This recorded series is from Kleppmann's Concurrent and Distributed Systems course which he teaches at University of Cambridge.
In case the name seems familiar, Kleppmann is the author of perhaps HN's favourite book "Designing Data-Intensive Applications" https://www.amazon.com/dp/1449373321
Not surprising to me (I'm in India), whenever I've reviewed someone's resume and they have a GitHub it's always a few dark green dots on a few days in an entire year for several years (and often just 2 years).
Pretty sure it's done for no reason other than to check a box on some recruiting agency's form "I contribute to open source"
People have started to value things like GitHub forks and stars as though they mean something. Create a metric and it will get abused, this is how the world works.
Stars usually mean your project is useful to someone, so they are indeed nice to see. They're also an endorsement of people who use a project and are apparently happy, so the project is more likely to do what it says and do it well.
These metrics aren't usually a problem until people attempt to game the system like it's done on platforms like youtube, but I'm not aware of this happening on github (at least not often).
People starting at $4K are the ones who work for consultancies like Infosys, Wipro, et al. There is a reason why they're paid so less. They're usually graduates from terrible engineering colleges who have no real engineering skills what so ever. They undergo a 6 month training period before they can even start working.
My friends in Google India on the other hand make close to $50K/yr. My friends in Google MTV make $200K/yr. So the difference is 4x, not 100x.
I'm guessing he's L3? SWE L3 averages 180K in Google.
My friend at Google is SWE L5 (which averages 350k), but he's at closer to 400K because Google's stock price appreciated considerably since he joined.
> Google India on the other hand make close to $50K/yr
Regardless, $50K in India is actually quite high. Many, many large US tech companies are happy to pay peanuts. The average for a large tech company is probably between around $10K/yr to $20k/yr USD, which in my opinion is horrifically abysmal. (Not to mention, I know of companies that hire people in India's neighbor Pakistan, and they are paying them around $400 USD per month, i.e. less than $5K/yr.)
It is an hour long talk (which I wouldn't have watched). I found js2's explanation very clear and helpful. Please don't be outright dismissive like that.
> Research has shown that, without that delay, users trust such websites less, or value them less, because the instantaneous response time is equated to less valuable work.
I'm pretty sure jdc was talking about this research, not the specific implementation.
Except this feed comes to me and I personally filter and select 8-10 links for the day. Helps to filter out the BS. I also tag the articles. Been doing this for over two years now, have curated over 3200+ links. Check it out, I try to select interesting and more engineering oriented articles and leave out the "Hello world" types.
Looks really nice. Especially the hand-picking part of human curation part. Based on the other reply of yours about monetization, wondering why aren't you actively monetizing it. The software engineering daily podcast makes about $60K+ a montb[1]. You can become like that interms of newsletter and aggregation. No?
I'm honestly more of a engineer / research person. I started this because this was something I was really excited by!
It do advertise every now and then but nothing too exciting in terms of $$. I did make a bunch of ideas on growing this into a blog + community + youtube channel + job board (for engineering heavy dev jobs). But I realised that would take quite a bit of time on the business side of things, and right now I just want to enjoy coding and building stuff.
This looks nice at a first glance. I have been looking for more dev oriented article lately and this seem like a good start.
On a side note just read about sqreen. Anyone with a clue to how useful such a product is in reality. I find application security related products very hard to evaluate from the docs without heavy usage and trial.
We try to provide a “dev-tool" approach to security: free trial, simple install and dev-friendly install, no need to configure the tool for hours before getting any value, etc.
I would recommend just to give it a trial.
I'm biased, but our customers love us. We serve both developers without time to handle security and large security teams. For the latter, we often see collaboration between developers and security teams.
Thanks for the HN link, that's what I looked for but somehow algolia wasn't giving me the result at the time.
Two points about a potential trial. 1) Since it's a runtime tool to actually see what it can detect I assume I will actually have to generate some attacks myself to actually see it in affect? It also makes false positive testing a little harder.
The reporting and such is on the cloud I presume? Are there some documentation on what happens at the agent level and what gets send to the cloud?
1) If your app has decent traffic it will be attacked. But we also describe how to scan your app with Arachni on our docs: https://docs.sqreen.com/using-sqreen/how-can-i-test-sqreen-d...
False positives on our RASP module are very rare. Most of our customers use it in blocking mode in production.
How we do it? By using the application context. Our detection is done in-app. It's based on parsers that tokenize the query and detect injections when the user input changes the structure of the query.
More details on our detection rules [1] and more details on how we do dynamic instrumentation [2]
2) It’s on the cloud [AWS]. But our agent doesn’t redirect your traffic or collect sensitive data. We scrub the data inside your agent before sending it to our servers (just like Sentry or New Relic). You can also customize this behavior. [3]
I do a little bit. Some affiliate income now and then (look at the first link in the website). But I don't really advertise much at all, just one plaintext link that too only on the home page.
Sometimes I get sponsors for my mailing list. In total I might have made a few thousand dollars.
It's run by a guy called Adrian Colyer, he picks up a good research paper every weekday and summarises it on the blog. He's very regular and covers about 200 papers per year. Topics covered mainly revolve around data science (ML, AI, etc) and data engineering (DBMS, distributed systems, etc), and to a lesser extent general software engineering and systems stuff.
