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Report: Grafana Labs Business Breakdown & Founding Story
Report: Grafana Labs Business Breakdown & Founding Story
A report from Contrary Research. Discover Grafana Labs' founding story, product, business model, and an in-depth analysis of their business.
“90% of our users will never pay us, and that’s by design. It’s really important for us to have a healthy open source community. That’s mission number one.”
Given how much of Grafana’s competitive advantage comes from the quality of their open source community, there is a constant need to maintain the relationship that the company has with the community. Every open source company has to find this same balance between building proprietary functionality while still maintaining the flexibility inherent in their open source model.
The most prominent case was when Amazon AWS (using Elastic’s open-source software, OpenSearch) released a data search tool directly competing with Elastic. In response, Elastic announced plans to change its software license to prevent AWS from using its software. Amazon responded by announcing plans to fork Elastic and maintain the software as a ‘truly open-source option.' All open-source software platforms face the risk of strip mining. Grafana Labs’ open-source offerings are no exception. For monitoring, this threat is lessened because the public cloud vendors have their existing solutions and it's a question of competitiveness vs. replication.
#company
·research.contrary.com·
Report: Grafana Labs Business Breakdown & Founding Story
Report: Zapier Business Breakdown & Founding Story
Report: Zapier Business Breakdown & Founding Story
A report from Contrary Research. Discover Zapier's founding story, product, business model, and an in-depth analysis of their business.
The average business today will use 88 applications across their organizations, and business professionals use 9.4 applications per day to complete their work. The application interplay is typically a repetitive chain of actions following an initial trigger. As one example, someone fills out an Airtable interest form, which triggers an email being sent out. That email triggers a meeting being booked, and that meeting populates a set of fields in a CRM.
In a 2021 survey, 88% of SMBs said business automation allows them to compete with larger companies, and 9 out of 10 knowledge workers claim automation improves productivity. Knowledge workers are the majority of the labor force, representing over 100 million workers in the United States, and 82% use or are planning to use automation software.
Wade Foster (CEO), Bryan Helmig (CTO), and Mike Knoop (President) founded Zapier right out of college. Over two days at a Startup Weekend event in Missouri, the trio built a product prototype that would later become Zapier. Their idea was rejected by Y Combinator, but the team continued to build the Zapier on nights and weekends.
Zapier was an early pioneer of the product-led growth sales motion. They made it free for any prosumer to get started without approval from their IT teams. That allowed the company to save on having a large sales team and helped them reach profitability two years after its founding. At their core, Zapier is positioned to make money only when users save time. The more time users save with zaps, the more likely they are to build other connections. The more number of connections, the more money Zapier makes.
Some of the most commonly connected tools on Zapier, like Slack, Salesforce, Google, and even Calendly, have announced workflow integrations products within their existing platforms to upsell their customers and capture the value of their integrations directly. Instead of having to rely on Zapier to connect Calendly to any other application you can build that same integration natively without having to leave Calendly’s platform.
Transfer by Zapier enables customers to process batches of data too large for the traditional Zapier pipeline to process. Transfer strengthens Zapier’s infrastructure to handle larger loads. The more data-centric every company becomes the more they need systems to manage that data. Zapier’s expansion into Transfer places them in the data pipeline market along with companies like Fivetran.
With the 2020 announcement of Google Workspace and Microsoft bundling their productivity suite into Teams, Zapier faces platform risk from these two major productivity suites. Zapier’s top 2 integrations are Google Sheets and Gmail.
Zapier skewed from the traditional way of building a large technology company by focusing on remote work (even paying employees $10,000 to move out of the Bay Area), not taking significant venture funding, building a product-led engine without a traditional sales team (only really adding people to the sales team in 2021), and pursuing profitability rather than growth.
