MongoDB is a document-oriented, open source database that is high performing, horizontally scalable, and full featured. It uses a flexible schema and stores data in flexible JSON-like documents which allows for an evolving schema. MongoDB can be easily scaled out across commodity servers and provides high availability with automatic replication and recovery. It supports dynamic queries and indexing and has drivers for many languages.
MongoDB 2.6 is the biggest MongoDB release ever. In this presentation you are going to explore which features, improvements and capabilities were added to the latest version and how you can smoothly upgrade your deployments.
MMS - Monitoring, backup and management at a single clickMatias Cascallares
MongoDB Management Service (MMS) makes operations effortless, reducing complicated tasks in big deployments to a couple of clicks. You can monitor, backup and manage your replica sets and sharded clusters through the MMS interface. In this presentation we are going to explore how to setup, use and get the best of MMS.
MongoDB Introduction talk at Dr Dobbs Conference, MongoDB Evenings at Bangalo...Prasoon Kumar
MongoDB is a leading nosql database. It is horizonatally scalable, document datastore. In this introduction given at Dr Dobbs Conference, Bangalore and Pune in April 2014, I show schema design with an example blog application and Python code snippets. I delivered the same in the maiden MongoDB Evening event at Delhi and Gurgaon in May 2014.
When constructing a data model for your MongoDB collection for CMS, there are various options you can choose from, each of which has its strengths and weaknesses. The three basic patterns are:
1.Store each comment in its own document.
2.Embed all comments in the “parent” document.
3.A hybrid design, stores comments separately from the “parent,” but aggregates comments into a small number of documents, where each contains many comments.
Code sample and wiki documentation is available on https://github.com/prasoonk/mycms_mongodb/wiki.
NoSQL datastores fall under the following categories: Key-value stores, document databases, column-family stores and graph databases. The traditional TPC-* tests are not sufficient for these heterogeneous database systems. MongoDB, CouchDB, Cassandra, HBase, Memcaches etc belong to one of 4 families and a common workload can be generated by ycsb to simulate your usecase and benchmark them.
In this session Sam Weaver, Product Manager at MongoDB will introduce MongoDB Compass, a new tool developed by MongoDB that allows you to easily visualize your MongoDB schema and build queries graphically. The session will include a practical demonstration of Compass as well as a discussion of its features and applications.
MongoDB 2.6 is the biggest MongoDB release ever. In this presentation you are going to explore which features, improvements and capabilities were added to the latest version and how you can smoothly upgrade your deployments.
MMS - Monitoring, backup and management at a single clickMatias Cascallares
MongoDB Management Service (MMS) makes operations effortless, reducing complicated tasks in big deployments to a couple of clicks. You can monitor, backup and manage your replica sets and sharded clusters through the MMS interface. In this presentation we are going to explore how to setup, use and get the best of MMS.
MongoDB Introduction talk at Dr Dobbs Conference, MongoDB Evenings at Bangalo...Prasoon Kumar
MongoDB is a leading nosql database. It is horizonatally scalable, document datastore. In this introduction given at Dr Dobbs Conference, Bangalore and Pune in April 2014, I show schema design with an example blog application and Python code snippets. I delivered the same in the maiden MongoDB Evening event at Delhi and Gurgaon in May 2014.
When constructing a data model for your MongoDB collection for CMS, there are various options you can choose from, each of which has its strengths and weaknesses. The three basic patterns are:
1.Store each comment in its own document.
2.Embed all comments in the “parent” document.
3.A hybrid design, stores comments separately from the “parent,” but aggregates comments into a small number of documents, where each contains many comments.
Code sample and wiki documentation is available on https://github.com/prasoonk/mycms_mongodb/wiki.
NoSQL datastores fall under the following categories: Key-value stores, document databases, column-family stores and graph databases. The traditional TPC-* tests are not sufficient for these heterogeneous database systems. MongoDB, CouchDB, Cassandra, HBase, Memcaches etc belong to one of 4 families and a common workload can be generated by ycsb to simulate your usecase and benchmark them.
In this session Sam Weaver, Product Manager at MongoDB will introduce MongoDB Compass, a new tool developed by MongoDB that allows you to easily visualize your MongoDB schema and build queries graphically. The session will include a practical demonstration of Compass as well as a discussion of its features and applications.
