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It all started around mid-November. I was looking for an open-source project to contribute to, but I didn’t want to join just anything. I had a few mental “metrics” to decide whether a community was a red flag or a green flag for me. When I found Meshery, almost all of those metrics turned green.
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I was looking for an inclusive community, having world-class engineers, who are active, have a strong culture and they are building some cool stuff having a large scale of impact.
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Meshery checked every single box for me. The community was engaging, very active, with some of the best engineers here. I remember when I joined their Slack workspace if I asked something, someone would reply almost instantly. I got even more excited by the enthusiasm and energy of each community member welcoming me in the newcomers channel.
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Choosing to contribute here has genuinely been one of the best decisions of my life.
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## Finding My Area of Impact
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When I joined, I wanted to learn things. So I started attending calls regularly. Slowly and gradually, I started contributing too, then delivering updates in the community calls, and consequently started climbing the contributor ladder.
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I still remember my first call with my mentor Lee Calcote and my friend Suhani. We were working on updating action versions in workflows. Later, we got into CI linting, and Lee called us to discuss it.
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That’s when I was introduced to pre-commit hooks using Husky. He suggested adding a pre-commit hook to Meshery so the code would lint automatically before commits.
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After some consistent contributions and regular participation in calls, Suhani and I both received a two-week Core Team trial consideration. There was some miscommunication from my side initially, so I wasn’t being called for it at first. When I asked Lee how I could best position my candidacy.
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He said:
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<Blockquote
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quote="Pick one area and burrow in like a tick inside of a water buffalo’s ear."
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person="Lee Calcote"
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title="Layer5 Founder"
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/>
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In simple words: Identify the single thing that you are the absolute best at, technical or non-technical, and create undeniable value there. It could be graphic design, project management, reviewing PRs, following up on action items, removing roadblocks, anything.
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That advice gave me direction.
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## Showing Up Before Being Asked
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I noticed that a few people were replying to newcomers in the Slack channel, helping resolve queries of others, and encouraging people. I thought I would do that too. I started replying to newcomers welcoming them, I also asked if I could help around hosting newcomer’s meet as well.
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Around that time, Ritesh was hosting the newcomers’ meeting, so I reached out to him. And some time later I started by co-hosting the newcomers’ meeting with Yash Sharma.
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## Key Takeaway
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1.**Think Like You Own the Community:** Before anyone asked me to, I started doing it, I showed up as if it’s my own community. That’s a mindset and behaviour I believe sets you apart from others and you grow very fast.
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If you have this mindset automatically these questions would come through your mind:
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- How could I improve this project?
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- How could I create more value?
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- How could I reduce friction for others?
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2.**Become a Mentor and a Mentee at the same time:** Even if you don’t know the answer to a question, you can still act like a leader as it’s a behaviour not a title. You can point someone to documentation or you can tag the right person that could help the person better. Reviewing PRs is another great way to learn and help.
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The idea is you encourage people, You call them to action, you learn with them along the way, that is something that I call Being a Mentor and a Mentee at the same time.
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<br/>
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Coming back to my journey, after co-hosting a few calls, Yash asked if I could host the second half from next week while he handled the first half. I was genuinely excited. Immediately after that call, he told me I did a great job, gave me some feedback, and handed over the full hosting to the meeting.
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3.**Continuing the cycle:** Here’s how I see it, first, you come in and learn how to do something well. Once you’ve mastered it, you share that knowledge and pass it on to others. Then you move on to a new challenge, but you stay involved as a mentor, keeping a watchful eye and stepping in whenever guidance or support is needed.
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<br/>
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You train others to do the same, and they go on to teach more people. The cycle continues. I also believe it’s a responsibility to share what I have learned. At the beginning of my journey, someone helped me climb the contributor ladder when I needed it. Now it’s my turn to do the same for someone else, and to teach them to carry that mindset forward.
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That’s how communities truly scale. That’s how leadership grows organically. Staying consistent with this mindset and behavior ultimately led me to becoming a Community Manager.
