I was going to write about why needing an app isn’t a good way to try get into business. (Hint: It is very expensive, if you can’t code it yourself.) However something else popped up, namely I am trying to sell off two domains: justcheckers.org and justcheckers.net that I own. These were for the justCheckers project, that I’m essentially shutting down. Anyways if you are interested in buying them off me, feel free to contact me.
I will say that the experience so far has been interesting. Thankfully there are some good resources for selling a domain or site. I’ve looked at two companies that handle the auction and transfer of these things Flippa and Sedo. Both are quite legitimate, but there were some bad reviews and some people claiming to have been scammed. I’m trying out Flippa first since it was founded by the fine folks at SitePoint, who I quite like for other reasons. Anyways, I’m hoping that I can find a good home for the domains.
I have not had a chance to blog in a while. Aside from the usual busyness of life, and the occasional bouts of illness, I have been distracted by a few new thing I’ve been learning: Rust, Kivy and Electron. I’ll write about Kivy and Electron in a future post. And a lot of that is centred around the upcoming product launches for Amber Penguin Software. But that is again for another post.
For the longest time, systems level programming (especially operating systems) have fascinated me. As part of that, I tried to learn the languages used to implement systems namely C and C++. While today I feel more comfortable with these languages, these still scare me with either their complexity (C++), their programming tools (gdb, gcc, autoconf, and minions) and their potential to do horrible things to your system if you are not careful. And bugs can be incredibly difficult to trace down and debug. So I while I have tried to code more C and C++, I still avoid them for these reasons.
Also I recommend listening to the New Rustacean podcast to learn Rust as well. It is not only informative, but very well executed by host Chris Krycho. So far I’ve listened to 10 episodes, and between the podcast, the koans and simply playing with Rust, I’ve learned a lot about Rust. In fact I feel more comfortable with Rust now then I have ever felt with C or C++.
In general UIs in Rust is a weak point for the language. Then again UI libraries are not the simplest thing to get off the ground, and it might be easier to rethink how we build them in general. Again this something I can get to in a future post.
At the end of May, I presented a talk at PyCon 2016, on using Docker with Python microservices. You can imagine the rush I felt getting to present on such a popular topic at such a large and important conference as PyCon! While it took me a while to recuperate after PyCon and Portland both of which were amazing. I would definitely do another talk at PyCon given the opportunity. Anyways I hope you enjoy watching the video of the talk! Below the video I also wrote about preparing for the talk, its reception, and a bit of the controversy that it stirred up below the fold. 🙂 (And I apologize for the lateness of this post, its been sitting in my backlog waiting to get finished for a few weeks now. 🙁 )
Microservices and Docker are all the rage for developing scalable systems. But what challenges will you face when developing and deploying Python apps using Docker to production? This talk goes into the real-life lessons learned from creating, deploying and scaling Dockerized Python applications.
About the talk
Preparation for the Talk
PyCon talks definitely take quite a bit of time and effort to prepare. In my case, the talk took 3 major revisions before becoming the talk that I actually presented at PyCon. What started off as a intro to some of the concepts of Docker with some minor Python points, became more of a lessons learned targetted at intermediate to advanced developers. One of the things I wished I had (and I planned to but didn’t pull of) was to mention and thank my team for helping me preparing my talk. So thank you Kevin Qiu, Biniam Bekele, Yele Bonilla, and Gavin D’Mello for all your support, sitting me through three versions of my talk, and all the amazing feedback! I’ll make sure to include a slide with thanks next time.
Overall the reception of the talk was amazing! The talk turned out quite a crowd, in fact filling up most of the room. (I’m not sure of the capacity of the room but I estimate over 300 people attended). I was pretty nervous, but with the exception of a few stumbles, I think I pulled off the talk quite well. I really enjoyed some of the questions that were fielded during the Q&A session, and also privately afterwards. I wish could of answered some of the Docker Machine and Amazon ECS questions better, but I simply have not worked with both technologies long enough to give proper advice.
The most surprising aspect of the talk was the controversy it stirred up. At the end of the Q&A you can hear some comments from a young lady about where I supposedly went horrbily wrong, and how there were tweets flying back and forth about it. I had turned off the notifications on my phone when I got up on stage, to avoid getting distracted. She persisted with telling (or trying to explain) what was wrong in the private gathering afterwards. Unfortunately she did not do a wonderful job of communicating, and I felt it took away time from others to ask their questions. It didn’t help her case that she admitted to being a novice at Docker. Please don’t that as an attendee, there are better ways to disagree and communicate that.
I later approached by a gentleman (thank you whoever you are), who mentioned I should go talk to the OpenShift guys since they had some concerns about my talk. News of the Twitter controversy worried me, because I hated the notion that I had gotten on stage and toled people to go and do the wrong thing. Especially when apparently I’m telling the opposite of what Glyph from Twisted said to do. After a brief chat (and a nice demo about their cool Kubernetes suite) from the OpenShift guys, I found out that Graham Dumpleton, the creator of mod_wsgi and who works on OpenShift had done a live tweeting commentary during my talk, where he disagreed with a few of my points. Long story short, eventually I was able to chat with Graham. He was a great sport and explained his points. Interestingly enough I had also talked with the folks at Docker. And they agreed with the points in my talk, and the logic behind my points. Essentially most of my points were based off the best practises they proposed.
