Renovate is a great tool to know about. For Go, you can keep modules updated automatically, but still leverage a pull request review process to allow automated checks to run before allowing the update.

This is particularly useful with Terraform dependencies, which I consider notoriously difficult to keep updated. Instead of needing to use ranges for modules, you can start specifying exact versions and this GitHub app will automatically check for updates periodically and submit version bumps.

Why? You can have a Terraform plan previewed and checked for any errors on a new version update with no work. This means your blast radius on updates would be reduced as you are staying up to date and previewing each update as it’s available.

No more 5 months of updates and figuring out what went wrong 😁

Here’s an example json config that shows how to allow automerging, while respecting minor/major version updates not enabling automerge.

Note that you’d want to install the auto-approver app they document in the marketplace if you have pull request reviews required.

In addition, if you use CODEOWNERS file, this will still block automerge. Consider removing that if you aren’t really leveraging it.

Progress

• Evaluated gorm usage best practices with Slack Gopher community.
• Obtained a great example to get me started on go routine and channels usage with multi-database queries.

Do you have a Chrome suggestion for a domain, url, or specific site location that you don’t want anymore?

You can remove an invalid suggestion that you don’t want popping up each time by using shift+delete.

If it’s the first entry it will remove it, or use arrow keys to highlight a different entry and press the same command.

Also relevant: To Delete Chrome Address Bar Suggestions with Mouse

Day 25 of 100

progress

• Worked with Gorm, my first experience with ORM based querying.
• Used gofakeit with gorm to connect to MSSQL Server in Docker and randomize name entries.
• Learned a bit about Context package and how it helps with propagation of cancellation.
• As a new user to this, the examples were very confusing as it mixed up go-mssqldb along with examples using just gorm. As I get better with it, I’ll try to log better introductory examples.

links

• Gorm
• Gofakeit

Day 24 of 100

progress

• Used glamour to render some nice console output.
• Formatted text testing some text tooling.
• Progressbar ui tested.
• Connected successfully to MSSQL Docker instance and returned results of query, rendering to to console .

links

• Glamour
• go-mssqldb

Day 23 of 100

progress

• Used Viper to load configuration for a CLI tool.
• Ran into problems with trying to print out map[string]interface{} type. Lots of magic performed by .NET to do this type of action. This is a lot more hands-on 😁.
• Had stability issues with VSCode today, so I finally switched over to Intellij with the Go plugin and it worked well. The keyboard mappings are different so that was painful, but still overall a good experience that got me unblocked.

links

• Viper
• Tablewriter

Day 22 of 100

progress

Using Dash, I read through much of the language specification. Dry reading for sure, but helped a bit in understanding a little more on stuff like arrays, slices, loops, etc.

Nothing profound to add, except to say I don’t think I want to write a language specification.

Day 21 of 100

progress

• Signed up for exercism.io, which is a pretty great website to work through progressively harder exercises.
• Did Hello world to start with as requires progressive steps through the exercises.
• Did a string concatenation exercise as well (Two Fer).

I like the mentor feedback system concept and submission of work. After I finish this, would be good to add myself as a mentor and contribute back to this community. This is a fantastic concept to help get acclimated to a new language and do progressively harder exercises to better learn the language usage.

links

• Two Fer

Day 20 of 100

progress

Hackerrank challenge “Bubble Sort”

Day 19 of 100

progress

Hackerrank challenge “Counting Valleys”

Day 18 of 100

progress

Hackerrank challenge “Sales by Match”

Excited. Have a new solution in the works to deploy Ola Hallengren via SSM Automation runbook across all SQL Server instances with full scheduling and synchronization to S3. Hoping to get the ok to publish this soon, as I haven’t seen anything like this built.

Includes:

• Building SSM Automation YAML doc from a PS1 file using AST & metadata
• Download dependencies from s3 automatically
• Credentials pulled automatically via AWS Parameter Store (could be adapted to Secrets Manager as well)
• Leverage s5cmd for roughly 40x faster sync performance with no aws-cli required. It’s a Go executable. #ilovegolang
• Deployment of a job that automates flipping instances to FULL or SIMPLE recovery similar to how RDS does this, for those cases where you can’t control the creation scripts and want to flip SIMPLE to full for immediate backups.
• Formatted deployment summary card sent with all properties to Microsoft Teams. #imissslack
• Management of these docs via terraform.
• Snippet for the setup of an S3 lifecycle policy automatically cleanup old backups. (prefer terraform, but this is still good to know for retro-active fixes)

I’m pretty proud of this being done, as it is replacing Cloudberry, which has a lot of trouble at scale in my experience. I’ve seen a lot of issues with Cloudberry when dealing with 1000-3000 databases on a server.

Once I get things running, I’ll see if I can get this shared in full since it’s dbatools + Ola Hallengren Backup Solution driven.

Also plan on adding a few things like on failure send a PagerDuty incident and other little enhancements to possible enable better response handling.

Other Resources

• dbatools
• Ola Hallengren
• AWS Docs on Automation Runbooks
• s5cmd
• AWS Quick Start for Microsoft SQL Server

I asked my daughter (3) how much she loved me. She held up her hands and said: “Five”.

