另外一則跟 Prime Video 有關的有趣留言

Hacker News 上的「Even Amazon can't make sense of serverless or microservices (world.hey.com)」這邊看到 DHH 抓到機會剛好戳了 AWS 的費用問題,不過讓我注意到的不是 DHH 的文章,而是在 Hacker News 上的留言 35823366,自稱是當時設計這個 serverless 架構的人出來解釋當時的確有壓力測試過,看起來也還 OK:

I actually designed the original serverless system (a few years back when I was still at Prime Video), and yes we did and it did sort of look like it could work until it didn't. Obviously wasn't the right solution for the scale we had in mind (or rather the type of problem we were working on) but it's sad to see the mistake of one team be used to justify shitting on serverless as a general solution.

但這是全新帳號的發言,拿這個 id 去找是可以翻到 TimboKZ 這個 GitHub 帳號,然後一路找也可以看到 Timur KuzhagaliyevLinkedIn 帳號,這個帳號裡面有提到 2019 到 2020 的時候在 Amazon 裡面當 SDE:

Worked on various computer vision projects as a part of Video Quality Analysis team at Prime Video.


拿 Cloudflare Workers 跑 Geolocation API

Hacker News Daily 上看到拿 Cloudflare Workers 跑 Geolocation API:「How to make simple Geolocation service」。

作者想要做一個很簡單的 Geolocation API,一開始的想法是在 AWS Lambda 上用 MaxMind 的資料,但 latency 偏高:

However, I quickly realized that the response time isn't what I've expected - on average the response took somewhere between from 200ms to 500ms. So I started looking for other options.

所以作者就想到是不是有有機會丟到 Cloudflare Workers 上,但發現 license 看起來是個問題,另外因為把 MaxMind 的資料庫丟進去,會超過 worker 的時間限制:

And for this case MaxMind offers GeoLite2 database, however you'll be in charge of hosting this database on your server and making regular updates of the database. You also need to make sure your project is compliant with MaxMind's License.

However, this solution had one really big caveat - MaxMind GeoLite2 database does not work on Cloudflare Workers due to some runtime limitations.

結果作者後來發現 Cloudflare Workers 上本身就會帶 Geoloation 資訊了,不需要另外拉 MaxMind 的資料查:

And after exploring their documentation, I realized that the Request object in function have an access to cf object, which contains some useful information about the visitor, including visitor's country!

另外我翻了一下價錢,主要是算次數的,看起來 Free Plan 就可以 100K/day (執行時間限制是 10ms),而如果是付費方案的話則是 USD$0.5/M (50ms),這樣對一些小專案來說,Free Plan 似乎是夠用了...

Cassandra 也被 AWS 包成服務了

也是剛剛發表的服務 (所以在 Twitter 上看到),把 Apache Cassandra 包成服務,叫做 Amazon Managed Apache Cassandra Service:「New – Amazon Managed Apache Cassandra Service (MCS)」。

而且是個 serverless 服務,直接用服務,不需要管理機器:

Amazon MCS is serverless, so you pay for only the resources you use and the service automatically scales tables up and down in response to application traffic.

從計費的方式也可以看出來這點,是對 Write request units、Read request units 與 Storage 收費,沒有看到機器的費用。

不過稍微算了一下不算便宜,如果沒有用到 Cassandra 的特性的話,比 DynamoDB 貴一些?

目前是 open preview 狀態,是個可以用但是不掛保證的意思:

Amazon MCS is available today in open preview in US East (N. Virginia), US East (Ohio), Europe (Stockholm), Asia Pacific (Singapore), Asia Pacific (Tokyo).


AWS Lambda 可以直接掛進 ALB 了...

AWS 這次對 Lambda 還發表了不少功能,除了前面提到透過 Layout 支援其他語言以外 (e.g. Ruby),這邊要再提到另外一個重要的功能。

這次是 ALB 可以直接呼叫 lambda function 了:「Lambda functions as targets for Application Load Balancers」。

以前還得靠 API Gateway 整半天 (因為版本設定),現在直接用 ALB 接就可以了?而且 ALB 這邊有規劃對應的 quota:

There is no change to the hourly price of ALB. The load balancer capacity units (LCUs) of ALB now include 0.4 GB per hour of data processing to AWS Lambda targets.

