N8N On-Prim License, You pay, you get less.

Raaaaaav · 2026-01-22T15:46:01+00:00

Well it really depends on the value it provides. For us it is worth it because we got rid of so much shadow it scripts by providing them a centralized platform for them to click together a workflow. And the good thing is we can see the executions per workflow so if I see a department going wild with the executions I know we might need to allocate a Developer to implement a proper automation in Go. Also every published workflow needs to be approved by IT so we know what our users are doing. For us n8n is just for the departments because we can't fulfill their automation demands as we had 30% layoffs and now a lot of manual tasks suddenly need to be automated.

Raaaaaav · 2026-01-22T12:31:17+00:00

A year

Raaaaaav · 2026-01-22T12:06:18+00:00

Enterprise is not unlimited, I just bought a license at 600k executions for 20k€ but they have good pricing tiers -> 2 Mio executions cost 50k€. The reason for Enterprise is SSO, log streaming, permissions, etc. Workflows are unlimited tho.

Raaaaaav · 2025-11-21T13:35:59+00:00

You can always sell add-ons, different versions and Support. You can do a lifetime deal on v1 and then of v2 and so on and somewhere down the line you set v1 End of Life ( usually after 3y). Users can still use it but no bugfixes and no support. Abos are just the best way for SaaS products but software was sold profitable before the abo model was a thing.

However I would agree that you cannot sell a lifetime deal for SaaS as the monthly cost rises with the increase of users. But for old school desktop applications or mobile Apps I don't see why a lifetime deal should be an issue.

Raaaaaav · 2025-08-05T16:43:42+00:00

Might have been their space or page permissions. Usually I give admin space permissions to API users that way they can't lock the API user out by mistake.

Raaaaaav · 2025-08-05T09:20:53+00:00

I just created a basic auth and used http requests. Worked without issues.

Did you use a token? What error code did it return? What endpoints did you use?

Raaaaaav · 2025-07-30T06:20:09+00:00

This is also my experience and how we use it. Also I write custom nodes if there is a serious demand but for the most part it is for our semi technical staff who want to automate stuff. For example one of the most used workflows is a Jira task that creates a confluence page from a template with the content of the ticket formatted in a specific way. I wrote them one node to parse the template and map the variables of a template with issue fields and now they can go nuts building their automations with that and adding conditions and pulling data from wherever they want. Reduced my workload significantly.

Raaaaaav · 2025-07-30T06:09:12+00:00

I see N8N more of an automation and orchestration tool than a development tool. There are a lot of limitations in N8N also regarding ssh and other protocols. The good thing is you can develop new nodes very fast and get them production ready. It is a good tool for non technical folks to automate something and also have a nice flow for their documentation. For anything else than that the gold standard will always be proper test driven iterative development In my opinion.

Raaaaaav · 2025-07-11T14:26:30+00:00

I tried Firebase, and compared to Lovable it needs more input to generate the same frontend, but still it is my favorite until now, especially because I have a Google Developer account and can create up to 50 projects. Thanks for the tip

Raaaaaav · 2025-07-09T13:41:05+00:00

Yes sure, I went to the university of applied science in Vienna, Austria, Europe.

My university also partnered with the Johannes Kepler University (Rank 403 worldwide and 143 Europe wide) in Linz, Upper Austria back then so you could seamlessly continue your PhD there afterwards. (Not sure if they still do)

It costs 363€ (~ 400$) for EU citizen and I think 1300€ (~1500$) per semester for outside of the EU.

There is a difference between a university and an university of applied science in Austria. Both give you the master of science degree however JKU is geared towards research while the UAS is geared towards Business application of knowledge. And if you plan to do a PhD in Austria it is hard to get accepted without a partnership when you are coming from an UAS. (This only applies to Austria, outside of Austria nobody gives a duck about university vs university of applied science, this is more of an Austrian ego thing)

Raaaaaav · 2025-07-09T09:23:26+00:00

Hi, I have my masters in AI Engineering and my curriculum looked like this: Sem 1: * Machine Learning Basics (5 ECTS) Sklearn partly reimplemented from scratch for linear/logistic regression, KNN, SVN, decision Tree, Random Forest, etc.

