Almost Every infrastructure decision I endorse or regret after 4 years

It's weird that one of the reasons that you endorse AWS is that you had regular meetings with your account manager but then you regret premium support which is the whole reason you had regular meetings with your account manager.

After listing dozens of infrastructure products/projects, "My general infrastructure advice is “less is better”.

That made me laugh. Yes I get that they probably didn't use all of these at the same time.

> Picking Terraform over Cloudformation: Endorse

I, too, prefer McDonald's cheeseburgers to ground glass mixed with rusty nails. It's not so much that I love Terraform (spelled OpenTofu) as that it's far and away the least bad tool I've used in the space.

This is the best post to HN in quite some time. Kudos to the detailed and structured break-down.

If the author had a Ko-Fi they would've just earned $50 USD from me.

I've been thinking of making the leap away from JIRA and I concur on RDS, Terraform for IAC, and FaaS whenever possible. Google support is non-existent and I only recommend GC for pure compute. I hear good things about Big Table, but I've never used in in production.

I disagree on Slack usage aside from the postmortem automation. Slack is just gonna' be messy no matter what policies are put in place.

>Since the database is used by everyone, it becomes cared for by no one. Startups don’t have the luxury of a DBA, and everything owned by no one is owned by infrastructure eventually.

This post was a great read.

Tangent to this, I've always found "best practices" to be a bit of a misnomer. In most cases in software and especially devops I have found it means "pay for this product that constrains the way that you do things so you don't shoot yourself in the foot". It's not really a "practice" if you're using a product that gives you one way to do something. That said my company uses a very similar tech stack and I would choose the same one if I was starting a company tomorrow, despite the fact that, as others have mentioned, it's a ton to keep in your head all at once.

given enough time you may regret every single one of them.

(2024)

past discussion: https://news.ycombinator.com/item?id=39313623

> Regret: Not adopting an identity platform early on. I stuck with Google Workspace at the start...

I've worked with hundreds of customers to integrate IdP's with our application and Google Workspace was by far the worst of the big players (Entra ID, Okta, Ping). Its extremely inflexible for even the most basic SAML configuration. Stay far, far away.

> There are no great FaaS options for running GPU workloads

Knative on k8s works well for us, there's some oddities about it but in general does the job

There is a lot of "stuff" for liking to keep it simple. Great article though!

You will never agree 100% with someone else when it comes to decisions like this, but clearly there is a lot of history behind these decisions and they are a great starting point for conversations internally I think.

Thanks. I've been meaning to write one of these for a long time, but you went into detail in a very effective, organized way.

I also reached a lot of similar decisions and challenges, even where we differ (ECS vs EKS) I completely understand your conclusions.

Thanks for sharing, really helpful to see your thinking. I haven't fully embraced FaaS myself but never regretted it either.

Curious to hear more about Renovate vs Dependabot. Is it complicated to debug _why_ it's making a choice to upgrade from A to B? Working on a tool to do app-specific breaking change analysis so winning trust and being transparent about what is happening is top of mind.

When were you using quay.io? In the pre-CoreOS years, CoreOS years (2014-2018), or the Red Hat years?

> There are no great FaaS options for running GPU workloads, which is why we could never go fully FaaS.

modal.com???

Using GCP gives me the same feeling as vibe-coded source code. Technically works but deeply unsettling. Unless GCP is somehow saving you boatloads of cash, AWS is much better.

RDS is a very quick way to expand your bill, followed by EC2, followed by S3. RDS for production is great, but you should avoid the bizarre HN trope of "Postgres for everything" with RDS. It makes your database unnecessarily larger which expands your bill. Use it strategically and your cost will remain low while also being very stable and easy to manage. You may still end up DIYing backups. Aurora Serverless v2 is another useful way to reduce bill. If you want to do custom fancy SQL/host/volume things, RDS Custom may enable it.

I'm starting to think Elasticache is a code smell. I see teams adopt it when they literally don't know why they're using it. Similar to the "Postgres for everything" people, they're often wasteful, causing extra cost and introducing more complexity for no benefit. If you decide to use Elasticache, Valkey Serverless is the cheapest option.

