Great observability via fast JSON serialization

As we come to the end of this phase of our performance and scale testing, we have turned our attention to the Flock Networks Operations REST API.

Flock Networks routing suite v20.3.5 is out now and it can sort and serialize the 763k BGP routes (as seen at LINX) into JSON and then stream them over HTTP in under 2s.

you@your-host:~$ time flockc bgp --prefix --host > bgp_table.json
real    0m1.972s
you@your-host:~$ wc bgp_table.json
   763307    763307 223051579 bgp_table.json

Because BGP routes have so much meta data (BGP path attributes etc) that is 223 MB of data.

 you@your-host:~$ ls -l bgp_table.json
 -rw-r--r-- 1 you you 223051579 Sep 30 09:51 bgp_table.json

If we are feeling a bit crazy we can now diff the internet backbone in real time !

you@your-host:~$ flockc bgp --prefix --host > bgp_table_later.json
you@your-host:~$ diff bgp_table.json bgp_table_later.json
 < {"ip_net":"","best_entry":{"neigh":{"neigh_ipv4_addr":"","attrs":{"origin":"Igp","as_path":{"segments":[{"segment_type":"AsSequence","segment_value":[65020,8607,2914,3257,20940,20940,16625]}]},"next_hop":"","atomic_aggregate":false}},"reason":"OnlyValidPeer"}}

Or we can deserialize using the language of our choice and take control of the data.

you@your-host:~$ flockc bgp --prefix --host -J --show-url*/sort/json

you@your-host:~$ python3
>>> import requests
>>> r = requests.get('*/sort/json')
>>> deserialized_json = r.json()
>>> len(deserialized_json)
>>> deserialized_json[42]
{'ip_net': '', 'best_entry': {'neigh': {'neigh_ipv4_addr': '', 'attrs': {'origin': 'Igp', 'as_path': {'segments': [{'segment_type': 'AsSequence', 'segment_value': [65020, 8607, 3356, 3491, 38040, 23969]}]}, 'next_hop': '', 'atomic_aggregate': False}}, 'reason': 'OnlyValidPeer'}}         

The Flock Networks Routing Suite has excellent observability because all operational state queries can be returned in JSON format using a machine friendly API.

More information on using the Operations REST API can be found here. The software can be downloaded from here.

Moving from C to Rust

I have spent many years systems programming in C. I have been playing around with Rust since 2015 and this year I decided to switch to primarily programming in Rust. This blog post is an attempt to explain why I have made this decision.

Although I have a background in Computer Science, at heart I’m a Developer / Network Engineer who just wants to “get stuff done” ™. I’ve played with many languages over the years and for me it was C and Python that stuck. I’m still a big fan of both of those languages.

When I first started playing with Rust, all my initial projects were checking how it felt as a systems programming language. That is, could I layout structures in memory as required ? How easy was it to call into C libraries using FFI ? And in particular how easy was it to interface with the Linux Kernel and put IP packets ‘on the wire’ ? I found Rust a good fit for this, probably because it is a C like language, so looked and felt familiar. As an aside, many developers who try Rust initially end up “fighting the borrow checker” that is built into the compiler. [In very rough terms the borrow checker makes sure that your code either has a single pointer to a mutable object, or multiple pointers to an immutable object, but never both]. If you are coming from programming in C then you can quite quickly work out why it’s complaining. However, it really makes you think hard about your data model, and who really owns each allocation of data. This can be painful if you are just trying to prototype something, but it is time well spent on anything that will end up in production.

My two compelling reasons for moving to Rust

Having decided that Rust was a capable systems programming language, I found there were 2 compelling reasons to make the move to Rust.

The first reason is that Rust is memory safe at compile time. This means you can say goodbye to the runtime memory corruption bugs you get in C. In safe Rust there is no ‘reading of’ or ‘writing to’ an invalid pointer. As I said earlier, I like C as a language, but hitting memory corruption bugs in production code is not fun. The worst part is that the point at which the program terminates, say due to a segfault to an invalid address, is likely to be thousands or millions of instructions after the code with the bug has executed. This makes finding the offending code difficult. I once spent over 3 weeks fixing a memory corruption bug in some IP Router software. That’s not something I’m proud of, but nor is it something I’m ashamed of. We could only reproduce the corruption when the device was running in production, and with all logging turned off. Fixing the bug came down to reasoning about 100,000’s of lines of C code. Eventually we came up with a theory about what was happening, wrote a ‘fix’ and the problem was never seen again. Whether we actually fixed the issue, or just changed some timing of events, I will never know. As an engineer this feels wholly inadequate.