Anyways I listed a few of Graham’s points with links to his blog posts (thanks again Graham!), and some of my quick thoughts on each one. A quick disclaimer about some of my points: the advice I gave worked for us in our datacentre, and that it might not work for others in other environments. It should work well, it might not be perfect, but it worked for us, and some of the folks at Mozilla. I gave a disclaimer at my other talk on a Ansible setup for WSGI apps at PyCon Canada, and I thought it was superfluous. But it turns out it is a useful thing to mention, and be explicit.
So the slide that caused a good portion of the controversy was the base image one. There I had provided an example Dockerfile on half the slide and discussed about base images and good Dockerfile practises, with points on the lower half. Now the example was meant as a toy and not necessarily complete. It is difficult, even impossible to present a well formated, perfect Dockerfile in that context. There is only so much room on a slide to fit both an illustrative example and some explanatory points. That is why I included links to some samples, that hopefuly did a better job of it.
Ah yes, the “enfant terrible” of my talk. 🙂 If you want to be controversial in your talk, mentioning something like this will get people’s attention. (Ironically, it was not my desire to stir up a controversy). Graham post a while back why you might want to use virtualenvs in your Dockerized app. It is a longish post, so I’ll give a shortened version. Basically when you base your image off some distro (say Ubuntu, Fedora or what not), there is a good chance of bringing in more Python packages in your system site packages than you expected. e.g. You’re building a Flask app, and the package maintainer included a version of Werkzeug in the base Python install, so now when you pip install Flask as part of your requirements you get the wrong version of Werkzeug.
And that is a valid point (with my example)… except if you use something like the official Python 2.7 base image… which installs just Python. I would argue that you would catch and resolve this issue, if you are auditing your Docker images. (And you should be always doing your due diligence and checking your base and resulting images. ) So yes… you don’t really need virtualenvs, but you can also use them if you are concerned that you might be getting conflicting packages.
Graham was right about the adding volume mapping in the Dockerfile being problematic. You should not define volume mounts in your Dockerfile, since they create extra files with sudo-like permissions on the host (see /var). In your own datacentre that isn’t a problem. A multi-tenant cloud provider like OpenShift, would disallow you to create those files. The documentation argument I provided is not all that useful, since you can document the mountpoints in the README that you would provide with the Docker image.
Base images are hard to get right. And there is a lot of debate whether or not to use tooling instead of base images. Graham says his warpdrive tool will do that sort of a thing. At work we build out our own tooling for building “standard” service Dockerfiles, and that just add another level of abstraction. I prefer base images since it while not ideal, provides less levels of abstractions that can get in the way when you’re debugging your Dockerfile setup. But your mileage may vary here.
So yes, good base images are hard. Try not to build your own unless you find it really useful and you have a great base to work from.
Installing GCC/Build Tools
In an ideal world one ought not have to include GCC, Python dev headers and so on. Yes, one can pip install using wheels, but that doesn’t always work out.
Formatting of the RUN command. This is not one of Graham’s points, but it did come up. Yes, you should format the RUN commands, with a line for each command and using a \ line continuation for readability. My slide didn’t have enough physical space to do so. My Rookeries example does a better job of this.
Running as Root
Graham is right, you should not run containerized apps as root. That is a bad security practise that can lead to an attacker compromising your Docker host via a privileged account on your Docker container. Again a bad example on my part, I should of added a USER command and dropped the VOLUME line, or maybe rethought the use of an example.
UWSGI and the HTTP flag
No, you don’t need it and you should use the UWSGI protocol if you put an NGINX container before your WSGI container. I left the flag in to make sure the example Dockerfile was runnable. My bad on trying to get a good illustrative example, but it wouldn’t be a good idea in production unless you feel comfortable exposing UWSGI to the direct HTTP traffic.
If you’re wondering why I’ve been so quiet these past few weeks, it is because I’ve been busy preparing to go to PyCon US in Portland this year!
I am very excited not only to be attending, but I will be giving a talk at PyCon US this year! I will be talking about Dockerizing Python microservices, and some of the lessons we’ve learned along the way at work. My talk will be on the first day (Monday May 30th) at 3:15-3:45 PM (PST). Videos of the all PyCon talks should be available a few days after the talk.
Finally I will be around in Portland for a few days after the sprints as well. I have never been to Portland, so I want to check out some of the sights around there. Let me know via Twitter or email if you want to meetup with me while I’m there. 🙂
Apologies for missing last week’s scheduled post and being late with this week’s post as well. I’ve been putting off writing articles and refilling my queue, with other things that have been (or seemed) more important than blogging. Either way, I’ll try to fix this so that next week I’ll be back to my regular schedule. –Dorian
These past weeks right before the start of the new year, I have been experimenting with something new. As part of trying to use server-side rendering for React client inside Rookeries, I decided to figure out how to achieve this using NodeJS. To kill a couple of birds with the same stone, I decided to use this as an opportunity to play around with ES6. In these next few blog post I will write about some of the lessons I learned along the way.
