure.md>)

Tags: [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-architecture](<https://devfeed.tech/tags/ai-architecture.md>), [context](<https://devfeed.tech/tags/context.md>), [data-infrastructure](<https://devfeed.tech/tags/data-infrastructure.md>), [database](<https://devfeed.tech/tags/database.md>)

### AI overview

The article argues that production failures in AI agents often stem from inadequate context management rather than the model itself. Reliable agent behavior requires current data, memory, permissions, observability, and awareness of system constraints, making context management a data infrastructure problem beyond basic retrieval or prompt engineering.

### Source excerpt

When your AI agent makes a bad decision in production, what do you blame?