Git connections while using PdaNet+

Sometimes we travel to my parents' place, who do not have internet or wifi. 

~Me, basically

We do have cell service, so working remote is possible. I use PdaNet+, a nice utility app for Android that turns my phone into a wifi hotspot on the MacBook. This works great for most everything that uses https. (Special ports, like a direct connection to Postgresql 5432 and the like do not work, likely blocked by phone carrier). This Wifi Direct connection on the Mac (Big Sur) requires a special proxy port, but then email clients and web browsers work great. 

However, git was giving me problems. An error like this:

$ git pull

fatal: unable to access 'https://***@bitbucket.org/***/***.git/': Could not resolve host: bitbucket.org

All other http works, but this does not? Aaarrgh!!

The fix: Set the proxy directly in git as well (same that is needed in WiFi Network settings)

$ git config --add http.proxy http://192.168.49.1:8000

(don't forget to `git config --global --unset http.proxy` when done). 

Now git works too. I'm living large on the edge of civilization : )

Edit: When using SSH Git (like BitBucket or GitHub required in 2022) the config has to be set another way. These lines were needed in ~/.ssh/config (and needed to be removed/commented when done)

ProxyCommand nc -x 192.168.49.1:8000 %h %p

ProxyCommand nc -X connect -x 192.168.49.1:8000 %h %p

ElasticBeanstalk HTTP Time

Web servers with NodeJS are fast, right? Yep, most of the time. The use case for our system is that users collect data with photos on their mobile app offline until they send their data. It's a nice hand-shake that the data exists on the device until the server receives it, so there is no data-loss and working offline was a requirement for the app. Typically an upload is a big JSON object and some photos. A few hundred K in most uploads. Recently one of our auditors keep a week's worth of data with a lot of photos, and gets a timeout when trying to send the data. 60 seconds and the upload fails. (We don't chunk it into multiple requests to maintain that handshake, and in 99.99% of the cases it is never a problem.)

We won't release a new mobile version for this single user, so the change needs to be made on the servers. Ours use ElasticBeanstalk, which is a fairly standard system setup, in that our traffic follows this flow:

LoadBalancer -> Instances, and each instance NGINX -> NodeJS

Lots of these stages can timeout on your HTTP requests, mostly by having a default. I have a testable HTTP request I made through Chome and watched the results in in the Dev Tools Network window. Initial testing died exactly at 60.

LoadBalancer

We are using AWS, so go to the EC2 service, on the left for Load Balancers, and change the "Idle Timeout." 

NGINX

This could have two places to change, one is NGINX itself (which is really handling all the web traffic) and the other is the NGINX-Node proxy. 

I made these changes in our server { context.

        client_max_body_size 50M;

        client_body_timeout 300s;

        keepalive_timeout 300s;

        send_timeout 300s;

And these in our location /api { (which is a proxy_pass to the nodejs upstream)

            proxy_send_timeout 300s;

            proxy_read_timeout 300s;

            send_timeout 300s;

These NGINX directives are all documented here: http://nginx.org/en/docs/dirindex.html. The main thing is to allow the connection to live with NGINX and upload for a while (the server changes), and that NGINX will keep the connection to node for longer (the location changes). These all had timeouts 30s - 60s.

This worked well! My test action made it to 120s. This increased my previous timeout values, but still not 300s like the settings suggested.

NodeJS

The default Node http servers could have timeouts on two places. First is the default server timeout (120s) and the second is the client request timeout. The server timeout defaults to 0 in Node 13 (and though we are using v12.18 this one was not an issue). Each request can have a different timeout as well. I made our two problematic endpoints have a longer timeout this:

req.socket.setTimeout(5 * 60 * 1000) // 5 minute timeout!

That was the final one. My test call actually completed in 4.3 minutes so the extended timings worked through the full system.

When did I start my Mac

Sometimes I wonder when I started my work day, typically when I set up my laptop at the office. There is a command for this!

pmset -g log | grep 'Display is turned on' | tail

pmset -g log | grep 'Wake from Normal' | tail

You can try either one, and get some output like this:

2020-06-09 07:47:49 -0400 Notification         Display is turned on                      

2020-06-09 07:48:56 -0400 Notification         Display is turned on                      

2020-06-09 08:39:29 -0400 Notification         Display is turned on                      

2020-06-09 08:46:16 -0400 Notification         Display is turned on 

A short list of useful activity with the time of day.  Yay!

Integration Tests in Jest - Specific Group Serialization

Jest is a cool testing framework for NodeJS, and was adopted by my favorite API framework actionheroJS. In past projects I used Mocha, but to try something new I'm using Jest.

Background

I like to write integration tests when testing my APIs (I find them the most meaningful) which typically has a group of API calls in a single test suite. User Permissions, Client Configurations, Business Processes, etc are tested together.  Most times a folder contains the group of test for that suite, and tests are expected to run sequentially because the data created for the "create" api calls could be used for the "update" "read" and "destroy" API calls as well.

