Helping agents ship code you trust to prod

Give your coding agents observability superpowers.

Connect your repos · No credit card required.

bluebox

works where you work

How Bluebox works

Gives your agents
eyes into prod

Scans your repo automaticallyDiscovers every service, database, and external dependency.
Guides OTel instrumentationAuto-generates OTel config and walks you through setup.
Reads your live services topologyPulls your live dependency graph: hosts, services, clusters, so your agent reasons in context, not in isolation.
Links production directly to your coding agentYour agent gets real runtime context before it writes a single line.

Briefs your agents
before building

Plan before you promptHave Bluebox think upfront so your agent executes instead of exploring.
Make your agents more effectiveBetter context means fewer iterations with less reasoning, even with smaller models.
Less reprompting, better outcomesBluebox briefs your agent upfront so it executes instead of exploring.
Know before you shipFull context before you build. Your agent executes against the runtime environment you're building for.

Finds issues before
they're issues

Monitors production signals continuouslyLatency, error rates, SLOs – all watched, all the time.
Surfaces incidents the moment they appearNo alert fatigue, only the signal that actually matters.
Investigates with full runtime contextTraces, logs, topology, and live code, correlated automatically.
Detects root-cause in your codeNot just infrastructure noise. The actual commit and code path that caused it.

Hands your agent a fix plan
as a GitHub Issue

Evidence-backed GitHub Issue, ready to act onThe trace, the offending lines, the blast radius: everything your agent needs to fix it.
Blast radius before you deployKnow exactly what's at risk. No surprises after you release.
You decide what happens nextHand it to your agent, fix it yourself, or close it. Bluebox never acts without your call.
Bluebox confirms the fix heldPost-deploy monitoring verifies the incident is closed, with data, not optimism.

Trusted and Open Standard

Trusted

Dynatrace powered insights

Causal AI under the hood. Not pattern-matching, not guesswork. Real root cause, every time.

GitHub native

GitHub Issues as output

Every fix lands as a GitHub Issue with all the context your agent or you needs to act. No new tools to learn.

Open standard

Built on OpenTelemetry

No vendor lock-in. Works with your existing OTel setup, or guides you through setting one up.

Built for developers who ship with coding agents

You're moving fast. Bluebox is the missing production observability layer. It checks what your agent can't see, so you can merge with confidence.

Don't take our word for it. Try it for free.

Connect your repos. Tell your agent. No credit card required.

Check out our latest blog articles

Use Case

Beyond "It Works on My Machine"

Coding agents are genuinely good at understanding a local codebase. Point one at a repository and it can read the architecture, trace the data flow, interpret configuration, and reason about what the code is supposed to do. But code doesn’t run in a repository. It runs in production, where traffic is real, services call each other under load, and the gap between "what the code says" and "what the system does" is exactly where incidents get introduced. An agent working only from the repository

Michael Beemer 7 min read 02 Sept 2026

Bluebox + Kiro + AWS DevOps Agent: Connecting AI Development and Operations with Production Intelligence

Bluebox, Kiro, and AWS DevOps Agent bring production intelligence directly into AI-driven software delivery. By connecting development and operations with shared runtime context, teams can build, deploy, investigate, and remediate issues using the same production-aware insights. Looking for the full technical walkthrough? Read the AWS blog: AI-driven software delivery with Kiro, AWS DevOps Agent and Bluebox by Dynatrace AI is rapidly transforming software development. Coding agents can gener

Jason Ostroski 3 min read 28 Aug 2026

building bluebox

Scaling an AI-Native Team Without Scaling Chaos

When AI makes implementation faster, context, decision-making, and trust become the real constraints. Here is what we are learning while building Bluebox. This post is part of a four-part series on how we built Bluebox, the engineering and organizational principles behind it, and how we use Bluebox to manage Bluebox. When software production changes, the team system has to change too. If AI is building your apps, AI should take care of your apps too. That idea is the starting point for Blu

Benedict Evert 9 min read 26 Aug 2026

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