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## Completing the Internship Before It Officially Began
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One day on a call, Lee introduced a migration project, moving docs.meshery.io from Jekyll to Hugo.I started digging into how the system was structured and understanding Jekyll, static site generators, etc.
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Lee kept saying:
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“If someone knows Jekyll and Hugo inside out, this is a one-day job.”
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He pushed me to complete it and set clear deadlines. It took me a little longer than expected, and even now it’s around 95% complete. But in terms of the learning curve, I learned an incredible amount by practically applying everything along the way.
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I can confidently say that I almost completed my LFX internship project even before the internship officially began. That’s a personal achievement for me.
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## Build Systems That Are Resilient, Not Fragile
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Here’s a design lesson I learned from the migration. In Jekyll, each page had a manually defined permalink. It sounds good because URLs never change. But in reality, although it may sound counterintuitive, it makes the system fragile.
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Every time if we restructure content, we have to manually update those permalinks. In Hugo, URLs are derived automatically from the folder structure. That makes the system more resilient and relative instead of absolute and brittle.
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Lee explained this concept to me with an analogy of how engineers design tall buildings in earthquake-prone regions. They don’t make them rigid and stiff. They make them slightly flexible so they can absorb shocks. Resilience beats rigidity.
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**What is the common trait shared by all the people who have succeeded in this community and later became great examples for others to follow?**
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The people who have truly succeeded in this community shared two defining qualities: they were helpful and they were consistent. They genuinely wanted to create value, they stayed curious, and showed up with a mindset of learning rather than just getting an internship.
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At the same time, they committed to steady effort, showing up daily, attending meetings, taking ownership, and staying engaged even through the hardest moments. Over time, their consistency compounded setting them apart and turning them into strong examples for others to follow.
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I also want to acknowledge a piece of advice from my mentor:
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<Blockquote
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quote="Just start contributing and get the experience you want, don’t let an internship get in your way."
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person="Lee Calcote"
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title="Layer5 Founder"
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/>
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## Acknowledgements
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I’m extremely grateful to Lee and everyone in this community. Lee is someone who invests heavily in his mentees.
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He pushes you, challenges you, and expects more from you, always with the intention of helping you grow and he is one of the people who will go to lengths to help you succeed, if you are ready to give your all.
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## Conclusion
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If there’s a piece of advice I’d offer to anyone reading this, it would be simple: be helpful, be consistent, and take ownership of your work. Strive to be both a mentee and a mentor, and choose at least one area to dive deeply into and truly understand.
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Open source is not just about code, it’s about people, collaboration, and shared learning. Community always comes before code. I hope I was able to share insights from my journey that might support you and perhaps even inspire you to contribute to open source. If you’d like to connect, collaborate, or simply chat about open source or LFX, feel free to reach out to me on [GitHub](https://github.com/CodexRaunak/) or [LinkedIn](https://www.linkedin.com/in/madan-raunak/).
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## Resources
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-[Diátaxis Framework](https://diataxis.fr/#) - A systematic approach to technical documentation authoring.
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-[Migration Plan](https://docs.google.com/document/d/1hRnGOmEeLAoFjn36Ny9KdC60Ha1nIRRpL_roOcKX8rc/edit?tab=t.0) - For migrating [docs.meshery.io](https://docs.meshery.io) to Hugo
@@ -31,11 +30,7 @@ Ten years after standardizing Kubernetes, the Cloud Native Computing Foundation
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Announced on November 11 the Certified Kubernetes AI Conformance Program creates open, community-defined standards for running AI workloads on Kubernetes. Kubernetes providers in the program certify their products for various types of AI workloads.
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<BlockquoteAlt
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quote="It starts with a simple focus on the kind of things you really need to make AI workloads work well on Kubernetes, Such as Dynamic Resource Allocation (DRA) across GPUs, TPUs, and all of the different types of AI hardware."
