Microsoft Agent Framework Reference Architecture Overview
End-to-end architecture for multi-agent systems on Microsoft's Agent Framework — orchestration, governance, and production deployment patterns.
Curated articles by topic — from 105+ published posts on Multi-Agent AI, FinOps, Cloud Infrastructure, Security, and Production Systems. See featured selection or browse all posts.
End-to-end architecture for multi-agent systems on Microsoft's Agent Framework — orchestration, governance, and production deployment patterns.
The philosophy, architectural clarity, and vendor lock-in concerns that drove migrating 18+ production agents in 90 days.
The eleven-layer envelope — no two adjacent layers share a single point of failure for the same class of attack.
The five interface contracts that define a multi-agent runtime — registry, dispatch, memory, governance, and observability.
Why single-turn benchmarks fail for multi-agent systems — evaluation design for conversation, tool use, and multi-step reasoning.
Google's Agent-to-Agent protocol implemented in Go — discovery, task management, and inter-agent communication patterns.
Slot reservation transitions, MERGE anti-pattern elimination, and capacity-based pricing for 57% data warehouse cost reduction.
Idempotent processing, PCI-aligned design, error-code orchestration with exponential backoff and DLQ resilience.
Protobuf contracts, gRPC migration, and service consolidation for a social platform serving 1M+ users.
Automated test coverage enforcement and Prometheus-based alerting for the Picnic social platform.
Enforcing accounting invariants in a peer-to-peer lending ledger — balanced entries, saga rollbacks, and audit trails.
Primary key strategies, write distribution, and avoiding hotspots in globally distributed Spanner deployments.
Compliance as code — SOC 2, ISO 27001, and policy automation for regulated cloud environments.
Cloud lifecycle automation and enterprise Kubernetes patterns from the Ericsson/AT&T/Microsoft collaboration.
OpenTelemetry integration, distributed tracing, and metrics collection for multi-agent AI workloads.
Change data capture pipelines, Datastream integration, and zero-downtime migration strategies.
Moving from on-demand to capacity-based slot reservations — commitment planning, autoscaling, and cost modeling.
Parent-child co-location in Cloud Spanner — when interleaving improves read performance and when it hurts write throughput.
Integrating OpenTelemetry into the Airship bare-metal lifecycle manager — AT&T/Ericsson collaboration on telco infrastructure.
Multi-cloud abstraction in Go — how Gocloud unified AWS, GCP, and Azure resource management under a single API.
RBAC, RLS, token exchange, envelope encryption, hash-chained audit logs, and red team exercises for a multi-agent financial assistant.
Every one of the 26 RBI FREE-AI recommendations mapped to a specific file in a working multi-agent platform.
Expressing healthcare compliance requirements as type-safe interfaces — governance enforcement, audit logging, and data protection.
Hash-chained append-only logs, tamper-evident storage, and the design decisions behind production audit trails.
IAPP's AI Governance Professional body of knowledge mapped to working code — from risk assessment to monitoring.
Zero-trust workload identity for service meshes — SVID issuance, attestation, and mTLS without secrets.
When graph-based retrieval outperforms vector similarity — trade-offs, cost, and performance for enterprise RAG.
ElevenLabs, STT/TTS pipelines, multilingual dialog, and the Kinetic India case study.
Why HL7 v2 remains critical in medical AI — Bodh architecture, FHIR R4 integration, and cost-aware diagnostics.
Adaptive retrieval strategies — when the model should retrieve, when it shouldn't, and how to score retrieval quality.
Cross-lingual retrieval for Indian languages — Bhashini integration, translation-aware embeddings, and code-switching handling.
Stdlib over libraries, single binary over framework, fail-closed defaults. The boring-on-purpose case for Go in regulated environments.
Twelve months of running multi-agent AI — SLIs, incident runbooks, drift detection, continuous adversarial testing, compliance posture as code.
What worked, what was hard, and what we'd do differently. Real numbers on agent count, timeline, bugs, and governance policies.
From error wrapping to interface design — opinions that shifted after years of production Go in cloud-native systems.
Compensating transactions, partial failure recovery, and the patterns for distributed payment processing rollbacks.
Business continuity planning for agentic AI — chaos engineering, failover testing, and resilience verification in production.
Soft memory caps, GC pacing in containers, and why GOMEMLIMIT changes every Go service running with a hard memory limit.
Bundling config, prompts, and UI assets into a single Go binary — collapsing multi-artefact deploys with embed.FS.
Range-over-function iterators, composable pipelines, and practical patterns for the iter.Seq interface.
30-minute stage talk on why most microservices migrations fail and how to structure one that ships.