This document summarizes a MongoDB live coding session presented by Tobias Trelle. It introduces MongoDB concepts like documents, collections, CRUD operations, queries including geospatial queries, replication, sharding, and the Java and Spring Data APIs. It also advertises MongoDB user groups in Dusseldorf and Frankfurt organized by codecentric AG.
MongoDB + Java - Everything you need to know Norberto Leite
Learn everything you need to know to get started building a MongoDB-based app in Java. We'll explore the relationship between MongoDB and various languages on the Java Virtual Machine such as Java, Scala, and Clojure. From there, we'll examine the popular frameworks and integration points between MongoDB and the JVM including Spring Data and object-document mappers like Morphia.
This talk is focused on tuning analysing and optimizing MongoDB query and index with the use of Database Profiler and "explain()" function.
Also, performance of database can also be impacted by configuring the underline ( Linux ) OS with some recommended settings which do not come by default.
This webinar took place on August 23, 2012.
Never worry about servers. Never worry about config files. Never worry about patches. Simply focus on your data with Heroku Postgres.
PostgreSQL is a powerful, reliable, and durable open-source SQL-compliant database. Now available as a fully-managed cloud database from salesforce.com, Heroku Postgres reduces the costs and administrative overhead compared to operating your own database. You can even create a database instance within seconds with a single click.
Watch this webinar to learn about:
:: When to use Heroku Postgres versus Database.com
:: What data you can and should store in Heroku Postgres
:: Architecting your application with Heroku Postgres
:: How to efficiently share data in your organization with Dataclips
:: How to take advantage of features such as Fork and Follow to scale
MongoDB + Java - Everything you need to know Norberto Leite
Learn everything you need to know to get started building a MongoDB-based app in Java. We'll explore the relationship between MongoDB and various languages on the Java Virtual Machine such as Java, Scala, and Clojure. From there, we'll examine the popular frameworks and integration points between MongoDB and the JVM including Spring Data and object-document mappers like Morphia.
This talk is focused on tuning analysing and optimizing MongoDB query and index with the use of Database Profiler and "explain()" function.
Also, performance of database can also be impacted by configuring the underline ( Linux ) OS with some recommended settings which do not come by default.
This webinar took place on August 23, 2012.
Never worry about servers. Never worry about config files. Never worry about patches. Simply focus on your data with Heroku Postgres.
PostgreSQL is a powerful, reliable, and durable open-source SQL-compliant database. Now available as a fully-managed cloud database from salesforce.com, Heroku Postgres reduces the costs and administrative overhead compared to operating your own database. You can even create a database instance within seconds with a single click.
Watch this webinar to learn about:
:: When to use Heroku Postgres versus Database.com
:: What data you can and should store in Heroku Postgres
:: Architecting your application with Heroku Postgres
:: How to efficiently share data in your organization with Dataclips
:: How to take advantage of features such as Fork and Follow to scale
After a short introduction to the Java driver for MongoDB, we'll have a look at the more abtract persistence frameworks like Morphia, Spring Data, Jongo and Hibernate OGM.
For developers new to MongoDB and Node.js, however, some the common design patterns are very different than those of a RDBMS and traditional synchronous languages. Developers learning these technologies together may find it a bit bewildering. In reality, however, these tools fit perfectly together and enable I high degree of developer productivity and application performance.
This webinar will walk developers through common MongoDB development patterns in Node.js, such as efficiently loading data into MongoDB using MongoDB's bulk API, iterating through query results, and managing simultaneous asynchronous MongoDB queries to provide the best possible application performance. Working Node.js and MongoDB examples will be used throughout the presentation.
MongoDB .local Munich 2019: New Encryption Capabilities in MongoDB 4.2: A Dee...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.
MongoDB .local Munich 2019: Best Practices for Working with IoT and Time-seri...MongoDB
Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
• Common components of an IoT solution
• The challenges involved with managing time-series data in IoT applications
• Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
• How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.
