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InfoQ Homepage Scalability Content on InfoQ

  • Plaid.com’s Monitoring System for 9600+ Integrations

    Plaid.com has integrations with over 9600 financial institutions, and their monitoring challenges arise from the heterogeneous nature of these integrations and as well as their large number. They rebuilt their monitoring system on Kinesis, Prometheus, Alertmanager and Grafana to solve the challenges of scalability and low latency.

  • How SendGrid Scales Its Email Delivery Systems

    SendGrid, a cloud based email service, has seen its backend architecture evolve from a small Postfix installation to a system hosted on their own data-centers as well as on the public cloud. Rewriting of services in Go, a gradual move to AWS, and a distributed Ceph-based queue allows the team to hand over 40 billion emails per month.

  • GitHub Engineering Adopts New Architecture for MySQL High Availability

    Github.com uses MySQL as a backbone for many of its critical services like the API, authentication and the Github.com website itself. Github’s engineering team replaced its previous DNS and VIP based setup with one based on Orchestrator, Consul and the Github Load Balancer to get around split brain and DNS caching issues.

  • How Edgemesh Rolled out Its P2P Web Acceleration Service to Production

    Edgemesh is a P2P web acceleration service based on the WebRTC protocol suite that offloads some of the the traffic normally handled by traditional CDNs to browser-based caches shared over a P2P network. They rolled out their release to production in the last few months and shared some of their experiences.

  • Data Preparation Pipelines: Strategy, Options and Tools

    Data preparation is an important aspect of data processing and analytics use cases. Business analysts and data scientists spend about 80% of their time gathering and preparing the data rather than analyzing it or developing machine learning models. Kelly Stirman spoke last week at Enterprise Data World 2017 Conference about the data preparation best practices.

  • The Long History of Microservices

    Microservices has a very long history, not as short as many believe. Neither was SOA invented in the 90s. We have been working with the core ideas behind services for five decades, Greg Young explained at the recent Microservices Conference in London, during his presentation on working with microservices.

  • Gil Tene: Understanding Hardware Transactional Memory

    In his presentation "Understanding Hardware Transactional Memory" at QCon New York 2016, Gil Tene introduces hardware transactional memory (HTM). Whereas the concept of HTM is not new, it is now finally available in commodity hardware. The purpose of HTM is to be able to write to multiple addresses in memory in an atomical way so that there cannot be inconsistencies in cooperation other threads.

  • LFE Brings Lisp to the Erlang Virtual Machine

    After 8 years of development, Lisp Flavoured Erlang (LFE) has reached version 1.0, bringing stable support for Lisp programming on the Erlang virtual machine (BEAM). LFE was created by Robert Virding, one of the initial developers of Erlang. InfoQ has spoken with Duncan McGreggor, current maintainer of LFE.

  • Microsoft Makes Available Their Platform for Building Microservices

    Microsoft has announced and made available the preview of Azure Service Fabric (ASF), a cloud platform including a runtime and lifecycle management tools for creating, deploying, running and managing microservices. ASF microservices can be deployed on Azure or on-premises on Windows Server private or hosted clouds. Support for Linux is to come in the future.

  • Google Unveils Details about Borg

    Google has published the paper "Large-scale cluster management at Google with Borg", unveiling details on a technology that was very little spoken about in the past.

  • Atlassian's Stash Data Center Offers High Availability and Scalability for Git

    Atlassian recently released Stash Data Center, a highly available and horizontally scalable deployment option for its on-premises source code and Git repository management solution Stash. New nodes can be added without downtime to provide active-active clustering and instant scalability.

  • The Architecture of a Scalable and Resilient Google Cloud Solution

    Google has recently published a paper providing architectural guidelines for creating a scalable and resilient solution running on their cloud platform. This article digests the respective paper extracting the main ideas and advice. These guidelines can be used with minor changes for deploying web applications on other clouds.

  • Alex Bordei on Scaling NoSQL Databases

    Network performance, virtualization and testing are some of the considerations to address performance and scalability issues with NoSQL databases. Alex Bordei wrote about scaling NoSQL databases and tips for increasing performance when using these data stores.

  • Martin Thompson Discusses the Reactive Manifesto 2.0

    The second version of the Reactive Manifesto was announced at September's GOTO conference in Aarhus. Martin Thompson discusses the need for a revised version of the Manifesto and what its changes mean for the burgeoning reactive community.

  • AWS Adds Hooks Into Expanded Auto Scaling Lifecycle

    Amazon Web Services recently added several features to its Auto Scaling service to improve control over the managed Amazon EC2 instances. It is now possible to hook into the pending and terminating lifecycle state transitions to perform custom operations, which is also available for in service instances via a new standby state. The DetachInstances API now allows to remove instances from a group.

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