Always use ECR in AWS. Even if you have some enterprise artifact manager with container support... run your prod container pulls with ECR. Do not enable container scanning, it just increases your bill, nobody ever looks at the scan results.

I no longer endorse using GitHub Actions except for non-business-critical stuff. I was bullish early on with their Actions ecosystem, but the whole thing is a mess now, from the UX to the docs to the features and stability. I use it for my OSS projects but that's it. Most managed CI/CD sucks. Use Drone.io for free if you're small, use WoodpeckerCI otherwise.

Buying an IP block is a complicated and fraught thing (it may not seem like it, but eventually it is). Buy reserved IPs from AWS, keep them as long as you want, you never have to deal with strange outages from an RIR not getting the correct contact updated in the correct amount of time or some foolishness.

He mentions K8s, and it really is useful, but as a staging and dev environment. For production you run into the risk of insane complexity exploding, and the constant death march of upgrades and compatibility issues from the 12 month EOL; I would not recommend even managed K8s for prod. But for staging/dev, it's fantastic. Give your devs their own namespace (or virtual cluster, ideally) and they can go hog wild deploying infrastructure and testing apps in a protected private environment. You can spin up and down things much easier than typical AWS infra (no need for terraform, just use Helm) with less risk, and with horizontal autoscaling that means it's easier to save money. Compare to the difficulty of least-privilege in AWS IAM to allow experiments; you're constantly risking blowing up real infra.

Helm is a perfectly acceptable way to quickly install K8s components, big libraries of apps out there on https://artifacthub.io/. A big advantage is its atomic rollouts which makes simple deploy/rollback a breeze. But ExternalSecrets is one of the most over-complicated annoying garbage projects I've ever dealt with. It's useful, but I will fight hard to avoid it in future. There are multiple ways to use it with arcane syntax, yet it actually lacks some useful functionality. I spent way too much time trying to get it to do some basic things, and troubleshooting it is difficult. Beware.

I don't see a lot of architectural advice, which is strange. You should start your startup out using all the AWS well-architected framework that could possibly apply to your current startup. That means things like 1) multiple AWS accounts (the more the better) with a management account & security account, 2) identity center SSO, no IAM users for humans, 3) reserved CIDRs for VPCs, 4) transit gateway between accounts, 5) hard-split between stage & prod, 6) openvpn or wireguard proxy on each VPC to get into private networks, 7) tagging and naming standards and everything you build gets the tags, 8) put in management account policies and cloudtrail to enforce limitations on all the accounts, to do things like add default protections and auditing. If you're thinking "well my startup doesn't need that" - only if your startup dies will you not need it, and it will be an absolute nightmare to do it later (ever changed the wheels on a moving bus before?). And if you plan on working for more than one startup in your life, doing it once early on means it's easier the second time. Finally if you think "well that will take too long!", we have AI now, just ask it to do the thing and it'll do it for you.

I see you regret Datadog but there's no alternative - did you end up homebrewing metrics, or are you just living with their insane pricing model? In my experience they suck but not enough to leave.

> “This EC2 instance type running 24/7 at full load is way less expensive than a Lambda running”.

For the same amount of memory they should cost _nearly_ identical. Run the numbers. They're not significantly different services. Aside from this you do NOT pay for IPv4 when using Lambda, you do on EC2, and so Lambda is almost always less expensive.

I disagree on Kubernetes versus ECS. For me, the reasons to use ECS are not having to pay for a control plane, and not having to keep up with the Kubernetes upgrade treadmill.

Feels like a minor glimpse into what's involved in running tech companies these days. Sure this list could be much simpler, but then so would the scope of the company's offerings. So AI would offer enough accountability to replace all of this? Agents juggling million token contexts? It's kind of hard to wrap my head around.

Great post. I even wouldn’t mind more details, especially about datadog, or as others pointed out, the kind of contradiction with aws support.

(2024)

Just FYI article is two years old

I would love to read more about the pros and cons of using a single database, if anyone has pointers to articles