Aggregation pipeline has been able to power your analysis of data since version 2.2. In 4.2 we added more power and now you can use it for more powerful queries, updates, and outputting your data to existing collections. Come hear how you can do everything with the pipeline, including single-view, ETL, data roll-ups and materialized views.
Mythbusting: Understanding How We Measure the Performance of MongoDBMongoDB
Benchmarking, benchmarking, benchmarking. We all do it, mostly it tells us what we want to hear but often hides a mountain of misinformation. In this talk we will walk through the pitfalls that you might find yourself in by looking at some examples where things go wrong. We will then walk through how MongoDB performance is measured, the processes and methodology and ways to present and look at the information.
MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDBMongoDB
Query performance can either be a constant headache or the unsung hero of an application. MongoDB provides extremely powerful querying capabilities when used properly. As a member of the solutions architecture team I will share more common mistakes observed and some tips and tricks to avoiding them.
This is a presentation given on October 24 by Michael Uzquiano of Cloud CMS (http://www.cloudcms.com) at the MongoDB Boston conference.
In this presentation, we cover Hazelcast - an in-memory data grid that provides distributed object persistence across multiple nodes in a cluster. When backed by MongoDB, objects are naturally written to Mongo by Hazelcast. The integration points are clean and easy to implement.
We cover a few simple cases along with code samples to provide the MongoDB community with some ideas of how to integrate Hazelcast into their own MongoDB Java applications.
Java Persistence Frameworks for MongoDBTobias Trelle
After a short introduction to the MongoDB Java driver we'll have a detailed look at higher level persistence frameworks like Morphia, Spring Data MongoDB and Hibernate OGM with lots of examples.
After a short introduction to the Java driver for MongoDB, we'll have a look at the more abtract persistence frameworks like Morphia, Spring Data, Jongo and Hibernate OGM.
For developers new to MongoDB and Node.js, however, some the common design patterns are very different than those of a RDBMS and traditional synchronous languages. Developers learning these technologies together may find it a bit bewildering. In reality, however, these tools fit perfectly together and enable I high degree of developer productivity and application performance.
This webinar will walk developers through common MongoDB development patterns in Node.js, such as efficiently loading data into MongoDB using MongoDB's bulk API, iterating through query results, and managing simultaneous asynchronous MongoDB queries to provide the best possible application performance. Working Node.js and MongoDB examples will be used throughout the presentation.
MongoDB .local Munich 2019: New Encryption Capabilities in MongoDB 4.2: A Dee...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.
MongoDB .local Munich 2019: Best Practices for Working with IoT and Time-seri...MongoDB
Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
• Common components of an IoT solution
• The challenges involved with managing time-series data in IoT applications
• Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
• How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.
Aggregation pipeline has been able to power your analysis of data since version 2.2. In 4.2 we added more power and now you can use it for more powerful queries, updates, and outputting your data to existing collections. Come hear how you can do everything with the pipeline, including single-view, ETL, data roll-ups and materialized views.
Mythbusting: Understanding How We Measure the Performance of MongoDBMongoDB
Benchmarking, benchmarking, benchmarking. We all do it, mostly it tells us what we want to hear but often hides a mountain of misinformation. In this talk we will walk through the pitfalls that you might find yourself in by looking at some examples where things go wrong. We will then walk through how MongoDB performance is measured, the processes and methodology and ways to present and look at the information.
MongoDB .local Munich 2019: Tips and Tricks++ for Querying and Indexing MongoDBMongoDB
Query performance can either be a constant headache or the unsung hero of an application. MongoDB provides extremely powerful querying capabilities when used properly. As a member of the solutions architecture team I will share more common mistakes observed and some tips and tricks to avoiding them.
This is a presentation given on October 24 by Michael Uzquiano of Cloud CMS (http://www.cloudcms.com) at the MongoDB Boston conference.
In this presentation, we cover Hazelcast - an in-memory data grid that provides distributed object persistence across multiple nodes in a cluster. When backed by MongoDB, objects are naturally written to Mongo by Hazelcast. The integration points are clean and easy to implement.
