Tag Archives: coding

Learning Go Episode 1 – Environment, Go Workspace, GOPATH/GOROOT, Types, and more Introduction

This is episode one of a multi-part series on “The Go Programming Language“. Not necessary, but if you’d like to follow along you can also pick up the book “The Go Programming Language” by Alan A. A. Donovan and Brian W. Kernighan. At the bottom of the description I have a link to the book publisher’s website and the respective book. I’ll be using that as a guideline and using a number of examples from the book. However I’ll also be adding a lot of additional material around Goland IDE from Jetbrains and Visual Studio Code. The video link to this session is at the bottom of the post, scroll all the way down and it’s waiting for you there.

3:28 – Getting started, introducing that the session I’m starting with a completely new Ubuntu Linux load so that I ensure we cover all of the steps to get up and running. These steps, even though they’re on Linux are reproducible on Windows 10 and MacOS, so any operating system is usable to follow along with, with only minor discrepancies.

5:04 – Introducing the book that I’ll be using as a guideline reference so that viewers can also follow along with a physical book. I’m a big fan of multisensory learning, so between a book, the stream, being able to ask questions in the channel, it’ll give viewers a chance to learn and undertake their coding adventures in Go using all sorts of methods.

Book Reference: “The Go Programming Language” by Alan A. A. Donovan and Brian W. Kernighan

6:58 – Discussing where Go is located on the web related to Github and the golang.org site that is useful in that one can even try out little snippets of Go code itself, on the site!

Github: https://github.com/golang/go
Golang: https://golang.org

10:40 – Setting export in the .bashrc file (or .bash_profile on MacOS or environment variables on Windows 10). Speaking of Windows 10 specifically, Linda Gregier wrote up a great blog post on getting Go setup on Windows specifically.

14:50 – Setting up the Go workspace path for GOPATH using the standard Go convention. From here I get into the first “Hello World!” with Go.

15:34 – Mention of setting up Go on a Docker container and how it is easier, but we’re staying focused on setting it up completely from scratch.

18:20 – Starting first code, a standard “Hello World” program.

19:50 – First build of that “Hello World” program.

20:34 – Here I introduce go run and how to execute a singular file instead of building an entire project.

21:32 – Installing some IDE’s to use for developing Go applications. The first two up for installation is Visual Studio Code and JetBrains Goland.

29:00 – A first variable, what is it, and how to declare one in Go in one of the ways one can declare a variable in Go!

31:08 – Introducing the terminal in Visual Studio Code.

37:12 – A little example of OBS, how I’m using it, and how I interact back and forth with chat and related tooling plus the virtual machine itself.

42:36 – Changing themes and adding plugins for Goland. In the plugins I also find the most epic of status bars, the Nyan Cat!

59:00 – Here I start to get back into some more specific Go details. Starting off with a Go command line parsing application. At this point I also cover several additional ways to declare variables, speak more about short declarations, and other ways to declare, assign, and use variables in Go.

At this point I also go through a number of examples to exemplify how to go about declaring variables, build, run, and explore the details of the code. Further along I also get into string formatting, concatenating, and related string manipulation with Go.

Other details include taking a look at extra ways to figure out Go code using autocomplete inside Goland and other exploratory features. Eventually before wrapping up I broach pointers, tuple declaration techniques, and how to declare additional functions beyond func main().

1:58:40 – Adding dependencies and generating random data. At this point I bring in a dependency. But before pulling in the dependency, after introducing it, I show how to go about doing.

2:00:10 – New machine, and I run into git not being available. The go get command uses git to pull dependencies so I go about why this is needed and the steps to install on Ubuntu.

2:09:20 – Introduction to more concepts around dependencies, what go get does versus managing dependencies with Go Dep.

2:10:00 – Installing Go Dep; MacOS, using curl, Linux installation, and a question sort of remains to get it running on Windows. The easiest method is using chocolatey however, so check that out if you’re going the Windows route.

2:15:20 – Setting up Go Dep integration with Goland.

2:23:55 – Showing off Goland’s commit dialog and some of the respective options.

Creating Distributed Database Application Starter Kits

I’ve boarded a bus, and as always, when I board a bus I almost always code. Unless of course there are people I’m hanging out with then I chit chat, but right now this is the 212 and I don’t know anybody on this chariot anyway. So into the code I go.