#company
·research.contrary.com·
Report: Zapier Business Breakdown & Founding Story
Build vs. Buy - Evaluating Edge Solutions | Section
Build vs. Buy - Evaluating Edge Solutions | Section
Enterprises are increasingly looking to edge computing solutions to solve modern business challenges, and bespoke needs have many of them asking themselves whether to build vs. buy.
·section.io·
Build vs. Buy - Evaluating Edge Solutions | Section
Prometheus: The Documentary
Prometheus: The Documentary
Watch and witness the journey of open-source monitoring system, Prometheus. Before Kubernetes existed—even before Docker—the team at Soundcloud already knew their monitoring system deserved a complete, fundamental revamp. Of course, as with anything in development, this was no easy task. Join us as we explore the story of Prometheus, from inception to adoption as told by the story’s key players including Julian Volz, Matthias Rampke, Björn Rabenstein, and more. In the end, you’ll see how a “problem to be solved” eventually led the industry to a completely new understanding of monitoring. We hope you’re ready to be inspired. 🔥 Check out the home for untold developer stories around open source, careers and all the other cool stuff developers are doing at cult.honeypot.io. Honeypot is a developer-focused job platform, on a mission to get developers great jobs. Wanna see what we're all about? Visit honeypot.io to find a job you love. To learn more about Honeypot: http://www.honeypot.io/?utm_source=youtube Follow us: Twitter: https://twitter.com/honeypotio Facebook: https://www.facebook.com/Honeypotio/ LinkedIn: https://www.linkedin.com/company/honeypotio/ Instagram: https://www.instagram.com/honeypot.cult/
·youtube.com·
Prometheus: The Documentary
10x (engineer, context) pairs
10x (engineer, context) pairs
Your actual output depends on a lot more than just how quickly you finish a given programming task. Everything besides the literal coding depends deeply on the way you interact with the organization around you.
For those who work inside Google, it’s well worth it to look at Jeff & Sanjay’s commit history and code review dashboard. They aren’t actually all that much more productive in terms of code written than a decent SWE3 who knows his codebase. The reason they have a reputation as rockstars is that they can apply this productivity to things that really matter; they’re able to pick out the really important parts of the problem and then focus their efforts there, so that the end result ends up being much more impactful than what the SWE3 wrote.
·benkuhn.net·
10x (engineer, context) pairs
Be impatient
Be impatient
Impatience is the best way to get faster at things. And across a surprising number of domains, being really fast correlates strongly with being effective.
Being impatient is the best way to get faster at things. And across a surprising number of domains, being really fast correlates strongly with being effective.
the most famous, interesting, powerful people all read their own email they’re almost universally good at responding to it quickly they’re always very, very curious. they have very little time. Anything with friction gets done “later”
people tend to be either slow movers or fast movers and that seems harder to change. Being a fast mover is a big thing; a somewhat trivial example is that I have almost never made money investing in founders who do not respond quickly to important emails.
And what you actually need is this bias towards action. The best founders work on things that seem small but they move really quickly. But they get things done really quickly. Every time you talk to the best founders they’ve gotten new things done. In fact, this is the one thing that we learned best predicts a success of founders in YC. If every time we talk to a team they’ve gotten new things done, that’s the best predictor we have that a company will be successful.
That means that moving quickly is an advantage that compounds. Being twice as fast doesn’t just double your output; it doubles the growth rate of your output. Over time, that makes an enormous difference.
#selfdev
·benkuhn.net·
Be impatient
Think real hard
Think real hard
The Feynman Algorithm for problem solving: Write down the problem; Think real hard; Write down the solution.
In retrospect, I wish those people had just told me “think real hard.” I was looking for an easy way out—One Weird Trick to Programming Better—but programming is too hard for that. That’s my preferred reading of the Feynman Algorithm: there is no one weird trick.
But 99% of the “secret”—the thing that separates me from Gell-Mann, or Jeff Dean—is tacit knowledge. It often can’t be articulated any better than “think real hard.” But, believe it or not, thinking real hard, for real long, does work.
