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Boosting NGINX Performance 9x with Thread Pools. Introduction It’s well known that NGINX uses an asynchronous, event-driven approach to handling connections. This means that instead of creating another dedicated process or thread for each request (like servers with a traditional architecture), it handles multiple connections and requests in one worker process. To achieve this, NGINX works with sockets in a non-blocking mode and uses efficient methods such as epoll and kqueue.

Because the number of full-weight processes is small (usually only one per CPU core) and constant, much less memory is consumed and CPU cycles aren’t wasted on task switching. The advantages of such an approach are well-known through the example of NGINX itself. It successfully handles millions of simultaneous requests and scales very well. But the asynchronous, event-driven approach still has a problem.

[Editor’s note: For NGINX Plus users, thread pools are supported in NGINX Plus Release 7.] The Problem Thread Pools It seems then we have another queue. Benchmarking. Distributed app development with nodejs and zeromq. cURL cheat sheet Cheat Sheet by ankushagarwal11. Named Data Networking: Motivation & Details - Named Data Networking (NDN) NDN is an entirely new architecture, but one whose design principles are derived from the successes of today’s Internet, reflecting our understanding of the strengths and limitations of the current Internet architecture, and one that can be rolled out through incremental deployment over the current operational Internet.

Context and Vision In the 1960s and 70s when the core ideas underlying the Internet were developed, telephony was the only example of successful, effective, global-scale communications. Thus while the communication solution offered by TCP/IP was unique and groundbreaking, the problem it solved was telephony’s: carrying a point-to-point conversation between two entities.

IP has exceeded all expectations for facilitating ubiquitous interconnectivity and so enabled dramatic changes in the world that we associate with the Internet. Information-intensive business like travel, banks and financial services long ago moved onto the Internet. Architectural Principles NDN Packets Names.

Veille

The basics of network intrusion prevention systems. Network intrusion prevention systems (IPSes) monitor and analyze an organization's network traffic to identify malicious activity and -- optionally -- stop that activity by dropping and/or blocking associated network connections. IPSes have been used for many years at key network locations, such as in close proximity to firewalls to identify a variety of network-based attacks that other security technologies are unable to detect.

The predecessor to network intrusion prevention systems, known as intrusion detection systems (IDSes), provide the same types of functionality, except IDSes cannot stop malicious activity. Most early network intrusion prevention systems used signature-based detection techniques that could, for example, identify communications from a particular worm based on known sequences of bytes unique to that worm. There are many network intrusion prevention systems available today and -- as the sidebar explains -- they come in three forms.

Karen Scarfone asks: Next Steps. How does HTTP file upload work?

Linux

SSI. CouchDB. Netflix Shares Cloud Load Balancing And Failover Tool: Eureka! Running the kernel in library mode. By Jonathan CorbetApril 8, 2015 Once upon a time, the only way to run the Linux kernel was as the primary operating system on a handy piece of hardware. Since then, though, other modes of operation have become possible: the kernel can, for example, be run as the guest of another kernel through virtualization, or as a user-space process with the user-mode Linux (UML) port. One mode that has not been supported is running the kernel as a library that can be called from within an application program, but that situation appears to be about to change thanks to a patch set which has just made its first appearance on the linux-kernel list.

This patch set, posted by Hajime Tazaki, goes by the name LibOS; it was presented (slides [slideshare]) at the recent Netdev 0.1 conference. LibOS is structured as if it were a new architecture port; it can be found under arch/lib in the kernel tree. One might wonder why this mode of operation would be useful. (Log in to post comments)

Mac

Internet. Api. Terminal. SQL. Google. Appareils. Lire-big-data-les-desillusions-pointent-deja-le-monde-informatique-60281. Selon John Foreman, data scientist chez MailChimp.com, la promesse marketing des big data ne ressemble guère à la réalité. Les critiques commencent à pointer les limites du big data, mais les analystes continuent de voir en lui un avenir radieux. Après les attentes démesurées, les désillusions ? La vague du big data a peut être atteint un pic, en tout cas pour ceux qui suivent le Gartner Hype Cycle. En d'autres termes, certains professionnels commencent à douter des annonces marketing autour de l'analyse big data et à adopter un point de vue plus critique sur les limites des systèmes big data. Selon le credo, plus une entreprise collectait de données, plus elle pourrait en extraire des informations pointues et utiles.

