I use FreeBSD jails and get a lot of value out of separate network stacks for each (vnet jails).
Would the NetBSD approach here be to lean more heavily on your lan infra to register hostnames with static addresses (pointing at NetBSD host) and then run a host proxy to forward & port-map to the relevant cell? Or is this the wrong kind of use-case for cells?
I don't personally like proxies, intermediaries, but that said they've been entirely normalised by kubernetes/traefik/haproxy type setups. I do find managing the bridge pseudo-devices, and the various bindings, and DHCP/SLAAC a bit painful because I actually don't understand it well.
I use bastille, and it seems to "just work" and I looked at Sylve and it had huge potential. When I ask for some ELI5 on bridge/net stuff, I don't get traction so my confusion remains.
I think a lot of people enable NAT methods which aren't that far removed from a host proxy or port-map. I don't like NAT (see comment above about k8s)
I was doing some looping recently with tcl and comparing against another implementation (called Jim [1], a very cool project in its own right) and wondered why datetime formatting was so slow when using `clock format`.
The code at [2] provided an alternative approach using C via critcl. It was interesting to see how malleable tcl can be.
Surely you’ve come across situations where line number 10,000,021 of a 60m line CSV fails to parse because there aren’t enough fields in that line of the file…? The issue is that you can’t definitively know which of the 50 fields is missing, so you have to fail the line or worse the file.
In my experience (perhaps more niche than yours since you mentioned it has been your day job), the lack of fall back options makes for brittle integrations. Failing entire files due to a borked row can be expensive in terms of time.
Having to ingest large CSV files from legacy systems has made me rethink the value of XML, lol. Types and schemas add complexity for sure, but you get options for dealing with variances in structure and content.
That is a problem, but it is also a problem with XML. Parsing the XML file to discover e.g. unmatching tags is far more CPU and memory expensive than correctly passing a CVS.
In both cases you'd fail the entire file rather than partial recovery.
Sounds useful from a mental health perspective .. am I right in thinking detractors are concerned about the loss of privacy needed to enforce the bill, or is it something else?
I’m sure that website didn’t mention AI at all a year ago; now it seems if you’re not doing something AI you aren’t the customer they built this platform for. Strange.
It was the other way around for us. All active users were interested in building multitenant apps that involved vector embeddings as well. So, it made sense to focus before we expand
Oh I see - thanks for clarifying. Also, apologies - I could have asked a question about AI demand instead of assuming you were slapping a "now with AI" label on your product.
I’m sure the role is meant to have some sort of value, but in the last decade I’ve only seen one human do a good job of it.
That person delivered value to the team and made a tangible difference to velocity (removing blockers) and effectiveness (retros, reminding people to apply lessons learned). As a consequence the team worked well and delivered good things.
The other Scrum Masters I’ve worked with seemed to operate on the assumption that having Master in their job title meant they knew more than everyone else.
Would it be correct to say the these client libraries provide the functionality (eg ease of transactions, once only, recovery) whereas your cloud offering solves the scaling / performance issues you’d hit trying to do this with a regular pg compatible DB?
I do a lot of consulting on Kafka-related architectures and really like the concept of DBOS.
Customers tend to hit a wall of complexity when they want to actually use their streaming data (as distinct from simply piping it into a DWH).. being able to delegate a lot of that complexity to the lower layers is very appealing.
Would DBOS align with / complement these types of Kafka streaming pipelines or are you addressing a different need?
Yeah exactly! The Kafka use case is a great one--specifically writing consumers that perform real-world processing on events from Kafka.
In fact, one of our first customers used DBOS to build an event processing pipeline from Kafka. They hit the "wall of complexity" you described trying to persist events from Kafka to multiple backend data stores and services. DBOS made it much simpler because they could just write (and serverlessly deploy) durable workflows that ran exactly-once per Kafka message.
I use FreeBSD jails and get a lot of value out of separate network stacks for each (vnet jails).
Would the NetBSD approach here be to lean more heavily on your lan infra to register hostnames with static addresses (pointing at NetBSD host) and then run a host proxy to forward & port-map to the relevant cell? Or is this the wrong kind of use-case for cells?