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person="Chris Aniszczyk"
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title="CTO, CNCF"
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/>
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Chris Aniszczyk, CTO of CNCF, said it starts with a simple focus on the kind of things you really need to make AI workloads work well on Kubernetes, such as Dynamic Resource Allocation (DRA) across GPUs, TPUs, and all of the different types of AI hardware.
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CNCF membership is squarely in support, Anisczyck said. For example, “Google’s obviously interested in this because they offer their TPUs, and they saw the success of what happened with the original Kubernetes conformance program, which attracted a lot of people to the platform.”
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@@ -59,23 +54,15 @@ Everyone is familiar with the offerings of the large hyperscalers for cloud comp
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**Vultr** , for example, is competing with the major cloud provider by offering a wide array of hardware options for hosting AI workloads, including AMD and NVIDIA GPUs, virtual CPUs, bare metal, and Kubernetes.
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<BlockquoteAlt
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quote="Vultr is an AI infrastructure specialist, Our core platform is a public cloud platform. We’re the functional equivalent of a hyperscaler. We are an alternative to AWS, GCP, or Azure, with the same global reach."
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person="Kevin Cochrane"
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title="CMO, Vultr"
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/>
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Kevin Cochrane, CMO of Vultr, said Vultr is an AI infrastructure specialist, that their core platform is a public cloud platform, and that they’re the functional equivalent of a hyperscaler—an alternative to AWS, GCP, or Azure, with the same global reach.
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“We are also one of the first to start specializing in AI infrastructure, the first one taking GPUs from NVIDIA. And most recently, the first to market with AMD GPUs. So currently, we’re the only global platform that offers a choice between NVIDIA and AMD,” Cochrane added.
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**Mirantis**, on the other hand, offers a full software stack private cloud solution for smaller organizations running their own GPUs. Mirantis software builds and manages private GPU clouds for their customers, said Dom Wilde, General Manager, Core Products.
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Their customers “are trying to figure out how to deliver monetized services around GPU technology. It started with GPU as a service, where we are helping companies rent some GPU capacity that is notoriously hard to get ahold of,” Wilde said.
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<BlockquoteAlt
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quote="Private GPU deployments also support data and application sovereignty, which we recognize as an opportunity to be a little disruptive around the hyperscalers, We help these companies reduce time to monetization for their GPUs and offer them expertise that can be difficult to obtain."
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person="Dom Wilde"
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title="General Manager, Core Products"
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/>
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Dom Wilde, General Manager of Core Products at Mirantis, said private GPU deployments also support data and application sovereignty, which they recognize as an opportunity to be a little disruptive around the hyperscalers, and that they help companies reduce time to monetization for their GPUs and offer expertise that can be difficult to obtain.
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@@ -87,11 +74,7 @@ In their sponsored keynote, **Solo.io** compared AI agents to microservices, hig
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**Buoyant**, the company behind the LinkerD service mesh, agrees. They announced LinkerD for AI agents at the conference, saying their customers were asking for it.
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<Blockquote
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quote="The service mesh provides security and reliability in a uniform way across the platform. We are starting with MCP because the first thing that you want agents to do is to be able to access the existing resources. Let’s say you’re building an agentic workflow for automating a business process. You’ll benefit from the service mesh providing zero trust, so you exdecute the business process with confidence, We give you the same capabilities that LinkerD gives you for microservices. We know there’s more to do, but that’s the starting point."
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person="William Morgan"
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title="CEO, Buoyant"
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/>
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William Morgan, CEO of Buoyant, said the service mesh provides security and reliability in a uniform way across the platform. They are starting with MCP because the first thing you want agents to do is access existing resources—for example, in an agentic workflow for automating a business process, you benefit from the service mesh providing zero trust so you execute the business process with confidence, with the same capabilities LinkerD gives you for microservices, though there is more to do.
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Buoyant also announced the availability of LinkerD for .NET applications on Windows.
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ConfigHub provides a new paradigm for provisioning, deploying, and operating cloud applications and infrastructure, including but not limited to Kubernetes.
