DishyDev

Very cool. Should flush out a few bugs.

I'd be interested to know why Valgrind vs the Clang AddressSanitizer and MemorySaniziter. These normally find more types of errors (like use-after-return) and I find it significantly faster than Valgrind.

The thing I don't like about day rates is where I've seen large consultancies pile in large inexperienced teams propped up by one or two seniors to do the actual job that needs doing.

With pay per day deals sometimes success for the consultancy is how many people they can get on a project, and less experienced people give higher profit margins. Being successful doesn't pay better than running late, and few clients have the knowledge or oversight to not get ripped off.

I know reality is far murkier than that and fixed price comes with different problems.

Looks like you can get a bit of a Node stack trace on mobile

```

  Error: Choose failed Missing field "user_id" in context for bucket_val = user_idError: Choose failed Missing field "user_id" in context for bucket_val = user_id
  at Decider.choose 
  (/src/packages/applications/monolith/bin/index.cjs:19115:41)
  at isCustomFeedsDisabled 
  (/src/packages/applications/monolith/bin/index.cjs:266576:32)
  at Object.shouldInclude 
 (/src/packages/applications/monolith/bin/index.cjs:266612:66)
  at Resolver.shouldIncludeChild (/src/packages/applications/monolith/bin/index.cjs:175841:26)
  at /src/packages/applications/monolith/bin/index.cjs:175901:40
  at Array.reduce (<anonymous>)
  at Resolver.iterate (/src/packages/applications/monolith/bin/index.cjs:175899:22)
  at Resolver.iterate (/src/packages/applications/monolith/bin/index.cjs:175938:55)
  at Resolver.iterate (/src/packages/applications/monolith/bin/index.cjs:175938:55)
  at Resolver.iterate (/src/packages/applications/monolith/bin/index.cjs:175938:55)

```

Looks like you can get a bit of a Node stack trace on mobile

```

  Error: Choose failed Missing field "user_id" in context for bucket_val = user_idError: Choose failed Missing field "user_id" in context for bucket_val = user_id
  at Decider.choose 
  (/src/packages/applications/monolith/bin/index.cjs:19115:41)
  at isCustomFeedsDisabled 
  (/src/packages/applications/monolith/bin/index.cjs:266576:32)
  at Object.shouldInclude 
 (/src/packages/applications/monolith/bin/index.cjs:266612:66)
  at Resolver.shouldIncludeChild (/src/packages/applications/monolith/bin/index.cjs:175841:26)
  at /src/packages/applications/monolith/bin/index.cjs:175901:40
  at Array.reduce (<anonymous>)
  at Resolver.iterate (/src/packages/applications/monolith/bin/index.cjs:175899:22)
  at Resolver.iterate (/src/packages/applications/monolith/bin/index.cjs:175938:55)
  at Resolver.iterate (/src/packages/applications/monolith/bin/index.cjs:175938:55)
  at Resolver.iterate (/src/packages/applications/monolith/bin/index.cjs:175938:55)

```

I've had to do a lot of scraping recently and something that really helps is https://pypi.org/project/requests-cache/ . It's a drop in replacement for the requests library but it caches all the responses to a sqlite database.

Really helps if you need to tweak your script and you're being rated limited by the sites you're scraping.

Not a great week for managed Kubernetes services as Digital Ocean have been having an ongoing issue since yesterday morning on their service https://status.digitalocean.com/incidents/fsfsv9fj43w7

My cluster was down this morning around 11 UTC. Not sure when it started working again but I'm back in business. Some comms from DO that there was an active issue and they were investigating would have saved a lot of time trying to debug.

I've had a good experience doing a couple of bug fix bounties for urllib3 https://github.com/urllib3/urllib3/issues . I'd be interested in how the maintainers how found running the bug bounty and if it's given them more useful fixes or if it just adds more noise to deal with

Average is around $120 for an hour for them.

Great write up on something I depend on a lot but don't understand well.

This also answers something I've always wondered about which is how Twisted and Tornado fit into the Python web framework landscape and whether I should use them. Tornado always seemed popular but slow and less intuitive than Flask/Django. And then Twisted was a far lower level library but people were still building APIs on it.

Where does Eventlet fit into the picture? Is it a similar box of magic monkey patches like GEvent?

I've used respondent.io successfully for a few years doing surveys on new developer tools and cloud provider portals.

This solves a really tricky Terraform problem I have at the moment about wanting to create Dev environments quickly but not wanting to recreate DNS, VNets and other core functions for every user. Will definitely be having a play with it.

Really well put on the risks and how outcome based projects aren't necessarily better aligned for good outcomes.

The best company I worked with did a multi-drop "agile" contract where there were several incremental prototypes and product releases with feedback and tuning the requirements to ensure we got what we needed in the end. That felt far more aligned and how I'd prefer to work but it took a lot of trust and a long relationship with the vendor.

I love the idea of doing independent technical due diligence work after enjoying doing software auditing and investigations in my current job. Looking at Gitlab's processes it seems like company structure, finances and legal checks make up a lot of the investigation. The software/infra/tech side seems quite short (Gitlab suggest their early technical diligence should be turned around in 2-3 days).

Do you think there's enough demand out there to have a company that does just technical (e.g. software quality, security) due diligence?

I always enjoy seeing what a good awk & sed user can achieve in bash.

However one of the not so good Devs I worked with used awk to load a large, deeply hierarchical JSON file. They refused to use a library to parse JSON. It was a many hundreds of line monstrosity.

Luckily when they left we were able to parse it in JQ instead .

I think Gitpod is a great product, and I've had a massive amount of use of their free tier. There's something pleasant about throwaway Ubuntu development environments. I can cover pretty much all of the major development use cases in it, even container work.

I just hope they survive long enough to take off as they're giving a lot away for free currently. Their dedicated instance setup looks like it'll cover the majority of businesses who'll likely have their own landing zones and cloud controls they can integrate into. Not being able to self host is a loss, but it might the right trade off.

I don't understand the AGPL bit well other than it was seen like poison by corporate risk types at my previous jobs.

I remember a colleague who was critical and pretty much the only person who knew how part of the business worked. He had a great analogy that for every new initiative and fresh recruit they brought into that area, it was like the organisation was hooking in another IV into him to draw more blood out. It's an image that always stuck with me to describe people in the situation Jeff found himself in.

As someone whose job involves maintaining uptime of a critical system that's dependent on Cosmos DB this sort of thing is scary. Where there's been other reliability issues with Cosmos before we've not had an understanding customer base, and it feels very out of my control.

I'm finding a lot of the reliability guarantees of Azure PaaS services are overblown or come with big caveats when you start to work with them in a serious way. For example I've had some bad reliability issues with Azure Functions not firing, or their premium function runtimes becoming unresponsive. And it seems like that's just the start of the outstanding issues with them https://github.com/Azure/azure-functions-host/issues

I think people need to look more carefully at these PaaS guarantees and look at what that 99.999% reliability Microsoft are claiming actually means.

This is a cool project, and really well presented.

I've looked doing similar, trying to query a large dataset through ranged lookups on a static file server in the past. I ran into issue of some hosters not providing support for ranged lookups. Or the CDNs I was using having behaviour like they only fetch the origin data source in 8MB blocks meaning there was quite a lot of latency when doing lots of small reads across a massive file.

It would have been interesting to find out a bit more about these topics, and see a bit more on performance.