MongoDB Kubernetes operator and MongoDB Open Service Broker are ready for production operations. Learn about how MongoDB can be used with the most popular container orchestration platform, Kubernetes, and bring self-service, persistent storage to your containerized applications. A demo will show you how easy it is to enable MongoDB clusters as an External Service using the Open Service Broker API for MongoDB
MongoDB for storing humongous music databasePrasoon Kumar
Musicbrainz is an encyclopedia of music tracks, artists and albums. It is available in PostgreSQL under CC license. 2 different approaches to load the database into MongoDB are examined - one where 4 tables are first denormalized in Postgres and then loaded into MongoDB. Other one loads them into MongoDB and denormalizes into a single collection there. We also show MongoDB's fulltext index.
Apache Calcite (a tutorial given at BOSS '21)Julian Hyde
The document provides instructions for setting up the environment and coding tutorial for the BOSS'21 Copenhagen tutorial on Apache Calcite.
It includes the following steps:
1. Clone the GitHub repository containing sample code and dependencies.
2. Compile the project.
3. It outlines the draft schedule for the tutorial, which will cover topics like Calcite introduction, demonstration of SQL queries on CSV files, setting up the coding environment, using Lucene for indexing, and coding exercises to build parts of the logical and physical query plans in Calcite.
4. The tutorial will be led by Stamatis Zampetakis from Cloudera and Julian Hyde from Google, who are both committers to
This presentation will demonstrate how you can use the aggregation pipeline with MongoDB similar to how you would use GROUP BY in SQL and the new stage operators coming 3.4. MongoDB’s Aggregation Framework has many operators that give you the ability to get more value out of your data, discover usage patterns within your data, or use the Aggregation Framework to power your application. Considerations regarding version, indexing, operators, and saving the output will be reviewed.
Overview of how containers are implemented with cgroups, namespaces and UnionFS, how images are created, how images and containers are related to one another, and how to build effective images
Better than you think: Handling JSON data in ClickHouseAltinity Ltd
Robert Hodges shows how ClickHouse, a relational database with tables, can offer high-performance analysis of JSON data. This talk provides a cookbook of schema design, indexing, data loading, and query tricks we gave learned over years of helping users build analytical apps for servicds logs, observability data, financial transactions, and other types of semi-structured data. Robert Hodges is CEO of Altinity and a certified database geek.
https://altinity.com
https://www.meetup.com/San-Francisco-Bay-Area-ClickHouse-Meetup
Optimizing Delta/Parquet Data Lakes for Apache SparkDatabricks
Matthew Powers gave a talk on optimizing data lakes for Apache Spark. He discussed community goals like standardizing method signatures. He advocated for using Spark helper libraries like spark-daria and spark-fast-tests. Powers explained how to build better data lakes using techniques like partitioning data on relevant fields to skip data and speed up queries significantly. He also covered modern Scala libraries, incremental updates, compacting small files, and using Delta Lakes to more easily update partitioned data lakes over time.
Understanding and Improving Code GenerationDatabricks
Code generation is integral to Spark’s physical execution engine. When implemented, the Spark engine creates optimized bytecode at runtime improving performance when compared to interpreted execution. Spark has taken the next step with whole-stage codegen which collapses an entire query into a single function.
Apache Calcite is a dynamic data management framework. Think of it as a toolkit for building databases: it has an industry-standard SQL parser, validator, highly customizable optimizer (with pluggable transformation rules and cost functions, relational algebra, and an extensive library of rules), but it has no preferred storage primitives. In this tutorial, the attendees will use Apache Calcite to build a fully fledged query processor from scratch with very few lines of code. This processor is a full implementation of SQL over an Apache Lucene storage engine. (Lucene does not support SQL queries and lacks a declarative language for performing complex operations such as joins or aggregations.) Attendees will also learn how to use Calcite as an effective tool for research.
This document provides an overview of Docker Swarm and how to set up and use a Docker Swarm cluster. It discusses key Swarm concepts, initializing a cluster, adding nodes, deploying services, rolling updates, draining nodes, failure scenarios, and the Raft consensus algorithm used for leader election in Swarm mode. The document walks through examples of creating a Swarm, adding nodes, deploying a service, inspecting and scaling services, rolling updates, and draining nodes. It also covers failure scenarios for nodes and managers and how the Swarm handles them.
