high-availability

Currently we are using a Jenkins as our CI system and there is one master server and slaves which are provisioned by Saltstack on Openstack. If our Jenkins master server goes down, we need to create a new master and we need to pull the files from the old master & put it in new ones but it's gonna take at least 30mins. Is there any way to setup Jenkins with High Availability? I already check with Gearman Plugin , however if the Gearman server goes down for some reason, we need to setup a HA for Gearman also. Is there any other ways to setup a High Availability for Jenkins? Jenkins doesn't have

Closed . This question needs to be more focused. It is not currently accepting answers. Learn more . Want to improve this question? Update the question so it focuses on one problem only by editing this post . What's the difference between failover and disaster recovery? Vinko Vrsalovic Failover: When one machine fails, another machine (usually in the same location) takes over and resumes service Disaster recovery: When Godzilla destroys your data center, you do have alternative locations to keep providing your service and protocols/means for the other location to know how to keep delivering

I am trying to build the very lightweight solution for zero downtime deployment for Java apps. For the sake of simplicity lets think that we have two servers. My solution is to use: On the "front" -- some load balancer (software) - I am thinking about HAProxy here. On the "back" - two servers, both running Tomcat with deployed application. When we are about to deploy new release We disable one of the servers with HAProxy, so only one server (let's call it server A, which is running old release) will be available. Deploy new release on other server (let's call it server B), run production unit

There is a great talk here about simulating partition issues in Cassandra with Kingsby's Jesper library . My question is - with Cassandra are you mainly concerned with the Partitioning part of the CAP theorem, or is Consistency a factor you need to manage as well? Cassandra is typically classified as an AP system, meaning that availability and partition tolerance are generally considered to be more important than consistency. However, real world systems rarely fall neatly into these categories, so it's more helpful to view CAP as a continuum. Most systems will make some effort to be consistent

What are the best practices for database design and normalization for high traffic websites like stackoverflow? Should one use a normalized database for record keeping or a normalized technique or a combination of both? Is it sensible to design a normalized database as the main database for record keeping to reduce redundancy and at the same time maintain another denormalized form of the database for fast searching? or Should the main database be denormalized but with normalized views at the application level for fast database operations? or some other approach? The performance hit of joining

What design patterns or techniques have you used that are specifically geared toward scalability ? Patterns such as the Flyweight pattern seem to me to be a specialized version of the Factory Pattern , to promote high scalability or when working within memory or storage constraints. What others have you used? ( Denormalization of Databases , etc.) Do you find that the rules change when high availability or scalability is your primary goal? Possible situations are: Mobile devices with more limited memory, processing power, and connectivity than a Desktop or Laptop High # of users on limited