How Thermo Fisher is Reducing Data Analysis Times from Days to Minutes with M...MongoDB
Speaker: Joseph Fluckiger, Senior Software Architect, ThermoFisher Scientific
Level: 200 (Intermediate)
Track: Atlas
Mass spectrometry is the gold standard for determining chemical compositions, with spectrometers often measuring the mass of a compound down to a single electron. This level of granularity produces an enormous amount of hierarchical data that doesn't fit well into rows and columns. In this talk, learn how Thermo Fisher is using MongoDB Atlas on AWS to allow their users to get near real-time insights from mass spectrometry experiments – a process that used to take days. We also share how the underlying database service used by Thermo Fisher was built on AWS.
What You Will Learn:
- How we modeled mass spectrometry data to enable us to write and read an enormous about of experimental data efficiently.
- Learn about the best MongoDB tools and patterns for .NET applications.
- Live demo of scaling a MongoDB Atlas cluster with zero down time and visualizing live data from a million dollar Mass Spectrometer stored in MongoDB.
MongoDB has been conceived for the cloud age. Making sure that MongoDB is compatible and performant around cloud providers is mandatory to achieve complete integration with platforms and systems. Azure is one of biggest IaaS platforms available and very popular amongst developers that work on Microsoft Stack.
New generations of database technologies are allowing organizations to build applications never before possible, at a speed and scale that were previously unimaginable. MongoDB is the fastest growing database on the planet, and the new 3.2 release will bring the benefits of modern database architectures to an ever broader range of applications and users.
MongoDB Days Silicon Valley: A Technical Introduction to WiredTiger MongoDB
Presented by Osmar Olivo, Product Manager, MongoDB
Experience level: Introductory
WiredTiger is MongoDB's first officially supported pluggable storage engine as well as the new default engine in 3.2. It exposes several new features and configuration options. This talk will highlight the major differences between the MMAPV1 and WiredTiger storage engines including currency, compression, and caching.
MongoDB .local Bengaluru 2019: Using MongoDB Services in Kubernetes: Any Plat...MongoDB
MongoDB Kubernetes operator is ready for prime-time. Learn about how MongoDB can be used with most popular orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications.
AWS is an incredibly popular environment for running MongoDB deployments. Today you have many choices about instance type, storage, network config, security, how you configure MongoDB processes, and more. In addition, you now have options when it comes to tooling to help you manage and operate your deployment. In this session, we’ll take a look at several recommendations that can help you get the best performance out of AWS.
In this webinar, we will be covering general best practices for running MongoDB on AWS.
Topics will range from instance selection to storage selection and service distribution to ensure service availability. We will also look at any specific best practices related to using WiredTiger. We will then shift gears and explore recommended strategies for managing your MongoDB instance on AWS.
This session also includes a live Q&A portion during which you are encouraged to ask questions of our team.
MongoDB 3.0 introduces a new pluggable storage engine API and a new storage engine called WiredTiger. The engineering team behind WiredTiger team has a long and distinguished career, having architected and built Berkeley DB, now the world's most widely used embedded database. In this talk we will describe our original design goals for WiredTiger, including considerations we made for heavily threaded hardware, large on-chip caches, and SSD storage. We'll also look at some of the latch-free and non-blocking algorithms we've implemented, as well as other techniques that improve scaling, overall throughput and latency. Finally, we'll take a look at some of the features we hope to incorporate into WiredTiger and MongoDB in the future.
The storage engine is responsible for managing how data is stored, both in memory and on disk. MongoDB supports multiple storage engines, as different engines perform better for specific workloads.
View this presentation to understand:
What a storage engine is
How to pick a storage engine
How to configure a storage engine and a replica set
MongoDB San Francisco 2013: Storing eBay's Media Metadata on MongoDB present...MongoDB
This session will be a case study of eBay’s experience running MongoDB for project Zoom, in which eBay stores all media metadata for the site. This includes references to pictures of every item for sale on eBay. This cluster is eBay's first MongoDB installation on the platform and is a mission critical application. Yuri Finkelstein, an Enterprise Architect on the team, will provide a technical overview of the project and its underlying architecture.
Webinar: Enabling Microservices with Containers, Orchestration, and MongoDBMongoDB
Want to try out MongoDB on your laptop? Execute a single command and you have a lightweight, self-contained sandbox; another command removes all trace when you're done. Need an identical copy of your application stack in multiple environments? Build your own container image and then your entire development, test, operations, and support teams can launch an identical clone environment.
Containers are revolutionizing the entire software lifecycle: from the earliest technical experiments and proofs of concept through development, test, deployment, and support. Orchestration tools manage how multiple containers are created, upgraded and made highly available. Orchestration also controls how containers are connected to build sophisticated applications from multiple, microservice containers.
