vaquarkhan

AWS Certification notes

Those are my personal notes on AWS Solution Architect certification preparation. Hope you find them usefull.

To pass AWS certification, you should have:

• Sound knowledge about most of the AWS services ( EC2, VPC, RDS, Cloudfront, S3, Route53 etc,)
• Hands on experience with AWS services.
• Good knowledge of disaster recovery, security and High availability architectures.

If you do not have prior hands-on experience and knowledge or you have little knowledge about AWS services, it is better to take an online course. If you already have experience in architecting solutions on AWS it is not necessary to take an online course.

vaquarkhan

package org.myorg.quickstart;

import org.apache.flink.api.common.functions.CoGroupFunction;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.operators.DataSource;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.util.Collector;

vaquarkhan

A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.

---

Index:

vaquarkhan

A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.

---

Index:

vaquarkhan

Introduction to Kafka

Kafka acts as a kind of write-ahead log (WAL) that records messages to a persistent store (disk) and allows subscribers to read and apply these changes to their own stores in a system appropriate time-frame.

Terminology:

• Producers send messages to brokers
• Consumers read messages from brokers
• Messages are sent to a topic

vaquarkhan

Messaging Microservices

Messaging and asynchronous patterns are completely natural with microservices, but a lot of the start of the art material concentrates on HTTP, JSON and REST. This document is about "Message-driven Microservices" with Spring. It tracks the convergence of various ideas that are floating around in Spring Cloud, Spring Boot and Spring XD.

There is already a spring-xd-module-runner project where we started experimenting with allowing user to develop and run an XD module locally. We can extrapolate from there to a more flexible model that leads optionally to a deployable XD module, but can also be used to form more flexible structures than a simple "stream".

Basic Programming Model

Just create MessageChannels "input" and/or "output" and add @EnableMessageBus and run your app as a Spring Boot app (single application context). You need to connect to the physical broker for the bus, which is automatic if the relevant bus imple

vaquarkhan

fernando@fernando-Vostro-5470:~$ curl start.spring.io

  .   ____          _            __ _ _
 /\\ / ___'_ __ _ _(_)_ __  __ _ \ \ \ \
( ( )\___ | '_ | '_| | '_ \/ _` | \ \ \ \
 \\/  ___)| |_)| | | | | || (_| |  ) ) ) )
  '  |____| .__|_| |_|_| |_\__, | / / / /
 =========|_|==============|___/=/_/_/_/
 
:: Spring Initializr ::  https://start.spring.io

vaquarkhan

This is study path related to microservices. It is not a study path on programming, if you want to improve in this sense please take a look at this.

Introductory Videos

• Microservices • Fowler
• Principles Of Microservices by Sam Newman
• Practical Considerations For Microservice Architecture
• Microservices Antipatterns

vaquarkhan

1. General Background and Overview

• Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
• Models and Issues in Data Stream Systems
• Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

vaquarkhan

• A Deeper Understanding of Spark Internals
• Spark Runtime Internals (By LianCheng)
• Spark Runtime Internal (By Zhu Nan)
• Spark Interals (Code reading Guide)
• Spark Internals Git book