Recent posts: 07 Feb 2026 » Why I joined OpenAI 05 Dec 2025 » Leaving Intel 28 Nov 2025 » On "AI Brendans" or "Virtual Brendans" 22 Nov 2025 » Intel is listening, don't waste your shot 17 Nov 2025 » Third Stage Engineering 04 Aug 2025 » When to Hire a Computer Performance Engineering Team (2025) part 1 of 2 22 May 2025 » 3 Years of Extremely Remote Work 01 May 2025 » Doom GPU Flame Graphs 29 Oct 2
アプリケーションのパフォーマンス問題の解決やチューニングで大切なのは問題のコアやボトルネックに最短パスで到達することである． 基本的なパフォーマンス分析の入り口はアプリケーションのスレッドがon-CPUで時間を消費しているかoff-CPUで時間を消費しているかを理解するところから始まる．on-CPUの場合はそれがuserモードかkernelモードかを特定し，さらにCPUプロファイリングによってどのcode pathがCPUを消費しているのかの分析に向かう．off-CPUの場合はI/OやLock，pagingといった問題の分析に向かう． Flame Graphはon-CPUでのパフォーマンスの問題が発覚した時に行うCPUプロファイリングを助ける．どのcode pathがボトルネックになっているのかを1つのグラフ上で理解できる．本記事ではFlame Graphとは何か? なぜ必要なのか? を解
GREE Advent Calendar 2015 の23日目担当の上竹です。普段はアプライアンスLB やネットワークの構築/運用をしております。 概要 バックボーンネットワークを設計運用していると、実際どのようなトラフィックがどのくらい流れているか中身を知りたい(見たい)ことがよくあります。 どのISP からどの回線へどのくらい流入があるのかだったり、どんなAS からどのくらいアクセスがきているか、これら様々な情報を正しく把握することは、Transit 回線やIX 回線をコントロールし今後のネットワーク戦略を考えるうえで非常に有益です。 また、昨今我々を悩ましているDDoS 対策の第一歩として、今流れているトラフィックをまず"知る"ということが必要だと思います。 そこで、今回ネットワークの見える化を、「NetFlow」、「Fluentd + ElasticSearch + Kibana」
Redash helps you make sense of your dataConnect and query your data sources, build dashboards to visualize data and share them with your company. “Redash is as essential as email to my company. We love data but accessing the data is a pain without Redash. Any company I go to, I get them hooked on Redash. It’s an easy sell :)” by Ben Dehghan, Co-Founder of Data Miner Read what our users say → Write
普段はサーバのメトリクス可視化のためにcloudforecastを使っていますが、某案件用に数秒単位で数十台のサーバのメトリクスを表示したいので、記事タイトルのような構成を作ってみた。 dstatでとった各種値の他に、nginxとmemcachedの情報も合わせて表示させています。 セットアップ もろもろのセットアップのメモ 監視サーバ まず、監視サーバにElasticsearchとkibanaをいれる。環境はCentOS6 $ sudo yum install java-1.7.0-openjdk $ sudo rpm -Uvh https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-1.x.x.noarch.rpm Elasticsearchは特に設定なく起動 $ sudo service
Bokeh documentation# Bokeh is a Python library for creating interactive visualizations for modern web browsers. It helps you build beautiful graphics, ranging from simple plots to complex dashboards with streaming datasets. With Bokeh, you can create JavaScript-powered visualizations without writing any JavaScript yourself. Finding the right documentation resources# Bokeh’s documentation consists
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Why Geckoboard?Most performance data reaches teams too late, through reports that are already stale, or dashboards locked away in tools that only a manager can see. Geckoboard gives every team a shared, live view. It pulls together data from your CRM, support platform, and other tools, and makes it visible on office screens, via shared links, and on mobile. When everyone sees the same current pict
As Twitter has moved from a monolithic to a distributed architecture, our scalability has increased dramatically. Because of this, the overall complexity of systems and their interactions has also escalated. This decomposition has led to Twitter managing hundreds of services across our datacenters. Visibility into the health and performance of our diverse service topology has become an important d
Graphite does three things: Kick ass. Chew bubblegum. Make it easy to store and graph metrics. (And it’s all out of bubblegum.) Learn more about Graphite About the Project Graphite is an enterprise-ready monitoring tool that runs equally well on cheap hardware or Cloud infrastructure. Teams use Graphite to track the performance of their websites, applications, business services, and networked serv
As soon as I saw a Flame Graph visualization I knew it would make a great addition to NYTProf. So I’m delighted that the new Devel::NYTProf version 5.00, just released, has a Flame Graph as the main feature of the index page. In this post I’ll explain the Flame Graph visualization, the new ‘subroutine calls event stream’ that makes the Flame Graph possible, and other recent changes, including impr
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