We cover a few simple cases along with code samples to provide the MongoDB community with some ideas of how to integrate Hazelcast into their own MongoDB Java applications.
Java Persistence Frameworks for MongoDBTobias Trelle
After a short introduction to the MongoDB Java driver we'll have a detailed look at higher level persistence frameworks like Morphia, Spring Data MongoDB and Hibernate OGM with lots of examples.
2012 Ford Fiesta Brochure | Mason City Ford, Waverly Ford, and Clear Lake FordIowa CarSales
Check out the 2012 Ford brochure provided by Mike Molstead Motors serving Mason City, Waverly, and Clear. Find the 2012 Ford top-quality vehicles for sale in Iowa. To learn more about our current sales and incentives give us a call at 800-332-2579. http://www.mikemolsteadmotors.com
The Social Challenge of 1.5°C Webinar: Karen O'Brientewksjj
Karen O'Brien, Susanne Moser, Ioan Fazey and others from Future Earth's Transformations Knowledge-Action Network discuss mobilising research around the social challenge of a 1.5°C target for climate action.
Building a Scalable Distributed Stats Infrastructure with Storm and KairosDBCody Ray
Building a Scalable Distributed Stats Infrastructure with Storm and KairosDB
Many startups collect and display stats and other time-series data for their users. A supposedly-simple NoSQL option such as MongoDB is often chosen to get started... which soon becomes 50 distributed replica sets as volume increases. This talk describes how we designed a scalable distributed stats infrastructure from the ground up. KairosDB, a rewrite of OpenTSDB built on top of Cassandra, provides a solid foundation for storing time-series data. Unfortunately, though, it has some limitations: millisecond time granularity and lack of atomic upsert operations which make counting (critical to any stats infrastructure) a challenge. Additionally, running KairosDB atop Cassandra inside AWS brings its own set of challenges, such as managing Cassandra seeds and AWS security groups as you grow or shrink your Cassandra ring. In this deep-dive talk, we explore how we've used a mix of open-source and in-house tools to tackle these challenges and build a robust, scalable, distributed stats infrastructure.
MongoDB, Hadoop and humongous data - MongoSV 2012Steven Francia
Learn how to integrate MongoDB with Hadoop for large-scale distributed data processing. Using tools like MapReduce, Pig and Streaming you will learn how to do analytics and ETL on large datasets with the ability to load and save data against MongoDB. With Hadoop MapReduce, Java and Scala programmers will find a native solution for using MapReduce to process their data with MongoDB. Programmers of all kinds will find a new way to work with ETL using Pig to extract and analyze large datasets and persist the results to MongoDB. Python and Ruby Programmers can rejoice as well in a new way to write native Mongo MapReduce using the Hadoop Streaming interfaces.
MongoDB Days Silicon Valley: MongoDB and the Hadoop ConnectorMongoDB
Presented by Luke Lovett, Software Engineer, MongoDB
Experience level: Introductory
MongoDB and Hadoop work powerfully together as complementary technologies. Learn how the Hadoop connector allows you to leverage the power of MapReduce to process data sourced from your MongoDB cluster.
NoSQL databases are often touted for their performance and whilst it's true that they usually offer great performance out of the box, it still really depends on how you deploy your infrastructure. Dedicated vs cloud? In memory vs on disk? Spindal vs SSD? Replication lag. Multi data centre deployment.
This talk considers all the infrastructure requirements of a successful high performance infrastructure with hints and tips that can be applied to any NoSQL technology. It includes things like OS tweaks, disk benchmarks, replication, monitoring and backups.
Presented at NoSQL Roadshow Berlin 2013 by David Mytton.
In this session we will cover wide area replica sets and using tags for backup. Attendees should be well versed in basic replication and familiar with concepts in the morning's basic replication talk. No beginner topics will be covered in this session
MongoDB: Optimising for Performance, Scale & AnalyticsServer Density
MongoDB is easy to download and run locally but requires some thought and further understanding when deploying to production. At scale, schema design, indexes and query patterns really matter. So does data structure on disk, sharding, replication and data centre awareness. This talk will examine these factors in the context of analytics, and more generally, to help you optimise MongoDB for any scale.
