Kong AI Gateway
Choose it when Kong is already strategic infrastructure.
You want LLM, MCP and A2A controls to share Kong identity, policies, operations, plugins and data-plane practices with the rest of your APIs.
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Independent decision brief
DVARA or Kong AI Gateway?
Both products now govern LLM, MCP and A2A traffic. The real decision is whether AI governance should extend an established API platform or run as a focused governance system with its own policy and evidence model.
Start with fit
Which operating model matches yours?
A useful comparison should help you eliminate the wrong option quickly.
DVARA
Choose it when AI governance should stand alone.
You need a smaller, governance-first platform with versioned policy, data controls and tamper-evident evidence across dedicated AI planes.
Four decisions
Compare the boundary, not the checklist
Each row explains the tradeoff and the question to take into a pilot.
Is this an API-platform decision?
Kong and DVARA start from different operational centres.
Kong AI Gateway
Kong AI Gateway extends a mature API gateway platform. Konnect manages the control plane while data-plane nodes can run in your infrastructure.
DVARA
DVARA is purpose-built for AI governance and runs its control and data-plane components in your environment.
Decision: Choose Kong when consolidating AI and API infrastructure matters. Choose DVARA when a focused AI governance boundary is easier to own.
How should model traffic be controlled?
Both provide provider abstraction and request-path controls.
Kong AI Gateway
Kong documents provider routing, load balancing, retries, cost controls, prompt guards, PII sanitization, content safety and OpenTelemetry.
DVARA
DVARA applies workspace policy, PII controls, cost attribution and tamper-evident audit across supported model connectors.
Decision: Map the policies you need to Kong AI Policies or DVARA policy conditions and test their defaults on streaming and non-streaming paths.
What do MCP and A2A require?
Kong now treats both protocols as first-class traffic types.
Kong AI Gateway
Kong provides MCP server entities, tool access controls, authentication, policies and protocol-aware A2A routing and telemetry.
DVARA
Enterprise deployments add MCP argument checks, PII controls, approval gates, loop detection and A2A hop governance.
Decision: Do not compare on protocol support. Compare tool-level authorization, payload controls, approval behavior, session handling and agent telemetry.
Which evidence model fits?
Both platforms log activity, but the mechanisms differ.
Kong AI Gateway
Kong exports AI, MCP and A2A logs, metrics and traces through Konnect and OpenTelemetry-compatible systems.
DVARA
DVARA records policy decisions and runtime activity in a tamper-evident audit trail surfaced through Flightdeck.
Decision: Choose the evidence format your security and audit teams can retain, verify and query without creating another reconciliation workflow.
Verified details
Facts that change the decision
These details are easy to lose in a broad feature matrix.
- Three traffic types
- Kong AI Gateway documents first-class LLM, MCP and A2A traffic support.
- Hybrid architecture
- The Konnect control plane is managed; registered data-plane nodes run in customer infrastructure.
- On-prem difference
- Self-hosted Kong uses services, routes and AI plugins rather than every Konnect AI entity.
- MCP policies
- MCP traffic can use authentication, ACLs, rate limits, transformations, logging and tool access controls.
- A2A controls
- Kong provides protocol-aware routing, agent-card rewriting and structured A2A telemetry.
- DVARA audit
- DVARA adds a HMAC-signed, hash-chained audit mechanism for governed decisions.
Bottom line
Extend Kong, or deploy focused AI governance?
Kong AI Gateway is compelling when Kong already anchors API identity, traffic policy and operations. DVARA is the clearer fit when the organisation wants a focused AI governance platform with versioned policy and tamper-evident evidence rather than a broader API platform.