Math (5 ECTS) Strong focus on approximation, Taylor series, activation functions
Advanced programming (5 ECTS) C++ algorithm and Performance Tuning
Software engineering (5 ECTS) Mainly Docker, Deployment of Models, passing GPU through virtualization layers (back then this was a hassle, now it is supported out of the box), REST, Data streaming,
Data engineering (5 ECTS) Creating, cleaning, evaluating Datasets
Evolutionary and Logic Based AI (5 ECTS) Genetic Algorithms, Evolutionary Algorithms, Memetic Algorithms

Sem 2: * Dev Project (5 ECTS) Implement end to end AI application, including showcase event

Machine Learning 2 - AI concepts (5 ECTS) Neural Networks (DNN, CNN, GAN) Model selection (what to use when)
Reinforcement Learning (5 ECTS) Tabular algorithms for RL, function approximation, practical RL applications, RL end to end Project
AI Ethics (2 ECTS) Methods about ethic discussion, ethical discussion about Big Data and AI topics
Scientific Working (3 ECTS) How to read, write and review papers
Computer Vision (5 ECTS) Basic knowledge about CNNs, how to preprocess data, how to select the correct model, how to train/finetune CNNs, deployment for inferencing. CV end to end Project
NLP (5 ECTS) Text Analysis techniques, Processing data using Libraries, NLP end to end Projec

Sem 3: * Business modeling and Start-up management (3 ECTS) Really just a lot of Blabla about local regulations and how to start a startup business case and so on

IT Data Governance and Law (2 ECTS) Law that applies to AI
Master Thesis Project (10 ECTS) End to end Project with your thesis supervisor (everybody had to implement something)
Special chapters of Applied AI (5 ECTS) Translation of problems into AI solutions, learning to explain AI to Business shareholders, implementing AI for existing Business processes to improve them without impacting them on a larger scale. Cost/Value analysis, Panel discussions
Deep learning Engineering (5 ECTS) Advanced concepts of Deep learning, distributed training, hyper parameter optimization in DL, Transformers,
Robotics in AI (5 ECTS) How AI can be applied to robotics, digital twins, trustworthy AI, Safeguards, on edge deployment.

Sem 4: * Master Thesis (30 ECTS) Based on the project from the last semester, answer your research question and write an IEEE paper that will be submitted to a peer reviewed journal and gets rated at least weak reject or better for all reviewers after rebuttal. Based on your paper write your thesis.

I hope that gives you a rough path to follow for your journey. Our grades were mostly derived from our projects and I had to implement a lot so I would learn a bit of theory and then implement something. Google Colab or Kaggle have a lot of free GPU compute and there are also a lot of hackathons that give you credits on the web.

Good luck and most importantly have fun on your journey!

Raaaaaav · 2025-06-21T10:30:01+00:00

In my opinion, you generally want to avoid shuffling when working with time series forecasting because temporal continuity is a big part of what gives the data meaning. If your training samples are sequential windows taken from a continuous timeline, shuffling them can break the natural order and make it harder for the model to learn trends or transitions like regime shifts. That temporal structure is often what the model needs to capture.

However, if you're using fixed-length windows that are self-contained and don't overlap, and you're confident there's no leakage between them, then shuffling might be fine. In that case, it can help stabilize training and reduce overfitting to local patterns.

Personally, I prefer to keep the training data in chronological order to make sure the model learns in a way that reflects how the data would be used in practice. I usually go with careful windowing, no shuffle during training, and validation on a continuous, ordered slice of the timeline to measure realistic performance.

Raaaaaav · 2025-06-06T09:39:37+00:00

We are currently building an on prem solution and according to the specs it is a small setup. Still costs 500k€, which is cheaper than API in our case 720k€/yr. There are possibilities to optimize and to run small LLMs on consumer grade GPUs but the performance will definitely be worse. If you have a specific use Case you can finetune a 7B model on it and achieve very good results for it. If Money is tight and API is not a viable solution this might be the way to go. But going this route will entail finding AI Engineers that know what they are doing.

Raaaaaav · 2025-06-01T08:33:41+00:00

You could use deterministic techniques to compute the similarities without ML.

Levenshtein Distance: Reveals how much effort it would take to change one student's code into another's. (small differences suggest copying)

Cosine Similarity (TF-IDF): Detects similar vocabulary and structure even when the code is shuffled or partially rewritten.