Un ingénieur de Google, qui a été gavé au big data plus que n'importe qui, a nommé cette notion « la déraisonnable efficacité des données ». Impossible de reconduire les mêmes traitements ? Le Gartner reste bien sûr encore optimiste. Consommation énergétique d'un smartphone. Replacing Middle Management with APIs by Peter Reinhardt. There’s a trend in Silicon Valley startups to create a software layer in industries that were traditionally pure human services. Uber and Lyft have created software layers in the taxi industry, 99designs Tasks in the visual design industry, Homejoy in the cleaning industry, and so on.

These new software services employ armies of human workers, optimizing their output, productivity and quality while driving price down. The software layer between the company and their armies of contractors eliminates a huge amount of middle management, and creates a worrisome disconnect between jobs that will be automated, and jobs of increasing leverage and value. This software layer generally has three parts: the user interface (UI) for the end customer, a programming interface (API) that actually dispatches a human worker, and a second interface for the worker to execute the task efficiently. For example, Uber has a mobile app (UI) that talks to their servers (API). What does that make the drivers?

Mobile

WebSockets. WebSocket est une technologie évoluée qui permet d'ouvrir un canal de communication interactif entre un navigateur (côté client) et un serveur. Avec cette API vous pouvez envoyer des messages à un serveur et recevoir ses réponses de manière événementielle sans avoir à aller consulter le serveur pour obtenir une réponse. Voir aussi Nous convertissons les données de compatibilité dans un format JSON.

Ce tableau de compatibilité utilise encore l'ancien format car nous n'avons pas encore converti les données qu'il contient. Vous pouvez nous aider en contribuant ! Notes pour Gecko Le support des WebSockets dans Firefox suit les évolutions continuelles de la spécification WebSocket. Gecko 6.0 Avant Gecko 6.0 (Firefox 6.0 / Thunderbird 6.0 / SeaMonkey 2.3), il y avait un objet WebSocket, mal nommé, qui a fait supposer à certains sites que les servicesWebSocket services n'étaient pas prefixés ; cet objet a été renommé en MozWebSocket. Gecko 7.0 Gecko 8.0 Gecko 11.0. Apache Kafka (gestion de messages dans archi distribuée)

When used in the right way and for the right use case, Kafka has unique attributes that make it a highly attractive option for data integration. Apache Kafka is creating a lot of buzz these days. While LinkedIn, where Kafka was founded, is the most well known user, there are many companies successfully using this technology. So now that the word is out, it seems the world wants to know: What does it do? Why does everyone want to use it? How is it better than existing solutions? What is Kafka? Kafka is one of those systems that is very simple to describe at a high level, but has an incredible depth of technical detail when you dig deeper. Like many publish-subscribe messaging systems, Kafka maintains feeds of messages in topics. Messages are simply byte arrays and the developers can use them to store any object in any format – with String, JSON, and Avro the most common. What makes Kafka unique is that Kafka treats each topic partition as a log (an ordered set of messages).

Kafka at Work. Server-sent events (push) (php) Developing a web application that uses server-sent events is quite easy. You'll need a bit of code on the server to stream the events to the web application, but the web application side of things works nearly identically to handling any other type of events. Receiving events from the server The server-sent event API is contained in the EventSource interface; to open a connection to the server to begin receiving events from it, you create a new EventSource object, specifying the URI of a script that generates the events. For example: var evtSource = new EventSource("ssedemo.php"); Once you've instantiated your event source, you can begin listening for messages: This code listens for incoming messages (that is, notices from the server that do not have an event field on them) and appends the message text to a list in the document's HTML. You can also listen for events, using addEventListener(): Sending events from the server The PHP code for the example we're using here follows: Error handling id.

Python

Cassandra. Hébergement. Ruby. Java. Spring. Transverse. JBehave. JavaScript.