We do this today very well. We provision 21 micro-services in an integrated environment under 8 minutes today on Kuberne

It took us almost 1.5 years to stabilize this complex CI setup by building additional tooling, telemetry and redoing how every application is deployed. For the sake of dev/prod parity, we had to deploy all these micro-services to production as well or else just the drift between the infrastructure and deployment setup will make the applications hard to reason about for developers and would have made ops for developers a nightmare.

You may be thinking — wait, you said we eliminate the need for a Lambda, but now you have one doing the post-processing. True! But you may or may not need that step, AND, the key here is that you are avoiding doing potentially time consuming processing during the API call (thus creating a slow/long response time for your API). Furthermore, with the streams API, you can fetch up to 1000 records for a single Lambda invocation (vs the limit of 25 on the incoming/batch write aspect). Therefore, you potentially could have 40x fewer Lambda invocations (if you can process all 1000 records in the 15 minute Lambda time limit). That said, the real key here for me was not doing the heavy processing we do during the API call, keeping the API itself very fast and having the fewest possible error scenarios.

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was the introduction of the shared folder. Besides being a great addition to Dropbox’s private instant-sync functionality, the shared folder had an ingrained marketing element to it — if you wanted to share your Dropbox folder with someone, they had to get the app, too.

Before its launch, analysts from research firm MoffettNathanson expected Disney to gain around 20 million subscribers by October 2020, but after raking in 10 million subscribers on the very first day, the streaming platform continued its meteoric rise through the new year and the pandemic. As it celebrated its first birthday this November, Disney boasted over 73 million subscribers. To put that in context, Disney expected to reach 60 million to 90 million subscriptions by 2024, but it has already blown past the lower estimate and is expected to reach the higher estimate by mid-2021. This makes Disney the second largest US-based streaming platform, only behind Netflix — an impressive feat for a platform that is just a year old. But Disney didn’t reach 73 million people with its brand new platform alone. It was generously helped by a streaming platform from India: Hotstar.

It was bad timing to raise money because we didn’t know what we were doing. We didn’t have a product and we didn’t have any revenue. Fast forward to today, however, and we have a product with close to €20.000 in monthly revenue. But regardless of this, we still ended up saying no to an investment. The primary reason for this is because it is still too early and we aren’t quite there yet.

People can help you scale what you are doing well and what works. But if you don’t know what you are doing, it will take you more time aligning a team. of 14 people than it would have taken to do the job alone. Not to mention that it’s super expensive

I thought money would accelerate our path towards finding our business model, but it only created a distraction, and ultimately led us to waste money on things we didn’t need to even think about.

Lastly, a subtle one. Note the code #if($foreach.hasNext),#end(line 293). That’s a way to add the trailing comma in after each item in the batch of items for the DynamoDB request. Dynamo is particular though, and does not allow a comma after the last item, which is why we have this wrapped in the conditional (i.e. only add the comma if there will be more items after it). Without this, DynamoDB will fail your request.

The post-processing we do takes longer and is fairly involved, and thus I wouldn’t want that being done synchronously on receipt of each of these events (nevermind on a batch of 25 events). Therefore, this architecture creates a very simple API that just worries about storing the raw data. Clients either get the format of that data right or they don’t, which is about the only error they can get from the API. Then later, we process these events (which is more time consuming).

We got community managers, marketing managers, sales managers, and all kinds of developers. We spent time designing the job description, marketing those, selecting people, onboarding them. It is a very straightforward task to do when you are a stable company. But when you don’t know what you are doing, have any revenue, and changing the direction every week, it is the recipe for disaster. Employees are not founders. They need direction and they can’t adjust every week. Even for founders it’s super hard and takes me as the CEO several discussions with the team.

A startup called Generated Media has released a tool called Anonymizer, which uses an A.I. system to analyze your face and synthesize a new portrait that’s mathematically similar. This doesn’t mean it actually looks like you, just that the algorithm thinks so.

While not required, as mentioned early on, I am doing asynchronous post-processing of these incoming events. This is handled via DynamoDB’s streams. This setup involves a Lambda function that listens to the DynamoDB stream which provides all events from Dynamo (insert, delete, update, etc.). Thus, in my case, for this post-processing, you do need to filter to just INSERT events.

A startup called Generated Media has released a tool called Anonymizer, which uses an A.I. system to analyze your face and synthesize a new portrait that’s mathematically similar. This doesn’t mean it actually looks like you, just that the algorithm thinks so.

Like so many other companies, Disney appeared destined to exit 2020 with a trail of disappointments, disasters, and crises needing management. The pandemic forced the company to shutter its revenue-generating theme parks, delay the release of highly anticipated movies in cinemas, and lay off thousands of employees. But while these events triggered huge quarterly losses and harmed public perception of the iconic entertainment giant, the company was able to simultaneously lean into its Disney streaming platform — fortuitously launched in November 2019 — as a much-needed lifeline and its brightest light at the end of the tunnel.

4.5 years ago my startup (Panda Training, which back then was a matchmaking platform for trainers offering training and companies that needed training) raised €200.000 from various funding sources. We ended up going from Helsinki to New York that summer after an initial “killer” run at local sales in the spring with a product that “was supposed to be ready by the time we arrived to NYC.”