Diego Pacheco Tech blog

This was the second consecutive year, I do lectures at QCon Sao Paulo. Las year(2015) I was talking about DevOps . This year(2016) I was talking about my experiences with the Netflix Stack for building Reactive Microservices with Java 8. The talk is available here .

Boto3 is a kick ass AWS client for python. If you are working as a DevOps Engineer with Cloud that's a library you must check it out. Boto3 improved a lot the design in comparison with boto2. For this blog post, I will show how to do 2 simple things but yet very powerful things. Besides boto, I will show how to use Paramiko  another cool library in Python which can manipulate SSH and connect to boxes and perform commands. You will need to have an AWS account and you SECRETS in hand in order to make the code work. You can use python 2 or python 3 both can work with boto3.

On the previous posts of the series Telemetry and Microservices part 1 and part 2  I described the desired features of a modern observability / telemetry platform should target to address microservices monitoring needs. I've also blogged about Alerting and monitoring with Sensu part 1 and part 2 .  For this post, I will cover some components of the open source telemetry landscape which you can take advantage of your microservice monitoring architecture. For this blog post I will be talking a little bit more about the following solutions: 1. Sensu 2. Prometheus 3. OpenTSDB 4. Netflix Atlas 5.  Riemann 6. Graphite

June 1st, 2016 I will be speaking about my experiences with NetflixOSS and Dynomite at the Season 4 Episode 2 Netflix meetup. You can check out some posts I did about the NetflixOSS stack: http://diego-pacheco.blogspot.com/2015/09/netflixoss-devops-stack-for.html http://diego-pacheco.blogspot.com/2015/11/netflix-dynomitedyno-cluster-for-redis.html There are POCs and code samples available in my Github which you can check it out here .  Cheers, Diego Pacheco

This is the second blog post about Sensu as an Alerting and Monitoring solution. If you did not read the first part I recommend you check it out here . For this blog post, I will share a Vagrantfile so you have run sensu in your machine easily.  To play with Sensu you need to have some components like:  * A sensu Client  * A sensu Server  * RabbitMQ  * Uchiwa for Sensu Server TLDR;  Check it out all file in my GitHub account .

Everpad is an Evernote client for Ubuntu Linux. Evernote does not run in Linux. However, there is this client. Everpad is not perfect but it's a UI which kinda of works. This blog post will teach you how to install and run Everpad on Ubuntu Linux 15.10. You will need to have an Evernote account in order to log in to your Evernote account in Everpad.

Sensu is an Infrastructure and monitoring / telemetry solution. There are big sites using it such as Yahoo, Yelp, Cisco, and Tesla. Sensu provides standard solutions for monitoring and alerting.Which I can say is okay.  However If you have been following my Telemetry and Microservices blog posts series( part1 and part2 ) you will see sensu is not ideal for other use cases like:  * Dynamic Thresholds / ML * Infrastructure Tracking * Canary Because Sensu it doesn't have a Time Series database. You can use Sensu with Graphite or InfluxDB to work around it. However IMHO the solution it would be: have collectors(collectd) to get basic HOST metrics plus app instrumentation and them make checkers that do queries over the TSDB.