這樣就更接近 serverless 了...

各家 Serverless 服務冷啟動 (Cold Start) 的時間

看到「Serverless: Cold Start War」這篇分析了 AWS LambdaAzure FunctionsGoogle Cloud Functions 的冷啟動特性。

裡面分析了多久沒有 request 會需要冷啟動、記憶體的大小對於冷啟動速度的影響、程式語言的影響,以及程式大小的影響。

對於量很少,但是又很在意速度的人來說也許可以研究一下。不過只要有點量 (就算一分鐘只有一次) 應該都不會遇到這塊問題...

Aurora Serverless MySQL 進入 GA

AWS 宣佈能 auto-scale 的 Aurora Serverless MySQL 進入 GA:「Aurora Serverless MySQL Generally Available」:


Aurora Serverless for Aurora MySQL is available now in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland).

以秒計費,但低消是 5 分鐘:

You pay a flat rate per second of ACU usage, with a minimum of 5 minutes of usage each time the database is activated.

us-east-1 的價錢來看,每個 ACU 是 USD$0.06/hour,而每個 ACU 大約是 standard instance 的價錢:

1 ACU has approximately 2 GB of memory with corresponding CPU and networking, similar to what is used in Aurora Standard instances.

但這沒看懂,是 db.t2.small 還是 db.t2.medium?另外比較是全速還是 small 的 20% 或 medium 的 40%?這部份也許還要再問看看才知道...

storage 與 I/O 的費用則是相同,倒是不用比較這塊... 再來不知道有沒有推出 Reserved ACU 的計畫,光是一年付清就差蠻多的。


SQS 可以打進 Lambda 了...

在昨天的 AWS 台北高峰會上,AWS 的人有提到這個功能應該要正式推出了,果然在回來不久後就看到消息了:「AWS Lambda Adds Amazon Simple Queue Service to Supported Event Sources」。

We can now use Amazon Simple Queue Service (SQS) to trigger AWS Lambda functions! This is a stellar update with some key functionality that I’ve personally been looking forward to for more than 4 years. I know our customers are excited to take it for a spin so feel free to skip to the walk through section below if you don’t want a trip down memory lane.

這算是 Serverless 架構下很自然會想要做的一環,當 SQS 裡面有東西的時候就呼叫 Lambda 起來做事,以往一般會透過 SNS 在中間接起來 (或是拿 S3 惡搞,因為 S3 也可以串 Lambda...),現在可以直接串了:

By adding support for SQS to Lambda we’re removing a lot of the undifferentiated heavy lifting of running a polling service or creating an SQS to SNS mapping.

這個功能本身不收費,但他需要的 SQS API call 與產生的 Lambda 當然是需要收費的:

There are no additional charges for this feature, but because the Lambda service is continuously long-polling the SQS queue the account will be charged for those API calls at the standard SQS pricing rates.

Amazon Aurora 的 Serverless 與 Multi-master

Amazon Aurora 推出了兩包玩意,第一包是 Serverless,讓需要人介入的情況更少:「In The Works – Amazon Aurora Serverless」。

在 Serverless 的第一個重點是支援以秒計費:

Today we are launching a preview (sign up now) of Amazon Aurora Serverless. Designed for workloads that are highly variable and subject to rapid change, this new configuration allows you to pay for the database resources you use, on a second-by-second basis.

然後是極為快速的 auto-scaling:

The endpoint is a simple proxy that routes your queries to a rapidly scaled fleet of database resources. This allows your connections to remain intact even as scaling operations take place behind the scenes. Scaling is rapid, with new resources coming online within 5 seconds

這兩個組合起來,讓使用端可以除了在 Amazon EC2 上可以快速 scale 外,後端的資料庫也能 scale 了...

第二個是 Multi-master 架構:「Sign Up for the Preview of Amazon Aurora Multi-Master」。

Amazon Aurora Multi-Master allows you to create multiple read/write master instances across multiple Availability Zones. This enables applications to read and write data to multiple database instances in a cluster, just as you can read across Read Replicas today.

(話說我一直都誤以為 Aurora 是 R/W master...)

Anyway,這個功能不知道怎麼疊上去的... 不笑得會不會有嚴重的 distributed lock issue,反而推薦大家平常都寫到同一台 (像是 PXC 就會這樣)。