Friday, 27 November 2015

Riemann monitors distributed systems.

Riemann streams are just functions which accept an event. Events are just structs with some common fields like :host and :service You can use dozens of built-in streams for filtering, altering, and combining events, or write your own.
Since Riemann's configuration is a Clojure program, its syntax is concise, regular, and extendable. Configuration-as-code minimizes boilerplate and gives you the flexibility to adapt to complex situations.

I wrote Riemann for operations staff trying to keep a large, dynamic infrastructure running with unreliable but fault-tolerant components. For engineers who need to understand the source of errors and performance bottlenecks in production. For everyone fed up with traditional approaches; who want something fast, expressive, and powerful.
See problems faster

Traditional monitoring systems run polling loops every five minutes, or roll up metrics on a minutely basis. In a Riemann infrastructure, clients (including stand-alone pollers) *push* their events to Riemann, which makes them visible within milliseconds. Low latencies let you see outages faster--and know the instant you've fixed the problem.
Throughput depends on what your streams *do* with events, but a stock Riemann config on commodity x86 hardware can handle *millions* of events per second at sub-ms latencies, with 99ths around 5ms. Riemann is fully parallel and leverages Clojure and JVM concurrency primitives throughout.
Developer Environment:

Developers are all switching between tabs to view deployments, logs, commits etc!

My next project is to make a "Developers Physical Environment"

Using a Raspberry Pi connect multiple screens and display on each

  • 1. Server logs, 
  • 2. Git commits
  • 3.Newrelic performance 
  • 4. Deployemtn Logs

and more!
Next weekend project todo:

Sunday, 22 November 2015

AWS Architecture Center

The AWS Architecture Center is designed to provide you with the necessary guidance and application architecture best practices to build highly scalable and reliable applications in the AWS cloud.


Thursday, 19 November 2015