Lakshmi shares his journey from electrical engineering and performance testing at Comcast to building his own AI-driven translation app without touching an IDE. The conversation dives deep into why the tester's mindset—always looking for edge cases, failure points, and hidden assumptions—makes them uniquely qualified to master natural language prompting and lead the charge in the age of AI.

In this episode, we discuss:

• The Evolution of Performance Engineering: How the shift to cloud auto-scaling mistakenly led teams to skip performance testing—and the massive cloud bills that brought it back.
• Why Testers Excel at Vibe Coding: How natural language has become the new programming interface, and why a QA mindset is the secret weapon for building resilient AI applications.
• Deterministic vs. Non-Deterministic Testing: Giving AI agents "personas" (like a 35-year-old mother looking for a mattress) to uncover unpredictable user paths in e-commerce.
• Moving Downstream with Failure Analysis: How Testkube is leveraging customizable agents to sift through logs, detect true flakiness, and move toward human-in-the-loop self-healing repositories.

Whether you're a developer curious about how AI is speeding up code deployment or a tester looking to claim your AI superpowers, this episode offers a fascinating look into the future of cloud-native quality assurance.

Drawing from her extensive product management experience at Fidelity Investments and Workday, Sahana breaks down why companies burn millions of dollars and years of engineering time building custom Internal Developer Portals (IDPs) like Backstage. Instead of relying solely on generic frameworks, she advocates for implementing a "production readiness layer"—a critical bridge between writing code and shipping it confidently to live environments.

Ole and Sahana also dive deep into the realities of AI in modern software development. They discuss why AI-generated code still desperately requires human oversight, the current limitations of AI in generating deterministic tests, and the strategic value of integrating existing top-tier tools (like Testkube) to maintain high-quality standards without reinventing the wheel.

Key Takeaways:

• The Cost of DIY Platforms: Why building internal developer portals from scratch can cost companies up to $16 million with delayed ROI.
• Defining Production Readiness: How companies can create a "trust layer" to ensure code is fully tested, governed, and truly ready for deployment.
• Backstage vs. Purpose-Built Tools: A candid discussion on why generic plugin frameworks might not solve core quality and testing issues.
• AI's Role in Testing: Why human context, sentiment, and oversight remain crucial when navigating AI-generated code and test creation.

As cloud-native architectures grow more complex, the need to decouple services during development is critical. Yacine explains how Microcks serves as a "Swiss Army Knife" for developers, offering a single solution to mock and test REST, gRPC, GraphQL, and Event-Driven protocols (like Kafka and NATS). They discuss the tool's evolution from a centralized Kubernetes operator to a developer-friendly utility that runs natively in IDEs and pipelines, enabling true "shift left" testing.

Later in the conversation, they explore the intersection of API testing and Artificial Intelligence. Yacine details how Microcks is embracing the AI era by using Copilots to generate mock data and leveraging the Model Context Protocol (MCP) to make existing APIs accessible to LLMs.

Key Topics Discussed:

• The CNCF Journey: Microcks’ status as a community-driven Sandbox project.
• Polyglot Support: Mocking REST, GraphQL, gRPC, and AsyncAPI with one tool.
• The Testing Lifecycle: How to reuse mock data artifacts for automated contract and conformance testing in CI/CD.
• Shift Left: Moving testing from QA environments to local developer laptops and IDEs.
• AI & MCP: Generating datasets with AI and exposing APIs as tools for AI Agents using the Model Context Protocol.

The conversation also digs into the mechanics of building AI-driven software, emphasizing why "evals" are critical for measuring success. Richard shares practical strategies for treating evaluations as data management problems and explains how his team uses simple AI agents to "babysit" CI pipelines and automatically resolve flaky tests.

Topics discussed:

• The Evolution of Telepresence: Moving from local debugging to headless execution in CI pipelines.
• Tests as Context: Why running a test suite is more effective than complex prompting for AI agents.
• Agentic Coding Strategy: Shifting focus from unit tests to integration and behavioral verification.
• AI Evals: Why evaluation is the most critical aspect of building reliable AI products.
• Babysitting CI: Using simple AI agents to identify and retry flaky tests automatically.