This document provides an introduction to NoSQL and MongoDB. It discusses that NoSQL is a non-relational database management system that avoids joins and is easy to scale. It then summarizes the different flavors of NoSQL including key-value stores, graphs, BigTable, and document stores. The remainder of the document focuses on MongoDB, describing its structure, how to perform inserts and searches, features like map-reduce and replication. It concludes by encouraging the reader to try MongoDB themselves.
ksqlDB: A Stream-Relational Database Systemconfluent
Speaker: Matthias J. Sax, Software Engineer, Confluent
ksqlDB is a distributed event streaming database system that allows users to express SQL queries over relational tables and event streams. The project was released by Confluent in 2017 and is hosted on Github and developed with an open-source spirit. ksqlDB is built on top of Apache Kafka®, a distributed event streaming platform. In this talk, we discuss ksqlDB’s architecture that is influenced by Apache Kafka and its stream processing library, Kafka Streams. We explain how ksqlDB executes continuous queries while achieving fault tolerance and high vailability. Furthermore, we explore ksqlDB’s streaming SQL dialect and the different types of supported queries.
Matthias J. Sax is a software engineer at Confluent working on ksqlDB. He mainly contributes to Kafka Streams, Apache Kafka's stream processing library, which serves as ksqlDB's execution engine. Furthermore, he helps evolve ksqlDB's "streaming SQL" language. In the past, Matthias also contributed to Apache Flink and Apache Storm and he is an Apache committer and PMC member. Matthias holds a Ph.D. from Humboldt University of Berlin, where he studied distributed data stream processing systems.
https://db.cs.cmu.edu/events/quarantine-db-talk-2020-confluent-ksqldb-a-stream-relational-database-system/
Kafka Connect is a framework which connects Kafka with external Systems. It helps to move the data in and out of the Kafka. Connect makes it simple to use existing connector configuration for common source and sink Connectors.
The document discusses different Docker networking drivers including null, host, bridge, overlay, and macvlan/ipvlan networks. It provides examples of creating networks with each driver and how containers on different networks will connect and obtain IPs. Specifically, it shows how the bridge driver sets up a private Docker bridge network (docker0 by default) and how overlay networks use VXLAN tunnels to connect containers across multiple Docker daemons.
Speaker: Matthias J. Sax, Software Engineer, Confluent
KSQL is the Streaming SQL engine for Apache Kafka that allows for continuous data stream processing. While KSQL looks very similar to SQL, it provides quite different semantics. First, KSQL queries can be defined over data streams, not just tables. Second, queries over tables are no snapshot queries, but run forever. And third, time is a core concept in KSQL and data stream processing in general. In this talk, we explore the nature of Streaming SQL and its temporal semantics that apply to both streams and tables. We will explain continuous queries semantics, the relationship between streams and tables, and demystify the temporal nature of KSQL tables. Furthermore, we dig into filter, aggregation, and join operations over stream and tables as well as stream specific operators like windowing. At the end, you will be equipped to query streams and tables using KSQL and understand their temporal relationship to each other.
The document discusses techniques for storing time series data at scale in a time series database (TSDB). It describes storing 16 bytes of data per sample by compressing timestamps and values. It proposes organizing data into blocks, chunks, and files to handle high churn rates. An index structure uses unique IDs and sorted label mappings to enable efficient queries over millions of time series and billions of samples. Benchmarks show the TSDB can handle over 100,000 samples/second while keeping memory, CPU and disk usage low.
This document provides an overview of Apache Flink internals. It begins with an introduction and recap of Flink programming concepts. It then discusses how Flink programs are compiled into execution plans and executed in a pipelined fashion, as opposed to being executed eagerly like regular code. The document outlines Flink's architecture including the optimizer, runtime environment, and data storage integrations. It also covers iterative processing and how Flink handles iterations both by unrolling loops and with native iterative datasets.