I’ve been re-reviewing the Docker and related collateral we offer at DataStax. In that review it seems like it would be worth having some starter kit applications along with these “default” Docker options. This post I’ve created to provide the first language & tech stack of several starter kits I’m going to create.

Starter Kit – The Todo List Template

This first set of starter kits will be based upon a todo list application. It’s really simple, minimal in features, and offers a complete top to bottom implementation of a service, and an application on top of that service all built on Apache Cassandra. In some places, and I’ll clearly mark these places, I might add a few DataStax Enterprise features around search, analytics, or graph.

The Todo List

Features: The following detail the features, from the users perspective, that this application will provide. Each implementation will provide all of these features.

  • A user wants to create a user account to create todo lists with.
  • A user wants to be able to store a username, full name, email, and some simple notes with their account.
  • A user wants to be able to create a todo list that is identified by a user defined name. (i.e. “Grocery List”, “Guitar List”, or “Stuff to do List”)
  • A user want to be able to logout and return, then retrieve a list from a list of their lists.
  • A user wants to be able to delete a todo list.
  • A user wants to be able to update a todo list name.
  • A user wants to be able to add items to a todo list.
  • A user wants to be able to update items in the todo list.
  • A user wants to be able to delete items in a todo list.

Architecture: The following is the architecture of the todo list starter kit application.

  • Database: Apache Cassandra.
  • Service: A small service to manage the data tier of the application.
  • User Interface: A web interface using React/Vuejs ??

As you can see, some of the items are incomplete, but I’ll decide on them soon. My next review is to check out what I really want to use for the user interface, and also to get a user account system figured out. I don’t really want to create the entire user interface, but instead would like to use something like Auth0 or Okta.

May I Ask?

There are numerous things I’d love help with. Are there any user stories you think are missing? Should I add something? What would make these helpful to you? Leave a comment, or tweet at me @Adron. I’d be happy to get some feedback and other’s thoughts on the matter so that I can ensure that these are simple, to the point, usable, and helpful to people. Cheers!

Twitz Coding Session in Go – Cobra + Viper CLI with Initial Twitter + Cassandra Installation

Part 2 of 3 – Coding Session in Go – Cobra + Viper CLI for Parsing Text Files, Retrieval of Twitter Data, Exports to various file formats, and export to Apache Cassandra.

UPDATED PARTS:

  1. Twitz Coding Session in Go – Cobra + Viper CLI for Parsing Text Files
  2. Twitz Coding Session in Go – Cobra + Viper CLI with Initial Twitter + Cassandra Installation (this post)
  3. Twitz Coding Session in Go – Cobra + Viper CLI Wrap Up + Twitter Data Retrieval

Updated links to each part will be posted at bottom of  this post when I publish them. For code, written walk through, and the like scroll down below the video and timestamps.

Hacking Together a CLI Installing Cassandra, Setting Up the Twitter API, ENV Vars, etc.

0:04 Kick ass intro. Just the standard rocking tune.

3:40 A quick recap. Check out the previous write “Twitz Coding Session in Go – Cobra + Viper CLI for Parsing Text Files” of this series.

4:30 Beginning of completion of twitz parse command for exporting out to XML, JSON, and CSV (already did the text export previous session). This segment also includes a number of refactorings to clean up the functions, break out the control structures and make the code more readable.

In the end of refactoring twitz parse came out like this. The completed list is put together by calling the buildTwitterList() function which is actually in the helpers.go file. Then prints that list out as is, and checks to see if a file export should be done. If there is a configuration setting set for file export then that process starts with a call to exportParsedTwitterList(exportFilename string, exportFormat string, ... etc ... ). Then a simple single level control if then else structure to determine which format to export the data to, and a call to the respective export function to do the actual export of data and writing of the file to the underlying system. There’s some more refactoring that could be done, but for now, this is cleaned up pretty nicely considering the splattering of code I started with at first.

50:00 I walk through a quick install of an Apache Cassandra single node that I’ll use for development use later. I also show quickly how to start and stop post-installation.

Reference: Apache Cassandra, Download Page, and Installation Instructions.

53:50 Choosing the go-twitter API library for Go. I look at a few real quickly just to insure that is the library I want to use.

Reference: go-twitter library

56:35 At this point I go through how I set a Twitter App within the API interface. This is a key part of the series where I take a look at the consumer keys and access token and access token secrets and where they’re at in the Twitter interface and how one needs to reset them if they just showed the keys on a stream (like I just did, shockers!)

