AWS tagging best practices – 5 things to know

I read AWS tagging best practices whitepaper which was published in December 2018 and distilled 5 takeaways.

1. Use cases – tags have several use-cases including:

  • Cost allocation – using AWS Cost Explorer you can break down AWS costs by tag
  • Access Control – AM policies support tag-based conditions
  • Automation – for example tags can be used to opt into or out of automated task
  • AWS Console Organization and Resource Groups – e.g. create a custom console that organizes and consolidates AWS resources based on one or more tags
  • Security Risk Management – use tags to identify resources that require heightened security risk management practices
  • Operations Support – I find this use case tightly related to the automation use case

2. Standardized tag names and tag values

There are only two hard things in Computer Science: cache invalidation and naming things.

Phil Karlton (check here)

A good practice as suggested in the whitepaper is to gather tagging requirements from all stakeholders and only then start implementing but a minimal step can be to define a convention for tags names and values that everyone can follow, see example from the document below.

tag names example


3. Cost allocation tags delay – this is something I experienced personally – “Cost allocation tags appear in your billing data only after you have (1) specified them in the Billing and Cost Management Console and (2) tagged resources with them”. And even then it can take around 24 hours to appear, take it into account.


4. Tag everything – sounds trivial but sometimes organizations tag only some of the resources, tag everything you can to get a more comprehensive and accurate data of your expenses. A nice feature in the Billing and Cost Management Console is the ability to find resources the don’t have a specific tags so you can easily find out what you missed.


5. Tags limitations – until 2016 AWS allowed up to 10 tags for a given resource. The current limit is 50. It definitely allows much more but it is still a limit to bear in mind when creating a tagging strategy. One way to avoid it is by using compound values, e.g. “anycompany:technical-contact = Susan Jones;sue.jones@anycompany.com; +12015551213” rather than a tag for each attribute (e.g. “anycompany:technical-contact-name = Susan Jones”).

4 interesting things (24/06/2021) – Hebrew

5 years ago I published a blog post about 5 blogs I read in Hebrew. three of those are still live and kicking and I enjoy them (reversim, software archiblog, the bloggerit) the other two are no longer active. Additionally, in those 5 years podcasts became much more popular so I also included 2 podcasts I listen to.

Maya writes algorithms – Maya started this blog while studying for job interviews. In the first posts she presented questions she bumped into and her solutions (and the stream of thought that brought her to those solutions). Later posts also include writing about specific tools (e.g kubectl, git hooks) or interpersonal skills like talking in conferences, being prepared for a code review, etc.


https://algoritmim.co.il/

Internet Israel – Ran Bar Zik is a very experienced Full stack developer and Tech journalist who is also well known for his dad jokes. He writes mostly about Front End and security (but not only) and published several books about software development in Hebrew (those are usually very hard to find).


https://internet-israel.com/

Big Picture (podcast) – a podcast about tech and strategy. Each episode is a deep dive into the strategy of one company such as snapchat, spotify, twilio, etc.

https://bigpicture.buzzsprout.com/

No Tarbut (podcast)- podcast about the daily life of software engineering teams. The topics range from more tech related episodes such as  monitoring, tools, etc. to so-called softer topics such as performance review, leading without authority, salary discussion, creating an inclusive culture. 

http://notarbut.co/

5 interesting things (20/06/2021)

9 Steps to Software Project Handovers – handover is always a challenge and especially when a person leaves the organization and is no longer available for questions or able to access the resources. Similar issues can also arise when you leave the project for a while and then come back – you don’t alway remember all the tricks you used to run the code or the tiny bits of each function. This post suggests practical steps and behaviours that many of them can be TL;DRed with the Zen of Python – “Explicit is better than implicit.”.
https://betterprogramming.pub/9-steps-to-software-project-handovers-9325fbb72cfc