The Right (and Wrong) Use Cases for MongoDBMongoDB
The document discusses the right and wrong use cases for MongoDB. It outlines some of the key benefits of MongoDB, including its performance, scalability, data model and query model. Specific use cases that are well-suited for MongoDB include building a single customer view, powering mobile applications, and performing real-time analytics. Cache-only workloads are identified as not being a good use case. The document provides examples of large companies successfully using MongoDB for these right use cases.
This presentation includes information on Kubernetes Architecture, Container Orchestration, Internal Routing, External Routing, Configuration Management, Credentials Management, Persistent Volumes, Rolling Out Updates, Autoscaling, Package Management, and a Hello World example using Helm.
2022-06-23 Apache Arrow and DataFusion_ Changing the Game for implementing Da...Andrew Lamb
DataFusion is an extensible and embeddable query engine, written in Rust used to create modern, fast and efficient data pipelines, ETL processes, and database systems.
This presentation explains where it fits into the data eco system and how it helps implement your system in Rust
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...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.
Federated Kubernetes: As a Platform for Distributed Scientific ComputingBob Killen
A high level overview of Kubernetes Federation and the challenges encountered when building out a Platform for multi-institutional Research and Distributed Scientific Computing.
Ever since the “CloudNative revolution” took over our development environment (devenv), we have never been more challenged (or more excited). With Kubernetes, Docker (Containerd) & many other microservice-related technologies, we have a handful of technologies to master before we write the first line of code.
Kubernetes is an open-source container management platform. It has a master-node architecture with control plane components like the API server on the master and node components like kubelet and kube-proxy on nodes. Kubernetes uses pods as the basic building block, which can contain one or more containers. Services provide discovery and load balancing for pods. Deployments manage pods and replicasets and provide declarative updates. Key concepts include volumes for persistent storage, namespaces for tenant isolation, labels for object tagging, and selector matching.
Soft Introduction to Google's framework for taming containers in the cloud. For devs and architects that they just enter the world of cloud, microservices and containers
Link: https://youtu.be/_lQhoCUQReU
https://go.dok.community/slack
https://dok.community/
From the DoK Day EU 2022 (https://youtu.be/Xi-h4XNd5tE)
The ability to extend Kubernetes with Custom Resource Definitions and respective controllers has led to the OperatorSDK, which became
the de facto standard for data service automation on Kubernetes. There are countless operator implementations available, and new operators are
being released on a daily basis. Organizations managing hundreds of Kubernetes clusters for dozens of developer teams are also challenged to
manage the lifecycle of hundreds of Kubernetes operators. The goal is to keep the operational overhead to a minimum.
In this talk, a closer look into the lifecycle of operators will be presented. With an understanding of how operators evolve, it becomes clear what
challenges during operator upgrades. A brief overview of lifecycle management tools such as Helm, OLM, and Carvel is presented in this context. In particular, it will be discussed whether these tools can help, which restrictions apply and where further development would be desirable.
At the end of this talk, you will know what operator lifecycle management is about, what its challenges are, and which tools may be used to reduce operational friction.
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Julian Fischer, CEO of anynines, has dedicated his career to the automation of software operations. In more than fifteen years, he has built several application platforms. He has been using Kubernetes, Cloud Foundry, and BOSH in recent years. Within platform automation, Julian has a strong focus on data service automation at scale.
In this talk, a closer look into the lifecycle of operators will be presented. With an understanding of how operators evolve, it becomes clear what
challenges during operator upgrades. A brief overview of lifecycle management tools such as Helm, OLM, and Carvel is presented in this context. In particular, it will be discussed whether these tools can help, which restrictions apply and where further development would be desirable.
At the end of this talk, you will know what operator lifecycle management is about, what its challenges are, and which tools may be used to reduce operational friction.
This talk was given by Julian Fischer for DoK Day Europe @ KubeCon 2022.
This document provides an agenda and overview for a presentation on training a Docker cloud using Clocker. The presentation will introduce Clocker and what it does to manage Docker clouds. It will discuss what a Docker cloud is and how Clocker provides multi-host and multi-container applications, networking, and container orchestration. The presentation will demonstrate Clocker's features for deploying applications using blueprints, managing mixed infrastructure including VMs and containers, and extending Brooklyn with Docker-specific capabilities.