This webinar introduces the concepts behind containers and orchestration, then explains the available technologies and how to use them with MongoDB. Finally, you will see a demonstration of exactly how to create a MongoDB replica set on Docker and Kubernetes within the Google Cloud.
Technical feature review of features introduced by MongoDB 3.4 on graph capabilities, MongoDB UI tool: Compass, improvements on the replication and aggregation framework stages and utils. Operations improvements on Ops Manager and MongoDB Atlas.
MongoDB .local Bengaluru 2019: Lift & Shift MongoDB to AtlasMongoDB
Managing and scaling the infrastructure for critical business data can be a real pain. To handle this massive scale of data effectively, thousands of users of MongoDB from all around the world have migrated their large and small databases to MongoDB Atlas.
By the end of this talk, you'll have a better understanding of the “how” and “why” of it, and will be able to leverage it in your organisation with elevated confidence. I'll demo the migration of a realtime application using MongoDB from existing cloud infrastructure to MongoDB Atlas.
If you're a developer, DBA or a business stakeholder, and your organisation is using/planning to use MongoDB on-premise or with any other cloud vendor, this talk will help you to gain insights into the best way to run MongoDB.
MongoDB .local Bengaluru 2019: New Encryption Capabilities in MongoDB 4.2: A ...MongoDB
Many applications with high-sensitivity workloads require enhanced technical options to control and limit access to confidential and regulated data. In some cases, system requirements or compliance obligations dictate a separation of duties for staff operating the database and those who maintain the application layer. In cloud-hosted environments, certain data are sometimes deemed too sensitive to store on third-party infrastructure. This is a common pain for system architects in the healthcare, finance, and consumer tech sectors — the benefits of managed, easily expanded compute and storage have been considered unavailable because of data confidentiality and privacy concerns.
This session will take a deep dive into new security capabilities in MongoDB 4.2 that address these scenarios, by enabling native client-side field-level encryption, using customer-managed keys. We will review how confidential data can be securely stored and easily accessed by applications running on MongoDB. Common query design patterns will be presented, with example code demonstrating strong end-to-end encryption in Atlas or on-premise. Implications for developers and others designing systems in regulated environments will be discussed, followed by a Q&A with senior MongoDB security engineers.
Shift: Real World Migration from MongoDB to CassandraDataStax
Presentation on SHIFT's migration from MongoDB to Cassandra. Topics will include reasons behind choosing to move to Cassandra, zero downtime migration strategy, data modeling patterns, and the benefits of using CQL3.
MongoDB in the Middle of a Hybrid Cloud and Polyglot Persistence ArchitectureMongoDB
The Sage Data Cloud enables next-generation cloud and mobile services via a Hybrid Cloud and Polyglot Persistence Architecture. Come learn how MongoDB and other cloud data stores make this a reality, and get an insight into our learnings and operations.
Webinar: Build an Application Series - Session 2 - Getting StartedMongoDB
This session - presented by Matthew Bates, Solutions Architect & Consulting Engineer at MongoDB - will cover an outline of an application, schema design decisions, application functionality and design for scale out.
About the speaker
Matthew Bates is a Solutions Architect in the EMEA region for MongoDB and helps advise customers how to best use and make the most out of MongoDB in their organisations. He has a background in solutions for the acquisition, management and exploitation of big data in government and public sector and telco industries through his previous roles at consultancy firms and a major European telco. He's a Java and Python coder and has a BSc(Hons) in Computer Science from the University of Nottingham.
Next in the Series:
February 20th 2014
Build an Application Series - Session 3 - Interacting with the database:
This webinar will discuss queries and updates and the interaction between an application and a database
March 6th 2014
Build an Application Series - Session 4 - Indexing:
This session will focus on indexing strategies for the application, including geo spatial and full text search
March 20th 2014
Build an Application Series - Session 5 - Reporting in your application:
This session covers Reporting and Aggregation Framework and Building application usage reports
April 3th 2014
Operations for your application - Session 6 - Deploying the application:
By this stage, we will have built the application. Now we need to deploy it. We will discuss architecture for High Availability and scale out
April 17th 2014
Operations for your application - Session 7 - Backup and DR:
This webinar will discuss back up and restore options. Learn what you should do in the event of a failure and how to perform a backup and recovery of the data in your applications
May 6th 2014
Operations for your application - Session 8 - Monitoring and Performance Tuning:
The final webinar of the series will discuss what metrics are important and how to manage and monitor your application for key performance.
