Downloads provided by UsageCounts
In today?s world, every customer is thinking of agility, parallel development and reducing cost, especially infrastructure cost and operational cost. We have seen SOA world where we have written code and multiple services talk to each other?s for a business use case, but sometimes we end up with one big code base which is monolithic in nature and maintenance is becoming difficult. We have seen customers are using cloud and paying for on-demand services without effectively utilizing resources. These problems invite micro-services. In this paper, I am going to discuss how one should use micro-service in a production environment and local machine, how to scale, monitor and support Blue-Green deployment.
Big Data Analytics Social Analytics Storage Analytics Containers Cloud computing Virtual Machines Google Runtime Data Mitigation Metadata Docker.
Big Data Analytics Social Analytics Storage Analytics Containers Cloud computing Virtual Machines Google Runtime Data Mitigation Metadata Docker.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 9 | |
| downloads | 13 |

Views provided by UsageCounts
Downloads provided by UsageCounts