14 posts tagged with "Comparison"

Corrections & Updates (2026-04-16): An earlier version of this article included three-year TCO tables with specific Euro totals and a managed-SaaS per-call rate. Those figures were illustrative but presented with a precision the underlying inputs did not support. This version replaces the fabricated tables with a qualitative framework and points to primary sources (salary databases, vendor pricing pages) so readers can plug in their own inputs. The qualitative conclusion — "for most mid-stage SaaS, OSS self-hosted beats custom build and matches or beats managed SaaS beyond moderate scale" — is unchanged. See commit history for the diff.

"We can build that ourselves in a sprint." We have all said it. Sometimes it is true. For most infrastructure decisions, it is not — especially for API gateways, where the scope of what "that" means expands significantly once you are in production.

This is the final installment of the SaaS Playbook series. We have covered multi-tenancy, rate limiting, audit logging, scaling, and production readiness. Now we tackle the meta-question: should you have built all of this yourself?

Corrections & Updates (2026-04-16): An earlier version of this guide included a Total Cost of Ownership table with specific monthly Euro ranges for self-hosted and managed options. Those figures were illustrative but presented with a precision the underlying inputs did not support. This version replaces the table with a qualitative framework and links to each vendor's public pricing page so readers can plug in their own request volumes and infrastructure rates. The qualitative conclusion — self-hosted open source wins at moderate-to-high scale, managed options stay competitive at low volume — is unchanged.

Choosing an API gateway as a small or medium business in 2026 is harder than it should be. Most comparison articles assume you have a dedicated platform team, a six-figure infrastructure budget, and months to spare on evaluation. Most SaaS companies have none of those things.

This buying guide is written for SMB teams: typically 5-30 engineers, a product that is live (or nearly live), and a need for production-grade API management without enterprise complexity and enterprise pricing.

The OWASP API Security Top 10 (2023) lists the most critical API security risks. An API gateway like STOA helps address several of these at the infrastructure layer — but not all of them. This article maps each OWASP risk to STOA's controls, with an honest assessment of what requires application-level implementation.

Proxy throughput benchmarks tell you how fast a gateway can forward HTTP requests. They tell you nothing about whether that gateway can serve AI agents, enforce guardrails on tool calls, or govern autonomous sessions. We built a new benchmark that measures what actually matters.

Migrating from Broadcom Layer7 API Gateway™ to an open-source alternative is a structured process that can be completed in 4-6 months using a phased, zero-downtime approach. This guide covers feature mapping, a five-phase migration roadmap, and practical guidance on translating Layer7's assertion-based policy model to modern open-source equivalents.

Kong and STOA both support the Model Context Protocol, but they approach it from opposite directions. Kong added MCP via plugins on its proven Nginx/Lua stack. STOA built MCP into the gateway core from day one. This article compares the two specifically on MCP capabilities — tool discovery, transport, authentication, governance, and agent workflow support — so you can choose the right MCP gateway for your AI agent architecture.

STOA Gateway adds less than 2 microseconds of total overhead per request with API key auth and rate limiting enabled. Every benchmark is reproducible with published scripts, and our Gateway Arena runs comparative tests every 30 minutes on identical infrastructure.

This post shares our benchmarking approach, key results, and how you can reproduce everything yourself.

Migrating from Axway API Gateway to an open-source alternative is a structured process that can be completed in 4-6 months using a phased, zero-downtime approach. This guide provides a feature mapping, migration roadmap, and practical advice for enterprise teams evaluating their options.

Three approaches dominate how AI agents call external tools in 2026: the Model Context Protocol (MCP), OpenAI Function Calling, and LangChain Tools. MCP is an open protocol for runtime tool discovery across any AI provider. OpenAI Function Calling is a proprietary API feature tightly integrated with OpenAI models. LangChain Tools is a framework abstraction that wraps tool definitions for orchestration pipelines. They solve different problems, operate at different layers, and can coexist in the same architecture.

WSO2 API Manager is an established open-source API management platform used by enterprises worldwide. As the API management landscape evolves — with AI agent protocols, Kubernetes-native architectures, and stricter European regulations — some teams are evaluating alternatives that better align with their current requirements. This guide provides a feature comparison, migration approach, and practical guidance.