%% date:: [[2023-11-01]] parent:: %% # [[2024 Conferences]] ## Conferences | | Date | Conference | Location | CFP Deadline | Status | | --- | -------------- | -------------------------------------------------------------------------------------- | -------------------- | ------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | ✅ | February 3-4 | [FOSDEM](https://fosdem.org/2024/) | Brussels, Belgium | N/A | Submitted, withdrawn [[system/cards/Emergent load testing - TestCon Europe 2023\|1]] | | ✅ | March 19-22 | [KubeCon EU](https://events.linuxfoundation.org/kubecon-cloudnativecon-europe/) | Paris, France | 26/11/2023 | ❌ Rejected [[Flirting with Risk - A playbook for continuous reliability\|1]] [[Trust but Verify - The SRE's Testing Toolkit\|2]] | | ✅ | March 22-23 | [PKM Summit](https://pkmsummit.com) | Utrecht, NL | N/A | ✅ [[system/cards/Doing it in public - observability for PKM\|1]] [[Roll for connections\|2]] | | ✅ | April 9-10 | [GrafanaCON 2024](https://grafana.com/about/events/grafanacon/2024/) | Amsterdam, NL | N/A (unconference, booth) | N/A | | ✅ | June 7-8 | [WeTest Athens](https://www.wetest-athens.gr/) | Athens, Greece | N/A (booth) | | | ✅ | June 12-14 | [Romanian Testing Conference](https://romaniatesting.ro/) | Cluj-Napoca, Romania | 30/11/2023 | ✅ Accepted [[Cartography of the Deep - distributed tracing for testing\|1]] | | ✅ | July 18-19 | [DevRelCon](https://nyc24.devrelcon.dev/) | New York, USA | N/A | To be confirmed with [[David Allen (DevRel)\|David]] | | ✅ | October 22-25 | [TestCon Europe](https://testcon.lt/) | Vilnius, Lithuania | N/A | ✅ Accepted >[[2024 Conferences#Flirting with Risk - A playbook for continuous reliability\|1]] [[2024 Conferences#Cartography of the Deep distributed tracing for testing\|2]] [[2024 Conferences#(Variant) Trust But Verify Observability for testers\|3]] | | ✅ | November 12-15 | [KubeCon US](https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/) | Utah, USA | 09/06/2024 | ✅ [Accepted](https://sessionize.com/app/speaker) [[2024 Conferences#The Telemetry of Togetherness observability tools for developer advocacy\|1]] >[[2024 Conferences#Watching the watchers How we do continuous reliability at Grafana Labs\|2]] | | 🎯 | November 19-22 | [Agile Testing Days](https://agiletestingdays.com/) | Potsdam, Germany | 11/02/2024 | ✅ Accepted >[[2024 Conferences#Flirting with Risk - A playbook for continuous reliability\|1]] [[2024 Conferences#Learning in public - How to learn stuff you have no business learning\|2]] | %% ## Ideas - Play in reliability - ~~Six Performance Testing Hats~~ - Testing as Flirtation (with [[Steve Upton]]) - Testing and Observability: Continuous Reliability - Learning in Public - ~~Burnout and Overwork~~ - How we do continuous reliability at Grafana Labs: 1M concurrent virtual users, [Mimir to 1 billion active time series](https://grafana.com/blog/2022/04/08/how-we-scaled-our-new-prometheus-tsdb-grafana-mimir-to-1-billion-active-series/) - distributed tracing (k6 + Tempo + Grafana) %% ## Talks ### [[Flirting with Risk - A playbook for continuous reliability]] Submitted to: [[KubeCon Europe 2024]] (rejected), [[Agile Testing Days 2024]] (accepted), [[TestCon Europe 2024]] (accepted)  #### Abstract (1000 character max) We often follow a script when we test for reliability: a series of steps with a binary outcome. Either the SLO is met (a pass), or it is exceeded (a fail). On its own, this type of verification is insufficient when testing real systems. Instead, we need a more dynamic approach that allows for a larger range of outcomes. Flirtation is more than just following a script. Flirtation is a conversation, a probing of the integrity of the rules of the game while playing it. When we flirt, we are observant, responsive, and open to possibilities. Good flirtation, like good testing, requires walking the line between safety and risk, ease and tension, consent and ambiguity. In this talk we discuss how practices like chaos engineering, fault injection, fuzzing, and observability help us explore the limits of a system and adapt to its responses. These alternative approaches, combined with the inherent playfulness of flirtation, improve the continuous reliability of complex, dynamic systems. #### Benefits to the Ecosystem (1000 character max) We all want our systems to be able to withstand real-world scenarios, but building confidence in their ability to do so is not straightforward. Software testing has a bad reputation of being insufficiently dynamic or realistic, and as a result is often overlooked in favour of observability. Insufficient testing, and the belief that testing and observability are at odds with each other, is a major risk to reliability and resilience. In this talk, we want to challenge people's assumptions of what testing looks like and update the testing playbook with new approaches that are more suited for modern, distributed systems. Our goal is for attendees to walk away with concrete test scenarios and observability best practices that they can use to improve system reliability. ### The Telemetry of Togetherness: observability tools for developer advocacy #### Abstract Our observability platforms are crucial for maintaining the health of applications and infrastructure every day. But what about the human components around