Get it on Google Play

AURA and Open-Source Agents for Production Operations

AURA and Open-Source Agents for Production Operations

Author: Software Engineering Daily July 14, 2026 Duration: 53:04
Software Engineering Daily
NewsTechnology

AI agents have transformed how software gets written, but the operational side of running software in production has not yet experienced a similar revolution. The same teams responsible for keeping systems healthy, investigating incidents, and managing reliability are still doing much of that work manually.

Mezmo is a Production AI company that makes autonomous operations fast, efficient, and safe. Their open source project, AURA, is a declarative agent framework specifically designed for SRE and platform engineering workflows. It takes a Kubernetes-inspired approach where teams define what they want agents to do rather than scripting every step of how to do it.

Andre Elizondo is the head of product at Mezmo, and he has a background in systems engineering, SRE, and observability. In this episode, Andre joins Kevin Ball to discuss what makes SRE agent workflows fundamentally different from coding agents, how AURA handles context engineering, AURA’s declarative configuration model, the spectrum of agent autonomy, and where the role of the SRE is headed as agents take on more of the operational work.

Full Disclosure: This episode is sponsored by Mezmo.

Kevin Ball or KBall, is the vice president of engineering at Mento and an independent coach for engineers and engineering leaders. He co-founded and served as CTO for two companies, founded the San Diego JavaScript meetup, and organizes the AI inaction discussion group through Latent Space.

Please click here to see the transcript of this episode.

Sponsorship inquiries: sponsor@softwareengineeringdaily.com

The post AURA and Open-Source Agents for Production Operations appeared first on Software Engineering Daily.


Dive into a curated collection from the vast library of Software Engineering Daily with Greatest Hits Archives-Software Engineering Daily. This podcast isn't about new trends or breaking news; instead, it serves as a thoughtfully assembled replay of the most impactful and enduring conversations from the show's history. Each episode selected for this archive represents a foundational discussion, a pivotal interview, or a deep exploration that has resonated deeply with the technology community over the years. You'll hear veteran engineers, pioneering founders, and insightful researchers break down complex topics-from distributed systems and database architecture to the human elements of building effective teams and sustainable engineering cultures. The archive format allows listeners to experience the essential building blocks of modern software thought leadership, all in one dedicated feed. Whether you're discovering these classic conversations for the first time or revisiting them with fresh perspective, this podcast provides a timeless resource. It cuts through the noise of the daily tech cycle to deliver substantive content that remains relevant long after its original release, offering a masterclass in the principles and practices that define our industry.
Author: Language: en-us Episodes: 50

Official website RSS
youtubelinkedinspotifyapple_music
Software Engineering Daily
Podcast Episodes
Scaling Agent Workloads at Vercel [not-audio_url] [/not-audio_url]

Duration: 51:25
Most AI agent setups today are built around a single session, where one user interacts with one agent at a time. However, that model breaks down when an agent has to serve a business, where thousands of requests can arri…
Inside Google’s Database Infrastructure for the AI Era [not-audio_url] [/not-audio_url]

Duration: 1:18:26
Historically, databases were responsible for storing data and returning exact results in response to queries. However, AI is now bending that contract in a new direction. Applications increasingly expect structured and u…
A Rust Framework to Simplify Distributed Systems [not-audio_url] [/not-audio_url]

Duration: 50:31
A Rust Framework to Simplify Distributed Systems Building software that runs across many machines is notoriously difficult. Developers have to grapple with problems such as race conditions, partial failures, and message…
Moving Beyond RAG with Precomputed Context [not-audio_url] [/not-audio_url]

Duration: 55:48
Retrieval has become one of the central problems in building useful AI systems. The standard approach to grounding a model in one’s own data has been retrieval augmented generation, or RAG, where an agent searches a vect…
The Death of Online Anonymity [not-audio_url] [/not-audio_url]

Duration: 52:42
Age verification is reshaping how people access the internet. An ever-growing patchwork of laws can now require government IDs, facial age estimation, or behavioral inference before you can enter digital spaces. Discord,…
TypeScript 7 and What Comes Next [not-audio_url] [/not-audio_url]

Duration: 57:15
TypeScript is a programming language that builds on JavaScript by adding a system of types. Those types let developers describe the shape of their data and catch mistakes before code ever runs, while also powering the au…
The Gap Between AI Spending and AI Value [not-audio_url] [/not-audio_url]

Duration: 54:42
It is widely reported that a gap has emerged between enterprise spending on AI and the durable value captured from that spend. Individual employees have enthusiastically adopted coding assistants and chatbots, yet those…
AI and the New Global Security Landscape [not-audio_url] [/not-audio_url]

Duration: 1:12:32
The conversation about AI often focuses on software, automation, and the race between attackers and defenders in code. However, some of the most consequential risks lie further afield, in domains where a mistake is measu…
How LLMs Are Reshaping Recommendation Systems [not-audio_url] [/not-audio_url]

Duration: 47:51
News feeds and recommendation systems have long relied on deep learning architectures that score each candidate item independently. As LLMs have matured, they have opened up a fundamentally different approach, where a sy…

12345»