The conversation dives deep into their cloud-native testing strategy. Matt explains how integrating Playwright for end-to-end tests created automated quality gates, giving them confidence with every deployment. He also shares their approach to non-functional testing with k6 to ensure their application can handle high-traffic events. A key highlight is their use of Tilt to spin up ephemeral environments for every pull request, enabling developers and QA to test features in isolation early in the process. This episode is a practical guide for anyone looking to build a robust testing culture supported by a modern CI/CD pipeline.

In this episode, Ole is joined by Yasmine, COO of CloudBolt, to explore the complex world of Kubernetes rightsizing. Drawing from her experience at Stormforge, Yasmine unpacks the evolution from using performance testing to generate optimization data to the sophisticated machine learning models used today. This conversation goes beyond the tools to address the core challenges every organization faces when trying to tame its cloud-native environment.

Tune in to learn:

• The People Problem: Why there's natural friction between platform teams and developers on resource management, and how to bridge that gap.
• Reliability First: The crucial mindset shift of viewing rightsizing as a tool for reliability and performance, with cost savings as the byproduct.
• The Scale Challenge: Why manual scripts and "setting an average" are bound to fail when managing thousands of dynamic workloads.
• Testing for Confidence: How robust performance and functional testing can validate automated resource changes and give teams the confidence to deploy them.

The conversation kicks off with Atul sharing his unique career path, highlighting how starting in manual testing gave him a foundational understanding of system failure points—an invaluable edge in the world of development and cloud native technologies.

The core of the discussion explores the profound impact of AI on testing and development workflows. Atul points out a critical challenge: while AI can generate code at 10x the previous velocity, our CI/CD pipelines often become a bottleneck, as they weren't designed to handle such a high volume of pull requests. This leads to a crucial conversation about the need to not only scale testing efforts to ensure proper coverage for AI-generated code but also to scale the underlying CI/CD infrastructure itself. They also touch upon the significant software supply chain security concerns that arise when integrating AI agents into the development lifecycle.

Shifting focus to the broader ecosystem, the episode examines why testing often feels like an afterthought in the cloud native community, particularly at events like KubeCon. Atul argues that teams are often so focused on application functionality that they're "blinded" to the complexities of testing the entire infrastructure stack—from service meshes to container orchestration—until something breaks. The conversation also covers the nuanced practice of testing in production, balancing its benefits with the inherent risks.

Discover how Cloudflare embraces the often-debated, yet crucial, practice of testing in production to validate real-world performance. Learn how observability becomes their indispensable guide to understanding complex system behavior under immense load. We'll also discuss the power of automated monitoring in catching anomalies, the importance of collaborating with SLO teams within Cloudflare, and how continuous improvement is fueled by accurate metrics and data analysis gleaned from their unique testing environment. Whether you're a DevOps engineer, SRE, or simply curious about how an internet giant ensures its services stand strong, this episode offers actionable strategies and a fascinating look into Cloudflare's blueprint for resilience.

Benjamin shares how his journey from consulting to founding Steadybit was shaped by one key lesson: the best learning happens when systems fail. He explains how chaos engineering can shift from a manual, reactive effort to a repeatable practice that empowers teams to uncover weaknesses before they cause real-world outages.

They also dig into the cultural side of resilience engineering—how game days can bring teams together, why you don’t need massive scale to get started, and what it takes to build an organization where failure leads to progress, not blame.

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This podcast is proudly sponsored by Testkube, the cloud-native, vendor-agnostic test execution and orchestration platform that enables teams to run any type of test automation directly within their Kubernetes infrastructure. Learn more at www.testkube.io.

Tony shares the origin story of Swagger: from its roots in solving REST client generation to how it became a foundational tool for testing, documentation, and collaboration across teams. He explains how OpenAPI specs gave rise to a new generation of spec-driven testing, enabling everything from automated validation to smarter negative test cases.

