K6 on Nicole van der Hoeven

Asimov

Wed, 02 Apr 2025 00:00:00 +0000

Asimov is the companion project to my talk Asimov’s Zeroth Law of Robotics. It’s an AI app built to be observed and tested: The Silent Enterprise, a single-player Star Trek text adventure. You play Data, and Claude is the game master. Every model call, dice roll, and turn shows up as telemetry in a Grafana that you can run on your own machine or in Grafana Cloud, and a k6 test suite, some of it judged by Claude, checks whether the AI follows the rules.

The game master has some known flaws, kept on purpose. It sometimes narrates a rescue that didn’t happen, or “destroys” a drone that’s still standing. The point of the demo is catching those flaws with telemetry, tests, and online evaluators.

The idea

Isaac Asimov’s three Laws of Robotics govern how robots behave. The talk argues for a law that comes before all of them: a robot must be observable, and, in its newest version, testable. AI systems fail differently from traditional software. There’s no single correct output to assert against, a response can be fluent and completely wrong, and models drift. You can’t test what you can’t see, and you can’t trust what you can’t test.

What’s in it

The game. A Go program with a command-line interface and an HTTP API. The game engine owns the rules and the state. Claude interprets the player’s input, makes the game master’s own rolls through a tool, and narrates, so a narration that contradicts the saved state is a defect that can be caught.
Telemetry. Traces, metrics, and logs go over OpenTelemetry to a local Grafana stack (Tempo, Prometheus, and Loki, with the game’s dashboard already loaded) or to Grafana Cloud. Generations can also go to Grafana Cloud’s Agent Observability, where online evaluators judge a sample of them.
Tests. A k6 suite with code checks, LLM judges, dice-trajectory evals, and whole playthroughs. All of it can run for free against a mock game master and judge.
No account needed to start. You can play offline with no API key, and see the local monitoring stack with one command and Docker.

The screenshot above is the game’s local Grafana dashboard.

The talks

I’ve given the talk, in several versions, at KubeCon Europe 2025, Dutch Cloud Native Day 2025, Newcrafts 2025, ExpoQA Madrid 2026, and HUSTEF 2026. The write-ups are linked below. The earlier talks used a Python and Flask version of the app, which has since been rewritten in Go.

Try it

The repository has a quick start for playing offline, a Docker-only path, and release binaries for Windows, macOS, and Linux.

Asimov's Zeroth Law of Robotics: Testing for AI (HUSTEF 2026)

Wed, 07 Oct 2026 10:00:00 +0200

This week I gave a keynote at HUSTEF 2026 in Budapest, Hungary. The talk is called Asimov’s Zeroth Law of Robotics: Testing for AI — a testing-focused evolution of a talk I’ve been giving (and rewriting) for a while, previously as Observability for AI at KubeCon EU 2025 in London, Dutch Cloud Native Day 2025 in Utrecht, NewCrafts in Paris, and ExpoQA Madrid 2026. Here’s the abstract:

A robot may not harm humans. A robot must obey humans. A robot must protect its own existence. These are Isaac Asimov’s three Laws of Robotics, created to govern the ethical programming of artificial intelligences. From the Butlerian Jihad to Skynet to cylons, we’ve been immortalizing our collective nightmares about artificial intelligence for years. But there’s an unmentioned law that comes as a prerequisite to all of that: a robot must be testable.

AI systems fail differently than traditional software. There’s no single correct output to assert against. A response can be fluent and completely wrong. Models drift silently over time. And yet we’re shipping AI into production — often without knowing what “passing” even looks like.

Observability is what makes testing possible. When we can see inside our AI systems — trace the chain of reasoning, measure what changed, surface what failed — we can start to write evaluations, define what “good” looks like, and catch regressions we didn’t know to look for.

In this talk, I explore what it means to test AI in the real world, drawing on lessons from building and evaluating an AI assistant for a large-scale observability platform. I’ll cover how evaluations work as the AI equivalent of a test suite, what to measure, how to catch hallucinations, and how to know when your model has regressed.

You cannot test what you cannot see — and you cannot trust what you cannot test.

The big shift in this version is right there in the Zeroth Law itself. In earlier iterations I argued that a robot must be observable. That’s still true — observability is the only way to see the reasoning behind a system and find out what actually happened. But I’ve come to think that pure knowledge isn’t the same as trust. You can know exactly what a system did and still not trust it. The only way to trust something is to put it through its paces: to know how it behaves in the situations you foresee, and even the ones you don’t. So the Zeroth Law has become a robot must be testable.