How to make an awesome Python package in 2021 – this post is a walk through building a python package. My main issue with it is the dependency management. I would put it in a different file, separate the development and usage dependency and lock the version – or shortly would rather use pipenv or poetry instead of pip but this could also be achieved with pip.

https://antonz.org/python-packaging/

A Simple Framework for Software Engineering Management – the suggested framework is indeed easy – 3 types of responsibilities (people management, delivery leadership and technical system ownership) vs 3 ranks of priorities (issues, things that are ok, ideas and aspirations). This framework is a good starting point for engineering leaders but also for engineers that can switch the people management with colleagues relations or similar or for personal growth. 

https://medium.com/swlh/a-simple-framework-for-software-engineering-management-f70b216540f2

Full Cycle Data Science (FCDS) – this is a heavy read but worth it both for data practitioners  and managers. Data science projects fail often. Sometimes it is because the problem is not defined well, other times because there is not enough data, data is not relevant, etc. FCDS tries to cast light and solve some of those problems – “In a nutshell, FCDS is a way of life that enables a single data practitioner to close the full product lifecycle and independently deliver end-to-end products, focusing only on where they bring added value”.
https://towardsdatascience.com/fcds-b2d2e6b08d34

Endorse People Publicly, and Other Actions for Allies –  Better Allies is an approach of making everyday actions to create inclusive and engaging workplaces. This post is a weekly newsletter where Karen Catlin (Advocate for Inclusive Workplaces) shares five simple actions to create a more inclusive workplace and be a better ally. This is a weekly reminder to be aware of biases and gaps and ideas to small and consistent changes that can make us and the people around us more comfortable and help everyone be the best version of themselves.
https://code.likeagirl.io/endorse-people-publicly-and-other-actions-for-allies-9352915c0956

5 interesting things – AWS edition (18/06/21)

As I collect items for my posts and wait until I have time to write about them I noticed I have many items related to AWS and decided to have a special edition.


12 Common Misconceptions about DynamoDB – many times our beliefs about certain tools or technology are based on hearing more than doing or doing but not getting into the depth of things and when running into a problem solving it with a solution we already know. This post describes features and qualities of DynamoDB that are sometimes ignored.

https://dynobase.dev/dynamodb-11-common-misconceptions/

Related Bonus – I really liked the link to Alex DeBrie post about single table design with DynamoDB

https://www.alexdebrie.com/posts/dynamodb-single-table/

AWS Chalice – it is not an official offering but rather a python code package for writing serverless applications. The syntax is very similar to Flask while there is a native support for local testing, AWS SAM and Terraform integration, etc. Disclaimer – if you are on multi-cloud I would not move from Flask or FastAPI to Chalice. Also note the used services (AWS lambda, AWS API Gateway, etc.) limits and make sure they don’t limit your app.

https://aws.github.io/chalice/index

Related Bonus – auth0 tutorial on How to Create CRUD REST API with AWS Chalice
https://auth0.com/blog/how-to-create-crud-rest-api-with-aws-chalice/


ElectricEye – “ElectricEye is a set of Python scripts (affectionately called Auditors) that continuously monitor your AWS infrastructure looking for configurations related to confidentiality, integrity and availability that do not align with AWS best practices.”. It is hard to know and follow all AWS best practices and this bundle of scripts is supposed to help uncover those. I have not tried it myself yet but it seems promising.
https://github.com/jonrau1/ElectricEye


My Comprehensive Guide to AWS Cost Control – computing and cloud costs take a big portion of every tech organization those days. Being a more valuable team member also means being aware of the costs and choosing wisely between the different alternatives.

https://corey.tech/aws-cost/


The Best Way To Browse 6K+ Quality AWS GitHub Repositories – most of the time we are not inventing the wheel and someone probably already did something very similar to what we are doing. Let’s browse github to find it and accelerate our process.

https://app.polymersearch.com/discover/aws

Bonus – AWS snowball – I found out that this service exists only this week and it blew my mind – https://aws.amazon.com/snowball/