Every few weeks, the AI-adjacent internet crowns a new corpse. SaaS is dead. OpenAI is dead. The IDE is dead. Humans writing code is dead. The structure is always the same: take a real observation, strip it of all nuance, and toll the death knell to feed the hype train. Rinse and repeat. The…
[](/blog/enterprise/cli-vs-mcp-enterprise-ai-governance)
The global financial services industry is undergoing a massive, API-driven revolution. With the global open banking market valued at $31.61 billion in 2024 and projected to grow to $135.17 billion by 2030, this shift is accelerating worldwide. This definitive guide explores the core APIs, the…
[](/blog/learning-center/guide-on-open-banking)
Every enterprise moving AI into production is about to face a familiar problem in an unfamiliar form: the cost explosion, but for LLMs. This is very similar to what happened with cloud. In the early days of cloud, teams spun up infrastructure with no visibility into who was consuming what. Finance…
[](/blog/enterprise/llm-cost-management-ai-showback-and-chargeback)
The microservices revolution promised agility and scalability. Teams could deploy faster, scale independently, and innovate without monolithic constraints. You gain speed and flexibility, but you also multiply trust boundaries, identities, network paths, and policy decisions. Then came AI, and…
[](/blog/engineering/5-best-practices-securing-microservices-scale)
Modern enterprise architecture faces a three-body problem. Three distinct traffic patterns pull your teams in different directions. External APIs serve mobile apps and partner integrations. Internal microservices communicate within Kubernetes clusters. AI and LLM calls flow to OpenAI, AWS Bedrock,…
[](/blog/enterprise/microservices-to-ai-traffic-kong-as-the-unified-control-plane)
AI APIs don't get enough credit for how much weight they're actually carrying. These AI APIs aren't merely technical connectors. They're, in fact, cost drivers and potential revenue engines. And when something goes sideways, they're ground zero. In production, they behave nothing like the…
[](/blog/engineering/monetize-ai-apis)
For enterprise teams evaluating API testing tools like Insomnia and Postman, understanding the real cost is critical. Postman’s recent changes and Insomnia’s alternative approach tell different stories. Let’s dive in. TL;DR: Free collaboration with Postman — a myth On March 1st, 2026, Postman…
[](/blog/enterprise/insomnia-vs-postman-evaluating-api-testing-tools)
Event-driven architectures (EDAs) have pretty quickly transformed from a niche engineering pattern to the all-pervasive central nervous system of the modern enterprise. With Apache Kafka at the helm, enterprises are rapidly shifting gears from synchronous REST APIs to asynchronous event streams to…
[](/blog/product-releases/kong-event-gateway-1-1)
We want to ensure that our customers know that Kong is not affected by the PyPI LiteLLM incident publicized yesterday. Kong does not rely on LiteLLM — whether PyPI-distributed or otherwise — for any components in our runtime stack. As you may know, a supply chain vulnerability affecting LiteLLM…
[](/blog/news/kong-not-affected-by-the-pypi-distributed-litellm-supply-chain-attack)
Bringing APIs and events together has always been a challenge. REST APIs give developers a familiar interface, while event brokers like Solace Broker excel at fan-out, filtering, and scalable, reliable event delivery. The tricky part? Bridging these two worlds without building a lot of custom glue.…
[](/blog/engineering/smarter-event-driven-apis-kong-solace)
Enterprise product teams are squarely in the throes of a massive shift. New Gartner research crystalized that companies using AI tools for product management are reaping a significant 35% productivity gain and achieving a two to three-year time-to-market advantage over those who wait. In their…
[](/blog/news/gartner-recognizes-kong-progressive-ai-adopter)
AI connectivity is enterprise infrastructure that governs, secures, routes, observes, and optimizes all AI interactions —providing the control layer organizations need to transform experimental AI into production-ready systems. Executive Summary AI adoption has moved past the "honeymoon phase" and…
[](/blog/enterprise/ai-gateways-for-scalable-ai-connectivity)
As enterprises race to deploy multicloud architectures and Agentic AI, they face a common bottleneck: "state." To govern AI token usage, manage agent-to-agent communication, or optimize performance via caching, API and AI gateways require a persistence layer to synchronize data. We’re excited to…
[](/blog/product-releases/multicloud-cloud-gateways-managed-redis-cache)
A persistent challenge arises as businesses adopt multicloud architectures and agentic AI: the need for state synchronization. API and AI gateways require a robust persistence layer to synchronize data, whether it's for governing AI token usage, facilitating agent-to-agent communication, or…
[](/blog/engineering/dedicated-cloud-gateways-managed-redis-multi-cloud)
As enterprises start deploying AI agents into real systems, a new architectural challenge is emerging. Agents need a reliable way to discover tools, services, and capabilities dynamically, instead of relying on hardcoded integrations. This is where the Model Context Protocol (MCP) ecosystem is…
[](/blog/engineering/mcp-registry-dynamic-tool-discovery)Secure your AI infrastructure with prompt guards, PII sanitization, and centralized governance. Control LLM costs with token-based rate limiting and semantic routing across providers.