I framed the whole thing around Asimov’s short story Runaround (from I, Robot) and its robot, Speedy. Speedy’s smuggler owners sent him to collect selenium on Mercury, and he got stuck in a loop — circling the selenium pool, unable to resolve the conflict between obedience (the second law) and self-preservation (the third). His owners couldn’t predict his behaviour and couldn’t reason about it, so they had to do the only thing left: go out into the danger zone and fix him in production. Speedy wasn’t untestable because his owners were incompetent or lacked the tools — he was untestable because he was never built to be tested. That’s the trap I think a lot of AI systems are walking into right now.

The through-line for a testing audience: AI is rewriting how software gets built, but it doesn’t rewrite the discipline of trust. Trust that a system does what we say it does, and that when it breaks we know why and can fix it — that’s always been the job, and it isn’t going anywhere. There’s a whole generation of AI engineers shipping software they haven’t tested and can’t explain, and when someone says “the agent does this,” our job is still to ask how do you know? Testing isn’t just going to survive the age of AI — testing is the reason AI gets to survive, if we make it testable.

I demoed this with my TTRPG side project: an AI Dungeon Master, instrumented and put under test. It turns out that writing evals for something non-deterministic forces you to confront your real requirements. I thought I knew exactly when a dungeon master should call for a dice roll — I GM myself! — but trying to put it into words (“in this situation I’d roll, but in that one I wouldn’t, because I want to keep the story moving”) surfaced decisions I’d never had to make explicit. Those are things we’d normally discover much later, in production. Having to figure them out up front is a win.

The Q&A was genuinely great and ranged well beyond the slides:

“When has an AI been tested enough?” Same answer as for anything else — it’s a mix of risk and budget. If it were a life-critical robot like Speedy, you test every scenario the people relying on it need. For my little demo app, less so.
Testers vs. developers in the age of AI. I said I’d fire developers before testers — provocatively, but the point stands: anyone can write code now. What made a good developer good was never the coding; it was communicating with business and engineers, translating requirements, finding creative-but-safe solutions. Testers already think at that level and translate across teams, which makes them more important in the age of AI, not less.
Defining expected results for non-deterministic systems, multi-turn evals (I give the simulated user a personality — adversarial, cooperative, beginner — rather than a script), and the broader shift from imperative to declarative: we no longer instruct step by step, we declare the end state we want, the way we do with Kubernetes.
Convincing colleagues not to fear AI. I don’t, really. AI is here to stay; the question isn’t whether you approve of it, it’s whether you want to stay in this industry and help make it safe and trustworthy — or sit on the sidelines.

I also recommended the book Slow AI, which lands where I do: not an AI apologist, not a boycott, but a clear-eyed list of what AI is and isn’t good for — and the reminder to keep checking whether a given use of AI is making you more capable or less.

The demo app (the instrumented AI DM) lives on GitHub, and I keep refining it with each iteration of this talk.

I’ll update this post with the recording once HUSTEF publishes it.

Resources

Slides
Demo app on GitHub
Slow AI (book)
Previous versions of this talk: KubeCon EU 2025 · Dutch Cloud Native Day 2025 · NewCrafts 2025 · ExpoQA Madrid 2026

AI Week Day 4: Evaluating (Grafana AI Week — Thursday)

Thu, 30 Jul 2026 09:00:00 +0100

Day four of AI Week is all about evaluating — because building an agent is the easy part; trusting it is where things get hard. The headline: Grafana Agent Observability is now generally available — the tool Grafana built for itself while scaling Assistant, once it grew too complex to evaluate with unit tests. Instrument your agent with the SDK and your conversations, tool calls, traces, latency, token use, and cost all become observable in one place; add evaluators (LLM judges plus deterministic checks) to score quality on live traffic, feed low-scoring conversations into your test suite, and gate CI on experiments comparing a candidate against a baseline. And because evaluator metrics land in Prometheus, you can get paged when a bad prompt change tanks quality. The fun bonus: k6 agentic testing — describe a browser test in plain language and an agent embedded in k6 drives the browser, no script required (they proved it by getting it to beat Wordle).

Transcript

It’s day four of Grafana Labs’ AI Week, and Thursday is all about evaluating — because building an agent is the easy part. Trusting it is where things get hard.

The big news: Grafana Agent Observability is now generally available. This is the tool we built for ourselves while scaling Grafana Assistant, when it grew too complex to evaluate with unit tests. Now it’s available to everyone on Grafana Cloud.