57:55 Here I discuss and show where to setup the environment variables inside of Goland IDE to building and execution of the CLI. Once these are setup they’ll be the main mechanism I use in the IDE to test the CLI as I go through building out further features.

1:00:18 Updating the twitz config command to show the keys that we just added as environment variables. I set these up also with some string parsing and cutting off the end of the secrets so that the whole variable value isn’t shown but just enough to confirm that it is indeed a set configuration or environment variable.

1:16:53 At this point I work through some additional refactoring of functions to clean up some of the code mess that exists. Using Goland’s extract method feature and other tooling I work through several refactoring efforts that clean up the code.

1:23:17 Copying a build configuration in Goland. A handy little thing to know you can do when you have a bunch of build configuration options.

1:37:32 At this part of the video I look at the app-auth example in the code library, but I gotta add the caveat, I run into problems using the exact example. But I work through it and get to the first error messages that anybody would get to pending they’re using the same examples. I get them fixed however in the next session, this segment of the video however provides a basis for my pending PR’s and related work I’ll submit to the repo.

The remainder of the video is trying to figure out what is or isn’t exactly happening with the error.

I’ll include the working findem code in the next post on this series. Until then, watch the wrap up and enjoy!

1:59:20 Wrap up of video and upcoming stream schedule on Twitch.

UPDATED SERIES PARTS

    1. Twitz Coding Session in Go – Cobra + Viper CLI for Parsing Text Files
    2. Twitz Coding Session in Go – Cobra + Viper CLI with Initial Twitter + Cassandra Installation (this post)
    3. Twitz Coding Session in Go – Cobra + Viper CLI Wrap Up + Twitter Data Retrieval

 

New Live Coding Streams and Episodes!

I’ve been working away in Valhalla on the next episodes of Thrashing Code TV and subsequent content for upcoming Thrashing Code Sessions on Twitch (follow) and Youtube (subscribe). The following I’ve broken into the main streams and shows that I’ll be putting together over the next days, weeks, and months and links to sessions and shows already recorded. If you’ve got any ideas, questions, thoughts, just send them my way.

Colligere (Next Session)

Coding has been going a little slow, in light of other priorities and all, but it’ll still be one of the featured projects I’ll be working on. Past episodes are available here, however join in on Friday and I’ll catch everybody up, so you can skip past episodes if you aren’t after specific details and just want to join in on future work and sessions.

In this next session, this Friday the 9th at 3:33pm PST, I’m going to be working on reading in JSON, determining what type of structure the JSON should be unmarshalled into, and how best to make that determination through logic and flow.

Since Go needs something to unmarshall JSON into, a specific structure, I’ll be working on determining a good way to pre-read information in the schema configuration files (detailed in the issue listed below) so that a logic flow can be implemented that will then begin the standard Go JSON unmarshalling of the object. So this will likely end up including some hackery around reading in JSON without the assistance of the Go JSON library. Join in and check out what solution(s) I come up with.

The specific issue I’ll be working on is located on Github here. These sessions I’m going to continue working on, but will be a little vague and will start working on the Colligere CLI primarily on Saturday’s at 10am. So you can put that on your schedule and join me then for hacks. If you’d like to contribute, as always, reach out via here, @Adron, or via the Github Colligere Repository and let’s discuss what you’d like to add.

Getting Started with Go

This set of sessions, which I’ve detailed in “Getting Started with Go“, I’ll be starting on January 12th at 4pm PST. You can get the full outline and further details of what I’ll be covering on my “Getting Started with Gopage and of course the first of these sessions I’ve posted details on the Twitch event page here.

  • Packages & the Go Tool – import paths, package declarations, blank imports, naming, and more.
  • Structure – names, declarations, variables, assignments, scope, etc., etc.
  • Basic Types – integers, floats, complex numbers, booleans, strings, and constants.

Infrastructure as Code with Terraform and Apache Cassandra

I’ll be continuing the Terraform, bash, and related configuration and coding of using infrastructure as code practices to build out, maintain, and operate Apache Cassandra distributed database clusters. At some point I’ll likely add Kubernetes, some additional on the metal cluster systems and start looking at Kubernetes Operators and how one can manage distributed systems on Kubernetes using this on the metal environment. But for now, these sessions will continue real soon as we’ve got some systems to build!

