Diego Pacheco Tech blog

NetflixOSS Released a pretty interesting new solution. A framework for GrpahQL fully integrated with Spring Boot. DGS is super easy to use. You basically have zero effort to use it with Spring boot applications. DSG works with Maven or Gradle, Java, or Kotlin. Some time ago I made some posts about GraphQL and BFF you might want to check it out here and here . You compare with this other approach(also with a video) available here . Without further due, let's get started.  The Video The Code https://github.com/diegopacheco/java-pocs/tree/master/pocs/dsg-fun Cheers, Diego Pacheco

Some time ago I was sharing my experiences with a Dynomite Remediation Process I wrote. Iḿ using remediation systems for a while and IMHO the add lots of value since they automate manual Cloud Operation work and save time for people. Currently, I refactored my Remediation code and now the same code can support Dynomite / Dynomite Manager but also Apache Cassandra. There are very similar concepts between Dynomite and Cassandra Remediation such as discovering AWS EC2 Ips to be remediated, AWs Resourcing(Creating SGs, Deleting LCs, Updating ASGs), Health checking(Is the node up and running? Could I remediate right now or you are in the middle of a backup or just booting up?). Once I identified that core concept I was able to create a high level and generic design for Cassandra and Dynomite. This is great for cases of Patch / Fix(apply a new AMI) or Scale Up(Increase the memory or CPU for instance). Although that the main use cases and most important ones there were some c...

Working with the cloud is great but it's not easy. The Cloud allows us spins machines pretty easily, however, update these machines are not that an easy task, especially if we talking about databases. Today I want to share some experience with remediation process I've built for Dynomite in my current project.  I'm using NetflixOSS Dynomite in production(AWS) for more than 2 years now both as cache but also as Source of Truth. I need to say that is rock solid and just works. However often we need to increase some machine capacity, i.e: Add more memory or increase the disk size. There are times where we need to apply patches on the OS - I use Amazon Linux on Production on EC2 and recently there was the Meltdown and Spectre situation. Other times there are telemetry or even provisioning and configuration bugs that need to be fixed.  No matter the reason you will always need, time to time, change something on the underlying AMI or in the Java or C application which is ru...

Dynomite is a kick-ass project. Basically, allow you to have strong consistency on top of NoSQL Databases. I've been using dynomite for a while in production( AWS ) and I can say the core is rock solid and it just works. Lots of developers use Windows or Mac for instance and dynomite is built in C and it's really meant for Linux(Like all good things).  So some time ago I made 2 simple projects to get started quickly with dynomite.  Basically, the project creates a simple dynomite 3 node cluster and let you run on your local machine with docker . There are 2 projects - One to create a dynomite cluster with Redis -- The other with Facebook's RocksDB (Experimental). So you can use it on your local machine to Debug and it works just fine. So why not go 1 step further and run Dynomite in AWS using docker? There are cool benefits if you do this approach.

Want to learn how to build microservices using Java 8, NetflixOSS Stack(Eureka, RxNetty, Feign, Hystrix, Ribbon) using Kubernetes(Minikube).  That's the real deal you read it right. Get my videos series: Building Effective Microservices 80% until 30th November 2017.

NetflixOSS Archius 2 is a great Dynamic Configuration solution for microservices. Archaius is based on Apache Commons Configurations project . Using Archaius we can load configurations from several sources such as OS env vars or any Database like Oracle or even from Zookeeper. If there is a missing configuration source you can add it pretty easy and load your configs.  Archaius can be used in any java project no matter if is a microservice or not.  Archaius also support dynamic configuration refresh via callbacks -- In short, this means you can reload your configs without re-deploy or downtime in your microservice -- which is really great. Archaius has many nice features. Archaius also is very modular and easy to extend there are some nice community extensions available as well. 

NetflixOSS Governator is a set of Google Guice extensions to create REST services using Jersey . Using Governator we can easily configure servers like Jetty and Tomcat in order to build microservices. We also can use set of guice modules to integrated with Archaius and Eureka-Client. Governator is not opinionated, it's similar to Spring Boot in comparison. However, Governator is configured to work with Guice and not Spring framework. Governator it's cool because you can define pretty much everything using java code and annotations in a declarative fashion. All code is configured in Guice so we can take benefit of Ioc and Dependency injection and end up creating solution more testable by nature.

Dynomite it's a great solution for clustering with NoSQL Databases like Redis . Eureka is a nice Registry & Discoverability Solution. We can get best of both worlds using Prana . Prana is a sidecar that enables non-JVM applications to register in Eureka. Sometimes we could easily use multiple discoverability solutions like DNS, ETCD, Eureka etc... However not all discoverability provide the same benefits some tools are better suited for some jobs them other. I like ETCD and make sense onKubernetes world but if you are doing Java Microservices eureka makes more sense. The triad(Eureka, Prana, Dynomite) is great, This is great because then you can do discoverability on your database nodes, this is not great for several reasons like: Use the same tool for Registry / Discoverability Enable all sorts of dynamic programming which is great for DevOps Engineering Avoid AWS Throttling issues Make dyno clients more dynamic and this is a better solution them DNS like route5...

Netflix Dynomite is Kick Ass Generic Dynamo implementation for K/V Stores. Recently Netflix released the Dynomite-Manager  at he NetflixOSS Meetup Season 4 Episode 2 . Dynomite and Dynomite-Manager are Rock Solid both are a beautiful piece of engineering work. Dynomite has High Throughput and Low Latency. It gives superpowers to Redis making him Strong Consistent with Quorum like semantics and multi-datacenter.  It's possible to use Dynomite as Cache or as a Data Store.

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

Dynomite is brilliant. Kudos for NetflixOSS team because it kicks ass. First all they mixed several interesting, battle tested and sexy architectural ideas and deliver into a single solution. What would be Dynomite? You can think as a kick Ass Cluster for Memcached and Redis. But its way more than that. Dynomite is integrated with the Netflix Stack so you can use with Eureka and the rest of the stack. You dont need use Redis or Memcached if you dont want because Dynomite is modular so you can use the NoSQL or thing behind it. Dynomite is based on the Amazon Dynamo paper, so it implements the Consistence Hashing Ring, with quorum-like mechanisms, so you can have strong consistency and dont loss data(similar to Cassandra and Riak ) and also have some low latency and high throughput using Redis or Memcached Behind. Dynomite is written in C and its a proxy, it uses the twitter twemproxy as base solution. Replication is a aymetric, dynomite has a java client called Dyno with has...

NetflixOSS ICE is AWS COST monitoring solution. Similar to cloud watch but IMHO is better. There are some issues with ICE first of all is kinda of buggy at least right now - something you got some NPE and is hard to figure out what you did wrong. Second - its kinda of slow to run first time it take some time because it does lots of processing to figure out the costs.  You need have your billing configure right on AWS and also you need a S3 bucket to store the billing data so ICE and read and show the charts for you. We will install ICE on Amazon Linux OS(CentOS based).

Netflix Vector is a great monitoring tool for linux boxes.  Today i will show how to install, configure and run Netflix vector. We will do that on the AWS cloud. I will do the installations on the Amazon Linux OS (CentOS Based) but IMHO you can use other OS if you want like Ubuntu.

There are lots of people talking about microservices. IMHO I don`t most of people get it - Microservices are about Isolation, Idependence and Anti-Fragility and this are principles most of frameworks did not have. So the botton line is in the end of the day if you dont have this you are just doing OLD SOA ou even worst you might just be doing WebServices. Netflix get it. All the components are build guided by core architecture principles and anti-fragility is on the heart of this components.