Kubernetes (commonly referred to as "K8s") is an open-source system for automating deployment, scaling and management of containerized applications It aims to provide a "platform for automating deployment, scaling, and operations of application containers across clusters of hosts". We will see Kubernetes architecture, use cases, basics and live demo
Kubernetes - how to orchestrate containersinovex GmbH
http://www.meetup.com/Docker-Karlsruhe/events/220797663/
mehr Meetups von inovex:
http://www.meetup.com/inovex-karlsruhe
http://www.meetup.com/inovex-munich
http://www.meetup.com/inovex-cologne
Recent momentum around the evolution of Containers are gradually increase in last two years.Containers virtualize an OS and applications running in each container believe that they have full access to their very own copy of that OS. This is analogous to what VMs do when they virtualize at a lower level, the hardware. In the case of containers, it’s the OS that does the virtualization and maintains the illusion.
Recent past many software companies have quickly adopted container technologies, including Docker Containers, aware of the threat and advantage of the approach. For example, Linux companies have also jumped into the ground, seeing as this as an opportunity to grow the Linux market. Also Microsoft is going to add features to support containers and VMware have made efforts in integrating support for Docker into virtual machine technology.
Recent momentum around the evolution of Containers are gradually increase in last two years.Containers virtualize an OS and applications running in each container believe that they have full access to their very own copy of that OS. This is analogous to what VMs do when they virtualize at a lower level, the hardware. In the case of containers, it’s the OS that does the virtualization and maintains the illusion.
Recent past many software companies have quickly adopted container technologies, including Docker Containers, aware of the threat and advantage of the approach. For example, Linux companies have also jumped into the ground, seeing as this as an opportunity to grow the Linux market. Also Microsoft is going to add features to support containers and VMware have made efforts in integrating support for Docker into virtual machine technology.
3 years ago, Meetic chose to rebuild it's backend architecture using microservices and an event driven strategy. As we where moving along our old legacy application, testing features became gradually a pain, especially when those features rely on multiple changes across multiple components. Whatever the number of application you manage, unit testing is easy, as well as functional testing on a microservice. A good gherkin framework and a set of docker container can do the job. The real challenge is set in end-to-end testing even more when a feature can involve up to 60 different components.
To solve that issue, Meetic is building a Kubernetes strategy around testing. To do such a thing we need to :
- Be able to generate a docker container for each pull-request on any component of the stack
- Be able to create a full testing environment in the simplest way
- Be able to launch automated test on this newly created environment
- Have a clean-up process to destroy testing environment after tests To separate the various testing environment, we chose to use Kubernetes Namespaces each containing a variant of the Meetic stack. But when it comes to Kubernetes, managing multiple namespaces can be hard. Yaml configuration files need to be shared in a way that each people / automated job can access to them and modify them without impacting others.
This is typically why Meetic chose to develop it's own tool to manage namespace through a cli tool, or a REST API on which we can plug a friendly UI.
In this talk we will tell you the story of our CI/CD evolution to satisfy the need to create a docker container for each new pull request. And we will show you how to make end-to-end testing easier using Blackbeard, the tool we developed to handle the need to manage namespaces inspired by Helm.
This document provides an overview of Kubernetes concepts including architecture, fundamental objects like pods and services, and demonstrations. It begins with an agenda then covers Kubernetes architecture including the master node, worker nodes, and control loop. It describes core objects like pods, replica sets, deployments, services, and labels/selectors. The document demonstrates deploying and accessing the guestbook application using these objects. It concludes with asking for questions and describing goals for educational meetups on cloud native technologies.
A basic introduction to Kubernetes. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications.
K8s in 3h - Kubernetes Fundamentals TrainingPiotr Perzyna
Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. This training helps you understand key concepts within 3 hours.
Recent momentum around the evolution of Containers are gradually increase in last two years.Containers virtualize an OS and applications running in each container believe that they have full access to their very own copy of that OS. This is analogous to what VMs do when they virtualize at a lower level, the hardware. In the case of containers, it’s the OS that does the virtualization and maintains the illusion.
Container Orchestration with Docker Swarm and KubernetesWill Hall
This presentation covers the basics of what container orchestration is providing pros and cons of Docker Swarm, Kubernetes and Amazon ECS and outlining the terms and tools you will need to successfully use them.