Presented at MongoDB Days London 2013 by David Mytton.
It's 10pm: Do You Know Where Your Writes Are?MongoDB
Speaker: Samantha Ritter, Software Engineer, MongoDB
Level: 200 (Intermediate)
Track: How We Build MongoDB
MongoDB 3.6 delivers three new features to help you develop resilient applications: retriable writes, a cluster-wide killOp command, and zombie cursor cleanup. These features share a common base, an idea called a logical session. This new cluster-wide concept of user state is the quiet magic that allows you to know, with certainty, the status of your operations. MongoDB engineer Samantha Ritter will describe the above features in-depth, discuss when and how logical sessions can be used by applications and administrators, and show you how we implemented sessions for large, distributed systems.
What You Will Learn:
- What logical sessions are and how they are implemented in the server
- How to leverage logical sessions for retriable writes
- How to pull the new cluster-wide killOp emergency break
SQL? NoSQL? NewSQL?!? What's a Java developer to do? - PhillyETE 2012Chris Richardson
The database world is undergoing a major upheaval. NoSQL databases such as MongoDB and Cassandra are emerging as a compelling choice for many applications. They can simplify the persistence of complex data models and offering significantly better scalability and performance. But these databases have a very different and unfamiliar data model and APIs as well as a limited transaction model. Moreover, the relational world is fighting back with so-called NewSQL databases such as VoltDB, which by using a radically different architecture offers high scalability and performance as well as the familiar relational model and ACID transactions. Sounds great but unlike the traditional relational database you can’t use JDBC and must partition your data.
In this presentation you will learn about popular NoSQL databases – MongoDB, and Cassandra – as well at VoltDB. We will compare and contrast each database’s data model and Java API using NoSQL and NewSQL versions of a use case from the book POJOs in Action. We will learn about the benefits and drawbacks of using NoSQL and NewSQL databases.
Unlocking Your Hadoop Data with Apache Spark and CDH5SAP Concur
Spark/Mesos Seattle Meetup group shares the latest presentation from their recent meetup event on showcasing real world implementations of working with Spark within the context of your Big Data Infrastructure.
Session are demo heavy and slide light focusing on getting your development environments up and running including getting up and running, configuration issues, SparkSQL vs. Hive, etc.
To learn more about the Seattle meetup: http://www.meetup.com/Seattle-Spark-Meetup/members/21698691/
Redundancy and high availability are the basis for all production deployments. With MongoDB high availability is achieved with replica sets which provides automatic fail-over in case the Primary goes down. In this session we will review multiple maintenance scenarios that will include the proper steps for keeping the high availability while we perform the maintenance steps without causing downtime.
This session will cover Database upgrades, OS server patching, Hardware upgrades, Network maintenance and more.
How MongoDB HA works
Replica sets components/deployment typologies
Database upgrades
System patching/upgrade
Network maintenance
Add/Remove members to the replica set
Reconfiguring replica set members
Building indexes
Backups and restores
Nach einer kurzen Einführung in verteilte Systeme zeige ich die Motivation für die Entstehung von NoSQL-Datenbanken auf. Ich stelle die Haupt-Kategorien der NoSQL-Datenbanken vor: Key-Value, Column Store, Graphen- und Dokumentenoriente Datenbanken. Danach gehe ich auf konkrete Datenbanken wie MongoDB, Neo4j und Redis ein.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
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.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