The second reason is that Rust is data race free at compile time. As discussed above, memory corruption in single threaded code can be very hard to debug. Memory corruption in multi-threaded code is an order of magnitude more complicated. In my experience, it is possible to write reliable multi-threaded C, but you need to be very conservative and keep the threading model very simple (no bad thing), but refactoring the code is a major undertaking. In multi-threaded code there is such an explosion of event sequences that can happen, it is not possible to have exhaustive testing in place. With CPU frequencies levelling off and being replaced by multiple cores, the future of systems programming will need to be multi-threaded.

Drawbacks of moving to Rust

Rust certainly has some drawbacks when compared to C. For me the main one is the size of the executable produced by the compiler. In my experience of writing similar applications in C and in Rust, Rust release binaries tend to be around 5x larger than C release binaries. This is a combination of the fact that the Rust compiler optimises for speed not size and Rust projects suffer from dependency bloat. The Rust binary can be made smaller, and the dependency bloat problem actually comes from the advantage that you can so easily reuse other people’s libraries. But with Rust there is an extra step you need to take before releasing code, and that is to audit what is contributing to the binary size and is it a reasonable trade off? In the same way performance needs to be benchmarked between releases, with Rust binary size also needs to be tracked, to catch and investigate any large increases.

Rust also currently suffers from long compile times, and IDE support using RLS is slow and a CPU hog.

Moving a development team from C to Rust

Moving a development team from implementing in language A to language B is always going to be a hard sell if they do not already know language B. The team will have years / decades of experience in language A. Rust is a new language so it is likely a team of C programmers will not know Rust.

On top of this, Rust tends to pay back during the final stages of the development life cycle. I would guess that a team that knows both C and Rust, who started working on a new project, would be able to ship the first version of the software earlier if they wrote it in C rather than Rust. Rust tends to catch bugs earlier, at compile time rather than run time, which delays the production of the next binary. Rust forces the developer to iterate over the data model, until it is clean, before the code gets too complex, again delaying the production of the next binary. With Rust the team will probably implement Unit tests and Integration tests as they develop because all the infrastructure is in hand. With C the team may choose to produce the binary first and then possibly wrap some testing around it after. The QA teams will hit runtime panics in Rust that are hidden in C, again pushing out the date that the project ships.

So the sales pitch to management would go something like this. We have a team of highly skilled C developers. I suggest our new product “The IP packet mangler” should be written in Rust. On one hand if we write it in C we will ship it earlier and bring in revenue earlier. On the other hand Rust is shiny and new and would look good on our CV’s. Also the Rust compiler gives very pleasant error messages.

But wait, by catching bugs early, Rust gives you a huge payback in the long term. The C team have shipped a release with more bugs than the Rust team. Customers will be hitting bugs in the C product that don’t exist in the Rust product. As each team is working on the v1.1 features the C team will be interrupted more on bug fixes. This will cause frustration as most bug fixes are more important than implementing new features. The C development team will be getting more randomly timed, high level interrupts of various length, stopping them doing the ‘real work’ of implementing the new features.

Maybe the v1.1 C and Rust versions will ship around the same time. After that the Rust team will pull ahead, as the bug backlog for both teams will now cover multiple releases. The Rust team will probably ship v1.2 and all subsequent releases earlier and to a higher quality.

Obviously there is a lot of conjecture in the above argument, and it is slightly tongue in cheek. However I think the main point stands that it is preferable to pay your development costs upfront and as early as possible.

In summary

You might be able to prototype faster in C, but I believe you will reach production quality faster in Rust. Also with Rust, keeping that production quality high going forward will be easier.

And that is why I have moved from C to Rust.