How Thermo Fisher is Reducing Data Analysis Times from Days to Minutes with M...MongoDB
Speaker: Joseph Fluckiger, Senior Software Architect, ThermoFisher Scientific
Level: 200 (Intermediate)
Track: Atlas
Mass spectrometry is the gold standard for determining chemical compositions, with spectrometers often measuring the mass of a compound down to a single electron. This level of granularity produces an enormous amount of hierarchical data that doesn't fit well into rows and columns. In this talk, learn how Thermo Fisher is using MongoDB Atlas on AWS to allow their users to get near real-time insights from mass spectrometry experiments – a process that used to take days. We also share how the underlying database service used by Thermo Fisher was built on AWS.
What You Will Learn:
- How we modeled mass spectrometry data to enable us to write and read an enormous about of experimental data efficiently.
- Learn about the best MongoDB tools and patterns for .NET applications.
- Live demo of scaling a MongoDB Atlas cluster with zero down time and visualizing live data from a million dollar Mass Spectrometer stored in MongoDB.
MongoDB has been conceived for the cloud age. Making sure that MongoDB is compatible and performant around cloud providers is mandatory to achieve complete integration with platforms and systems. Azure is one of biggest IaaS platforms available and very popular amongst developers that work on Microsoft Stack.
New generations of database technologies are allowing organizations to build applications never before possible, at a speed and scale that were previously unimaginable. MongoDB is the fastest growing database on the planet, and the new 3.2 release will bring the benefits of modern database architectures to an ever broader range of applications and users.
MongoDB Days Silicon Valley: A Technical Introduction to WiredTiger MongoDB
Presented by Osmar Olivo, Product Manager, MongoDB
Experience level: Introductory
WiredTiger is MongoDB's first officially supported pluggable storage engine as well as the new default engine in 3.2. It exposes several new features and configuration options. This talk will highlight the major differences between the MMAPV1 and WiredTiger storage engines including currency, compression, and caching.
MongoDB .local Bengaluru 2019: Using MongoDB Services in Kubernetes: Any Plat...MongoDB
MongoDB Kubernetes operator is ready for prime-time. Learn about how MongoDB can be used with most popular orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications.
AWS is an incredibly popular environment for running MongoDB deployments. Today you have many choices about instance type, storage, network config, security, how you configure MongoDB processes, and more. In addition, you now have options when it comes to tooling to help you manage and operate your deployment. In this session, we’ll take a look at several recommendations that can help you get the best performance out of AWS.
In this webinar, we will be covering general best practices for running MongoDB on AWS.
Topics will range from instance selection to storage selection and service distribution to ensure service availability. We will also look at any specific best practices related to using WiredTiger. We will then shift gears and explore recommended strategies for managing your MongoDB instance on AWS.
This session also includes a live Q&A portion during which you are encouraged to ask questions of our team.
MongoDB 3.0 introduces a new pluggable storage engine API and a new storage engine called WiredTiger. The engineering team behind WiredTiger team has a long and distinguished career, having architected and built Berkeley DB, now the world's most widely used embedded database. In this talk we will describe our original design goals for WiredTiger, including considerations we made for heavily threaded hardware, large on-chip caches, and SSD storage. We'll also look at some of the latch-free and non-blocking algorithms we've implemented, as well as other techniques that improve scaling, overall throughput and latency. Finally, we'll take a look at some of the features we hope to incorporate into WiredTiger and MongoDB in the future.
The storage engine is responsible for managing how data is stored, both in memory and on disk. MongoDB supports multiple storage engines, as different engines perform better for specific workloads.
View this presentation to understand:
What a storage engine is
How to pick a storage engine
How to configure a storage engine and a replica set
MongoDB San Francisco 2013: Storing eBay's Media Metadata on MongoDB present...MongoDB
This session will be a case study of eBay’s experience running MongoDB for project Zoom, in which eBay stores all media metadata for the site. This includes references to pictures of every item for sale on eBay. This cluster is eBay's first MongoDB installation on the platform and is a mission critical application. Yuri Finkelstein, an Enterprise Architect on the team, will provide a technical overview of the project and its underlying architecture.
Webinar: Enabling Microservices with Containers, Orchestration, and MongoDBMongoDB
Want to try out MongoDB on your laptop? Execute a single command and you have a lightweight, self-contained sandbox; another command removes all trace when you're done. Need an identical copy of your application stack in multiple environments? Build your own container image and then your entire development, test, operations, and support teams can launch an identical clone environment.
Containers are revolutionizing the entire software lifecycle: from the earliest technical experiments and proofs of concept through development, test, deployment, and support. Orchestration tools manage how multiple containers are created, upgraded and made highly available. Orchestration also controls how containers are connected to build sophisticated applications from multiple, microservice containers.