MongoDB Live Hacking
1. MongoDB Live Coding Session
tobias.trelle@codecentric.de
@tobiastrelle
codecentric AG
2. „It‘s not my fault the chapters are short,
MongoDB is just easy to learn“
from „The Little MongoDB book“
codecentric AG
3. MongoDB User Groups by codecentric
MongoDB User-Gruppe Düsseldorf
https://www.xing.com/net/mongodb-dus
@MongoDUS
Contact: Tobias Trelle
MongoDB User-Gruppe Frankfurt/Main
https://www.xing.com/net/mongodb-ffm
Contact: Uwe Seiler
codecentric AG
4. What is MongoDB?
Named from „humongous“ = gigantic http://www.mongodb.org
NoSQL datastore, Open Source https://github.com/mongodb
support from manufacturer 10gen http://www.10gen.com
Highly scalable (scale-out)
Stores so called „documents“
Supports replication & sharding
Map/Reduce
Geospatial indexes / queries
codecentric AG
5. Basic structure of a MongoDB server
Server
Database
Relational counterpart But …
Flexible
Table Collection
Schema
Row Document
- Arrays
Column Field
- recursive
codecentric AG
6. What‘s a document?
Single record that can be stored in a collection
JSON = JavaScript Object Notation (internal representation BSON = Binary JSON)
var doc = {
title: „MongoDB_Live_Hacking.pptx“,
tags: [ „cc“, „mongodb“, „nosql“ ],
slides: [
{ nr = 1, header = „MongoDB User Groups by codecentric“},
{ nr = 2, header = „MongoDB at codedcentric WiKi“},
…
]
};
codecentric AG
7. Live Session
CRUD operations
Queries
Geospatial Queries
Map/Reduce
Replication
Sharding
Raw Java API & Spring Data API
codecentric AG
8. Geospatial Queries
Queries based on
2-dimensional coordinates
_id: "A", position: [0.001, -0.002]
_id: "B", position: [0.75, 0.75]
_id: "C", position: [0.5, 0.5]
_id: "D", position: [-0.5, -0.5]
Queries based on distances
& shapes
Details:
http://blog.codecentric.de/en/2012/02/spring-data-mongodb-geospatial-queries/
codecentric AG
9. Map/Reduce
Data processing algorithm based on two phases: map & reduce
Code execution co-located with the data
Map phase can be run in parallel (on multiple nodes etc.) on huge data sets
MongoDB map / reduce:
runs on a subset of / all documents of a collection
Map / Reduce algorithms are JS functions
Output documents of the map function are input to the reduce function
Results are documents stored in a target collection
codecentric AG
11. MongoDB Replication
A cluster is called „replica set“
Uses Master/Slave replication
Writes from clients go to the master only
If the master goes down, the slaves elect a new master (n > 2)
Replica set w/ n = 3
Slave 1
Client Master
Slave 2
codecentric AG
12. MongoDB Sharding
Data is distributed over n nodes, each record is persisted only once
Data only on the shard nodes
Config Server = book keeper, knows where the data is
Switch: Gateway for clients
Sharding setup
Config
Server Shard 1
Shard 2
Client Switch
codecentric AG
13. MongoDB Sharding in Production
Each shard is a replica set + 3 config servers
Source: http://www.mongodb.org/display/DOCS/Sharding+Introduction
codecentric AG
16. MongoDB API
Drivers for many languages (Java, Ruby, PHP, C++, …)
Low level Java API: MongoDB Java Driver
Spring Data MongoDB: Repository Support + Objekt/Collection Mapping
Spring Data
CrudRepository PagingAndSortingRepository
Spring Data Spring Data Spring Data Spring Data
JPA MongoDB Neo4j …
JpaRepository MongoRepository GraphRepository
MongoTemplate Neo4jTemplate
Embedded REST
JPA Mongo Java Driver
JDBC
RDBMS MongoDB Neo4j …
codecentric AG
17. QUESTION?
Tobias Trelle
codecentric AG
Merscheider Str. 1
42699 Solingen
tel +49 (0) 212.233628.47
fax +49 (0) 212.233628.79
mail Tobias.Trelle@codecentric.de
twitter @tobiastrelle
www.codecentric.de
www.mbg-online.de
blog.codecentric.de
www.xing.com/net/mongodb-dus
codecentric AG 20.08.2012 17