the projects we contribute to? In this talk, we'll walk you through a real example of how we gain new insights into the impact of our initiatives on our community by tracking: - metrics such as engagement rates, event attendance, and contribution levels - detailed logs from community events like webinars and hackathons - tracing sequences of community interactions - continuous profiles of local champions We’ll share how we created a solution using OpenTelemetry, Loki, Grafana, Tempo, Mimir, and Pyroscope to apply observability techniques to our community initiatives. By treating our community engagement like our application infrastructure, we’ve been able to gather and analyze data to enhance our impact and improve our developer relations. Community observability, after all, is no less important than application observability. #### Benefits to the Ecosystem There's a lot of discussion about the observability of the systems and the applications we build, but almost nothing about the communities around them. Yet communities can make or break open source projects. How do we make sure our communities are not just productive, but inclusive? Open-source communities in particular often have to strike the balance between encouraging contributions and making projects commercially viable so that they're sustainable. Community observability is a key way to constantly measure progress towards those goals. In this talk, we want to provide the audience with actionable, practical, and open-source ways to address this glaring lack in most observability stacks. ### Watching the watchers: How we do continuous reliability at Grafana Labs #### Abstract (1000 characters) Nothing is foolproof. Everything fails eventually. Observability tools help predict and lessen the impact of those failures, as the watchers of your software systems. But who watches the watchers? At Grafana Labs, we're not immune to production incidents. Just like any company, we still sometimes move too quickly. We run complex, microservices-based systems ourselves, so we have to eat our own dogfood on a daily basis. In this talk, I reveal: - how we solved a years-long mystery that cost us $100,000+ - how we got our internal Mimir clusters to reliably hold 1.3 billion time series for metrics - what we've had to do to scale our Loki clusters to handle 324 TB of logs a day - what our Grafana dashboards to monitor Grafana Cloud look like Sometimes, it's easier to learn from failures in observability than from successes. This talk is a confession of some of our worst sins as well as a realistic look under the hood at how we're improving the continuous reliability of our stack. #### Benefits to the ecosystem Grafana Labs is known as a pioneer in the observability space, and we create and maintain many open-source projects to keep systems reliable: Grafana, Loki, Tempo, Mimir, Prometheus, Pyroscope, k6, OnCall, Alloy, and more. But this talk isn't about our successes: it's about our failures. Instead of talking about observability best practices, I want to talk about mistakes that are so common that even we have made them-- and I want to talk about how others can avoid them. What are the things that can fall through the cracks even when you already have safety nets in place and more monitoring than you could ever dream of? What happens when you're not watching the right things? How do you account for the human factor in observability? In this talk, I intend to expose some internal processes with the goal of promoting transparency, open knowledge sharing, and meaningful discussionsi about what it REALLY means for a company and a team to be observable. ### The psychology of impatience #### Abstract ### Trust But Verify: The SRE's Testing Toolkit - testing for SREs: ways that SREs could incorporate testing into their jobs (contract testing, xk6-kubernetes, xk6-disruptor, xk6-operator, Faro, RUM, testcontainers?), why observability needs testing, field data vs lab data #### Abstract (1000 character max) Observability tools give us the data we need to understand how a system behaves under different circumstances. Understanding the limits and thresholds helps us *trust* that a system works the way we want it to. But is trusting really enough? Software testing helps us question our assumptions and the integrity of the data we're basing them on. It provides a framework of ritual dissent and systematic doubt that we can use to strengthen our confidence in our observations. In this talk, we show how we can use testing to verify our observations and go beyond collecting data. We demonstrate how to use open-source projects like Grafana, k6, Faro, Testcontainers, Keda, and others that should be part of every SRE's testing toolkit. Having a tester's mindset of experimentation and curiosity can help us make a system more reliable-- and ultimately, testing can verify whether our trust is misplaced. #### (Variant) Trust But Verify: Observability for testers - observability for testers: ways that testers could incorporate observability into their jobs, why observability needs testing, field data vs lab data ##### Abstract (1000 character max) Testing gives us the data we need to understand how a system behaves under expected circumstances. Systematically exposing the system to a barrage of test scenarios