This webinar introduces the concepts behind containers and orchestration, then explains the available technologies and how to use them with MongoDB. Finally, you will see a demonstration of exactly how to create a MongoDB replica set on Docker and Kubernetes within the Google Cloud.
Technical feature review of features introduced by MongoDB 3.4 on graph capabilities, MongoDB UI tool: Compass, improvements on the replication and aggregation framework stages and utils. Operations improvements on Ops Manager and MongoDB Atlas.
MongoDB .local Bengaluru 2019: Lift & Shift MongoDB to AtlasMongoDB
Managing and scaling the infrastructure for critical business data can be a real pain. To handle this massive scale of data effectively, thousands of users of MongoDB from all around the world have migrated their large and small databases to MongoDB Atlas.
By the end of this talk, you'll have a better understanding of the “how” and “why” of it, and will be able to leverage it in your organisation with elevated confidence. I'll demo the migration of a realtime application using MongoDB from existing cloud infrastructure to MongoDB Atlas.
If you're a developer, DBA or a business stakeholder, and your organisation is using/planning to use MongoDB on-premise or with any other cloud vendor, this talk will help you to gain insights into the best way to run MongoDB.
MongoDB .local Bengaluru 2019: New Encryption Capabilities in MongoDB 4.2: A ...MongoDB
Many applications with high-sensitivity workloads require enhanced technical options to control and limit access to confidential and regulated data. In some cases, system requirements or compliance obligations dictate a separation of duties for staff operating the database and those who maintain the application layer. In cloud-hosted environments, certain data are sometimes deemed too sensitive to store on third-party infrastructure. This is a common pain for system architects in the healthcare, finance, and consumer tech sectors — the benefits of managed, easily expanded compute and storage have been considered unavailable because of data confidentiality and privacy concerns.
This session will take a deep dive into new security capabilities in MongoDB 4.2 that address these scenarios, by enabling native client-side field-level encryption, using customer-managed keys. We will review how confidential data can be securely stored and easily accessed by applications running on MongoDB. Common query design patterns will be presented, with example code demonstrating strong end-to-end encryption in Atlas or on-premise. Implications for developers and others designing systems in regulated environments will be discussed, followed by a Q&A with senior MongoDB security engineers.
Shift: Real World Migration from MongoDB to CassandraDataStax
Presentation on SHIFT's migration from MongoDB to Cassandra. Topics will include reasons behind choosing to move to Cassandra, zero downtime migration strategy, data modeling patterns, and the benefits of using CQL3.
MongoDB in the Middle of a Hybrid Cloud and Polyglot Persistence ArchitectureMongoDB
The Sage Data Cloud enables next-generation cloud and mobile services via a Hybrid Cloud and Polyglot Persistence Architecture. Come learn how MongoDB and other cloud data stores make this a reality, and get an insight into our learnings and operations.
Webinar: Build an Application Series - Session 2 - Getting StartedMongoDB
This session - presented by Matthew Bates, Solutions Architect & Consulting Engineer at MongoDB - will cover an outline of an application, schema design decisions, application functionality and design for scale out.
About the speaker
Matthew Bates is a Solutions Architect in the EMEA region for MongoDB and helps advise customers how to best use and make the most out of MongoDB in their organisations. He has a background in solutions for the acquisition, management and exploitation of big data in government and public sector and telco industries through his previous roles at consultancy firms and a major European telco. He's a Java and Python coder and has a BSc(Hons) in Computer Science from the University of Nottingham.
Next in the Series:
February 20th 2014
Build an Application Series - Session 3 - Interacting with the database:
This webinar will discuss queries and updates and the interaction between an application and a database
March 6th 2014
Build an Application Series - Session 4 - Indexing:
This session will focus on indexing strategies for the application, including geo spatial and full text search
March 20th 2014
Build an Application Series - Session 5 - Reporting in your application:
This session covers Reporting and Aggregation Framework and Building application usage reports
April 3th 2014
Operations for your application - Session 6 - Deploying the application:
By this stage, we will have built the application. Now we need to deploy it. We will discuss architecture for High Availability and scale out
April 17th 2014
Operations for your application - Session 7 - Backup and DR:
This webinar will discuss back up and restore options. Learn what you should do in the event of a failure and how to perform a backup and recovery of the data in your applications
May 6th 2014
Operations for your application - Session 8 - Monitoring and Performance Tuning:
The final webinar of the series will discuss what metrics are important and how to manage and monitor your application for key performance.