Here’s how it works: instrument your agent with the SDK, and your conversations, tool calls, traces, latency, token use, and cost all become observable in one place. Then add evaluators — LLM judges plus deterministic checks — to score quality on live traffic. Low-scoring conversations feed your test suite, and experiments let you compare a candidate against a baseline before you ship — you can even make it a CI gate. And because evaluator metrics land in Prometheus, you can get paged if a bad prompt change tanks quality in production.

But my favorite part of today? k6 agentic testing. Describe a browser test in plain natural language, and an agent embedded in k6 drives the browser for you — no script at all. And to prove it, we gave it one job: beat Wordle. Go watch that video. I’ll wait.

Everything’s at grafana.ai — see you tomorrow for the finale: using AI where your team already works.

Asimov's Zeroth Law of Robotics: Observability for AI (ExpoQA Madrid 2026)

Tue, 26 May 2026 10:00:00 +0200

This week I gave the opening keynote at ExpoQA Madrid 2026 in Madrid, Spain. I presented a talk called Asimov’s Zeroth Law of Robotics: Observability for AI, which I had previously given at KubeCon EU 2025 in London, at Dutch Cloud Native Day 2025 in Utrecht, and at Newcrafts in Paris. Here’s the abstract:

A robot may not harm humans. A robot must obey humans. A robot must protect its own existence. These are Isaac Asimov’s three Laws of Robotics, created to govern the ethical programming of artificial intelligences. From the Butlerian Jihad to Skynet to cylons, we’ve been immortalizing our collective nightmares about artificial intelligence for years. But there’s an unmentioned law that comes as a prerequisite to all of that: a robot must be observable.

In this talk, I discuss the different types of AI, the factors that make observing AI different from observing applications, and the telemetry signals specific to AI that we might want to listen to. How do we deal with large data sets? How do we observe for model drift? How do we take into account the costs of LLMs? How can we use distributed tracing to follow event sequences? Part cautionary tale and part technical demo, this talk shows how to instrument and monitor AI apps using OpenTelemetry, Prometheus, OpenLit, and more.

This was a keynote slot at a testing-focused audience, which gave me the chance to lean more into the evals vs. observability framing — what evals can and can’t tell you about an AI system in production, and how distributed tracing fills the gap that benchmarks leave behind. The demo app (a Flask-based “play.py” instrumented with OpenTelemetry, flowing into Tempo for traces, Prometheus for metrics, and Loki for logs) is still on GitHub, and I’ve been refining it with each iteration.

Here’s the recording of the talk:

Resources

Demo app on GitHub

Grafana k6 Community Call — Secrets Management & AI Script Authoring

Thu, 30 Apr 2026 16:30:00 +0100

The first k6 Community Call in over a year, and we packed it. I sat down with four of the people building k6 — Bukola Ayodele, Facundo Batista (Software Engineer), Vicente Ortega (Senior Backend Engineer), and Charlie Burnett (Product Manager) — to walk through two new pieces of work that have shipped recently, plus a look at what’s coming in k6 v2.

What we covered

🔐 Secrets management in k6 Cloud (Facundo)

A new way to store API tokens, passwords, and other sensitive values for your tests — centralized in Grafana’s secrets manager, encrypted at rest, and never visible in the UI or API once written. Your scripts reference secrets by name, and at runtime the values are injected and automatically redacted from logs.

Why this matters for load testers:

No more hardcoded credentials sitting in scripts or in Git
Easy rotation — change the secret value, every script that uses it picks up the new value, no script edits needed
Same script works across dev/staging/prod by just swapping which secrets are scoped to which environment
Works with k6 OSS locally too — your local runs can pull cloud-managed secrets when you want them

Facundo Batista demoed the full flow: creating a secret in the Grafana Cloud UI (name, description, labels — up to 10 per secret, all write-only), and using it in a script with one line. There’s also an API for programmatic management.

🤖 Grafana Assistant k6 script authoring mode (Vicente)

This is the AI-powered script generation that’s been in the works for a while — fine-tuned specifically for k6 best practices, not a generic “ask an LLM to write you a load test” workflow. The interesting bit is the context sources Assistant can pull from when generating a script:

A service name — Assistant analyzes the existing telemetry data to discover endpoints and shapes
A GitHub repository URL — pulls the code to understand the API
An OpenAPI specification — generates tests that exercise every endpoint with realistic request shapes
Existing observability data — metrics, logs, traces from your actual production traffic

Generated scripts come with proper structure, error handling, checks, and TODO comments where the model genuinely doesn’t know what to write (e.g. for auth tokens, request bodies, or anything that needs your secrets — by design, Assistant won’t fabricate those). You can also point it at an existing script and ask it to refactor or extend.