Existing episodes of this series you can check out here.

Getting Started with Multi-model Databases

This set of sessions I’ve detailed in “Getting Started with a Multi-model Database“, and this one I’ll be starting in the new years also. Here’s the short run down of the next several streams. So stay tuned, subscribe or follow my Twitch and Youtube and of course subscribe to the Composite Code blog (should be to the left, or if on mobile click the little vertical ellipses button)

  1. An introduction to a range of databases: Apache Cassandra, Postgresql and SQL Server, Neo4j, and … in memory database. Kind of like 7 Databases in 7 Weeks but a bunch of databases in just a short session!
  2. An Introduction – Apache Cassandra and what it is, how to get a minimal cluster started, options for deploying something quickly to try it out.
  3. Adding to Apache Cassandra with DataStax Enterprise, gaining analytics, graph, and search. In this session I’ll dive into what each of these capabilities within DataStax Enterprise give us and how the architecture all fits together.
  4. Deployment of Apache Cassandra and getting a cluster built. Options around ways to effectively deploy and maintain Apache Cassandra in production.
  5. Moving to DataStax Enterprise (DSE) from Apache Cassandra. Getting a DSE Cluster up and running with OpsCenter, Lifecycle Manager (LCM), and getting some queries tried out with Studio.

DataStax Developer Days

Over the last week I had the privilege and adventure of coming out to Chicago and Dallas to teach about operations and security capabilities of DataStax Enterprise. More about that later in this post, first I’ll elaborate on and answer the following:

  • What is DataStax Developer Day? Why would you want to attend?
  • Where are the current DataStax Developer Day events that have been held, and were future events are going to be held?
  • Possibilities for future events near a city you live in.

What is DataStax Developer Day?

The way we’ve organized this developer day event at DataStax, is focused around the DataStax Enterprise built on Apache Cassandra product, however I have to add the very important note that this isn’t merely just a product pitch type of thing, you can and will learn about distributed databases and systems in a general sense too. We talk about a number of the core principles behind distributed systems such as the pivotally important consistent hash ring, datacenter and racks, gossip, replication, snitches, and more. We feel it’s important that there’s enough theory that comes along with the configuration and features covered to understand who, what, where, why, and how behind the configuration and features too.

The starting point of the day’s course material is based on the idea that one has not worked with or played with a Apache Cassandra or DataStax Enterprise. However we have a number of courses throughout the day that delve into more specific details and advanced topics. There are three specific tracks:

  1. Cassandra Track – this track consists of three workshops: Core Cassandra, Cassandra Data Modeling, and Cassandra Application Development. [more details]
  2. DSE Track – this track consists of three workshops: DataStax Enterprise Search, DataStax Enterprise Analytics, and DataStax Enterprise Graph. [more details]
  3. Bonus Content – This track has two workshops: DataStax Enterprise Overview and DataStax Enterprise Operations and Security.  [more details]

Why would you want to attend?

  • One huge rad awesome reason is that the developer day events are FREE. But really, nothing is ever free right? You’d want to take a day away from the office to join us, so there’s that.
  • You also might want to even stay a little later after the event as we always have a solidly enjoyable happy hour so we can all extend conversations into the evening and talk shop. After all, working with distributed databases, managing data, and all that jazz is honestly pretty enjoyable when you’ve got awesome systems like this to work with, so an extended conversation into the evening is more than worth it!
  • You’ll get a firm basis of knowledge and skillset around the use, management, and more than a few ideas about how Apache Cassandra and DataStax Enterprise can extend your system’s systemic capabilities.
  • You’ll get a chance to go beyond merely the distributed database system of Apache Cassandra itself and delve into graph, what it is and how it works, analytics, and search too. All workshops take a look at the architecture, uses, and what these capabilities will provide your systems.
  • You’ll also have one on one time with DataStax engineers, and other technical members of the team to ask questions, talk about architecture and solutions that you may be working on, or generally discuss any number of graph, analytics, search, or distributed systems related questions.

Where are the current DataStax Developer Day events that have been held, and were future events are going to be held? So far we’ve held events in New York City, Washington DC, Chicago, and Dallas. We’ve got two more events scheduled with one in London, England and one in Paris, France.

