幹壞事是進步最大的原動力
桌機換成 Xubuntu 22.04 後會遇到手動鎖定螢幕時，螢幕不會進入省電模式，遇到的情況有點像是「DPMS Suspend on Screen Lock」這邊提到的情境。
這類問題如果用 search engine 一時間沒有找到解法的話，最好的方法都是直接去讀 source code，然後就發現透過 Ctrl+Alt+L 觸發的 /usr/bin/xflock4 其實是個 shell script，從 code 讀可以發現裡面只負責 lock 的部分，本來就跟 DPMS 無關。
我在下面提供的方案就是自己處理螢幕的部分，也就是自己先跑 DPMS 指令，然後再回頭呼叫 /usr/bin/xflock4：
#!/bin/sh /usr/bin/xset dpms force off exec /usr/bin/xflock4
把 Ctrl+Alt+L 的觸發程式掛上來，這樣就會正常處理了...
Amazon EFS 提供 One Zone 的版本，用較低的可靠度提供更低的價錢：「New – Lower Cost Storage Classes for Amazon Elastic File System」。
價錢大約是 53 折，不過要注意不在同一個 AZ 時使用會有頻寬費用：
Standard data transfer fees apply for inter-AZ or inter-region access to file systems.
目前想的到的是 /net/tmp 這類的用途，資料掉了也就算了，考慮到可靠度，其他的用途好像暫時想不到...
在 Hacker News Daily 上看到 Apple M1 為什麼這麼快又省電的解釋，可以當作一種看法：
1/ In case you were wondering: Apple's replacement for Intel processors turns out to work really, really well. Some otherwise skeptical techies are calling it "black magic". It runs Intel code extraordinarily well.
— Robᵉʳᵗ Graham?, provocateur (@ErrataRob) November 25, 2020
可以在 Thread reader 上面讀：「Thread by @ErrataRob on Thread Reader App – Thread Reader App」。
看起來 Apple 在規劃的時候就有考慮 x86 模擬問題，所以在記憶體架構上直接實做了對應的模式，大幅降低了當年 Microsoft 在 Surface 上遇到的問題：
3/ The biggest hurdle was "memory-ordering", the order in which two CPUs see modifications in memory by each other. It's the biggest problem affecting Microsoft's emulation of x86 on their Arm-based "Surface" laptops.
4/ So Apple simply cheated. They added Intel's memory-ordering to their CPU. When running translated x86 code, they switch the mode of the CPU to conform to Intel's memory ordering.
另外一個比較有趣的架構是，Apple M1 上面的兩個 core 有不同的架構，一顆對效能最佳化，另外一顆對效率最佳化：
13/ Apple's strategy is to use two processors: one designed to run fast above 3 GHz, and the other to run slow below 2 GHz. Apple calls this their "performance" and "efficiency" processors. Each optimized to be their best at their goal.
在 wikipedia 上的介紹也有提到這兩個 core 的不同，像是 L1 cache 的差異 (128KB 與 192KB)，以及功耗的差異：
The M1 has four high-performance "Firestorm" and four energy-efficient "Icestorm" cores, providing a configuration similar to ARM big.LITTLE and Intel's Lakefield processors. This combination allows power-use optimizations not possible with Apple–Intel architecture devices. Apple claims the energy-efficient cores use one tenth the power of the high-performance ones. The high-performance cores have 192 KB of instruction cache and 128 KB of data cache and share a 12 MB L2 cache; the energy-efficient cores have a 128 KB instruction cache, 64 KB data cache, and a shared 4 MB L2 cache. The Icestorm "E cluster" has a frequency of 0.6–2.064 GHz and a maximum power consumption of 1.3 W. The Firestorm "P cluster" has a frequency of 0.6–3.204 GHz and a maximum power consumption of 13.8 W.
再加上其他架構上的改善 (像是針對 JavaScript 的指令集、L1 的提昇，以及用 TSMC 最新製程)，累積起來就變成把 Intel 版本壓在地上磨蹭的結果了...
剛剛看到 Amazon EBS 的 Cold HDD (sc1) 大幅降價 40%：「AWS announces 40% price reduction for Amazon Elastic Block Store (EBS) Cold HDD (sc1) volumes」。
Cold HDD (sc1) 主要是拿來堆資料的，直接掛上來操作比起 Amazon S3 還是方便不少，這次的降價算是懶人的福音？
現在的「Amazon EBS pricing」頁面已經更新了，想要比較的話可以從 archive.is 上面的「Amazon EBS pricing」對比。價錢的部份從十一月九號自動生效：
Amazon EBS customers automatically benefit from this new lower price, which is effective starting November 9th, 2020.
Amazon RDS 推出了 ARM 的版本：「New – Amazon RDS on Graviton2 Processors」，包含了 MySQL、MariaDB 與 PostgreSQL 的版本都有支援，不過看起來需要比較新版的才能用：
You can choose between M6g and R6g instance families and three database engines (MySQL 8.0.17 and higher, MariaDB 10.4.13 and higher, and PostgreSQL 12.3 and higher).