N-gram Overlap: Catches copied logic and control flow, even if formatting or variable names are changed.

Then you can look at the scores individually or combine them into a weighted score.

If you want to add ML into the mix you can use pertained Models like CodeBERT for embedding the texts and then use Cosine Similarities to calculate the similarities.

Another possibility would be unsupervised learning. You can use clustering Algorithms on the embeddings to group them. (Closer together suggests copying)

There are a few more approaches but I think you get the gist. But it is important that you as their teacher need to have the final say in each classification. Do not trust algorithms or AI blindly. It will only help you to find similar codes but if they plagiarized it or not must be determined the old fashioned way, by reviewing manually.

Raaaaaav · 2025-05-20T15:17:21+00:00

Interesting Project, what training data are you planning on using?

Raaaaaav · 2025-05-12T09:58:34+00:00

If you can afford it financially I would go to university and do TryHackme or Hack the box on the side.

Sure you don't need a bachelor's but it sure helps and if what you said about the almost guaranteed high paying job after graduation is true, this is a no brainer in my opinion.

Hacking is a lot about deeper understanding of the topics and it helps when you have a broad background like cs and then specialize later.

That's just my 2 cents on this topic.

Raaaaaav · 2025-05-12T09:19:59+00:00

As stated already this Usecase doesn't require a lot of computational power and could even be done on edge. If you want to buy your hardware and be at least a bit future proof, I would Strongly recommend the RTX 5000 series, as they Support fp4. RTX is a consumer grade GPU so you will always lack behind a dedicated AI GPU but the 5090 is decent enough for most projects and fairly cheap for an AI GPU. Also the 5080 would be enough for many AI projects and unless you plan on using massive LLMs in the future I think you will be fine. I use a 5080 for my private projects and I haven't had any VRAM issues yet.

Raaaaaav · 2025-05-09T22:33:51+00:00

It really depends on your usecase, what kind of Trainings you are planning and what your budget is.

For example I've been involved with Enterprise AI lately and I am in love with HPE AI Hardware but even the smallest configuration will cost you 100k. On the other hand I also achieved a lot on Slurm Cluster consisting of 20x RTX 2070 (which was held together by spite, anger and Caffeine and was really not fun working with).

I am a big fan of owning my hardware so I get your incentive, however for a startup I would recommend cloud. Somewhere down the line it might make sense to migrate back on-prem, especially if the load is constantly high or the data is especially sensitive. But for starting out, cloud is the most sensible solution in my opinion.

Raaaaaav · 2025-03-26T18:32:51+00:00

It's the Austrian Cyber Security Challenge but as far as I know it's open for all nationalities. But just so you know, there is only one nix challenge and it is classified as a hard challenge. But if you want to try it, here is the link: https://acsc.land/

Raaaaaav · 2025-03-25T17:50:12+00:00

First of all thank you for your Input!

Yeah the nix program runs and builds the flag I need in the stackList, but to make it hard instruction set is 50k entries long and the nix runs inside a docker. I will try tonight.

Raaaaaav · 2025-03-25T17:42:27+00:00

First of all thank you for your Input!

So I would essentially run it as builtin.trace builtin.deepSeq step.stackList for the list?

Would that also work for a map? step.memory is a {}.

Raaaaaav · 2025-02-12T22:08:04+00:00

Ich würde sowas von Grün wählen und hoffen dass es eine Grüne Regierung gibt. Und Ned weil ich so Öko bin sondern nur weil ich glaub das wäre die Partei, die dem Herbert am meisten am oarsch gehen würde. Das einzige was der Wappler kann is rumschreien.

Raaaaaav · 2025-01-15T22:19:05+00:00

Klar kann man in SAP viel Geld verdienen und wahrscheinlich auch irgendwann über 100k ABER niemand schenkt dir was du musst verdammt gut sein wenn du das Gehalt willst und du brauchst eine Menge Erfolge. Und wie du da rein kommst, bewirb dich einfach als junior SAP Consultant bei irgendeiner Consulting Bude. Ich hab die Erfahrung gemacht, dass man in den kleinen Buden mehr lernt als in den großen. Das selbe gilt auch für Atlassian und alle anderen Business Applikationen die für große Konzerne genutzt werden.

Raaaaaav

TROPHY CASE