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High availability for non-clustered Redis Redis Sentinel provides high availability for Redis when not using Redis Cluster. Redis Sentinel also provides other collateral tasks such as monitoring, notifications and acts as a configuration provider for clients. This is the full list of Sentinel capabilities at a macroscopic level (i.e. the big picture): Monitoring. Sentinel constantly checks if your
At Spool, we calculate our key metrics in real time. Traditionally, metrics are performed by a batch job (running hourly, daily, etc.). Redis backed bitmaps allow us to perform such calculations in realtime and are extremely space efficient. In a simulation of 128 million users, a typical metric such as “daily unique users” takes less than 50 ms on a MacBook Pro and only takes 16 MB of memory. Spo
Our dashboard software has taken a big step forward in real-time data streaming! Any custom data push will immediately be reflected on your dashboard! This video is a quick demo of the speed of updates with our new real-time backend in place! If you would like to read the nerdy details about how it works behind the scenes, please keep reading! The diagram below roughly captures how our dashboard s
A journey to center of Redis I’ve been using Redis lately and I really love the work they have done. In one of my recent projects I had a typical scenario of having users on different channels, and since the old front-end (Javascript) was doing a JSONP through jQuery, I had to take in account for people who were not able to get back to channel due to some disconnection. Yes, its a typical scenario
Radish is an analysis and monitoring tool for Redis.Smart Metrics Tracking project specific metrics is made easy with Radish. Sparklines quickly show high density data in a simplified and useful manner. Intelligent Interface Radish is equipped with a minimal user interface that stands out of the way, empowering you to focus on data and project metrics. Real-Time Monitoring Monitor critical incomin
The internet is full of things: trolls, awesome programming threads, p0rn, proofs of how cool and creative the human beings can be, and of course crappy benchmarks. In this blog post I want to focus my attention to the latter, and at the same time I'll try to show how good methodology to perform a benchmark is supposed to be, at least from my point of view. Why speed matters? In the Web Scale era
Soon after I started at Tumblr all the way back in May, I was tasked with reworking our aging notifications system. A notification is the item that shows up in your dashboard, interleaved with posts, that tells you that another Tumblr blog reblogged or liked one of your posts or started following your blog. Until recently, notifications had been served up by a fairly standard MySQL layer with some
Kue is a feature rich priority job queue for node.js backed by redis. A key feature of Kue is it's clean user-interface for viewing and managing queued, active, failed, and completed jobs. At any point in the job's life-time you can view verbose details, including the job's arbitrary data, creation, update, failure, and completion times. Jobs may update their progress in increments, providing vita
You probably already know by now that Redis is that super fast in-memory (disk persistency being available through snapshots or append only mode) key-value store providing smart data types. In the past we’ve also talked about Redis virtual memory as a solution to improve memory efficiency. Rich Schumacher and Will Larson started an experiment to better understand the memory costs of Redis datastru
Redis is different than other database solutions in many ways: it uses memory as main storage support and disk only for persistence, the data model is pretty unique, it is single threaded and so forth. I think that another big difference is that in order to take advantage of Redis in your production environment you don't need to switch to Redis. You can just use it in order to do new things that w
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