This talk will introduce the philosophy and features of the open source, NoSQL 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 to store books. We’ll cover inserting, updating, and querying the database of books.
Dev Jumpstart: Build Your First App with MongoDBMongoDB
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 to store books. 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.
MongoDB presentation for NYC Python's June meetup. Brief discussion on non-relational databases in general followed by an example of using MongoDB as a blog's backend
This presentation was given at the LDS Tech SORT Conference 2011 in Salt Lake City. The slides are quite comprehensive covering many topics on MongoDB. Rather than a traditional presentation, this was presented as more of a Q & A session. Topics covered include. Introduction to MongoDB, Use Cases, Schema design, High availability (replication) and Horizontal Scaling (sharding).
Dev Jumpstart: Build Your First App with MongoDBMongoDB
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 to store books. 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.
Dev Jumpstart: Build Your First App with MongoDBMongoDB
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.
This webinar will walk you through building a simple location-based check-in app in MongoDB. We’ll cover the basics of MongoDB’s document model, query language, map reduce framework, and deployment architecture.
In this webinar you will discover:
- Why MongoDB is being adopted in organizations large and small
- How easy it is to start building applications with MongoDB
- Key features for manipulating and accessing data
- High availability and scale-out architecture
Back to Basics 2017: Mí primera aplicación MongoDBMongoDB
Descubra:
Cómo instalar MongoDB y usar el shell de MongoDB
Las operaciones básicas de CRUD
Cómo analizar el rendimiento de las consultas y añadir un índice
Presentation on MongoDB given at the Hadoop DC meetup in October 2009. Some of the slides at the end are extra examples that didn't appear in the talk, but might be of interest.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
3. MongoDB is a ___________ database
1. Document
2. Open source
3. High performance
4. Horizontally scalable
5. Full featured
4. 1. Document Database
• Not for .PDF & .DOC files
• A document is essentially an associative array
• Document = JSON object
• Document = PHP Array
• Document = Python Dict
• Document = Ruby Hash
• etc
5. 1. NoSQL Data Model
Key-Value
Store
Riak
Memcache
Project
Voldemort
Redis
BerkeleyDB
Document
Database
MongoDB
CouchDB
OrientDB
Column-Family
Stores
Amazon
SimpleDB
Cassandra
Hbase
Hypertable
Graph
Databases
Neo4J
FlockDB
OrientDB
6. 2. Open Source
• MongoDB is an open source project
• On GitHub
• Licensed under the AGPL
• Started & sponsored by MongoDB Inc (formerly
known as 10gen)
• Commercial licenses available
• Contributions welcome
7. 3. High Performance
• Written in C++
• Extensive use of memory-mapped files
i.e.read-through write-through memory caching.
• Runs nearly everywhere
• Data serialized as BSON (fast parsing)
• Full support for primary & secondary indexes
• Document model = less work
10. 4. High Availability
• Automated replication and failover
• Multi-data center support
• Improved operational simplicity (e.g., HW swaps)
• Data durability and consistency
12. 5. Full Featured
• Ad Hoc queries
• Real time aggregation
• Rich query capabilities
• Strongly consistent
• Geospatial features
• Support for most programming languages
• Flexible schema
15. $ tar –zxvf mongodb-osx-x86_64-2.6.0.tgz
$ cd mongodb-osx-i386-2.6.0/bin
$ mkdir –p /data/db
$ ./mongod
Running MongoDB
16. MacBook-Pro-:~ $ mongo
MongoDB shell version: 2.6.0
connecting to: test
> db.cms.insert({text: 'Welcome to MongoDB'})
> db.cms.find().pretty()
{
"_id" : ObjectId("51c34130fbd5d7261b4cdb55"),
"text" : "Welcome to MongoDB"
}
Mongo Shell
17. _id
• _id is the primary key in MongoDB
• Automatically indexed
• Automatically created as an ObjectId if not provided
• Any unique immutable value could be used
18. ObjectId
• ObjectId is a special 12 byte value
• Guaranteed to be unique across your cluster
• ObjectId("50804d0bd94ccab2da652599")