#selfdev
·benkuhn.net·
Think real hard
No one can teach you to have conviction
No one can teach you to have conviction
fast vs slow feedback • modeling people vs. modeling the problem • mentors vs. mistakes • why you should do the hard thing now
People sometimes tell me that they want to join a startup, so that they can learn how it works, and eventually start one themselves. I usually end up suggesting that they skip straight to step 2 and start one themselves. Why is that? Isn’t it better to learn from someone else’s mistakes than to have to make all of them yourself? At least for me, the answer’s been sometimes yes, but sometimes no.
I knew exactly which parts of our codebase they’d point out as the biggest problems, but that wasn’t the only decision I faced—I also needed to envision what the problem parts should ultimately look like, and then find the fastest path to get from here to there, and then spend months executing the plan. There were too many decisions, and the stakes were too high, for my 95%-accurate simulated guesses to be good enough.
Overall, I probably did a pretty bad job. But, importantly, I was able to see my mistakes play out in the real world. Instead of modeling what other people would tell me to do, I built a model of the problem directly. So when I got negative feedback, it wasn’t “Mentor X thinks this plan is bad” but “the world works differently than you expected.”
You learn many more details about why it was a bad idea. If someone else tells you your plan is bad, they’ll probably list the top two or three reasons. By actually following through, you’ll also get to learn reasons 4–1,217.
This pattern repeated itself across lots of different types of hard decision. I’d start out too uncertain to act with conviction; I’d procrastinate or implement bad plans; but after enough iterations of that, I’d end up understanding a lot more about the problem space. Ultimately, I’d end up with a broad base of tacit knowledge and heuristics that were richer than anything I could get from reading books or talking to people. At that point, I’d finally be able to build the conviction I needed to make good calls.
This applies to any domain that’s open-ended and requires a lot of complex decisions with long time horizons. Take the original example of running a company. By far the most important part of the CEO’s job is the high-conviction decisions. What product should we build? What strategy should we pursue? Who should we hire? And so on.
If you join a company where someone else is already making those decisions well, you’ll never get the type of practice that you need in order to build your own models and heuristics. You’ll end up with a good, but not perfect, model of “what would my boss do?"—a model that can make the 95% of easy decisions, but not the 5% of hard ones that add the most value.
#selfdev#share
·benkuhn.net·
No one can teach you to have conviction
Painful Sex
Painful Sex
A free, bilingual, inclusive encyclopedia of the pussy* made for you to understand: menstruation, menopause, reproduction, sex & masturbation, infections, contraception & abortion, vaginal health, and more.
#personal
·pussypedia.net·
Painful Sex
Geoffrey Litt on Twitter
Geoffrey Litt on Twitter
I'm super impressed by the approach @craftdocsapp is taking to data ownership.At the same time, I think they're hitting the limits of modern data storage platforms, and hinting at precisely why we need a new kind of "collaborative filesystem".Quick thread to explain:— Geoffrey Litt (@geoffreylitt) March 22, 2021
#share
·twitter.com·
Geoffrey Litt on Twitter
The Rule of Three
The Rule of Three
Every programmer ever born thinks whatever idea just popped out of their head into their editor is the most generalized, most flexible, most one-size-fits all solution that has ever been conceived. We think we've built software that is a general purpose solution to some set of problems, but we are
#share
·blog.codinghorror.com·
The Rule of Three
Crypto data, where and when you need it.
Crypto data, where and when you need it.
We build products that make crypto data more accessible. Use our dashboard to explore, or pull data directly into your spreadsheet with our sheets product.
#data
·artemis.xyz·
Crypto data, where and when you need it.