Enter Jest. Every test file is able to run in parallel and the state is independent of the other tests. Serial in a single file and parallel across many files. Great for running all the tests, but makes it hard to share state between them. To group my API calls I could either:

1. Put them all in a single file to test out the entire suite. Or...
2. Build up some testing data before each suite runs. 

I did not like #1 because the files would get huge. Each group might have 4-15 API calls that need exercised, plus setup/teardown and a few error cases. That's a lot of lines. Code folding in my IDE?

I did not like #2 too much either - custom testing code to "build the data" at the start of each test, plus a 5 sec or so boot time for a backend API instance to start on the server. Smaller files leads to a lot of boots and a lot of time (even with extra cores and Jest workers). Perhaps a DB seed file could ensure certain data would be available, but that's as dynamic as building on the fly and it's one more thing to maintain for the test suite.

What Does Not Work

To find a solution, I learned some things.

First, you cannot create a single, shared global to use across all your test suites. Lots of chatter about that here, but the summary is only JSON-serializable things can be global values. API tokens or WebSocket URLs? Sure. Instantiated objects with functions and all sorts of other initialized data, like an actionhero api instance?  No way. Each test suite is running in its own worker thread, meaning it has its own scope and cannot "talk to" the others (and don't try because they're all running parallel which could lead to craziness!).

Second, and this is true for many Node test frameworks (Mocha for sure), is that test setup (the describes) is synchronous while test running (it(), test(), beforeEach(), etc) is asynchronous. For Jest, you cannot instantiate a variable inside a describe() block that you want to use in your tests. You can initiate a variable, but must instantiate inside a test() or beforeAll() function.  The describe() functions all run at the start of testing synchronously, to setup what tests will run. The actual tests and variable instantiation happen when the test run, so if the variable was assigned in a describe() block, and not a test block, that assignment took place in the setup phase and likely does not contain what you expect it to (often leading to "cannot read property X of undefined" errors).

Solution

Let's jump into the solution, and it was as "simple" as sharing the API instance in the worker process scope in the same way that the api instance is used in the actionhero api.
Here we have a single actionhero instance started before all the test suites are run, and stopped after. Describe blocks are run in the order they are defined, so we describe the suites here, but the contents are in other files and can define their own beforeAll() or afterEach() functions. The convention is that are in their own describe() block.

Be sure to put that __test__/lib directory in your ignore patterns, or Jest will try to run them.

"jest": {

"testPathIgnorePatterns": [

"./__tests__/lib/*/*"

],

It is possible to change "describe('Create', createTests)" to "createTests()" by changing the export of the create.ts to be like this:

export default () => {

return describe('Create', () => {

I do not prefer it that way because some information would be hidden in 00-template-tests.ts, but it's an option!

You could probably do some fancy "walked directory" imports to find all the files in ABC order and include them in your suite - depending how large your suite grows or how annoying you find it to update the main test file.

That's how I'm running Jest tests in sequential groups, but maintaining parallel suites for all part of my API. Working for now, and I'll update this post if something goes terribly wrong : ) 

Winston v2 to v3 and Papertrail Logging

Winston is a logging library for NodeJS and has a bunch of community-built “transports” that use the Winston API to log to different places. Maybe “Console” and “Single File” while developing, and “logging service like papertrail” and “rotating log file” while in production. Code in the application “just logs” and configuration sends the messages where they should go. That how it works in our framework of choice, actionhero. 

Well, Winston went through a big upgrade to v3. This affected my project because the framework we were using had used Winston 2.x, and when I upgraded Node versions and our framework version, suddenly we were using Winston 3.x and my logs to papertrail stopped! We were using the Winston-papertrail transport which has been watching Winston v3 in a few different issues. While it worked, the logging looked junky because the transport was not updated and basically printed messages twice in the same log to Papertrail. Ugly, but at least functional again.

That’s where I ended yesterday and was just going to deal with it, when I found there was a v2 branch for Winston-papertrail. They say it’s not complete (some connect error cases) and I had to change my formatting a little in my application, but it works lovely and everything is back and running again. The community is slow moving on the Winston-papertrail project but it’s hanging in there and any Node project moving from v2 to v3 of Winston and wants Papertrail should be aware of it.

The Senior

Titles are a funny thing. Sometimes we like to play them down, and sometimes we like to have big, fancy ones. Banks typically make lots of people "V.P."s so you know you're talking to somebody important. The CEO of my last company said, "you could call me the janitor as long as I got paid more than you." When it comes to developer positions, an often used term is "Senior" and it seems to mean different things at different places.

What is "The Senior"? 

At a previous company, a large defense contractor, there was a technical progression for Software Engineers: Associate -> Engineer -> Senior -> Staff -> Senior Staff -> Principle. It went on from there but not many reached the higher ones. (Remember that previous CEO of mine? ; ) Being a "senior" at that company put you squarely in at a Level 3 Technical position, and was directly related to your experience, education and pay scale. Outside of these extremely large organizations, a "senior developer" means many different things. And it is not consistent among companies.

