Tech Bytes

  Pros and Cons of CI-CD Pipelines CI-CD pipeline What is Continuous Integration? Continuous integration   (CI) and continuous delivery (CD) are the latest and one of the most used trends in software development. CI is when developers continuously and frequently integrate code in a shared repository or main branch multiple times in a day. But the changes that are made goes through several automated tests to rectify problems and get checks done. What is Continuous Delivery? Continuous delivery / Deployment is  a n extension of CI. In CD, the developers and other team members ensure that every change that takes place is releasable in the system. CD pushes the build further to delivery environments. CD, like CI has quantifiable risks. Pipelines are deployable unit paths once CI and CD are in place. Pros of CI/CD · Smaller codes are simple and have less unintended consequences. · Mean time to resolution ( MTTR ) is faster and shorter. · Fault isolation is smaller and faster. ...

  Graph database vs Relational database what is database What is database? A database is a collection of  logically related information  in an organised way so that it can be easily accessed, managed and updated. Some other operations can also be performed on database such as adding, updating and deleting data. A database could be simple as a single text file with a list of names or it could be complex as a large bunch of text files including some data. On the basis of different types of information, databases are of various types. Here, we will talk about  Graph and Relational databases . Full article:  http://entradasoft.com/blogs/graph-database-vs-relational-database Graph database graph database As the name suggests, it is a type of database in which graph structures are used to represent data. It is a database that uses graph structures for  semantic queries   with nodes, edges and properties to store and represent data in a uniform manner. A key ...

  Apache Spark vs Apache Storm difference between apache spark and storm Introduction to data streaming The need for real-time data streaming is growing exponentially due to the increase in real-time data. With streaming technologies leading the world of Big Data, it might be tough for the users to choose the appropriate real-time streaming platform. Two of the most popular real-time technologies that might consider for opting are Apache Spark and Apache Storm. One major key difference between the frameworks Spark and Storm is that Spark performs Data-Parallel computations, whereas Storm occupies Task-Parallel computations Apache Spark Apache Spark is a ge n eral-purpose, lighting fast,  cluster-computing  technology framework, used for fast computation on large-scale data processing. It can manage both batch and real-time analytics and data processing workloads. Apache Storm Apache Storm is an open-source, scalable fault-tolerant, and real-time stream processing computat...

Apache Pulsar Outperforms Apache Kafka by 2.5x on OpenMessaging Benchmark! Open messaging In a recent announcement by industry analyst firm Gigaom, the   OpenMessaging   benchmark performance results showed that Apache Pulsar delivers consistently superior throughput and latency even if at an increasing scale. OpenMessaging is a collaborative Linux Foundation effort that is supported by many large-scale companies with a mission to create a vendor-neutral, globally adopted and open standard for distributed messaging that can be deployed in on-premise, cloud and hybrid use cases. According to Gigaom, Apache Pulsar has outpaced Kafka cross all the workloads tested in their evaluation using the OpenMessaging benchmark. Here are t h e key results of the evaluation of  Apache Pulsar  and  Apache Kafka  using OpenMessaging benchmark: · Around 150% higher maximum throughput with Apache Pulsar. · Around 40% lower message latency and greater consistency in latency. ·...

Cloud Computing Deployment Models Cloud deployment models   What are the most popular   cloud deployment models ? There are four types of them: public, private, hybrid and community clouds. Additionally, there are also distributed clouds, multiclouds, poly clouds and other models, but they are not so widespread. As  cloud technology  is providing users with so many benefits, these benefits must have to be categorized based on users requirement.  Cloud deployment model  represents the exact category of cloud environment based on proprietorship, size, and access and also describes the nature and purpose of the cloud. Most organizations implement cloud infrastructure to minimize capital expenditure & regulate operating costs. Fu l l article:  http://entradasoft.com/blogs/cloud-computing-deployment-models-technical-know-how About deployment model Public Cloud Public Cloud  is a type of cloud hosting that allows the accessibility of systems & i...