helps us *trust* that a system works the way we want it to. But is trusting really enough? Observability helps us question our assumptions and the integrity of the data we're basing them on. It provides a framework of ritual dissent and systematic doubt that we can use to strengthen our confidence in our experiments. In this talk, Nicole van der Hoeven shows how we can use observability to verify our test results and supplement lab data with field data. She demonstrates why the practices of DevOps and testing aren't really as far apart as we might think, and how making an application observable should be an essential part of every tester's toolkit. Observability can help us make a system more reliable by exposing its real outputs-- and ultimately, observability can verify whether our trust is misplaced. ### [[Cartography of the Deep - distributed tracing for testing]] #### Abstract (300 word max) 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. #### Key takeaways - Black-box testing can be useful, but we can provide more value with our testing by making our tests observable. - OpenTelemetry is a set of tools that standardize the observability of our systems. - Distributed tracing isn't just for SREs; load testers can use it to be able to follow the path of a request throughout the system. - We can use projects like k6 + Tempo + Grafana to improve the continuous reliability and performance of our systems. ### [[Learning in public - How to learn stuff you have no business learning]] Submitted to: [[Agile Testing Days 2024]] #### Abstract One of the hardest things about working in tech is the constant pace that we need to keep up with to remain useful. This is particularly true for testers: there's always some new tool, technology, or framework that we need to learn to be effective at our jobs. Now, we _could_ just react to every new project and learn from scratch... but that's not the most efficient or sustainable way to do it. What we need is a system for learning that grows with us and helps us make connections between projects while creating a visible portfolio of demonstrable knowledge. What we need is to learn in public. Learning in public is a fundamental subversion of how most of us learn to learn. Instead of waiting until the end to show off the resulting work, learning in public shows the process of creating it. This means we can make mistakes freely, learn faster than ever with feedback from others, learn the right things, and really enjoy the process rather than rushing to the finish line. In this talk, you'll learn practical tips and public examples of how to learn everything from Kubernetes to chaos engineering to speaking Dutch, how to create your own personal wiki that establishes you as a thought leader in any field, and how to get so good they can't ignore you--all by learning in public.  ## Speaker bio ### Tech #### <500 characters Nicole is a Senior Developer Advocate at Grafana Labs and a performance engineer with over a decade of experience in breaking software and learning to build it back up again. She has lived in the Philippines, the US, Australia, the Netherlands, and Portugal, helping teams all over the world improve the reliability of their systems. She plays tabletop roleplaying games three times a week, makes videos on YouTube about taking notes, and studies more languages than she can remember. ### PKM Nicole makes YouTube videos about PKM and learning. She's made a beginner course about Obsidian called Obsidian for Everyone, has a newsletter called *Thinking in Public*, and is currently writing a book called *Doing It in Public*... which, of course, she's writing in public. She thinks learning in public is the most authentic, rewarding, and efficient way to learn. In her day job, she is a Senior Developer Advocate at Grafana Labs with over a decade of experience in performance engineering: the science of making software systems faster, more resilient, and more productive. Nicole has lived in five countries, speaks several languages, plays tabletop roleplaying games three times a week, and dreams about open-sourcing all the things. ## Interesting facts I have lived in five countries across four continents, and I hold three citizenships. I speak 9 languages to varying levels of proficiency. ## Additional Resources ### Socials LinkedIn: https://www.linkedin.com/in/nvanderhoeven/ Mastodon: https://pkm.social/@nicole Site: https://nicolevanderhoeven.com YouTube: https://youtube.com/@nicolevdh ### Presentation Recordings - Emergent Load Testing: Rules for Organized Chaos (KubeCon EU 2023, Amsterdam): https://www.youtube.com/watch?v=Og4-Z6j_0M0 - Load testing and distributed tracing with k6 and Tempo (ObservabilityCON On the Road 2023, Sydney, Australia): https://www.youtube.com/watch?v=ZP2aa5qjNOg - Grafana Office Hours on YouTube: https://www.youtube.com/playlist?list=PLDGkOdUX1Ujrrse-cdj20RRah9hyHdxBu - Nicole van der Hoeven on YouTube: https://www.youtube.com/@nicolevdh - List of speaking engagements on personal website, along with videos: https://nicolevanderhoeven.com/speaking/ ## Talks to recycle? - [[system/cards/Emergent load testing - TestCon Europe 2023|Emergent load testing - TestCon Europe 2023]] - [[system/cards/The Lost Art of Taking Good Notes|The Lost Art of Taking Good Notes]] -