Future events? With a number of events completed and a few on the calendar, we’re interested in hearing about future possible locations for events. Where are you located and where might an event of this sort be useful for the community? I can think of a number of cities, but organizing them into order to know where to get something scheduled next is difficult, which is why the team is looking for input. So ping me via @Adron, email, or just send me a quick message from here.

A Go Repo & Some Go Code

Wrapped up another Twitch stream (follow here) and streamed live via YouTube where the video is now (subscribe here, video here). However the more interesting part IMHO was where I broke down a few key parts of the application building features around file writes, reads, JSON marshalling, and some other functionality. I also put together a repo of the code I put together here on Github (code shown and explained below). I dove into this topic in the later part of the stream which I’ve time tagged below. For the full timeline and the rest of the video just watch from the beginning of the video. I do make some progress working on Colligere, but I’ll cover that topic in a subsequent blog entry and Twitch stream.

  • 1:32:40 – Creating a new application with Jetbrains Goland to show off how to use the Go core libraries around the user, JSON, and some basic file creation and writing.
  • 1:36:40 – At this point I start adding some basic code to pull the current user and collect some information about that user.
  • 1:40:42 – I extract the error code using the Goland refactoring feature and setup a func check() for error checking. That cleans up the inline code a bit.
  • 1:43:10 – Here I add to the user data retrieved some environment variables to that list of collected data. I also cover again, as I have a number of times, how the environment variables are pulled in IDE versus user session versus out of IDE.
  • 1:47:46 – Now I add a file exists check and start working on that logic.
  • 1:48:56 – Props to Edd Turtle on a solid site on Go. Here’s the blog entry, and respectively the path to more of Edd’s material @ https://golangcode.com/. Also, Edd seems like a good guy to follow @eddturtle.
  • 2:01:33 – Starting the JSON Work here to marshal and unmarshall.
  • 2:26:33 – At this point I push the code up to Github (repo here) using the built in Goland VCS features. I realize I’ve named the repo “adron” by accident so I rename it, close Goland, and then clone the code back down locally with Goland’s VCS features. It’s kind of interesting to see Goland go through the 2-factor auth for this too.
  • 2:58:56 – The Seattle Thrashing Code outtro!

There were a few notes I took during the session with my collected links and references for things I looked up. Those included the following:

The code for the Github repo, ended in this state. Just a single main.go file, which shows how to use several features of Go and capabilities of the core libraries.

package main

import (
	"encoding/json"
	"io/ioutil"
	"log"
	"os"
	"os/user"
	"strconv"
)

type UserInformation struct {
	Name     string   `json:"name"`
	UserId   int64    `json:"userid"`
	GroupId  int64    `json:"groupid"`
	HomeDir  string   `json:"homedir"`
	UserName string   `json:"username"`
	GroupIds []string `json:"groupids"`
	GoPath   string   `json:"gopath"`
	EnvVar   string   `json:"environmentvariable"`
}

func main() {
	currentUser, err := user.Current()
	check(err)
	changeDataForMarshalling(currentUser)
}

func changeDataForMarshalling(currentUser *user.User) {
	groupsIds, err := currentUser.GroupIds()
	check(err)
	userId, err := strconv.ParseInt(currentUser.Uid, 6, 64)
	check(err)
	groupId, err := strconv.ParseInt(currentUser.Gid, 6, 64)
	check(err)

	workingUserInformation := &UserInformation{
		Name:     currentUser.Name,
		UserId:   userId,
		GroupId:  groupId,
		HomeDir:  currentUser.HomeDir,
		UserName: currentUser.Username,
		GroupIds: groupsIds,
		GoPath:   os.Getenv("GOPATH"),
		EnvVar:   os.Getenv("NEW_STRING_ENVIRONMENT_VARIABLE"),
	}

	resultingUserInformation, _ := json.Marshal(workingUserInformation)

	filename := "collected_values.json"
	if _, err := os.Stat(filename); os.IsNotExist(err) {
		writeFileContents(err, filename, string(resultingUserInformation))
	} else {
		newUserInformation, err := openFileMakeChanges(filename)
		writeFileContents(err, filename, newUserInformation)
	}
}

func openFileMakeChanges(filename string) (string, error) {
	jsonFile, err := os.Open(filename)
	check(err)
	defer jsonFile.Close()
var changingUserInformation UserInformation
	byteValue, _ := ioutil.ReadAll(jsonFile)
	json.Unmarshal(byteValue, &changingUserInformation)
changingUserInformation.Name = "Adron Hall"
	changingUserInformation.GoPath = "/where/is/the/goland"
	newUserInformation, _ := json.Marshal(changingUserInformation)
return string(newUserInformation), err
}