Similar to MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Development or Production (20)
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB
This presentation discusses migrating data from other data stores to MongoDB Atlas. It begins by explaining why MongoDB and Atlas are good choices for data management. Several preparation steps are covered, including sizing the target Atlas cluster, increasing the source oplog, and testing connectivity. Live migration, mongomirror, and dump/restore options are presented for migrating between replicasets or sharded clusters. Post-migration steps like monitoring and backups are also discussed. Finally, migrating from other data stores like AWS DocumentDB, Azure CosmosDB, DynamoDB, and relational databases are briefly covered.
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!MongoDB
These days, everyone is expected to be a data analyst. But with so much data available, how can you make sense of it and be sure you're making the best decisions? One great approach is to use data visualizations. In this session, we take a complex dataset and show how the breadth of capabilities in MongoDB Charts can help you turn bits and bytes into insights.
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDBMongoDB
Are you new to schema design for MongoDB, or are you looking for a more complete or agile process than what you are following currently? In this talk, we will guide you through the phases of a flexible methodology that you can apply to projects ranging from small to large with very demanding requirements.
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...MongoDB
Humana, like many companies, is tackling the challenge of creating real-time insights from data that is diverse and rapidly changing. This is our journey of how we used MongoDB to combined traditional batch approaches with streaming technologies to provide continues alerting capabilities from real-time data streams.
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB
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.
Join this talk and test session with a MongoDB Developer Advocate where you'll go over the setup, configuration, and deployment of an Atlas environment. Create a service that you can take back in a production-ready state and prepare to unleash your inner genius.
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]MongoDB
Our clients have unique use cases and data patterns that mandate the choice of a particular strategy. To implement these strategies, it is mandatory that we unlearn a lot of relational concepts while designing and rapidly developing efficient applications on NoSQL. In this session, we will talk about some of our client use cases, the strategies we have adopted, and the features of MongoDB that assisted in implementing these strategies.
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB
Encryption is not a new concept to MongoDB. Encryption may occur in-transit (with TLS) and at-rest (with the encrypted storage engine). But MongoDB 4.2 introduces support for Client Side Encryption, ensuring the most sensitive data is encrypted before ever leaving the client application. Even full access to your MongoDB servers is not enough to decrypt this data. And better yet, Client Side Encryption can be enabled at the "flick of a switch".
This session covers using Client Side Encryption in your applications. This includes the necessary setup, how to encrypt data without sacrificing queryability, and what trade-offs to expect.
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!MongoDB
These days, everyone is expected to be a data analyst. But with so much data available, how can you make sense of it and be sure you're making the best decisions? One great approach is to use data visualizations. In this session, we take a complex dataset and show how the breadth of capabilities in MongoDB Charts can help you turn bits and bytes into insights.
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your MindsetMongoDB
When you need to model data, is your first instinct to start breaking it down into rows and columns? Mine used to be too. When you want to develop apps in a modern, agile way, NoSQL databases can be the best option. Come to this talk to learn how to take advantage of all that NoSQL databases have to offer and discover the benefits of changing your mindset from the legacy, tabular way of modeling data. We’ll compare and contrast the terms and concepts in SQL databases and MongoDB, explain the benefits of using MongoDB compared to SQL databases, and walk through data modeling basics so you feel confident as you begin using MongoDB.
MongoDB .local San Francisco 2020: MongoDB Atlas JumpstartMongoDB
Join this talk and test session with a MongoDB Developer Advocate where you'll go over the setup, configuration, and deployment of an Atlas environment. Create a service that you can take back in a production-ready state and prepare to unleash your inner genius.
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB
The document discusses guidelines for ordering fields in compound indexes to optimize query performance. It recommends the E-S-R approach: placing equality fields first, followed by sort fields, and range fields last. This allows indexes to leverage equality matches, provide non-blocking sorts, and minimize scanning. Examples show how indexes ordered by these guidelines can support queries more efficiently by narrowing the search bounds.
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++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.
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB
The document describes a methodology for data modeling with MongoDB. It begins by recognizing the differences between document and tabular databases, then outlines a three step methodology: 1) describe the workload by listing queries, 2) identify and model relationships between entities, and 3) apply relevant patterns when modeling for MongoDB. The document uses examples around modeling a coffee shop franchise to illustrate modeling approaches and techniques.
