Tag Archives: persistent

讓 Firefox 連線數變多 (然後加快速度)

最近換到 Firefox 後覺得開很多 tab 時很卡,但 CPU 也沒滿,大概是某種 lock/mutex/semaphore 機制導致硬體資源沒用完但是自己限制住...

找資料研究的時候發現 Firefox 對單一 server 的最大連線數是 6 個,而 Chrome 是 10 個:「Max parallel http connections in a browser?」。這對於網路速度夠的使用者就很卡,像是透過 RSS reader 同時對一個站台狂開分頁時就會卡住。

翻了一下 Firefox 的設定,找到相關的幾個設定,其中上面提到的是 network.http.max-persistent-connections-per-server,預設的確是 6 個,改成 10 個後測了一天好不少,決定改成跟 IE11 一樣的 13 個... (奇怪的數字)

另外一個是 network.http.max-connections,預設是 900 了,應該夠用...

GitHub 重新定位 Redis 的功能...

GitHub Engineering 說明了他們為什麼改變 Redis 的使用情境:「Moving persistent data out of Redis」。

GitHub 裡面,Redis 有兩種不同的情境,一種叫做 transient Redis,只用做 cache:

We used it as an LRU cache to conveniently store the results of expensive computations over data originally persisted in Git repositories or MySQL. We call this transient Redis.

另外一種則是打開 persistence 功能,叫做 persistent Redis:

We also enabled persistence, which gave us durability guarantees over data that was not stored anywhere else. We used it to store a wide range of values: from sparse data with high read/write ratios, like configuration settings, counters, or quality metrics, to very dynamic information powering core features like spam analysis. We call this persistent Redis.

這邊講的是 persistent Redis 被換成用 MySQL (InnoDB) 儲存:

Recently we made the decision to disable persistence in Redis and stop using it as a source of truth for our data. The main motivations behind this choice were to:

  • Reduce the operational cost of our persistence infrastructure by removing some of its complexity.
  • Take advantage of our expertise operating MySQL.
  • Gain some extra performance, by eliminating the I/O latency during the process of writing big changes on the server state to disk.

For the majority of callsites, we replaced persistent Redis with GitHub::KV, a MySQL key/value store of our own built atop InnoDB, with features like key expiration. We were able to use GitHub::KV almost identically as we used Redis: from trending repositories and users for the explore page, to rate limiting to spammy user detection.

後面講了不少轉換的過程 (還包含了某些功能的改寫),但沒有講的太清楚為什麼不繼續使用 Redis。

目前只能就提到的三點問題來看,persistent 的 i/o 成本可能太高?而且難以再壓榨效能出來?而相反的,InnoDB 已經花了很多力氣在上面,直接拿來用反而可以解決問題?

不過看得出來這個轉換還是花了不少力氣,看得出來有些 application 使用 Redis 的模式不能直接搬到 InnoDB 上,花了時間改寫...

APT (Advanced Persistent Threat)

維基百科對 APT (Advanced Persistent Threat) 的定義是:

Advanced Persistent Threat (APT) APT is a set of stealthy and continuous computer hacking processes, often orchestrated by human(s) targeting a specific entity.

針對特定個人或團體進行攻擊,這邊的 entity 通常是指有權限存取系統,或是手上握有機敏資料的人,這些人的帳號密碼,或是系統權限是有價值的。

這幾年因為行動裝置普及,再加上行動裝置上驗證起來會比較麻煩,成為 APT 攻擊的首選。