Encore on Twitter
Encore on Twitter
“We're currently focused on building a next-gen cloud infrastructure provisioning system. In essence, it's an intelligent planner that not only models your app's required infra but will also take any of your arbitrary constraints into account. (1/x)”
#share
·twitter.com·
Encore on Twitter
Steve Blank Mapping the Unknown – The Ten Steps to Map Any Industry
Steve Blank Mapping the Unknown – The Ten Steps to Map Any Industry
A journey of a thousand miles begins with a single step  Lǎozi 老子 I just had lunch with Shenwei, one of my ex-students who had just taken a job in a mid-sized consulting firm.  After a bit of catch…
e could object I handed him a pen and a napkin and asked him to write down the names of companies and concepts he read about that have anything to do with the semiconductor business – in 30 seconds.
As you keep reading more materials, you’ll have more questions than facts. Your goal is to first turn the questions into testable hypotheses (guesses). Then see if you can find data that turns the hypotheses into facts. For a while the questions will start accumulating faster than the facts. That’s OK.
Drawing a diagram of the relationships of companies in an industry can help you deeply understand how the industry works and who the key players are. Start building one immediately. As you find you can’t fill in all the relationships, the gaps outlining what you need to learn will become immediately visible.
My suggestion was to use the diagram in the third mapping pass as the beginning of a wall chart – either physically (or virtually if he could keep it in all in his head). And every time he learned more about the industry to update the relationship diagram of the industry and its segments. (When he pointed out that there were existing diagrams of the semiconductor industry he could copy, I suggested that he ignore them.
What he didn’t know was that this was only the first step in a ten-step industry mapping process.
#research
·steveblank.com·
Steve Blank Mapping the Unknown – The Ten Steps to Map Any Industry
An Interview With Replit Founder Amjad Masad
An Interview With Replit Founder Amjad Masad
An interview with Amjad Masad, the co-founder and CEO of Replit about Replit’s long-term potential, Masad’s background growing up in Jordan and how that made him a fighter, whether Repl…
You also have to remember this is pre-GitHub acquisition so dev tools as a space was really nonexistent and it wasn’t getting a lot of funding at the time.
One immediate insight that I had is that developers are one of the most important people, job, role, whatever you want to call it, for the future. And so, “Okay, how can you make this thing, the sorcery magic — whatever you’re going to call it — this modern magic accessible to more people?”
Some of the benefits including access to every open source package in the world, built around this open source operating system called Nix. Actually Nix is not really an operating system, it’s an operating system generator. So it’s a functional programming language that generates an operating system based on inputs and those inputs are packages.
. Do you see Replit in the long run bridging that gap? Or is this a situation where you’re going to be so easy to use and so easy to get started and then you’ll just keep building features over time that you’ll capture the next generation and you don’t need to worry about the gray beards over there saying like, “Oh, that’s trivial. I could have built that if I wanted to.”
So a lot of computer revolutions, a lot of these big companies start kind of simple, start like a toy, and a lot of the initial beachhead market is hobbyists, teachers, schools and things like that, and that’s a great place to be in.
That’s an inevitability, whether we build it or not, and I think we’re going to build it, and part of the reason I think we’re going to build it is because people have been saying we’re going to get killed by Microsoft or Github or whatever for a long time, and it hasn’t happened.
I think one of my favorite Steve Jobs moments was at the All Thing Digital conference, I think it’s now called Code. They were pressing him on Flash, “Why haven’t you built Flash?” And what he said was amazing. He said, “We can only have a few big bets and we want to bet on the future of the web and HTML5, and we think Flash is the past.”
Our bet on Nix was we were the first major startup to do that. Every step of the way we’re taking really contrarian bets that end up becoming mainstream in a few years, and I bet you Nix is going to be mainstream in a year or two. I think we have a very good talent for figuring out where the future of programming and technology and software is going and we want to bet on that.
One way to think about Replit is, if Airbnb and Uber, the sharing economy, found idle assets in people’s homes and cars, Replit is finding idle assets in brains. There’s a lot of people in the world that can contribute massively to the Internet and software and we’re going to bring them online and we’re going to augment them with technology and AI and they’re going to be able to build the future. That’s a part of the bet
They figured out how to build this creative economy around games and a lot of people that grow up playing Roblox want to program Roblox. This is a very cool company and we have a lot of overlap in audience. So yeah, I mean if you’re sitting down and you want to program, you have a choice of programming Roblox or programming Replit to build an app, and have more choice of software and have more choice and more freedom to do things and have a lot more access to open source and things like that, but also Roblox is a compelling platform to be a creator on.
