Spark, Mesos, Akka, Cassandra and Kafka (SMACK) stack real time Big Data
Enterprise Big Data Cloud architect/developer need to use Big data solutions deployed in Cloud for reliability, scalability, agility, availability, and security. There are no comprehensive end-to-end hands on experience for Developers and Enterprise architects have to be able to design Big data solutions which can maximize for linear scalability and high availability. Why? Big data Analytics use-cases require sub-second response time with at least 99.99 % availability using massively parallel processing.
We will start with Apache Cassandra. Apache Cassandra is one of the best solutions for storing data for high availability and scalability. Modeling strategies help in designing solutions based on the application flow. Later, we will explore Cassandra time series data modeling.
Big Data applications require a faster speed of data processing and analysis. We will study topology with examples for building Spark applications. We will deep dive into Apache Spark applications, which connect into Cassandra. Spark streaming is used for processing real-time data.
We will explore Spark, Mesos, Akka, Cassandra and Kafka (SMACK) stack. We will look at how SMACK stack is helping build massively scalable applications in the cloud. Mesos is distributed systems kernel that can run on every machine and provides applications like Hadoop, Spark, Kafka, Elastic Search with APIs for resource management and scheduling across entire datacenter and cloud environments. Mesos help with scalability to 10,000 nodes and is fault-tolerant replicated master slave using ZooKeeper. Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM. Kafka is a distributed publish-subscribe messaging system that is designed to be fast, scalable, and durable.
The objective for this talk is to give clear direction on how to create scalable cloud ready Big Data applications with practical recopies to solve common problems. Building Elastic, Resilient, Scalable, Multi-workload, Efficient, and Isolated architecture using SMACK stack.
Enterprise Big Data Cloud architect/developer need to use Big data solutions deployed in Cloud for reliability, scalability, agility, availability, and security. There are no comprehensive end-to-end hands on experience for Developers and Enterprise architects have to be able to design Big data solutions which can maximize for linear scalability and high availability. Why? Big data Analytics use-cases require sub-second response time with at least 99.99 % availability using massively parallel processing.
We will start with Apache Cassandra. Apache Cassandra is one of the best solutions for storing data for high availability and scalability. Modeling strategies help in designing solutions based on the application flow. Later, we will explore Cassandra time series data modeling.
Big Data applications require a faster speed of data processing and analysis. We will study topology with examples for building Spark applications. We will deep dive into Apache Spark applications, which connect into Cassandra. Spark streaming is used for processing real-time data.
We will explore Spark, Mesos, Akka, Cassandra and Kafka (SMACK) stack. We will look at how SMACK stack is helping build massively scalable applications in the cloud. Mesos is distributed systems kernel that can run on every machine and provides applications like Hadoop, Spark, Kafka, Elastic Search with APIs for resource management and scheduling across entire datacenter and cloud environments. Mesos help with scalability to 10,000 nodes and is fault-tolerant replicated master slave using ZooKeeper. Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM. Kafka is a distributed publish-subscribe messaging system that is designed to be fast, scalable, and durable.
The objective for this talk is to give clear direction on how to create scalable cloud ready Big Data applications with practical recopies to solve common problems. Building Elastic, Resilient, Scalable, Multi-workload, Efficient, and Isolated architecture using SMACK stack.
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of Architecture working at Salesforce. Rohit has extensive experience architecting multi-tenant cloud-native solutions in Resilient Microservices Service-Oriented architectures using AWS Stack. In addition, Rohit has a proven ability in designing solutions and executing and delivering transformational programs that reduce costs and increase efficiencies.
As a trusted advisor, leader, and collaborator, Rohit applies problem resolution, analytical, and operational skills to all initiatives and develops strategic requirements and solution analysis through all stages of the project life cycle and product readiness to execution.
Rohit excels in designing scalable cloud microservice architectures using Spring Boot and Netflix OSS technologies using AWS and Google clouds. As a Security Ninja, Rohit looks for ways to resolve application security vulnerabilities using ethical hacking and threat modeling. Rohit is excited about architecting cloud technologies using Dockers, REDIS, NGINX, RightScale, RabbitMQ, Apigee, Azul Zing, Actuate BIRT reporting, Chef, Splunk, Rest-Assured, SoapUI, Dynatrace, and EnterpriseDB. In addition, Rohit has developed lambda architecture solutions using Apache Spark, Cassandra, and Camel for real-time analytics and integration projects.
Rohit has done MBA from Babson College in Corporate Entrepreneurship, Masters in Computer Science from Boston University and Harvard University. Rohit is a regular speaker at No Fluff Just Stuff, UberConf, RichWeb, GIDS, and other international conferences.
Rohit loves to connect on http://www.productivecloudinnovation.com.
http://linkedin.com/in/rohit-bhardwaj-cloud or using Twitter at rbhardwaj1.