Platform & Operations
MCP 2026-07-28: What Changed in the Ratified Spec
The ratified MCP 2026-07-28 spec drops session state for a stateless core, adds MRTR and CIMD, and formalizes Tasks, MCP Apps, and EMA as extensions.
Platform & Operations
Platform & Operations
MCP servers, workflows, observability, and the control-plane engineering behind it.
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MCP Server Governance: The Complete Guide
The authoritative reference for bringing MCP servers under governance: security model, authentication, tool scoping, rate limits, monitoring, and hardening.
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Platform & Operations
OpenTelemetry GenAI Semantic Conventions: What's Stable
As of mid-2026, no gen_ai.* OpenTelemetry attribute is stable — what moved, what that means for teams instrumenting agents now.
Platform & Operations
LLM Observability Tools for Security and Compliance Teams
Langfuse, LangSmith, Arize Phoenix, and Braintrust evaluated for audit-trail and compliance readiness — not eval quality.
Platform & Operations
MCP STDIO RCE Vulnerability Wave (2026) Explained
OX Security's April 2026 disclosure found a design-level flaw in Anthropic's MCP SDKs enabling remote code execution via STDIO transport.
Platform & Operations
LiteLLM Enterprise Alternatives: Beyond Self-Hosting
When LiteLLM's self-hosted model stops scaling and what teams evaluate instead — Portkey, Kong AI Gateway, Cloudflare AI Gateway, and TrueFoundry.
Platform & Operations
Agent Evaluations: Catching Quality Regressions Before Users Do
Agents regress silently when prompts, models, tools, or data change. Learn how to build an evaluation harness that catches it — scoring methods, what to measure, and where evals belong in the pipeline.
Platform & Operations
LLM Gateway Comparison 2026: Security and Governance
Portkey, LiteLLM, Kong AI Gateway, and Cloudflare AI Gateway compared for routing, spend control, and security — how to shortlist for your team.
Platform & Operations
Agent Topology Maps: Seeing the Dependency Graph
An agent estate is a graph of agents, tools, data sources, and models. Learn what a topology map should show, which questions it answers that a list cannot, and how to keep it accurate.
Platform & Operations
High Availability for an AI Control Plane
A control plane in the request path is a dependency for every agent call. Learn which components must be fail-closed, which can degrade, and how to design failure modes deliberately rather than discovering them.
Platform & Operations
Post-Incident Forensics for AI Agents
Reconstructing what an agent did, why it did it, and what it touched requires evidence most deployments never record. Learn the minimum record set and the investigation sequence that uses it.
Platform & Operations
MCP Server Registries: Publishing, Discovery, and Ratings
A registry is where MCP server choices get made, which makes it a supply-chain control point. Learn what a registry entry should carry, how ratings get gamed, and why internal catalogues beat public ones.
Platform & Operations
Detecting Shadow MCP Servers
Developers add MCP servers to their agents in minutes, without review. Learn how to find the ones already running in your environment and how to make the governed path easier than the ungoverned one.
Platform & Operations
Publishing Agents to a Marketplace: The Review Gate
A marketplace that lets publishers approve their own listings has no review at all. Learn the listing lifecycle, why self-certification must be structurally impossible, and what review should actually check.
Platform & Operations
MCP OAuth 2.1 and PKCE, Explained Step by Step
The Nov 2025 MCP authorization flow, step by step: protected-resource metadata, client registration, PKCE, and RFC 8707 resource-bound tokens.
Platform & Operations
MCP Server Vetting: Registry Risk and How to Manage It
Third-party MCP servers are supply-chain risk: registry provenance, tool-description audits, version pinning, and an approval workflow that scales.
Platform & Operations
MCP Gateway Comparison 2026: Options and Trade-offs
A 2026 survey of MCP gateway options — open-source gateways, API-gateway extensions, and governance control planes — and how to choose between them.
Platform & Operations
Evaluating AI Agent Observability Tooling
A practical guide to what AI agent observability must cover — cost, behavior, and policy compliance — and the key criteria for choosing the right tooling.
Platform & Operations
MCP Gateway: What to Look For
Evaluate MCP gateways on four criteria that actually matter: agent authentication, per-tool scoping, rate limits, and forensic audit logging.
Platform & Operations
Guardrail Nodes: Inline Policy in Agent Workflows
A guardrail node placed in a workflow graph makes policy visible where it applies. Learn what these nodes should do, the silent no-op failure to avoid, and how they relate to connection-level enforcement.
Platform & Operations
Agent Task Marketplaces and Escrow
When agents post and accept paid work across organizations, the payment mechanism becomes a security surface. Learn the task lifecycle, where escrow protects each side, and the leaks to design out.
Platform & Operations
Building Golden Datasets for Agent Evals
The dataset is the hard part of evaluation, not the harness. Learn how to source cases, structure expectations for non-deterministic systems, version the set, and keep it from rotting.