🚀 k6 v2 (Charlie)

Release candidate 1 is out, GA is very soon. The headline changes:

Extensions marketplace — community protocols and integrations
Enhanced Playwright browser support with compatible syntax
New assertions library
MCP / agent connectivity for AI-driven workflows
DNS, MQTT, and other network protocols

Migration advice from Charlie Burnett: pin your script versions, test your existing scripts against the RC before GA hits, and don’t rush.

🔮 What’s next on the AI roadmap (next 1–2 months)

Visual browser-based testing experience
Enhanced observability workflow automation
Improved user-journey creation across both personal and enterprise apps
Integration with autonomous monitoring systems

Resources

Thanks to Bukola, Facundo, Vicente, and Charlie for joining, and to everyone who showed up live.

Asimov's Zeroth Law of Robotics: Observability for AI (Newcrafts 2025)

Thu, 06 Nov 2025 12:23:19 +0100

Today I presented at Newcrafts in Paris, France. I gave a talk I’ve given before, called Asimov’s Zeroth Law of Robotics: Observability for AI, which I had previously presented at KubeCon EU in London and at Dutch Cloud Native Day 2025 in Utrecht. I was happy to present it again, as it gave me the chance to further refine my demo application, which you can find on GitHub.

The main change I made was to use the “AI as judge” approach that I had previously only talked about in theory. In this version of the demo app, I use AI in both the game as well as in the testing of the game, showing how AI can be integrated into both the application and its observability/testing stack. It was really interesting to note that testing with AI ended up exposing more defects than my hardcoded test cases did, which goes to show the potential of AI-driven testing.

Asimov's Zeroth Law of Robotics (Dutch Cloud Native Day 2025)

Thu, 03 Jul 2025 15:01:24 +0200

Today I presented at the Dutch Cloud Native Day 2025 in Utrecht, the Netherlands. I gave a talk titled Asimov’s Zeroth Law of Robotics: Observability for AI, which I had previously presented at KubeCon EU earlier on in the year, in London. I was very happy to be able to present it again, because it gave me the opportunity to improve the demo app I used, which you can find on GitHub.

Asimov's Zeroth Law of Robotics: Observability for AI (KubeCon EU 2025)

Wed, 02 Apr 2025 13:46:42 +0200

Today I gave a talk at KubeCon EU 2025 in London called “Asmiov’s Zeroth Law of Robotics: Observability for AI”. Here’s the abstract:

A robot may not harm humans. A robot must obey humans. A robot must protect its own existence. These are Isaac Asimov’s three Laws of Robotics, created to govern the ethical programming of artificial intelligences. From the Butlerian Jihad to Skynet to cylons, we’ve been immortalizing our collective nightmares about artificial intelligence for years. But there’s an unmentioned law that comes as a prerequisite to all of that: a robot must be observable.

In this talk, I discuss the different types of AI, the factors that make observing AI different from observing applications, and the telemetry signals specific to AI that we might want to listen to. How do we deal with large data sets? How do we observe for model drift? How do we take into account the costs of LLMs? How can we use distributed tracing to follow event sequences? Part cautionary tale and part technical demo, this talk shows how to instrument and monitor AI apps using OpenTelemetry, Prometheus, OpenLit, and more.

Cartography of the Deep: Distributed Tracing for Testing (Romanian Testing Conference)

Thu, 13 Jun 2024 12:24:02 -0700

I presented a talk today at the Romanian Testing Conference 2024 in Cluj-Napoca, Romania! My talk was called “Cartography of the Deep: Distributed Tracing for Testing” and it covered how to tie in distributed tracing into tests to get a better understanding of your system under test.

Here are my slides!

Abstract

From the Scandinavian Kraken that drags entire ships to their early graves to the Philippine Bakunawa said to rise from the waters to swallow the moon, our existential fears about what lurks at the bottom of our own oceans has inspired us to create hundreds of folkloric monsters across cultures. We’ve charted the surface of our planet, but the vast majority of the ocean floor remains a mystery.

The mysterious depths of modern software architectures makes it difficult for us to test a system for performance and reliability. The easy solution? Unmanned underwater probes: send inputs to the system, and judge its state based on the outputs that return. But this method is often too limited to tell us what’s really going on when something goes wrong. What if there were a way to make our tests themselves more observable?