Whether you're maintaining legacy services, scaling microservices, or figuring out how to test AI-powered workloads in distributed environments, Tony’s insights into API resilience, tooling, and testing culture are not to be missed.

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This podcast is proudly sponsored by Testkube, the cloud-native, vendor-agnostic test execution and orchestration platform built for modern infrastructure. Run any test, at any stage, from right inside your Kubernetes cluster.

Cherif shares how his team manages application testing across both cloud and on-prem environments, why manual and exploratory testing still play a crucial role, and how tools like Testkube, Terraform, and ArgoCD help automate quality at scale.

They also dig into the cultural side of QA: how to foster shared responsibility for testing across dev and QA teams and why testing in production doesn’t deserve its bad reputation.

If you’re working in a regulated space or looking to improve your cloud-native testing strategy, this conversation offers practical takeaways you can apply right away.

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This podcast is proudly sponsored by Testkube, the cloud-native, vendor-agnostic test execution and orchestration platform that enables teams to run any type of test automation directly within their Kubernetes infrastructure. Learn more at www.testkube.io

Joe shares real-world insights from his work helping teams bake governance into CI/CD pipelines without slowing down delivery. From debugging GitHub Actions to building a culture of shared responsibility, this episode is packed with practical advice on making governance feel less like red tape—and more like a safety net for scaling teams.

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This podcast is proudly sponsored by Testkube, the cloud-native, vendor-agnostic test execution and orchestration platform that enables teams to run any type of test automation directly within their Kubernetes infrastructure. Learn more at www.testkube.io

Daniel shares hard-won insights on testing in production, infrastructure validation, and why contract testing is essential when working with external dependencies. From technical best practices to organizational mindset shifts, this episode unpacks what it really takes to make testing a first-class citizen in the cloud-native world.

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This podcast is proudly sponsored by Testkube, the cloud-native, vendor-agnostic test execution and orchestration platform that enables teams to run any type of test automation directly within their Kubernetes infrastructure. Learn more at www.testkube.io

From infrastructure-level chaos testing to critical-path monitoring in production, Joe walks through the tooling, strategies, and cultural shifts that enabled UWM to test across multi-cloud, multi-cluster environments. They discuss why off-the-shelf tools often fall short, how internal platforms should be treated like products, and what it means to build resilience into both systems and teams.

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This podcast is proudly sponsored by Testkube, the cloud-native, vendor-agnostic test execution and orchestration platform that enables teams to run any type of test automation directly within their Kubernetes infrastructure. Learn more at www.testkube.io

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This podcast is proudly sponsored by Testkube, the cloud-native, vendor-agnostic test execution and orchestration platform that enables teams to run any type of test automation directly within their Kubernetes infrastructure. Learn more at www.testkube.io

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This podcast is proudly sponsored by Testkube, the cloud-native, vendor-agnostic test execution and orchestration platform that enables teams to run any type of test automation directly within their Kubernetes infrastructure. Learn more at www.testkube.io

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This podcast is proudly sponsored by Testkube, the cloud-native, vendor-agnostic test execution and orchestration platform that enables teams to run any type of test automation directly within their Kubernetes infrastructure. Learn more at www.testkube.io

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This podcast is proudly sponsored by Testkube, the cloud-native, vendor-agnostic test execution and orchestration platform that enables teams to run any type of test automation directly within their Kubernetes infrastructure. Learn more at www.testkube.io

We’ll explore the challenges of testing in cloud-native environments, the role of observability, automation, and emerging trends that are shaping the future of testing. Whether you're a tester, developer, or platform engineer, this podcast is for anyone looking to extend their testing strategies into today's cloud native world.

Thanks for listening!

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This podcast is sponsored by Testkube—the cloud-native testing framework that helps teams automate, orchestrate, and scale their testing workflows in Kubernetes environments. With Testkube, testing shifts left for faster feedback and scales right to meet the demands of modern, distributed systems. 

Learn more at testkube.io