func writeFileContents(err error, filename string, text string) {
	f, err := os.OpenFile(filename, os.O_CREATE|os.O_WRONLY, 0600)
	check(err)
	defer f.Close()

	if _, err = f.WriteString(text); err != nil {
		panic(err)
	}
}

func check(err error) {
	if err != nil {
		log.Fatal(err)
	}
}

The import section includes several core libraries for the application “encoding/json”, “io/ioutil”, “log”, “os”, “os/user”, and “strconv”. Then I’ve got a structure declared that I use throughout the code with various fields.

Then just for the heck of it I created a changeDataForMarshalling function and passed in userInfo and parsed the string results of gid and uid to int data types. From there the remaining values are passed in then marshalled to JSON and written to a file, depending on if it’s a new file or existing. The writing however I broke out to a function dubbed writeFileContents. Definitely some more refactoring and tweaking to really make it functional and usable, but shows easily what strconv, marshalling, and other features of these core libraries do. This code provides some examples on what functionality Colligere will use to read in schema configuration, edit, and save that schema. More about that in the next Twitch few streams.

DevRel Data: Presentation & Deductions

Before diving into conclusions, let’s take a look at some answers to questions asked. This is a slice of answers, with totals for the charts and such. After a few months of answers I’ll have another follow up to see how things may or may not change.

Do you like video material?

chart

What specifically do you, or would you like to watch in video? Screencasts, short videos, conversational, or some other type of videos?

  • Screencasts/tutorials
  • I love both screencasts going through big topics and short videos that cover smaller tips and gotchas.
  • Videos with a specific outcome as the goal, whether achieved or not. Showing the process of something.. like hey, here’s how you building out a Postgres cluster using streaming replication and repmgr and pgpool… Kind of thing.
  • Bite sized content, maybe 2 minutes, to teach me one thing.
  • Editing. No jokes, no “hey what’s up guys” with 60 second intros. Discuss the problem, then solve it.
  • Demos, learning a new way of doing something
  • Doesn’t matter short or long, but has to be deeply technical with code examples that I can actually apply
  • I watch videos mostly for fun.
  • Screencast
  • Short videos of say 5-10 minutes each covering different concept of the subject matter
  • (videos work best in a classroom setting where time/attention is precommitted, or as part of a tutorial)
  • conversational
  • Short videos.
  • If it’s too long, it ends up on my todo list forever (not good). So shorter is better. And something that benefits from visuals, rather than something that could just be written.
  • I also watch LinkedIn Learning when just starting a new tech. to get a general overview and pick up a tip or tow, then I read books and the Internet from there.
  • short videos

What kind of written material do you like?

chart2

Do you like other material mixed in that details the reason for the tech, the story, or such?

chart3

Is there anything that comes to mind, that you’d like to have me or the team I’m working with (@ DataStax) put together that you’d find useful, entertaining, or related.

  • Place priorities on designing materials for more depth (i.e., more linked material) as well as less attention-nuisance. That’s no criticism of your work, merely the gestalt of where we work — so less noise is a better way to stand out and make materials useful.
  • Maybe focus more on written material – code & architecture material (books, articles) rather than videos and twitch. It is much easier to consume and is easily googlable. Also I’d suggest making blog posts target a specific common issue or question – sometimes I see posts that I don’t really care about or the problem is so narrow that I don’t want to read about it. I’d read about building resilient and highly available architectures in various configurations.
  • Database reliability, scalability, migrations and such stuff is interesting.
  • Anything to do with machine learning.
  • Data model examples, starting up a Cassandra node, configuring YAML, etc

Deductions

I’m going to go backwards through the questions and discuss what I’ve deducted, and in some ways what has surprised me among the answers!

First there’s the “Is there anything that comes to mind, that you’d like to have me or the team I’m working with (@ DataStax) put together that you’d find useful, entertaining, or related.” request and questions.

