How Silicon Valley, in a Show of Monopolistic Force, Destroyed

If you missed @clare_liguori's Continuous Delivery session this week (like I did) then good news, it's available on-demand now 🎊

https://t.co/78b8sI2hHs

And here's my play-by-play for the session

🧵...

This is a typical CD pipeline in AWS.

This is far more complex than the most complex CD pipeline I have ever had! Just cos it's complex, doesn't mean it's over-engineered though. Given the blast radius, I'm glad they do releases carefully and safely.

If you look closely, beyond all the alpha, beta, gamma environments, it's one-box in a region first then the rest of the region, I assume starting with the least risky regions first.

For anyone thinking about going multi-region (after the recent Kinesis outage), this is one of the complexities you need to consider. To do multi-region right and deploy safely (minimize blast radius), this is one of the complexities you have to factor in.

This "deploy small at first then more broadly" principle applies to #serverless apps too, though you can't "deploy to one box". You can do it with canary deployments instead, CodeDeploy supports this practice for Lambda (using weighted aliases) out-of-the-box.

Most commonly used AWS services:

🧵👇🏻

1. Elastic Compute Cloud (EC2):

EC2 instances are basically servers with an operating system which can be used to run your applications on the internet just like you run your applications on your laptop during development.

2. Relational Database Service (RDS):

RDS is a distributed relational database service.

Amazon RDS is available on several database instance types - optimised for memory, performance or I/O - and provides six familiar database engines to choose from, including:

- Amazon Aurora
- PostgreSQL
- MySQL
- MariaDB
- Oracle Database
- SQL Server

3. Elastic Container Service (ECS):

AWS ECS is a fully managed container orchestration service.

ECS has been a foundational pillar for key Amazon services and it can natively integrate with other services such as Amazon Route 53, Secrets Manager, AWS Identity and
...

Facebook -- having taken out full-page ads in the NYT, Washington Post, and WSJ -- is generally seen as the primary victim of the new app privacy controls coming in iOS14. But Google is perhaps even more vulnerable to ATT. Why has Google remained silent? (1/X)

2/ First, background: here's a high-level overview of how ATT / IDFA deprecation impacts advertisers and ad networks, and why this whole ordeal has put advertisers and ad networks into a state of panic:

3/ Google is equally as susceptible to harm from ATT as Facebook. Google's UAC product -- esp its tROAS and tCPA campaign objectives -- relies as much on IDFA-indexed monetization and engagement data as FB's mobile product does. But Google has one big weakness wrt ATT: YouTube

4/ Broadly, view-through attribution accounts for a disproportionate % of conversions from YouTube app install impressions. This means: user sees the YT ad, doesnt click, downloads app later, & Google is able to claim it by reconciling IDFA seen at impression to IDFA seen in app

5/ View-through attribution is nonexistent in the ATT paradigm as it relies on the IDFA; some significant portion of YT's attributed conversions will evaporate. So why isnt Google vocally opposing ATT? Two reasons: consumer optics and its duality as ad network / mobile platform

One of the big promises of software is composability. You can build rich, powerful experiences out of basic building blocks.

APIs add new things to the toolbox. For example: Treasury, which lets an app/platform store, move, and track a business’

I've been a small business owner and can talk at length about SMB banking, and will later, but let's put on the software developer hat right now.

Lots of software talks about money, keeps records about money, does calculations about money, but can't *touch* money.

This is extremely frustrating when you're building SaaS apps for businesses, because you have total control over your UX right until your app needs to touch money... at which point all data about it lives in a silo you can't access.

So you generally push work to the operator.

For example, suppose you’re writing a business-in-a-box system for electricians, including an invoicing feature.

You need to be able to read bank transactions to reconcile. You probably can't. The owner can. So you ask the owner to do mind-numbing work a computer does better.

It sure would be great if your business customers had bank accounts you could actually introspect and operate on their behalves! You could just get the list of incoming payments and match against the invoices.

There is some software to write but it is not rocket science.