|----ts-----||---mac---||-pid-||----inc-----|
4 3 2 3
34. MongoDB Drivers
• Official Support for 12 languages
• Community drivers for tons more
• Drivers connect to mongo servers
• Drivers translate BSON into native types
• mongo shell is not a driver,but works like one in some
ways
• Installed using typical means (maven,npm,pecl,gem,
pip)
40. Retrive using Comparison Operators
$gt,$gte,$in,$lt,$lte,$ne,$nin
• Use to query documents
• Logical:$or,$and,$not,$nor Element:$exists,$type
• Logical:$or,$and,$not,$nor Element:$exists,$type
• Evaluation:$mod,$regex,$where Geospatial:$geoWithin,$geoIntersects,$near,$nearSphere
41. Modelling comments (1)
• Two collections–articles and comments
• Use a reference (i.e. foreign key) to link together
• But.. N+1 queries to retrieve article and comments
{
‘_id’: ObjectId(..),
‘title’:‘Schema design in MongoDB’,
‘author’:‘mattbates’,
‘date’: ISODate(..),
‘tags’: [‘MongoDB’, ‘schema’],
‘section’:‘schema’,
‘slug’:‘schema-design-in-mongodb’,
‘comments’:[ObjectId(..),…]
}
{ ‘_id’: ObjectId(..),
‘article_id’: 1,
‘text’: ‘A great article,helped me
understand schema design’,
‘date’: ISODate(..),,
‘author’:‘johnsmith’
}
43. Modelling comments (2)
• Single articles collection–
embed comments in article
documents
• Pros
• Single query, document designed
for the access pattern
• Locality (disk, shard)
• Cons
• Comments array is unbounded;
documents will grow in size
(remember 16MB document
limit)
{
‘_id’: ObjectId(..),
‘title’:‘Schema design in MongoDB’,
‘author’:‘mattbates’,
‘date’: ISODate(..),
‘tags’: [‘MongoDB’,‘schema’],
…
‘comments’:[
{
‘text’: ‘Agreatarticle,helpedme
understandschemadesign’,
‘date’:ISODate(..),
‘author’:‘johnsmith’
},
…
]
}
44. Modelling comments (3)
• Another option: hybrid of (2) and (3),embed
top x comments (e.g.by date,popularity) into
the article document
• Fixed-size (2.4 feature) comments array
• All other comments ‘overflow’ into a comments
collection (double write) in buckets
• Pros
– Document size is more fixed – fewer moves
– Single query built
– Full comment history with rich query/aggregation
45. Modelling comments (3)
{
‘_id’:ObjectId(..),
‘title’:‘SchemadesigninMongoDB’,
‘author’:‘mattbates’,
‘date’:ISODate(..),
‘tags’:[‘MongoDB’, ‘schema’],
…
‘comments_count’:45,
‘comments_pages’:1
‘comments’:[
{
‘text’: ‘Agreatarticle,helpedme
understandschemadesign’,
‘date’:ISODate(..),
‘author’:‘johnsmith’
},
…
]
}
Total number of comments
• Integer counter updated by
update operation as
comments added/removed
Number of pages
• Page is a bucket of 100
comments (see next slide..)
Fixed-size comments array
• 10 most recent
• Sorted by date on insertion
46. Modelling comments (3)
{
‘_id’: ObjectId(..),
‘article_id’: ObjectId(..),
‘page’: 1,
‘count’: 42
‘comments’: [
{
‘text’: ‘A great article,helped me
understand schema design’,
‘date’: ISODate(..),
‘author’:‘johnsmith’
},
…
}
One comment bucket
(page) document
containing up to about 100
comments
Array of 100 comment sub-
documents
47. Modelling interactions
• Interactions
– Article views
– Comments
– (Social media sharing)
• Requirements
– Time series
– Pre-aggregated in preparation for analytics
48. Modelling interactions
• Document per article per day–
‘bucketing’
• Daily counter and hourly sub-
document counters for interactions
• Bounded array (24 hours)
• Single query to retrieve daily article
interactions; ready-made for
graphing and further aggregation
{
‘_id’: ObjectId(..),
‘article_id’: ObjectId(..),
‘section’:‘schema’,
‘date’: ISODate(..),
‘daily’: {‘views’: 45,‘comments’: 150 }
‘hours’: {
0 : {‘views’: 10 },
1 : {‘views’: 2 },
…
23 : {‘comments’: 14,‘views’: 10 }
}
}
49. JSON and RESTful API
Client-side
JSON
(eg AngularJS, (BSON)
Real applications are not built at a shell–let’s build a RESTful API.
Pymongo driver
Python web
app
HTTP(S) REST
Examples to follow: Python RESTful API using Flask microframework
50. myCMS REST endpoints
Method URI Action
GET /articles Retrieve all articles
GET /articles-by-tag/[tag] Retrieve all articles by tag
GET /articles/[article_id] Retrieve a specific article by article_id
POST /articles Add a new article
GET /articles/[article_id]/comments Retrieve all article comments by
article_id
POST /articles/[article_id]/comments Add a new comment to an article.