官方宣稱可以提供 35% 的效能提昇，考慮費用的部份會有 52% 的 c/p 值提昇：
Graviton2 instances provide up to 35% performance improvement and up to 52% price-performance improvement for RDS open source databases, based on internal testing of workloads with varying characteristics of compute and memory requirements.
對於 RDS 這種純粹就是個服務的應用來說，感覺應該不會有什麼轉移成本，只要測過沒問題，換過去等於就是現賺的。看起來等 RI 約滿了就可以切...
Amazon EC2 的 Reserved Instances 宣佈降價：「EC2 Price Reduction – For EC2 Instance Saving Plans and Standard Reserved Instances」。
文章裡先列出 M5/C5/R5 的：
可以看到 R5 在一年是完全沒動，然後有些也是 0%，不過大多數應該是都有降：
Below I’ve given a snapshot of some of the savings across the M5, C5, and R5 instance types, however there are also price reductions for the instance types C5n, C5d, M5a, M5n, M5ad, M5dn, R5a, R5n, R5d, R5ad, R5dn, T3, T3a, Z1d, and A1.
以這些資料看起來是降了一些，但實際想要翻 T3a 系列機器的歷史資料時發現不好找，用搜尋引擎可以在「Where can I find Amazon EC2 price history?」這邊看到「https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonEC2/current/index.csv」這個地方，看起來是「New – AWS Price List API」這邊的資訊，不過看起來沒有 RI 的資料，只有 AmazonEC2 的資料 (所以對應到的都是 $0.00)。
之後看看有沒有其他地方有留這些資訊好了...
GitHub 宣佈了提昇免費版的功能，以及付費版的降價消息：「GitHub is now free for teams」。
昨天是這樣：(從這邊撈的，然後發現好像有人寫了個機器人，每天都叫 web.archive.org 去撈一份...)
現在變成：
本來付費的個人方案 (Pro) 的功能都直接下放到免費版本了，而一般公司用的 Team 版本從 $9/m/user 降到 $4/m/user。有個富爸爸之後就可以任性...
前幾天才在 Ptt 上回了一些對 Lambda 與 Serverless 的想法，結果剛剛看到 Lambda 被納入 Savings Plans 裡面了：「Savings Plan Update: Save Up to 17% On Your Lambda Workloads」。
最多 17% 的折扣，看起來比其他的低不少，應該是因為 Lambda 比起 EC2 或是 Fargate 更動態的關係：
Today I am happy to be able to tell you that Compute Savings Plans now apply to the compute time consumed by your AWS Lambda functions, with savings of up to 17%.
現有的 Savings Plans 如果沒有用完的部份也會自動套用進去。先放著看看...
在「How Backblaze Buys Hard Drives」這篇裡面提到了 Backblaze 採購硬碟的策略，可以看到完全都是偏成本走向，所以裡面的策略一般個人用不太到，一般企業也不應該照抄，但拿來看看還蠻有趣的...
像是因為硬碟太多，所以硬碟的使用電量是他們在評估成本時蠻重要的一環，這點在一般的情境下不太會考慮到：
Power draw is a very important metric for us and the high speed enterprise drives are expensive in terms of power cost. We now total around 1.5 megawatts in power consumption in our centers, and I can tell you that every watt matters for reducing costs.
另外也提到了 SMR 硬碟的特性，在單位成本雖然有比較高的容量，但導致架構面需要配合 (cache)，而也會有工程端的成本提昇，所以不是很愛：
SMR would give us a 10-15% capacity-to-dollar boost, but it also requires host-level management of sequential data writing. Additionally, the new archive type of drives require a flash-based caching layer. Both of these requirements would mean significant increases in engineering resources to support and thereby even more investment. So all-in-all, SMR isn’t cost-effective in our system.
成本面上，他們觀察到的現象是每季會降 5%～10%：
Ideally, I can achieve a 5-10% cost reduction per terabyte per quarter, which is a number based on historical price trends and our performance for the past 10 years.
另外提到了用 SAS controller 可以接多個 SATA 硬碟的事情 (雖然還是成本考量)，但這塊也蠻有趣的：
Longer term, one thing we’re looking toward is phasing out SATA controller/port multiplier combo. This might be more technical than some of our readers want to go, but: SAS controllers are a more commonly used method in dense storage servers. Using SATA drives with SAS controllers can provide as much as a 2x improvement in system throughput vs SATA, which is important to me, even though serial ATA (SATA) port multipliers are slightly less expensive. When we started our Storage Pod construction, using SATA controller/port multiplier combo was a great way to keep costs down. But since then, the cost for using SAS controllers and backplanes has come down significantly.
相較於 Amazon EC2 有 Spot Instance (可以利用 Spot Instance 的競價機制省下很多費用)，這次 AWS re:Invent 時 Fargate 也推出了對應的產品線：「AWS Fargate Spot Now Generally Available」。
跟 EC2 的相同，你在上面跑的應用程式必須可以接受隨時中斷服務 (i.e. 必須是 crash-safe)，常見的情境是 worker 類的程式。
價錢上大約在三折 (寫這篇時 us-east-1 目前的價錢)，考慮到啟動的速度比 EC2 快很多，這樣好像是個可以考慮的方案...