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<Blockquote
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quote="ConfigHub keeps the configuration clean and up to date, and then maps it into the running state to catch any drift at the same time, There’s actually a missing notion of a collective sense of truth for the configuration, which is what’s relevant to operations. So that’s what we are bringing together."
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person="Alexis Richardson"
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title="Founding Member of Technical Oversight Committe(TOC) and GitOps Creator"
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/>
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Alexis Richardson, founding member of the Technical Oversight Committee (TOC) and GitOps creator, said ConfigHub keeps the configuration clean and up to date and maps it into the running state to catch drift at the same time, and that there is a missing notion of a collective sense of truth for configuration that is what is relevant to operations—that is what they are bringing together.
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Similarly, Lee Calcote, CEO of Layer5, the company behind the CNCF Meshery project, announced their new product called Kanvas Designer, which provides an interactive, shared space for collaboration on configuration across an enterprise’s Kubernetes estate.
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A lot of the current projects and vendor product focus appears to be on “next level” capabilities i.e. assuming Kubernetes is already widely used as the cloud deployment platform, and looking to solve next-level challenges.
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<Blockquote
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quote="Let’s call it day two operations. People are saying, yes we have Kubernetes, and it’s working well. What do we need to do next?"
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person="Chris Aniszczyk"
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title="CTO, CNCF"
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/>
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Chris Aniszczyk, CTO of CNCF, described it as day two operations: people already have Kubernetes working well and are asking what to do next.
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“Maybe we need an IDP (Internal Developer Platform), or we need to improve how we do observability. People always care about improving observability, which is especially crucial in the age of AI,” he said. “I basically call this platform engineering, as a way to improve how you build and run platforms in your company, so we have projects such as Backstage, Argo, and Crossplane for example,” he added. “We’ve learned from past KubeCons that if we just purely focused on Kubernetes, we wouldn’t have such a wide ecosystem.”
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In this context Chronosphere, which builds observability solutions specifically for Kubernetes, announced their next-level observability product release with AI guided troubleshooting.
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<BlockquoteAlt
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quote="Our approach is to focus on where we can differentiate ourselves with respect to the developer experience, The first is this idea of guided troubleshooting where we study the behavior of the very best developers in the organization, who approach troubleshooting from the position of deep knowledge about the system. We figured out how to use AI to expose that same hypothesis-driven approach to troubleshooting for those who don’t have that deep knowledge."
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person="Colleen White"
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title="Head of Product, Chronosphere"
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/>
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Colleen White, Head of Product at Chronosphere, said their approach is to focus on where they can differentiate with respect to the developer experience, starting with guided troubleshooting: they study how the best developers in the organization troubleshoot from deep knowledge of the system and use AI to expose that same hypothesis-driven approach to those who do not have that deep knowledge.
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And Dash0, a new company that is focusing on simplifying observability data collection and analysis entirely based on OpenTelemetry, announced its new version as well.
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<Blockquote
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quote="We launched last year and right from the beginning, it was really about being OpenTelemetry native. In other words, implementing the first tool around OpenTelemetry, the new standard for observability. Not just integrating it. A lot of the observability companies treat OpenTelemetry as just one input out of many. We just treat the data as OpenTelemetry all the time. There’s also something called the semantic convention of open Telemetry, which basically specifies a naming convention, and by doing so, we can now aggregate and create context and say, give me all the logs, metrics, and traces of that part because they all use the same tag name."
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person="MIrko Novakovic"
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title="CEO, Dash0"
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MIrko Novakovic, CEO of Dash0, said they launched last year with a focus on being OpenTelemetry native—implementing the first tool around OpenTelemetry, the new standard for observability, not merely integrating it. Many observability companies treat OpenTelemetry as one input among many; Dash0 treats the data as OpenTelemetry throughout. The semantic convention of OpenTelemetry specifies naming so they can aggregate and create context—for example, to pull all logs, metrics, and traces for a part because they share the same tag name.
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