POST /users Register a user user
GET /users/[username] Retrieve user’s profile
PUT /users/[username] Update a user’s profile
51. $ git clone http://www.github.com/prasoonk/mycms_mongodb
$ cd mycms-mongodb
$ virtualenv venv
$ source venv/bin/activate
$ pip install –r requirements.txt
$ mkdir –p data/db
$ mongod --dbpath=data/db --fork --logpath=mongod.log
$ python web.py
[$ deactivate]
Getting started with the skeleton code
52. @app.route('/cms/api/v1.0/articles', methods=['GET'])
def get_articles():
"""Retrieves all articles in the collection
sorted by date
"""
# query all articles and return a cursor sorted by date
cur = db['articles'].find().sort('date’)
if not cur:
abort(400)
# iterate the cursor and add docs to a dict
articles = [article for article in cur]
return jsonify({'articles' : json.dumps(articles, default=json_util.default)})
RESTful API methods in Python + Flask
53. @app.route('/cms/api/v1.0/articles/<string:article_id>/comments', methods = ['POST'])
def add_comment(article_id):
"""Adds a comment to the specified article and a
bucket, as well as updating a view counter
"””
…
page_id = article['last_comment_id'] // 100
…
# push the comment to the latest bucket and $inc the count
page = db['comments'].find_and_modify(
{ 'article_id' : ObjectId(article_id),
'page' : page_id},
{ '$inc' : { 'count' : 1 },
'$push' : {
'comments' : comment } },
fields= {'count' : 1},
upsert=True,
new=True)
RESTful API methods in Python + Flask
54. # $inc the page count if bucket size (100) is exceeded
if page['count'] > 100:
db.articles.update(
{ '_id' : article_id,
'comments_pages': article['comments_pages'] },
{ '$inc': { 'comments_pages': 1 } } )
# let's also add to the article itself
# most recent 10 comments only
res = db['articles'].update(
{'_id' : ObjectId(article_id)},
{'$push' : {'comments' : { '$each' : [comment],
'$sort' : {’date' : 1 },
'$slice' : -10}},
'$inc' : {'comment_count' : 1}})
…
RESTful API methods in Python + Flask
55. def add_interaction(article_id, type):
"""Record the interaction (view/comment) for the
specified article into the daily bucket and
update an hourly counter
"""
ts = datetime.datetime.utcnow()
# $inc daily and hourly view counters in day/article stats bucket
# note the unacknowledged w=0 write concern for performance
db['interactions'].update(
{ 'article_id' : ObjectId(article_id),
'date' : datetime.datetime(ts.year, ts.month, ts.day)},
{ '$inc' : {
'daily.{}’.format(type) : 1,
'hourly.{}.{}'.format(ts.hour, type) : 1
}},
upsert=True,
w=0)
RESTful API methods in Python + Flask
56. $ curl -i http://localhost:5000/cms/api/v1.0/articles
HTTP/1.0 200 OK
Content-Type: application/json
Content-Length: 335
Server: Werkzeug/0.9.4 Python/2.7.5
Date: Thu, 10 Apr 2014 16:00:51 GMT
{
"articles": "[{"title": "Schema design in MongoDB", "text": "Data in MongoDB
has a flexible schema..", "section": "schema", "author": "prasoonk", "date":
{"$date": 1397145312505}, "_id": {"$oid": "5346bef5f2610c064a36a793"},
"slug": "schema-design-in-mongodb", "tags": ["MongoDB", "schema"]}]"}
Testing the API – retrieve articles
57. $ curl -H "Content-Type: application/json" -X POST -d '{"text":"An interesting
article and a great read."}'
http://localhost:5000/cms/api/v1.0/articles/52ed73a30bd031362b3c6bb3/
comments
{
"comment": "{"date": {"$date": 1391639269724}, "text": "An interesting
article and a great read."}”
}
Testing the API – comment on an article
58. Schema iteration
New feature in the backlog?
Documents have dynamic schema so we just iterate the
object schema.
>>> user = {‘username’:‘matt’,
‘first’:‘Matt’,
‘last’:‘Bates’,
‘preferences’: {‘opt_out’: True } }
>>> user.save(user)
63. For More Information
Resource Location
MongoDB Downloads mongodb.com/download
Free Online Training education.mongodb.com
Webinars and Events mongodb.com/events
White Papers mongodb.com/white-papers
Case Studies mongodb.com/customers
Presentations mongodb.com/presentations
Documentation docs.mongodb.org
Additional Info info@mongodb.com
Resource Location