wmfiv

Have you looked at Kinesis Firehose? It was pretty much build for this use case although you will still need to see if you can define a partitioning scheme probably in combination with an S3 Select query to meet your query requirements.

https://aws.amazon.com/kinesis/data-firehose/?nc=sn&loc=0

https://aws.amazon.com/blogs/aws/s3-glacier-select/

Because you already have a $50B business that runs on the slow thing. So from a risk and cost/benefit analysis making the slow thing fast sounds a lot better than "rewrite everything".

Also security, compliance, disaster recovery, many geographic / data locality issues, and maybe most importantly comfort-level for enterprise IT departments. For example we have a product in a regulated industry and running on AWS gets us past many of the hurdles our large customers throw up.

Except you’ve picked out two of the most complex and deep services as “foundational”.

Yes that's right. You can use SSM to port forward. Here's an example of the SSH configuration.

host i-* mi-*

    ProxyCommand sh -c "aws ssm start-session --target %h --document-name AWS-StartSSHSession"

You're looking for TeamCity, https://www.jetbrains.com/teamcity/.

Yeah I used the ARM price. I should have pointed that out. It's definitely a tradeoff. Here's a few things I think are advantageous for Lambda,

* Integration with all the AWS Event Sources.

* Faster autoscaling.

* No need to setup a VPC (subnets, NAT gateway, security groups, VPC endpoints potentially, etc)

* No need to setup autoscaling, multi-AZ, etc.

* No need to support long lived instances.

I don't think one is always better than the other.

Insanely expensive is definitely a flexible term. I think numbers help here.

Provisions Concurrency $8.64 / GB / month

256 MB per Lambda (Assuming Python, Ruby, NodeJS, or Rust)

$2.16 per Lambda per month

A lot of organizations can probably make a good business case for keeping 100s or even 1000s of Lambda's warm. You also don't need to keep them warm 24x7, can get an additional 12% discount using savings plans, and if you're a big guy you get your EDP discount.

That sounds right about ML startups. But ML startups or even venture funded companies are a very small percentage of companies - especially when it comes to spending signficant dollars.

It's priced at almost 100x revenue.

Most companies except the ones paying AWS/Azure/GCP a combined $100B+ per year and growing fast?

"Eating AWS's lunch" seems quite speculative. R2 is a blog post. S3 is the industry standard to the extent that everyone else creates products based on a subset of the S3 API. S3 is also a cornerstone of the AWS ecosystems which has enormous gravitational pull.

Cloudfare is an exciting company with a lot of great products. But they're less than 1% the size of AWS or Azure. Let's see what happens.

Oh that's nice! Thank you.

A potential next step if it fits your workflow is to create a macro triggered by save. I have one that optimizes imports, reformats code and do silent code cleanup.

This a life changing video by Gil Tene on this topic. Bottom line is because of the number requests to support a single customer "request", the high percentiles are the ones that actually matter.

https://www.youtube.com/watch?v=lJ8ydIuPFeU&list=WL&index=22...

Just so it's clear to everyone, companies much smaller than SAP or Microsoft self insure. In the United States virtually every employer with more than 500 employees is going to self insure.

And while these companies do have access to detailed claim data in theory, in practice access to this data is typically heavily limited a small number of HR or finance employees who are responsible for healthcare accounting and financial management and the data presented is typically restricted to a large claim report within a monthly/quarterly reporting period.

Probably need to add 4. Akka.

Depending on the project a database (Postgres) can make a nice database, queue and cache. You get transactions among all three which which makes life much simpler in the beginning and it will happily march along processing thousands or tens of thousands of TPS. You can scale by adding read replicas and eventually moving to separate databases for each purpose.

If you're on the JVM then ActiveMQ (and other Java queues) will usually run embedded and have options to use a database for persistence.

This just isn't accurate. Messaging solutions have always supported request-reply. Just as examples,

https://activemq.apache.org/how-should-i-implement-request-r...

https://nats.io/documentation/concepts/nats-req-rep/

https://www.rabbitmq.com/direct-reply-to.html

Right. For those interested OpenHFT has created a really nice set of open source solutions to do this.

https://github.com/OpenHFT/Chronicle-Queue#design

For those interested in this type of thing, Li Haoyi created an in depth look at the Scala structures.

http://www.lihaoyi.com/post/BenchmarkingScalaCollections.htm...

It includes some interesting commentary as well.

Scala and Clojure should run under pljava. Probably not a lot of people doing that though!

Java's reputation for sluggishness was really formed based on people's experience with Applets and Swing applications and especially badly written Applets and Swing applications.

Java in the real world is fast. That's why it's used as the backbone of so many large organizations and so many scale out solutions (Cassandra, Kafka, Hadoop, etc) are written in Java.

Another entry in the not Haskell category, Functional Programming in Scala is outstanding.

Absolutely. This is a sign that the system is working. Amazon doesn't have a monopoloy on jobs that allows it to pay dramatically under market for warehouse workers.

Roofing especially in a hot climate is harder more demanding work than a warehouse job. And it pays considerably more.

I'm not saying their workplace is great. I'm just saying it's not directly tied to their success. They run large logistics warehouses. That's just hard physical labor where you're paid based on production. A great big portion of the food you eat is also picked under those conditions.

Are you suggesting that by winning in ecommerce and cloud computing they're gaining a monopoloy on jobs? Seems like a stretch.

There have always been and probably always will be unpleasant jobs. I watched 6 guys replace the roof of my neightbor's house yesterday in Houston. It was 100 degrees on the ground so I'd imagine it was intensely unpleasant working 8 hours on the ashphalt shingle roof. Does that make the roofing business exploitive? Should we all abandon our roofs?

What are examples of the small businesses that survived Walmart/Target but are now being killed by Amazon? Small hosting providers maybe.

These numbers look pretty good compared to my experience with large corporate organizations.

That is nice. It's also almost indistuishable from Java 10. The string interpolation at the end is the last big syntactic nicety Java is missing - at least relative to this example.