Making web stack tasty using Cloudformation

1) MongoDB is used to collect analytics data from GitHub pages in real-time with over 10-15 million page views per day stored across 13 servers. 2) Data is stored in a denormalized manner across multiple collections to optimize for space, RAM, and read performance while live querying is supported. 3) As data volume grows over time, the data will need to be partitioned either by time frame, functionality, or individual servers to support the increased load.

Social Analytics with MongoDB

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This summary provides an overview of Buddy Media's experience using MongoDB for three stages of a project: Stage 1 was a non-critical logging application where they learned MongoDB is not like MySQL and to use subdocuments instead of rows/tables. Stage 2 involved critical user data with spikes where they learned to use modifier operators carefully and implement indexing and replica sets. Stage 3 was for real-time analytics of user events, requiring flexibility and high write volumes. They store aggregated metrics instead of individual events and use upserts and $inc to update in bulk, providing faster performance than SQL for their needs.

Elasticsearch und die Java-Welt

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Elasticsearch is an open source search and analytics engine that is distributed, horizontally scalable, reliable, and easy to manage. The document discusses how to install and interact with Elasticsearch using various Java clients and frameworks. It covers using the standard Java client directly, the Jest HTTP client, and Spring Data Elasticsearch which provides abstractions and dynamic repositories.

This document introduces mysqlnd_uh, a PHP extension that allows extending the mysqlnd PHP extension. It provides the following key points: - mysqlnd_uh allows hooking into mysqlnd's plugin architecture to modify its behavior through connection and result proxies. This can be used to add custom logging, input validation, or other preprocessing. - Examples are given showing how to set a custom timezone for all connections through a connection proxy, and how to replace query results with hardcoded data through a result proxy. - The document outlines mysqlnd's plugin architecture and which core files can be extended, such as mysqlnd.c and mysqlnd_result.c. It also discusses security considerations for proxies.

Node.js 與 google cloud storage

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Operational Intelligence with MongoDB Webinar

This document discusses using MongoDB for operational intelligence and real-time analytics of log and event data. It describes how MongoDB can ingest large volumes of data from multiple sources at high write volumes. Queries can then be performed rapidly to analyze the data and drill down into specific events. The aggregation framework is used to generate rollups and reports from the data on-demand or on a scheduled basis.

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MongoDB: How it Works

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MongoDB - Sharded Cluster Tutorial

This document provides an overview and instructions for deploying, upgrading, and troubleshooting a MongoDB sharded cluster. It describes the components of a sharded cluster including shards, config servers, and mongos processes. It provides recommendations for initial deployment including using replica sets for shards and config servers, DNS names instead of IPs, and proper user authorization. The document also outlines best practices for upgrading between minor and major versions, including stopping the balancer, upgrading processes in rolling fashion, and handling incompatible changes when downgrading major versions.

Using MongoDB and Python

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MongoDB can be used to store and query document-oriented data, and provides scalability through horizontal scaling. The document stores provide more flexibility than relational databases by allowing dynamic schemas with embedded documents. MongoDB combines the rich querying of relational databases with the flexibility and scalability of NoSQL databases. It uses indexes to improve query performance and supports features like aggregation, geospatial queries, and text search.

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Node.js is a platform for building scalable server-side web applications using JavaScript. It uses non-blocking I/O and event-driven architecture to handle thousands of concurrent connections with high throughput and low latency. Some key features include using Google's V8 JavaScript engine, support for CommonJS modules, asynchronous and event-driven programming, and a large ecosystem of open-source modules. Node.js is particularly suited for real-time web applications that require bidirectional communication.

Peggy elasticsearch應用

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The document discusses Elasticsearch concepts and operations including: 1. Field datatypes in Elasticsearch including simple, hierarchical, and specialized types. 2. Search operations using GET and POST, and query syntax including query_string, bool, date range, and nested queries. 3. Additional query parameters like size, from, sort, filter, and aggregations to customize search results. 4. The scan and scroll API for efficiently retrieving large result sets.

Template of rds

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This CloudFormation template defines the parameters and resources needed to create an encrypted RDS database instance running MySQL. It specifies parameters for the database name, instance ID, class, allocated storage, username, and password. The template defines an AWS::RDS::DBInstance resource that uses these parameters to create an encrypted RDS database instance with the provided configuration.

Hadoop - MongoDB Webinar June 2014

The document discusses Mongo-Hadoop integration and provides examples of using the Mongo-Hadoop connector to run MapReduce jobs on data stored in MongoDB. It covers loading and writing data to MongoDB from Hadoop, using Java MapReduce, Hadoop Streaming with Python, and analyzing data with Pig and Hive. Examples show processing an email corpus to build a graph of sender-recipient relationships and message counts.

