Nightmare VS python-fake-data-producer-for-apache-kafka

Nightmare JS is a web automation library designed for websites that don’t own APIs and want to automate browsing tasks. Nightmare JS is mostly used by developers for UI testing and crawling. It can also help mimic user actions(like goto, type, and click) with an API that feels synchronous for each block of scripting.

If you want to make your own custom solution, i recommend looking into puppeteer or nightmare. They are browser automation tools that can do this kind of work.

install any end to end testing system, such as playwright, puppeteer, or nightmare

- https://open.segment.com

come effettuare il logout tramite script. Immagino si tratti di inviare un form con nome utente e password, in tal caso con strumenti come https://github.com/segmentio/nightmare#examples dovresti riuscire con facilità

Depends on the use-case. If you want to save complete websites for offline usage I've created [telescopy](https://www.npmjs.com/package/telescopy) for that. If you need to extract content from one html-page then try something like [nightmare.js](https://github.com/segmentio/nightmare)

I had good experience with Aiven in the past, we needed something located in the EU: https://aiven.io/

Access to Aiven

One of the hardest questions we answer for our large enterprise customers is why they should choose Aiven instead of managing their own database and streaming services. It can seem counterintuitive that paying extra for a managed service can save you money. However, when we factor in economies of scale - particularly in regards to access to specialized knowledge and tooling - the case for managed services becomes clear. This was certainly the case for some of our MySQL clients earlier this year, where their investments in Aiven paid off in the form of a quietly managed bug fix.

And Kafka + Kafka Connect has https://www.confluent.io/ https://aiven.io/ https://upstash.com/ (and not quite Kafka, but protocol-compatible, https://redpanda.com/)

Fake data utility - https://github.com/aiven/python-fake-data-producer-for-apache-kafka

For PostgreSQL, similar offerings are: * Google Cloud SQL * AWS RDS * Digital Ocean Postgres * Azure Database for Postgres * Aiven, Instaclustr etc

Aiven - https://aiven.io/

Majority of companies layer DevRel on top of marketing as a sort of afterthought, and that’s usually a recipe for failure. All four co-founders at Aiven (the company where I work at) have been long-time open-source maintainers/contributors and highly value the work of DevRel. Similar examples can be seen at HashiCorp, where co-founder Armon Dadgar has been doing DevRel on the whiteboard since the early days of the company. Technical founders know the value of DevRel and know when to form a DevRel team. This is very different from bringing your first DevRel hire onboard and making them convince the leadership why the company needs DevRel in the first place. If your developer advocate needs to explain to the technical leadership the need for DevRel, that's a red flag for that individual and the company.

I wonder when Aiven https://aiven.io/ (or something similar) will start supporting hetzner.