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Heroku Blog

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Building AI-Powered Observability with Heroku Managed Inference and Agents

If you’ve ever debugged a production incident, you know the drill: IDE on one screen, Splunk on another, Sentry open in a third tab, frantically copying error messages between windows while your PagerDuty keeps buzzing.

You ask “What errors spiked in the last hour?” but instead of an answer, you have to context-switch, recall complex query syntax, and mentally correlate log timestamps with your code. By the time you find the relevant log, you’ve lost …

Heroku and GitHub Enterprise Server: Stronger Security, Seamless Delivery

Today, we are thrilled to announce the General Availability (GA) of the Heroku GitHub Enterprise Server Integration.

For our Enterprise customers, the bridge between code and production must be more than just convenient. It must be resilient, secure, and governed at scale. While our legacy OAuth integration served us well, the modern security landscape demands a shift away from personal credentials toward managed service identities.

An Update on Heroku

Today, Heroku is transitioning to a sustaining engineering model focused on stability, security, reliability, and support. Heroku remains an actively supported, production-ready platform, with an emphasis on maintaining quality and operational excellence rather than introducing new features. We know changes like this can raise questions, and we want to be clear about what this means for customers.

There is no change for customers using Heroku today. Customers who pay via credit card in the Heroku …

Building AI Search on Heroku

If you’ve built a RAG (Retrieval Augmented Generation) system, you’ve probably hit this wall: your vector search returns 20 documents that are semantically similar to the query, but half of them don’t actually answer it.

A user asks “how do I handle authentication errors?” and gets back documentation about authentication, errors, and error handling in embedding space, but only one or two are actually useful.

This is the gap between demo and production. Most tutorials stop at vector search. This reference architecture shows what comes next. This AI Search reference app shows you how to build a production grade enterprise AI search using Heroku Managed Inference and Agents.

Optimize Search Precision with Reranking on Heroku AI

Today, we are announcing the general availability of reranking models on Heroku Managed Inference and Agents, featuring support for Cohere Rerank 3.5 and Amazon Rerank 1.0.

Semantic reranking models score documents based on their relevance to a specific query. Unlike keyword search or vector similarity, rerank models understand nuanced semantic relationships to identify the most relevant documents for a given question. Reranking acts as your RAG pipeline’s high-fidelity filter, decreasing noise and token costs by identifying which documents best answer the specific query.

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