I’ll take that as a win considering that’s all the fingers on that hand. 😂

Free Means You Are the Product

Over time, I’ve begun to look at products that are free with more judgment. The saying is: “If it’s free, you are the product”. This often means your data and privacy are compromised as the product.

This has resulted in me looking more favorably at apps I would have dismissed in the past, such as Leave Me Alone.

Leave Me Alone

The notion of buying credits for something I could script, click, or do myself made me use sporadically last year. This year, I took the plunge and spent $10 and appreciate the concept and cost.

If you have a lot of tech interaction, you’ll have a slew of newsletter and marketing subscriptions coming your way. This noise can drown your email.

I saw one Children’s clothing place that got my email on a receipt generate an average of 64 emails a month!

Leave Me Alone helps simplify the cleanup process by simplifying the summary of noisiest offenders, and one-click unsubscribes to any of these.

You can use an automatically generated rating based on ranked value on mailing lists, read engagement, number of emails sent monthly, and more.

Take a look, the free start is enough to figure out if you like it.

Other Tools

Combine this type of tool with:

• Kill The Newsletter
• Inoreader (RSS Reader)
• Subscription Score: a really promising tool made by the same folks, but haven’t added at this time as price seems a bit high for this specific feature if I’m already using their app. (at this time $49 a year). Be nice if this was a feature provided automatically to those who bought 250 credits or more since it’s powered by the data mining of lists users unsubscribe from the most.

You’ll be more likely to keep up to date with this noise reduced. Last tip: Add GitHub Release notes like Terraform and others as a subscription in your RSS reader, and it might reduce the noise via email and slack on releases.

Day 17 of 100

progress

• reviewed adding excel conversion to cli
• shelved this after reviewing implementation requirements
• this is one of those cases where PowerShell makes much more sense for adhoc work as converts pscustomobject (similar to struct) via pipeline automatically to excel sheet.

Day 16 of 100

progress

• refactored AWS SDK call to export a named file using flags.
• Iterated through regions so cli call aggregated all results from all regions into single JSON.
• Working with v1 makes me want v2 so much more. The level of pointers required is ridiculous. At one point I had something like &*ec2 due to the SDK requirements. Having to write a filter with: Filters: { Name: aws.String("foo")} is so clunky. I believe in v2 this is greatly simplified, and the code is much cleaner.

links

• DescribeRegionsInput

Day 15 of 100

progress

• figured out scope issues with pointer and struct
• Used omitempty in struct
• exported final report in json format after searching for matching image id from ec2 instance image id
• Find it interesting how much more wordy the go search method was, but appreciate it in a way as the “syntactic” sugar that’s missing also is the reason there is more complication at times in languages like PowerShell/C#.

Day 14 of 100

progress

• built golang function with aws-sdk that returned ec2 instances, images
• Joined the data together together to search for matching image from the ec2 metadata
• generated json report from results and final struct

Day 14 of 100

progress

• Migrated my new aws lambda logger from zap to zerolog. Zap gave me some problems initially so zerolog is my favorite structured logger right now, much simpler.
• Constructed go-task runner file for launching go test and go build/run.
• Structured logging required a little bit of refactor but worked.

Here’s an example of providing back a logged string (don’t log secrets normally, but I’m in testing phase) with structure.

	log.Debug().
		Str("decodedBinarySecret", decodedBinarySecret).
		Str("secretString", secretString).
		Msg("Depending on whether the secret is a string or binary, one of these fields will be populated.")

Based on my improved understanding of conversions vs type assertions, the need to convert using a “cast” (Go calls these conversions, and yes it makes a copy in memory for this):

log.Info().Str("requestDump", string(requestDump)).Msg("request information")

Type assertions are done when working with an interface. I’m still working on my understanding of interfaces as they are their own beast in Go. Unlike most other languages, a Go type implements an interface when all the required methods are matched. This provides a great deal of the flexibility in Go interfaces.

The scoping of the interfaces is important, and while I listened to a lecture on this, I didn’t yet work through the interface design principles to ensure the best resusability/narrowness of scope concepts. I think that’s going to take more “getting my hands dirty” for it to click.

links

• zerolog

I couldn’t get past this for a while when I accidentally stumbled across a fix. I believe the fix was merged, however this problem still existed in 0.13.4 so I stuck with it.

When investigating the cause, I found this PR which intended this to be the installer behaviour for the implicit global cache, in order to match 0.12. Any providers found in the global cache directory are only installed from the cache, and the registry is not queried. Note that this behaviour can be overridden using provider_installation configuration. That is, you can specify configuration like this ~/.terraform.d/providercache.tfrc

GitHub Issue Comment

I used the code snippet here: micro ~/.terraform.d/providercache.tfrc

Wasn’t sure if it was interpreted with shell, so I didn’t use the relative path ~/.terraform.d/plugins, though that might work as well.

provider_installation {
  filesystem_mirror {
    path = "/Users/sheldonhull/.terraform.d/plugins"
  }
  direct {
    exclude = []
  }
}

After this terraform init worked.