Reed Allman Speaking on the RocksDB Meetup Dec 4th
Reed Allman, a systems-level engineer at Iron.io, will be talking at the RocksDB meetup on Thursday, December 4th, 2014. The meeting will be at the Facebook headquarters in Menlo Park, CA.
Read MoreIron.io Adds Named Schedules
Iron.io is pleased to announce named schedules as a feature in its IronWorker service. Giving names or labels to schedules may seem a small feature but it’s been a common request from a number of users managing large workloads. Users can now give scheduled tasks labels when uploading the tasks to IronWorker or add them…
Read MoreDocker in Production — What We’ve Learned Launching Over 300 Million Containers
Docker in Production at Iron.io Overview Earlier this year, we made a decision to run every task on IronWorker inside its own Docker container. Since then, we’ve run over 300,000,000 programs inside of their own private Docker containers on cloud infrastructure. Now that we’ve been in production for several months, we…
Read MoreCEO Chad Arimura Speaking at Data 360 Conference on Real-time Data
Data 360° Conference (Oct 22-23, 2014) Chad Arimura, CEO and Co-Founder of Iron.io, will be speaking at the Data 360° Conference in Santa Clara this week. The conference brings together leading figures in data processing and analysis to discuss trends in big data, cloud infrastructure, real-time data analysis, and distributed computing. Specific emphasis is on…
Read MoreIron.io Adds Longer Running Workers
Long-Running Workers are Now Available in IronWorker Iron.io is happy to announce long-running workers are now available within IronWorker. Up until now, workers running on the platform have been limited to 60 minutes in duration. Users on Production and Enterprise plans or using Dedicated Clusters can now have workers that run for hours at…
Read MoreHow to Build an ETL Pipeline for ElasticSearch Using Segment and Iron.io
Overview ETL is a common pattern in the big data world for collecting and consolidating data for storage and/or analysis. Here’s the basic process: Extract data from a variety of sources Transform data through a set of custom processes Load data to external databases or data warehouses Segment + Iron.io + Elasticsearch = A…
Read MoreNew FFmpeg IronWorker Stack For Easy Video Processing
FFmpeg is the leading cross-platform solution to record, convert and stream audio and video. Dealing with audio and video can eat up resources, making the activity a great fit for IronWorker by moving the heavy lifting to the background. In the past, usage of FFmpeg with IronWorker would require that our users include and install…
Read MoreOrchestrating PHP Dependencies with Composer and IronWorker
Package your dependencies on IronWorker using composer Overview This is a tutorial describing how to include and use the PHP package management tool Composer with IronWorker. Composer is a tool for dependency management in PHP. It allows you to declare the dependent libraries your project needs, and it will install them in your project for…
Read MoreHow Cine.io Uses Node.js and IronWorker to Handle Their Background Processing
The following is a guest blog post by Thomas Shafer describing how cine.io deploys their workers within Iron.io to handle all of their background processing. Cine.io is the only true developer-focused live streaming service. We offer APIs and SDKs for all mobile platforms and language frameworks and let developers build and ship live-streaming capabilities with…
Read MoreMessage Queues for Buffering: An IronMQ and Python Case Study
Using IronMQ and Python to as a Buffer between Systems Connecting systems and moderating data flows between them is not an easy task. Message queues are designed for just this purpose – buffering data between systems so that each can operate independently and asynchronously. Here’s a short article on using IronMQ to buffer a CMS…
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