Sometimes the title is self-defined. If someone thinks they are "senior" and can convince their boss or hiring manager the same, they'll get the title. Some companies have (loosely or strictly) defined criteria for what senior means, and some are too small to think about titles so it seems like people just make things up. I'm looking at you, "Chief Awesomeness Officer at New Startup Company." Everyone there gets a good title because both of you needed cool business cards : )

Is a senior based on experience in years? Skill? A gut feeling - "I know it when I see it." I've seen the title claimed by people that were skilled and/or experienced, but still felt something was lacking. They were good at what they did, but were they a senior in my eyes? Something seemed off, the title did not match.

Trust

To wrap up, for organizations without a defined progression structure, it comes down to trust. What can I trust this person with? 

• new team member/mentee? 
• entire team?
• research project or incubator idea?
• maintain a legacy project that business critical? 
• product roadmap?
• deadline?
• customer (interaction)?

Some people might have skills at some of these, and some experience as well. Ultimately it comes back to the stakeholders, and if they can trust their "Senior" with their product. Placing people in their strength areas is important, and in my opinion, a senior could simply be trusted with more. Maybe more in a few select areas, or just more areas in general. 

In the end, do not worry about titles. Keep working hard and growing your skill set so that you can be trusted with more. A good indication of what you could do is what you have already done (e.g. - What have you done in production setting that earned money?) 

Stakeholders will notice, and are seeking to find, people they can trust with their product. 

Performance Matters

Performance matters. And when we develop code we want it to be lean and efficient. Those algorithm courses we took in college and the study of Big O notation surely lets us write performant software. Algorithms that are fast, using the minimal amount of memory are sure to wow our stakeholders!

[Those of you working in the embedded space can probably skip this entire post. Performance does matter where CPU, GPU and RAM are limited. I cut my teeth for years programming towards and recording Technical Performance Measures on avionics display software. Every millisecond counted and when our load time requirement of "3 seconds" failed because of "3012 ms" - anything is on the table to increase performance. If performance is the requirement, it matters everywhere, and you should care all the time! ]

When does performance matter?

Unless performance is part of your requirements, it doesn't.

Most game and app developers, or those using modern web technologies (front end or server-side), well, performance does not matter that much.

At least, it does not matter that much right now.

When developing a modern system, do not focus on the optimal performance of your code in the first pass. Yes, you might be able to hand code a more efficient sorter than .sort() and you might save a few bytes from your network packets if you minify/uglify your payloads yourself. You might even move an algorithm from O(n^2) to O(n log n) in only a few hours.

The thing is, it just does not matter right now. Until your code is deployable in production, time spent optimizing and tweaking for the sake of algorithm performance is wasted time. Get it working. Make sure it is robust, passes your tests and can be deployed. That is the only time to go back and optimize. Focus on writing readable, maintainable, testable, deployable code first.

Does performance ever matter

For most projects, it probably doesn't. It could be a good exercise to code some whiz-bang algorithm or try to reduce the number of statements or calls needed in a function. Once your software is working and deployed is the time to know if performance matters. Why spend time optimizing something that might change? Or a feature that gets cut?

Consider these things as you decide if might matter:

Human-speed vs computer speed

Computers are really fast. Humans are not. If you are optimizing for something that will be noticed at human speed, don't. Why worry about a list of 100, 1000, or 10,000 items? You CPU will burn through those operations whether sorting or mapping or whatever. If the function you are performing is part of a user interaction, they will not notice the time savings between 157ms and 194ms. And a computer will do a lot in those 37ms. 

How often does this happen

Some functions and data flows happen often and concurrently. Speeding up those could have noticeable gains, even to us slow humans. However, some flows happen very irregularly. We have a special admin action that will gather a certain report. The report is costly to run, but is only requested maybe weekly. If all our concurrent users asked for this report every few seconds, our system would come to a halt! Time to optimize! As it is, the time needed to optimize is not worth the single, transient blip. Let's spend our effort on more worthwhile User Stories. 

Just scale up

Hardware is cheap. Can your current performance metric just be solved by buying a bigger machine? If your DB layer is running slow, is it worth your time to profile and optimize all your SQL statements and maybe rearrange your data tables? Or could you just buy a bigger server? Same for CPU, RAM, Network, etc. Do not sweat these performance decisions too early (after your initial planning) because sometimes a bigger machine will fix a lot of problems. In today's cloud world, a push of a button and little more yearly expense could save hundreds of hours of Dev/QA time. 

How to know if performance matters

Ultimately, you'll never know if performance matters if you are not measuring it. Performance metrics are absolutely necessary to 1) know where to focus and 2) know if it worked! Anyone that tells you "that's slow" or code reviews "that's not efficient" has absolutely no data to back that up! What is "slow"? What is "efficient"? Is there a suggestion that will satisfy this arbitrary feeling of slow? Until you can measure performance, you cannot know what is not performant or if you got better!

For a modern web system, you will see performance losses at the system (and typically network) level more than your code. Making 10 HTTP calls in series? You might notice that. Consider how those can be reduced or run in parallel. Is your DB more efficient with multiple JOINs or separate queries? What user actions are used the most? What are the slow ones? What is most efficient to make stakeholders happy? 

Start measuring and measure as much as you can. Then you'll really know where performance matters.