jm + agents   3

Bots won't replace apps. Better apps will replace apps
As I’ll explain, messenger apps’ apparent success in fulfilling such a surprising array of tasks does not owe to the triumph of “conversational UI.” What they’ve achieved can be much more instructively framed as an adept exploitation of Silicon Valley phone OS makers’ growing failure to fully serve users’ needs, particularly in other parts of the world. Chat apps have responded by evolving into “meta-platforms.” Many of the platform-like aspects they’ve taken on to plaster over gaps in the OS actually have little to do with the core chat functionality. Not only is “conversational UI” a red herring, but as we look more closely, we’ll even see places where conversational UI has breached its limits and broken down.
apps  bots  chatops  chat  ui  messaging  silicon-valley  agents  alexa  siri  phones 
april 2016 by jm
Observability at Twitter: technical overview, part II
Interesting to me mainly for this tidbit which makes my own prejudices:
“Pull” vs “push” in metrics collection: At the time of our previous blog post, all our metrics were collected by “pulling” from our collection agents. We discovered two main issues:

* There is no easy way to differentiate service failures from collection agent failures. Service response time out and missed collection request are both manifested as empty time series.
* There is a lack of service quality insulation in our collection pipeline. It is very difficult to set an optimal collection time out for various services. A long collection time from one single service can cause a delay for other services that share the same collection agent.

In light of these issues, we switched our collection model from “pull” to “push” and increased our service isolation. Our collection agent on each host only collects metrics from services running on that specific host. Additionally, each collection agent sends separate collection status tracking metrics in addition to the metrics emitted by the services.

We have seen a significant improvement in collection reliability with these changes. However, as we moved to self service push model, it becomes harder to project the request growth. In order to solve this problem, we plan to implement service quota to address unpredictable/unbounded growth.
pull  push  metrics  tcp  stacks  monitoring  agents  twitter  fault-tolerance 
march 2016 by jm
Huginn
a system for building agents that perform automated tasks for you online. They can read the web, watch for events, and take actions on your behalf. Huginn's Agents create and consume events, propagating them along a directed event flow graph. Think of it as Yahoo! Pipes plus IFTTT on your own server. You always know who has your data. You do.


MIT-licensed open source, built on Rails.
ifttt  automation  huginn  ruby  rails  open-source  agents 
april 2014 by jm

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