MongoDB: Comparing WiredTiger In-Memory Engine to Redis

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New to MongoDB? This talk will introduce the philosophy and features of MongoDB. We’ll discuss the benefits of the document-based data model that MongoDB offers by walking through how one can build a simple app. We’ll cover inserting, updating, and querying the database of books. This session will jumpstart your knowledge of MongoDB development, providing you with context for the rest of the day's content.

Webinarserie: Einführung in MongoDB: “Back to Basics” - Teil 3 - Interaktion ...

The document discusses MongoDB basics including: 1) Inserting and querying documents using operators like $lt and $in 2) Returning documents through cursors and using projections to select attributes 3) Updating documents using operators like $push, $inc, and $addToSet along with bucketing and pre-aggregated reports It also covers durability options like acknowledged writes and waiting for replication.

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High-profile security breaches have become embarrassingly common, but ultimately avoidable. Now more than ever, database security is a critical component of any production application. In this talk you'll learn to secure your deployment in accordance with best practices and compliance regulations. We'll explore the MongoDB Enterprise features which ensure HIPAA and PCI compliance, and protect you against attack, data exposure and a damaged reputation.

Nodejs - A-quick-tour-v3

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Node.js is a server-side JavaScript platform for building scalable network applications. It uses non-blocking I/O and event-driven architecture, which makes it very efficient for data-intensive real-time applications that run across distributed devices. Some key features of Node.js include CommonJS modules, child processes, HTTP servers, TCP servers, DNS lookups, file watching and a package management system. Popular applications built with Node.js include web frameworks, real-time applications, crawlers and streaming.

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This document discusses CloudFormation and Elastic Beanstalk. CloudFormation allows provisioning and managing AWS resources through templates, while Elastic Beanstalk provides a web service for deploying and scaling web applications using predefined templates. The document compares the two services and provides examples of use cases where each would be more suitable. It also discusses how tools like Mobingi can provide application lifecycle management across multiple cloud platforms.

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The document discusses infrastructure as code best practices on AWS. It provides an overview of using AWS CloudFormation to define infrastructure in code. AWS CloudFormation allows infrastructure to be provisioned in an automated and repeatable way using templates that are version controlled like code. The document outlines the key components of a CloudFormation template including parameters, mappings, resources, outputs and conditionals. It also discusses using CloudFormation to bootstrap applications on EC2 instances.

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Template of rds

Hadoop - MongoDB Webinar June 2014

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The document discusses infrastructure as code and AWS CloudFormation. It provides an overview of using AWS CloudFormation templates to define infrastructure in code. Templates allow infrastructure to be version controlled and treated like code. They can be used to provision AWS resources in a declarative and repeatable way. The document also covers using CloudFormation to bootstrap applications on EC2 instances through the use of the AWS::CloudFormation::Init metadata key.

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With the AWS Cloud you have an on-demand, programmable infrastructure that you can manage using tools and practices from software development. You can create resources when you need and dispose of them when you don’t. Using Amazon CloudFormation you can describe your architecture in text files. To change your infrastructure, you edit those files. Having application and infrastructure code in a single, robust, versioned repository like Git gives a lot of advantages. Using AWS Elastic Beanstalk you can link your Git branches to different infrastructure environments (e.g. test, production) and automate deployments. You can create test environments on-demand, even for a short time. Instead of continuously update your resources, you can recreate them quickly from scratch, simplifying lifecycle management and making deployments immutable. As a result, you have more time to focus on the unique features of your application.

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Find out how to create automated infrastructure deployments using versioned Infrastructure as Code - CloudFormation templates on AWS. This talk will walk through two example CloudFormation templates. The first template will show how to use CloudFormation via AWS cli commands to create a Chef Server 12 instance and have it upload it’s client validation pem into private S3 bucket also created by the template. The second template will show how to use CloudFormation to create multiple client node instances in AWS EC2 and have them automatically bootstrap into the new Chef 12 Server instance. Links will be provided to the CloudFormation template code used for the demo for example purposes. https://youtu.be/WXLDdGxfEsI

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While many organizations have started to automate their software development processes, many still engineer their infrastructure largely by hand. Treating your infrastructure just like any other piece of code creates a “programmable infrastructure” that allows you to take full advantage of the scalability and reliability of the AWS cloud. This session will walk through practical examples of how AWS customers have merged infrastructure configuration with application code to create application-specific infrastructure and a truly unified development lifecycle. You will learn how AWS customers have leveraged tools like CloudFormation, orchestration engines, and source control systems to enable their applications to take full advantage of the scalability and reliability of the AWS cloud, create self-reliant applications, and easily recover when things go seriously wrong with their infrastructure.

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