In this talk, you will learn how to use open-source tools to instrument performance tests, identify bottlenecks at the code level using distributed tracing, and map out a system using a type of software bathymetry. You’ll also learn about the Mariana Trench expeditions, the difficulties of operating in a high-pressure underwater environment, and how to come face to face with monsters of our mythologies.

Entendiendo los sintéticos (Café con Grafana #008)

Thu, 11 Jan 2024 16:00:25 +0100

En este episodio de Café con Grafana les traemos a Marcelo Magallón, experto en monitoreo sintético, quien viene precisamente a contarnos que es en sí un sintético. Él nos va a mostrar algunos ejemplos, casos de uso y mucha mas diversión!

Lee la documentación sobre el monitoreo de sintéticos en Grafana Cloud aquí.

Repasemos el G-stack (Café con Grafana #005)

Thu, 30 Nov 2023 13:57:52 +0100

En este episodio de Café con Grafana tenemos a Raul Marin, Solutions Engineer (Ingeniero de soluciones?) quien viene a darnos una repasada completisima de todo el stack de Grafana. TODO! Pues hay muchos que no conocen todas las herramientas, caracteristicas y posibilidades que Grafana Labs viene a ofrecer.

Dimensionando el Grafana Suite (Café con Grafana #004)

Thu, 23 Nov 2023 13:51:25 +0100

Almudena Vivanco viene a platicarnos de todos los experimentos y pruebas a las que someten a toda la suite de Grafana. Desde Mimir hasta k6 ella pone al limite todos los elementos constantemente. Además nos dará muchos tips de su experiencia para usar Grafana y mucho mas!

Realistic Tests with Testcontainers (Grafana Office Hours #20)

Fri, 17 Nov 2023 11:40:46 +0100

In this episode of Grafana Office Hours, we talk about realistic unit tests utilizing actual instances of databases and other dependencies. We’ll be joined by Manuel de la Peña from AtomicJar, and Pablo Chacin from Grafana to learn how we can use the Testcontainers open-source framework to create lightweight, throwaway dependencies for our tests.

Load Testing on Kubernetes with k6 Private Load Zones (Grafana Office Hours #19)

Fri, 10 Nov 2023 10:46:48 +0100

This week, we’re talking about how you can do load testing on Kubernetes with k6 Private Load Zones, a new feature on Grafana Cloud k6 that leverages the k6 Kubernetes operator to allow you to run distributed load tests against applications behind a firewall. Here to discuss this new feature are Senior Software Engineer Olha Yevtushenko, Product Manager Daniel González Lopes, Developer Advocate Paul Balogh, and Senior Developer Advocate Nicole van der Hoeven.

(ES) Cómo hacer pruebas de carga con Grafana k6 (Café con Grafana #003)

Wed, 08 Nov 2023 13:43:50 +0100

Daniel González Lopes nos viene a demostrar cómo hacer pruebas de carga con Grafana k6 desde zero, y cómo utilizar k6 para ejecutar otros tipos de pruebas. En este episodio para principiantes, hablaremos también sobre la relación entre pruebas y observabilidad.

Resources

Combining Frontend and Backend Performance With John Hill (Grafana Office Hours #18)

Fri, 03 Nov 2023 12:30:43 +0100

In this episode of Grafana Office Hours, my colleagues Marie Cruz, Paul Balogh, and I talk to John Hill, a Web UI Test Engineer and Grafana k6 champion, to talk about how the Grafana and k6 ecosystems can be used to ensure performance in mission-critical applications like NASA’s Open MCT.

Distributed tracing with Grafana Cloud k6 (Grafana Office Hours #14)

Sat, 07 Oct 2023 08:31:03 +0200

My friend Marie Cruz and I interview Senior Software Engineer Łukasz Gut about a new feature: Distributed Tracing with Grafana Cloud k6. He discusses what distributed tracing is, why it matters, and how it can help teams find reliability issues faster.

Celebrating 100 episodes of k6 Office Hours (k6 Office Hours #100)

Fri, 08 Sep 2023 20:56:43 +0200

In this 100th episode of k6 Office Hours, the Grafana Developer Advocates celebrate how it all started! Join us at this live fika with our favorite drinks and discuss our favorite moments and episodes.