The answers here didn’t surprise me much at all. Within DevRel from Microsoft to DataStax to Google to many other organizations we have this ongoing battle between “write a whole book on it” or “make it 2 minutes short”. It’s wildly difficult to determine what format, what timing, and what structure material needs to be in for it to be most useful to people. So when I saw the answer that reads, “Place priorities on designing materials for more depth (i.e., more linked material) as well as less attention-nuisance.” I immediately thought, “yeah, for real, but ugh…” it’s difficult. However, I’m working on more thorough material, some of it will be paywalled via LinkedIn Learning or Pluralsight and other material may be available by book in the coming months. But there will be other material that will indeed be long form how to material on how to really put things together – from scratch and from the basis of “we have X thing and need to hack it so we can add a feature”.

The next answer I got in this section that I completely agree with is increasing the focus on written material. I’m making tons of video, and I’ve got that down to the point where it’s actually easier and faster to do most of it then it is to write things down. However I realized, especially from my own point of view, that written material actually ends up being vastly more useful than video material. That’s also why, even with the video material, when I’m covering specifics I aim to provide a linkable timeline and a blog entry with the code and other changes shown in the video. Thanks for reinforcing these efforts and giving me that indirect encouragement to make this process and the results even better. More written material is on its way!

As for the database reliability, scalability, migrations, machine learning, data modeling, Cassandra node starting, and all that it’s in the queue and I’m getting to it as fast as I possibly can.

Next question I asked is, “Do you like other material mixed in that details the reason for the tech, the story, or such?

It appears, albeit not a huge contingent of people, some people are curious about biking, train coding, and making good grub! Hey, that’s groovy cuz I’ve got a show coming out which is basically the behind the scenes videos about all those topics that make the coding and technology hacking possible!

The one outlier in this set however is clearly the request for “Ways to simplify life to dig through those algorithms faster, easier, better?” which I didn’t suspect would be any different then the other answers for this questions. Which left me surprised and ill-prepared on what to do about fulfilling what is clearly a demand. I’ll have to up level my blog posts around algorithms. I did do a couple a long while ago now in “Algorithms 101: Big Sums” which I completed in Go and another I wrote up “Algorithms 101: Roads & Town Centers” which I have 90% of the answer complete but I’ve never finished the blog entry! I guess it’s time to get the algorithm train coupled up and ready to depart!

Then the question, “What kind of written material do you like?

Two options lead by a healthy margin for this question: Demos w/ Write Up and Blog Articles. With this coupled up to the first question it’s clear that written material via blog and demoes via blog should and ought to be top priority. They are, however they’re a whole helluva lot of work, so I only get them produced but so fast. Got some gems coming on Go, Bash, Cassandra, and a few other demo, tech, and historical information.

Next up was single page cheat sheets and documentation, followed closely by books. I kind of expected documentation and books, but wow that single page cheat sheets option is higher rated than I would have suspected and by proxy I’ve immediately added that to my produce this type of material list! I put it in as a very secondary thought but it’s going to get into that increased focus queue.

The last one with some semblance of demand is pamphlet size short form. This one almost seems like a fluke, but I’ll ponder putting together some of these. I know O’Reilly has their short novelette size books which cover a particular topic. They hand these out for free at conferences and seem pretty solid. Maybe I’ll work one of those into the queue? Maybe.

The other three options scraped by with 1%, so somebody was choosing them. So the vi mug isn’t a priority nor the short explainer videos. Which seems in contention with video content demands around shorter content. I guess, explainer videos just doesn’t sound useful!

The next question I just put together a top three of the results, “What specifically do you, or would you like to watch in video? Screencasts, short videos, conversational, or some other type of videos?

  1. Make screen casts.
  2. Make screen casts generally short.
  3. Make screen cases that are short and on a specific and deep dive into a topic.

This seems kind of in conflict with itself, but I’m going to aim for it and try to hone the skill further. So that I can produce screen casts, screen casts that are generally short, and make sure that these screen casts that are short are on a specific and deep dive into a topic. Whew, got it.

Finally, “do you like video material?

chart

At this time, 53.8% of you have said yes. I had guessed it would be around 50%.

I had guessed no would be about 25%, and at 23.1% I wasn’t to far off.

The other respective mishmash of answers made for interesting depth to the questions that followed this question.

Article Summary & TLDR

Produce more topic specific, detailed material around screen casts and blog entries!

End of story.

For more on this information, why I asked, and what I do check out my article titled “Evangelism, Advocacy, and Activism in The Technology Industry” and for some of the big victories for big corporations check out “The Developer Advocates – Observations on Microsoft’s New Competence“.