Platform & Operations
Webhook Security: Signing and Verifying Events
HMAC signatures plus timestamp replay windows are the minimum bar for secure webhooks — here's why unsigned endpoints are dangerous and how to fix them.
Platform & Operations
OTLP Telemetry Ingest for Agent Discovery
You cannot govern agents you do not know about. OpenTelemetry ingest turns existing instrumentation into an agent inventory. Learn what the ingest path has to solve, the tenant-isolation trap, and how discovery becomes governance.
Platform & Operations
Versioning and Rollback for AI Agents
Version AI agent workflows like code, diff changes between snapshots, and roll back safely when a new version causes regressions or runaway costs in production.
Platform & Operations
Dead-Letter Queues for Failed Agent Jobs
A dead-letter queue nobody watches is a place where work goes to be forgotten. Learn what belongs in a DLQ, how to alert on it, and how to replay safely once the cause is fixed.
Platform & Operations
Threat Model: Over-Broad MCP Tool Scope
Over-broad MCP tool permissions give attackers an amplified attack surface. Learn the failure modes and control classes that shrink the blast radius.
Platform & Operations
Benchmarking Agents: What Public Numbers Can and Cannot Tell You
Public agent benchmarks are useful for narrowing a shortlist and misleading as a selection criterion. Learn what they measure, how contamination distorts them, and how to benchmark against your own workload.
Platform & Operations
Retries and Idempotency in Agent Workflows
At-least-once delivery plus agents that take real actions equals duplicate side effects. Learn where idempotency keys belong, why retries are a cost multiplier, and how to make replay safe.
Platform & Operations
How to Rate-Limit AI Agents
Design abuse-resistant rate limits for AI agents: choose the right unit, window shape, and enforcement scope to protect costs and downstream systems.
Platform & Operations
How to Monitor MCP Tool Calls
Gain full visibility into every MCP tool call an AI agent makes — with attribution, policy decisions, and cost data needed for security and compliance.
Platform & Operations
Orchestration Patterns for Multi-Agent Systems
Compare pipeline, hub-and-spoke, and blackboard orchestration patterns for multi-agent AI — with security, cost, and auditability trade-offs for each.
Platform & Operations
Observability for AI Agents: Logs, Metrics, and Traces
How logs, metrics, and distributed traces apply to AI agents—what to instrument, where costs hide, and how to connect all three for fast incident triage.
Platform & Operations
Rate Limiting and Abuse Prevention for AI APIs
Request counts alone don't protect AI APIs. The layered controls that work: per-connection limits, spend caps, tool allow-lists, and trust gates.
Platform & Operations
MCP Server Authentication: OAuth 2.1 vs API Keys
OAuth 2.1 vs API keys for MCP servers after the Nov 2025 spec: PKCE, RFC 8707 resource indicators, token lifetimes, revocation, and when each fits.
Platform & Operations
Securing MCP Servers: An Authentication Guide
Most MCP servers ship with no authentication. Learn how to add identity verification, per-caller tool scoping, and guardrails to production servers.
Platform & Operations
Scoping MCP Tool Permissions: Least Privilege for Tools
Grant AI agents the minimum MCP tool access they need — no more. Learn how allow-lists, per-tool rate limits, and policy gates prevent blast-radius breaches.
Platform & Operations
MCP Server Security: A Complete Checklist
A practical MCP server security checklist covering authentication, tool-level authorization, rate limits, forensic logging, and monitoring for agents.
Platform & Operations
What Is the Model Context Protocol (MCP)? A Practical Guide
MCP gives AI agents a standard way to call external tools and retrieve context. Learn what it is, how it works, and the security controls it needs.
Platform & Operations
API-First: The Praesidia API Surface
Every platform action is an API call. Learn how Praesidia's OpenAPI-described surface lets you automate governance, integrate tooling, and extend the platform.
Platform & Operations
The Platform Admin Console
The platform admin console gives super-admins cross-tenant visibility, DLQ triage, two-person governance controls, and GDPR erasure on a separate access plane.
Platform & Operations
Real-Time Events over WebSocket
A persistent, authenticated WebSocket stream replaces polling for agent tasks, workflow runs, and budget alerts — and what safe multi-tenant fan-out requires.
Platform & Operations
Health Probes and Readiness for AI Infrastructure
How to design liveness and readiness probes for AI services — what to check, how to avoid false positives, and what a production health surface looks like.
Platform & Operations
Webhooks and SIEM Forwarding
Stream AI agent events to your own systems and forward security signals to a SIEM — so agent activity is visible in the tooling your team already uses.
Platform & Operations
Organization API Keys and Scopes
Issue, scope, and rotate organization API keys to give each integration only the access it needs — and limit blast radius when a credential is exposed.