Grafana k6 for WebSockets and infrastructure testing (Grafana Office Hours #11)

Fri, 08 Sep 2023 20:54:28 +0200

In this episode of Grafana Office Hours, Solution Architect Huzaifa Asif talks about how he has used Grafana k6 for WebSockets and infrastructure testing, and how k6 can be used for general reliability testing in addition to load testing. He is joined by Grafana Labs Developer Advocates Nicole van der Hoeven and Paul Balogh.

What's new in k6 browser? (k6 Office Hours #98)

Fri, 11 Aug 2023 20:37:25 +0200

k6 browser adds browser-level APIs to automate browser actions and collect web performance metrics as part of your k6 test. It’s an experimental module, and there is a good reason why!

In this k6 Office Hours, Developer Advocates Marie Cruz and Nicole van der Hoeven are joined by Software Engineers Ankur Agarwal and Daniel Jimenez to discuss the breaking changes that are about to come to k6 browser! You wouldn’t want to miss this.

Work week in the life of a Developer Advocate

Wed, 03 Nov 2021 00:31:46 +0000

Before I became a Developer Advocate, I didn’t really know what developer advocates did - so here’s my attempt at explaining what it is I do for a living!

Weekly breakdown

Here’s a list of my activities during this week:

Friday
- Filmed new ending for video #1
- Figured out integration options
- Did k6 Office Hours
- Prepared for Clubhouse talk
- Participated in customer demo
Saturday
- Did post-production for k6 Office Hours
- Talked at a Clubhouse meetup
Sunday
- Wrote (team profile) blog post #1
- Wrote talking points for Racket
- Started writing blog post #2
Monday
- Edited video #1
- Created thumbnail, description
- Scheduled video #1
Tuesday
- Created slides for presentation
- Played with Prometheus and Grafana for webinar
- Had a virtual coffee with colleagues
- Finished writing blog post #2
Wednesday
- Went to four meetings
- Caught up on emails, Slack, and social media (last night)
- Wrote blog post #3
Thursday
- Scripted and filmed videos #2 and #3
- Started editing video #2
- Talked to a potential guest on livestream

Performance Testing with k6 and Cypress (Ministry of Testing)

Tue, 23 Mar 2021 19:52:48 +0100

My friend Marie Drake and I teamed up to give a presentation about performance testing at a Ministry of Testing (Philippines) meetup, and we talked about using Cypress for front-end performance testing and k6 for back-end performance testing.

K6 on Nicole van der Hoeven

Asimov

The idea

What’s in it

The talks

Try it

Asimov's Zeroth Law of Robotics: Testing for AI (HUSTEF 2026)

Resources

AI Week Day 4: Evaluating (Grafana AI Week — Thursday)

Transcript

Asimov's Zeroth Law of Robotics: Observability for AI (ExpoQA Madrid 2026)

Resources

Grafana k6 Community Call — Secrets Management & AI Script Authoring

What we covered

🔐 Secrets management in k6 Cloud (Facundo)

🤖 Grafana Assistant k6 script authoring mode (Vicente)

🚀 k6 v2 (Charlie)

🔮 What’s next on the AI roadmap (next 1–2 months)

Resources

Related Context Horizon pieces

Asimov's Zeroth Law of Robotics: Observability for AI (Newcrafts 2025)

Asimov's Zeroth Law of Robotics (Dutch Cloud Native Day 2025)

Asimov's Zeroth Law of Robotics: Observability for AI (KubeCon EU 2025)

Cartography of the Deep: Distributed Tracing for Testing (Romanian Testing Conference)

Abstract

Entendiendo los sintéticos (Café con Grafana #008)

Repasemos el G-stack (Café con Grafana #005)

Dimensionando el Grafana Suite (Café con Grafana #004)

Realistic Tests with Testcontainers (Grafana Office Hours #20)

Related links

Load Testing on Kubernetes with k6 Private Load Zones (Grafana Office Hours #19)

Related links

(ES) Cómo hacer pruebas de carga con Grafana k6 (Café con Grafana #003)

Resources

Combining Frontend and Backend Performance With John Hill (Grafana Office Hours #18)

Distributed tracing with Grafana Cloud k6 (Grafana Office Hours #14)

Celebrating 100 episodes of k6 Office Hours (k6 Office Hours #100)

Grafana k6 for WebSockets and infrastructure testing (Grafana Office Hours #11)

What's new in k6 browser? (k6 Office Hours #98)

Work week in the life of a Developer Advocate

Weekly breakdown

Performance Testing with k6 and Cypress (Ministry of Testing)