# API Metrics Published articles for API Metrics. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Beyond the 200 OK: Architecting Observability for AI DevFeed: [Beyond the 200 OK: Architecting Observability for AI]() Original publisher: [Read original article]() Author: Adriano Mota Published: 2026-09-11T07:00:00Z Content type: article Language: en Sources: [Nordic APIs]() Topics: [ai observability](), [observability](), [Application Performance Management (APM)](), [AI Agent](), [Artificial Intelligence]() Tags: [ai](), [ai-agent](), [ai-agents](), [ai-observability](), [api-logging](), [api-metrics](), [api-monitoring](), [api-security](), [api-testing](), [apm](), [artificial-intelligence](), [blog](), [generative-ai](), [llm](), [mcp](), [observability]() ### AI overview An article about designing observability for AI systems beyond traditional APM metrics, with emphasis on tracking quality, cost, retrieval, and agent behavior. ### Source excerpt Traditional monitoring tools, such as application performance monitoring (APM), were engineered to monitor deterministic software where specific inputs reliably lead to predictable outputs through hard-coded logic. When a traditional API fails, it usually throws a 500 Internal Server Error. But when an AI agent fails, it might return a perfectly healthy 200 OK status code ... ## Are We Overengineering Modern Infrastructure? DevFeed: [Are We Overengineering Modern Infrastructure?]() Original publisher: [Read original article]() Author: Art Anthony Published: 2026-08-14T07:00:00Z Content type: opinion Language: en Sources: [Nordic APIs]() Topics: [data](), [Kubernetes]() Tags: [2026](), [api-logging](), [api-metrics](), [api-monitoring](), [apis](), [blog](), [cloud-native](), [devops](), [infrastructure](), [kubernetes](), [platform-summit](), [summit](), [uk]() ### AI overview The article previews Faith Sodipe's Nordic APIs Summit 2026 talk about scaling data ingestion while avoiding unnecessary Kubernetes use. It focuses on whether modern infrastructure has become overly complex. ### Source excerpt Ahead of his 2026 Nordic APIs Summit talk on scaling data ingestion without turning to Kubernetes, we check in with Bauer Media Group UK's Faith Sodipe to talk about infrastructure complexity. In the tech space, perhaps more than in any other, we are always looking for the next big thing. Whenever a new platform, standard, ... ## The right way to turn off your old APIs DevFeed: [The right way to turn off your old APIs]() Original publisher: [Read original article]() Author: HTTP Toolkit; Tim Perry Published: 2021-01-21T10:30:00Z Content type: tutorial Language: en Sources: [HTTP Toolkit]() Topics: [API](), [HTTP](), [Internet Engineering Task Force (IETF)](), [Logging](), [stripe]() Tags: [api-metrics](), [apis](), [http](), [ietf](), [logging](), [standards](), [stripe]() ### AI overview This tutorial explains how to safely shut down old HTTP APIs. It recommends checking usage through metrics or logging, considering internal translation to newer APIs, and creating a deprecation plan when continued support is impractical. It also discusses two draft headers from the IETF Building Blocks for HTTP APIs working group. ### Source excerpt All things come to an end, even HTTP APIs. However great your API may be today, one day you'll want to release a completely new version, an improved but incompatible endpoint, a new parameter that solves the same problem better, or to shut down your API entirely. Your current API will not be live forever. Inconveniently though, your API has clients. If you shut down endpoints, parameters, or entire APIs without properly warning them then they're going to be very unhappy. How do you shut down your APIs safely, making it at easy as possible for your users? There are right ways to do this, including two new draft headers being standardized by the exciting new IETF "Building Blocks for HTTP APIs" working group, designed to help with this exact process. Let's take a look. Make a plan First up: check if the API in question actually has any clients. Hopefully you have some API metrics or at least logging somewhere. If you don't, add some! If you do, and you can tell for sure that nobody is using this API anymore, then you win. Turn it off right now, delete the code, skip this article and have a well-deserved nap. The next question, if you're not napping, is to ask yourself whether there's an alternative to shutting down this API. Everything you turn off will break somebody's code and take their time to fix it. It's good for the health of your client ecosystem and the web as a whole if APIs keep working. In many cases, old APIs can be translated internally, to transparently transform requests into calls to a new API instead, without maintaining two completely independent versions. This is a fundamental part of the API versioning approach at Stripe who include transformations with all API changes to ensure that requests for incompatible old versions continue to work as before, automatically translating the requests and responses to use the newer code as required. Translation like this isn't always possible, and doing so forever can entail significant extra complexity, but if ## Application visibility DevFeed: [Application visibility]() Original publisher: [Read original article]() Author: Square Engineering Published: 2015-07-10T07:00:00Z Content type: opinion Language: en Sources: [Square Corner Blog RSS Feed]() Topics: [Monitoring](), [dashboards](), [Microservices](), [Instrumentation](), [site-reliability-engineering]() Tags: [api](), [api-metrics](), [dashboards](), [ecosystem](), [engineering](), [instrumentation](), [metrics](), [microservices](), [microservices-architecture](), [monitoring](), [systems]() ### AI overview Square describes the monitoring and alerting systems it uses to improve application visibility as its technology stack grows from Rails monoliths to a microservices architecture. The article presents principles for usability, focused metrics, instrumentation, actionable alerts, and reproducible problems, and introduces tools for dashboards, dependencies, events, exceptions, capacity, and deployments. ### Source excerpt A sneak peek into various monitoring and alerting systems used at Square.