Platform & Operations
Closing the Loop with a Product Feedback Board
Turn scattered user requests into ranked roadmap signal with a built-in feedback board that supports voting, moderation, and multi-tenant visibility.
Platform & Operations
Slack and Multi-Channel Alerting
Route AI agent budget alerts, guardrail violations, and task failures to Slack and other channels with a reliable, tenant-isolated dispatcher pattern.
Platform & Operations
Unsubscribe, Suppression, and Preference Centers
Build a compliant email opt-out system with enforced suppression lists, per-category preferences, and bounce handling that protects your sender reputation.
Platform & Operations
Transactional Email and Templates
Reliable transactional email for AI platforms: how consistent templates, authenticated sending, and delivery safeguards keep security and billing flows intact.
Platform & Operations
Web Push Alerts for AI Operations
Browser push notifications deliver agent failures and budget alerts to operators the moment they happen — no open tab or email check required.
Platform & Operations
In-App Notifications That Cut Through
How a purpose-built in-app notification system keeps AI platform operators informed of critical agent events and alerts without noise or alert fatigue.
Platform & Operations
Auth Monitoring and Login Security
How to capture, aggregate, and act on authentication events in your AI platform so credential attacks surface in minutes, not days.
Platform & Operations
Visualizing AI Usage and Cost
Charts, dashboards, and cost breakdowns that make AI agent spend legible — from real-time KPIs to anomaly detection and per-team attribution.
Platform & Operations
Prometheus Metrics and Observability
Praesidia exposes a standard Prometheus metrics endpoint so you can monitor AI agent task throughput, latency, and spend using the tools your team already runs.
Platform & Operations
Global Search Across Your AI Estate
Search across agents, tasks, connections, workflows, and audit logs from a single entry point — find any resource in your AI estate instantly.
Platform & Operations
Saved Views for Faster Operations
Saved views let AI operations teams restore any dashboard state in one click — cutting investigation setup time and reducing filter errors under pressure.
Platform & Operations
Service Level Objectives for AI Services
Set measurable SLOs for task success rate, latency, and agent availability — then alert before users notice. A practical guide for AI agent deployments.
Platform & Operations
Executive Reports for AI Governance
Turn AI activity into board-ready governance reports covering usage, cost, and risk — with scheduled delivery and export for compliance teams.
Platform & Operations
The Operations Dashboard for Your AI Estate
How an AI operations dashboard correlates agent counts, spend, trust scores, and security events in one view — and what to do when the numbers look wrong.
Platform & Operations
Advanced Analytics for AI Operations
Go beyond basic dashboards: model comparison, cost-per-team allocation, anomaly detection, and compliance analytics for AI operations teams.
Platform & Operations
Analytics and the Event Stream
How a per-interaction event model powers AI agent dashboards, cost attribution, and forensic investigation — without additional collection infrastructure.
Platform & Operations
Per-Org Feature Overrides and Canary Rollouts
Per-org feature overrides let you enable a capability for one tenant, observe real behavior, and expand gradually — without touching your deployment pipeline.
Platform & Operations
Plan Gating and Feature Flags
Plan-based feature flags gate capabilities by subscription tier while per-org overrides enable safe canary rollouts — no deployment pipeline changes required.
Platform & Operations
Real-Time Collaborative Workflow Editing
How real-time collaboration on AI workflow canvases works: CRDTs for conflict-free edits, durable working documents, presence, and per-edit authorization.
Platform & Operations
Bring Your Own Key: Managing LLM Configurations
Register your own LLM provider keys in one encrypted registry, route workloads to the right model, and eliminate key sprawl — without platform lock-in.
Platform & Operations
Registering and Governing MCP Servers
Register MCP servers centrally, enforce per-tool permissions and rate limits, and log every invocation for audit — governance that unmanaged connections lack.
Platform & Operations
Reusable Workflow Templates
Workflow templates let teams deploy proven agent pipeline patterns in one click — spreading best practices and simplifying governance across the organization.
Platform & Operations
Chat-to-Build: Generating Workflows with AI
Turn a plain-language description into a reviewable multi-agent workflow draft in seconds. Learn how AI generation works and where human review stays essential.
Platform & Operations
Triggering Workflows: Scheduled, Webhook, and Event
The three ways to start an AI workflow—cron schedules, signed webhooks, and platform events—and which trigger fits each operational pattern.
Platform & Operations
Executing and Monitoring Workflow Runs
How workflow runs execute node-by-node, how per-run spend caps prevent cost overruns, and how to observe, pause, cancel, and retry runs in real time.
Platform & Operations
Designing AI Workflows on a Visual Canvas
A node-and-edge visual canvas lets you compose, version, and audit multi-step AI agent workflows before anything runs — catching gaps that code reviews miss.
Platform & Operations
Managing API Consumers with Applications
Register every API consumer as a named Application with scoped credentials and per-agent access controls — so you can see and revoke what each can do.