The Project and Its Architecture
To help me focus my learning, I decided to concentrate around a project that would provide a skeleton for my learning. I choose to recreate one of my earlier Flask project, which runs the Amber Penguin Software website. This web application acts as a cross between a static file website and a CMS, by serving template pages that render Markdown into the body of each page. The routing is a fairly trivial look up of flat files, and returning a 404 error page when a page is not found. The tech stack being Flask, a simple [J]inja2](http://jinja.pocoo.org/) template and Markdown as the Markdown rendering engine.
My project consisted of four phases:
Recreate the current setup using a NodeJS tech stack,
Add a simple JSON API to host the API and a simple React component that was “renderable” via the server and the client.
Build out the React app to handle routing and retrieving the content of each page, with a first time server load and subsequent calls via Ajax calls to the JSON API from the frontend React components.
Host the completed app using my existing Ansible setup.
The first task consisted of figuring out what NodeJS technologies I could use to recreate the Python/Flask app. Turns out that the language specific communities in the web app world like to borrow heavily from each other. Just as Ruby’s Sinatra microframework inspired Python’s Flask, so did Node’s ExpressJS take notes from Flask. Jinja2 inspired Mozilla’s Nunjucks and a bunch of other similar templating libraries. (I ended up using Nunjucks since it is the most mature library) Marked replaced Markup. The tricky part was actually replacing Python’s io.open() to open files. With a bit of experimentation I figured out how to use Node’s fs (file system) module and its readFile() and readFileSync() methods.
In short I could translate the tech stack this way:
Flask ⇒ ExpressJS
Jinja2 ⇒ Nunchucks
Markdown ⇒ Marked
Next time, I’ll go into the details of setting up the ExpressJS apps and routes.
I recently upgraded my version of Ubuntu to 15.04. In the process, I found out that my init system had changed from Upstart to systemd. While having something as fundamental as the init system management was a bit annoying, it isn’t as bad as some folks are making it out on the Web. Here are some of the things I learned as worked with systemd in fixing my CouchDB server. Part of this is based on this excellent guide on using systemd for Upstart users. The other part is just experimentation on my part.
Checking the Status of All Services
sudo systemctl status
Hint: feel to grep through the output to find anything
At first I could not find the CouchDB service. I had to uninstall the package and purge the packages and then reinstall it:
After that the service showed up in the systemd services, rather than just having an Upstart service.
Checking the Status of a Service
sudo systemctl status $MY_SERVICE
Starting and Stopping a Service
sudo systemctl [start|stop|restart] $MY_SERVICE
Logging Service Activity
This was an interesting thing in systemd. Normally one has to look at the Upstart log at /var/log/upstart/$JOB.log. systemd provides its own logging mechanism, so to see the log of a service you have to use the journalctl utility.
sudo journalctl -u $MY_SERVICE
The output behaves just like one would expect from less.
Once I got over my initial head scratching of how to use systemd, it was not bad. Rather it feels different, but not in a bad way honestly. I might look into this more closely and see if I prefer using something like systemd over supervisord for controlling even WSGI apps.
The one disappointing thing that I discovered related to my experiments with systemd, or rather specifically with CouchDB in Ubuntu 15.04. There doesn’t seem to be a way to configure CouchDB to have admin users with passwords for some reason I can’t quite fathom. In the meantime, I guess I’ll have to stick to running CouchDB from a Docker container until I can resolve the issue natively.
I am super excited to announce that I will be doing a talk at PyCon Canada this year! I will be talking about migrating from using Fabric to deploy my WSGI app (Rookeries) to using a combination of Invoke and Ansible. PyCon Canada will be happening in Toronto at the University of Toronto campus Saturday November 7 to Sunday November 8, 2015. My talk will on the Sunday at 3:45-4:15 PM. Videos of the talks should be available about a day or two after the talk. I look forward to seeing everyone there!
About 2 or 3 months ago, when testing a deployment of a microservice at work
with Eric, our head Ops admin, we were looking at the JSON output of one of
the REST endpoints. Rather than looking at the raw output from curl, I
piped the output through JSON tool in the Python standard library:
It is also possible to format the output of the JSON to display only relevant
information. For instance if I want to find out the status of the components
that make up Bitbucket I can do the following:
$ curl -X GET -s http://status.bitbucket.org/api/v2/components.json | jq .
That however will give me a whole lot of extra data that I might not want. So
instead I might to narrow down and re-format the JSON data to something more
manageable with some jq magic:
I won’t explain that particular string in detail. But it will basically
craft a new JSON object, and generate new filtered objects when iterating
over the old array. Overall jq is pretty neat and is extremely fast to work
There is also a Python bindings library for jq. I am considering using it to
help with mapping JSON into Python objects. However I have not played around
with it long enough to know if the extra dependencies are worthwhile or
whether or not it will bring a lot of benefits to Rookeries.