The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 30 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Kreps: Confluent relegated its core cash-cow product to engineers' spare time
“Originally it was like a small group that was working on the cloud offering. And then we were like, no, okay, everybody. Only does the cloud thing, and we will work on the software product in our spare time. Team by team, which is a very dangerous thing to do,…”
Kreps: Amazon built Kinesis to imitate Kafka before monetizing the open-source
“Amazon had a system that was actually built in, I believe imitation of Kafka called Kinesis. So it was incompatible, but kind of looked roughly like it. And that was popular. And we were like, oh man, that's going to take the opportunity. And if it doesn't, Th…”
Narkhede: Confluent probably would have failed if it started as SaaS-only
“Would it have just been feasible if we started with a SaaS only offering? And the answer is probably not because, you know, one of the most important things an open source company needs to do is quickly establish yourself as the market leader, quickly establis…”
Narkhede: Confluent chose not to separate on-prem and cloud sales teams
“We actually decided to not split it. And that was because we ultimately wanted to transition to a cloud first business. So we put in a, instead a lot of thought and a lot of investment in sales enablement you know, internal education of why this is important, …”
Narkhede: Commercial open-source requires all project creators to found together
“For the success of an open source company, all the creators should be part of it. And when that doesn't happen, you have two companies and they're competing on things they shouldn't be competing on, which mostly comes down to pricing and it's just a race to th…”
Narkhede: Confluent ignored narrow ICPs to capture the broad Kafka base
“Kafka, you know, that was one of the reasons why we couldn't or we didn't sort of narrowly focus on an ICP like traditional companies do for good reason. It was because, you know, the Kafka adoption base was so broad and for Confluent to quickly convert those …”
Kreps: CEOs must learn ~80% of what functional executives know
“I think CEOs need to know, you know, about 80% of what their executives know about their function, I think, over time. So really kind of learn that discipline. Not enough to be good Add it, but enough to be, to know what good is and know if it's going well.”
Kreps: Existing Customer Pressure Naturally Starves Second Products
“I think inherently that a second product is always. Kind of irrelevant to people's main goals, you know, and the, all the pressure of a business is to satisfy the customers that you have, the big prospects coming in the door, that, that kind of main flow of bu…”
Narkhede: Transitioning enterprise sales to consumption models is the hardest challenge
“Sales was just a whole different, you know, dynamic. It was The most difficult one to solve for because in the early days, you know, if you're offering a software product, you have the traditional salespeople who are used to selling a subscription-based softwa…”
Narkhede: Kafka was used by 50% of Fortune 500 when Confluent launched
“Confluent kind of started with a proven technology that was used at, you know, roughly 50% of Fortune 500 companies at that point in time.”
Narkhede: Confluent relicensed add-ons to stop cloud vendors reselling managed services
“So we introduced value-added offerings like stream processing, KSQL, under licenses that were similar, very similar in spirit to the open source friendly Apache two dot O, but these licenses had specific provisions that prevented other entities from just offer…”
Kreps: Engineering decisions are knowable, early startup decisions are unknowable
“Certainly for engineering decisions. They're mostly knowable and there's mostly kind of right and wrong answers, but usually, especially the early phase of the company, you're making a lot of kind of very big critical decisions with a lot of unknowable aspects…”
Kreps: High-level company problems are inherently cross-functional
“Anything that's not working
At a high level is inherently cross-functional. And you know, you'll see a weird phenomenon where people in each function are often don't have enough global context to totally diagnose it.”
Kreps: Demanding a three-month timeline forces engineering teams to break assumptions
“If you kind of just go back and say, well, okay, you know, what would the three month version of it look like? Maybe that's totally impossible, but a significant portion of the time, there is something you could do in three months. And what would that be? Is t…”
Kreps: Confluent coined 'data in motion' against databases for its IPO
“Our approach to that was for the IPO was very much like, okay, databases, data at rest. But now all the parts of the company are connected. There's going to be an equally important problem of data in motion. And so, you know, the goal was to convey, Hey, these…”
Narkhede: Features enabling end users should remain open source
“Features that directly
Enabled the end users of the open source product.
We believe should ideally remain open source or be open source.”
Narkhede: MongoDB Atlas is arguably the most successful cloud product
“And back then I remember that the CPO of MongoDB and today Atlas, their product is the most successful cloud product out there, arguably.”
Narkhede: Operational ease is the right starting point for open-source companies
“The first one was operational ease, you know, offering tools and enhancements to simplify the deployment, management, and scaling of Kafka clusters, which is actually, I think, the right starting point for many open source companies.”
Narkhede: Confluent never split engineering teams between cloud and on-prem
“We kept the foundational teams the same. So there was only one team ever working on Apache Kafka and the foundation. There was only one team that was ever developing a specific proprietary feature set. So we never split, you know, specific teams or individual …”
Kreps: Confluent's initial seed round shifted to a Benchmark-led Series A
“And it went from something where LinkedIn was going to be the kind of major investor to being, you know, a smaller part of the round. And it went from kind of a seed investment to a series A through the course of that fundraising process. But yeah, it was, you…”
Kreps: Confluent struggled for years to expand into data processing
“One of the more recent versions of this was we felt is very important for the company to do the processing of data, not just the flow. And we worked on this largely unsuccessfully for a number of years.”
Kreps: LinkedIn offered an unprecedented balance sheet investment in Confluent
“When we went to quit, LinkedIn was like, oh, okay, well, this is, you know, first of all, we don't really want you to leave, but if you're going to leave, we do think this is really valuable. We would be interested in investing.
And we were like, okay.
Off the…”
Kreps: Confluent's one-year pitch roadmap took five years to complete
“What we had pitched was actually very close to what we built. It's just, I said we were going to do it in a year. And I think in practice, The first thing we launched was much less than that. And to do everything on the slide took like five years.”
Narkhede: Confluent was founded four years after Kafka was open-sourced
“So this conference started four years after Apache Kafka was open sourced and became successful and
It was very much an organic decision.”
Narkhede: Confluent hired MongoDB's CPO as cloud strategy advisor
“And proactively reached out to the CPO there and regularly had conversations, hired him as an advisor at Confluent and was very helpful in avoiding some of the problems that they ran into and learning from the experience that they were, they had because they w…”
Narkhede: Confluent's initial branding was easy because of Kafka's popularity
“At Confluent, we could lean on the brand of a very popular Open source projects, so the zero to one branding phase was actually really easy. With Ocelor, you're, you know, humbled that you're starting with something that people don't really know about.”
Narkhede: Confluent had to combat strong developer DIY mentality around Kafka
“We spent a lot of time focusing on convincing the company that they didn't need a team managing Kafka or their team could be much smaller. Effectively, you're dealing with a, you know, target customer base that just wants to do it themselves, right? So the DIY…”
Narkhede: Confluent initiated SaaS product two years in
“So about two years in, we realized that there must be a SaaS offering because at that time, the whole industry was in the middle of this transition from on-prem environments to the public cloud.”
Narkhede: Chose closed-source SaaS for Oscilar to avoid hybrid software headaches
“I specifically chose a company that would be entirely different. You know, the reasons are like, A, one is just simplicity. You know, you kind of have the experience you've had already balancing building a software business and a SaaS business and trying to ba…”