They try to gamify their onboarding, but what the hell is a Git Commit? How am I going to understand what a Git Commit is if I can’t code? And so we’re really at the absolute beginning of a process and we teach people the tools, and in the process we’re also going to change the tools to make them better.
AM: In 2013, I read this paper called On The Naturalness Of Software. I actually have it on my website because I love that paper so much. So this paper — I read it fairly early on and it basically says code is like natural language. They actually have this statistical reason for why they think code can be thought of as natural language. An
We actually haven’t really focused on growth, growth happened on its own just because the product is good. Now, we’re focused more on commercialization and we’re going to bring a ton of what we call Power Ups.
Contributing to other projects, bounties, all sorts of stuff. We’re going to build an economy on top of Cycles.
#stories
·stratechery.com·
An Interview With Replit Founder Amjad Masad
Assume nobody is going to help you. | Derek Sivers
Assume nobody is going to help you. | Derek Sivers
When you assume nobody is going to help, you have to use all of your strength and resources. You can’t wait, because there’s nobody to wait for. It keeps your focus on the things in your control — not outside circumstances. It’s productive pessimism.
#selfdev
·sive.rs·
Assume nobody is going to help you. | Derek Sivers
Saying no to everything else | Derek Sivers
Saying no to everything else | Derek Sivers
“I didn’t talk to anybody during that year… I didn’t hang out. I just worked. I had a book in mind and I had decided I would finish it or kill myself. I could not run away again, or let people down again, or let myself down again. This was it, do or die.”
#selfdev
·sive.rs·
Saying no to everything else | Derek Sivers
The Superiority of ‘Trial & Error’
The Superiority of ‘Trial & Error’
Nassem Taleb and a mozzarella video show us how trial & error is actually a superior life strategy.
When seen in this light, the Buzzfeed crew couldn't have possibly failed. They had some randomness in their attempts, but each attempt cost little when the outcome was failure, and they could afford to make repeated attempts, slowly adjusting from the results of each batch.
Taleb goes further, in fact. He argues that you don't have to be smart if you have convexity in your payofff. You don't even need to have a plan. You merely need to make repeated bets where your positive outcomes outstrip your losses. So long as you are sufficiently rational — that is, you don't repeat the same mistakes twice — you are guaranteed to come out ahead. And not just a little ahead, way ahead.
For instance, if you choose a career that benefits from convexity, you are likely to outdo the people who choose a career without convexity. This is why successful business owners do much better than successful software engineers over the long term. Provided the business owner plays optimally, she only needs one win to make up for her losses; the software engineer on the other hand has to make incremental progress over time.
The strategy that is optimal differs in both fields: for entrepreneurs, the optimal strategy is trial & error (as many bets for as low a cost as possible during a single career); for software engineers, it's better to stick to one thing and build up expertise for that thing over the course of a career.
He goes a little overboard in making fun of 'academic types' in his books, but the main thrust of his argument is still valid: you don't need to be the smartest person to win in convexity competitions — you merely need to be the most rational. The ones who are smart but who aren't rational are more likely to plough on ahead and repeat their old mistakes, instead of learning from each iteration and changing key variables for the next trial.
“This is not a new idea; this is the idea of the age of reason. This is the philosophy that guided the men that made the democracy that we live under. The idea that no one really knew how to run a government led to the idea that we should arrange a system by which new ideas could be developed, tried out, and tossed out if necessary, with more new ideas brought in—a trial and error system.” — Richard P. Feynman, What Do You Care What Other People Think?
#selfdev
·commoncog.com·
The Superiority of ‘Trial & Error’