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB
MongoDB Atlas Data Lake is a new service offered by MongoDB Atlas. Many organizations store long term, archival data in cost-effective storage like S3, GCP, and Azure Blobs. However, many of them do not have robust systems or tools to effectively utilize large amounts of data to inform decision making. MongoDB Atlas Data Lake is a service allowing organizations to analyze their long-term data to discover a wealth of information about their business.
This session will take a deep dive into the features that are currently available in MongoDB Atlas Data Lake and how they are implemented. In addition, we'll discuss future plans and opportunities and offer ample Q&A time with the engineers on the project.
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & GolangMongoDB
Virtual assistants are becoming the new norm when it comes to daily life, with Amazon’s Alexa being the leader in the space. As a developer, not only do you need to make web and mobile compliant applications, but you need to be able to support virtual assistants like Alexa. However, the process isn’t quite the same between the platforms.
How do you handle requests? Where do you store your data and work with it to create meaningful responses with little delay? How much of your code needs to change between platforms?
In this session we’ll see how to design and develop applications known as Skills for Amazon Alexa powered devices using the Go programming language and MongoDB.
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...MongoDB
aux Core Data, appréciée par des centaines de milliers de développeurs. Apprenez ce qui rend Realm spécial et comment il peut être utilisé pour créer de meilleures applications plus rapidement.
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...MongoDB
Il n’a jamais été aussi facile de commander en ligne et de se faire livrer en moins de 48h très souvent gratuitement. Cette simplicité d’usage cache un marché complexe de plus de 8000 milliards de $.
La data est bien connu du monde de la Supply Chain (itinéraires, informations sur les marchandises, douanes,…), mais la valeur de ces données opérationnelles reste peu exploitée. En alliant expertise métier et Data Science, Upply redéfinit les fondamentaux de la Supply Chain en proposant à chacun des acteurs de surmonter la volatilité et l’inefficacité du marché.
MongoDB .local Paris 2020: Les bonnes pratiques pour sécuriser MongoDBMongoDB
Chaque entreprise devient une entreprise de logiciels, fournissant des solutions client pour accéder à une variété de services et d'informations. Les entreprises commencent maintenant à valoriser leurs données et à obtenir de meilleures informations pour l'entreprise. Un défi crucial consiste à s'assurer que ces données sont toujours disponibles et sécurisées pour être conformes aux objectifs commerciaux de l'entreprise et aux contraintes réglementaires des pays. MongoDB fournit la couche de sécurité dont vous avez besoin, venez découvrir comment sécuriser vos données avec MongoDB.
MongoDB .local Paris 2020: Tout savoir sur le moteur de recherche Full Text S...MongoDB
Venez en apprendre davantage sur notre nouvel opérateur de recherche en texte intégral pour MongoDB Atlas. Il s'agit d'une amélioration significative des fonctionnalités de recherches de MongoDB et c'est également la solution de recherche en texte intégral la plus simple et la plus puissante pour les bases de données MongoDB Atlas.
Cette présentation est importante pour quiconque a mis en place ou en visage de mettre en place une fonctionnalité de recherche dans son application MongoDB.
Vous assisterez à une démo de $searchBeta, apprendrez comment cela fonctionne, découvrirez des fonctionnalités spécifiques vous permettant d'obtenir des résultats de recherche pertinents et apprendrez comment vous pouvez commencer à utiliser la recherche en texte intégral dans votre application dès aujourd'hui.
How Social Media Hackers Help You to See Your Wife's Message.pdfHackersList
In the modern digital era, social media platforms have become integral to our daily lives. These platforms, including Facebook, Instagram, WhatsApp, and Snapchat, offer countless ways to connect, share, and communicate.
Advanced Techniques for Cyber Security Analysis and Anomaly DetectionBert Blevins
Cybersecurity is a major concern in today's connected digital world. Threats to organizations are constantly evolving and have the potential to compromise sensitive information, disrupt operations, and lead to significant financial losses. Traditional cybersecurity techniques often fall short against modern attackers. Therefore, advanced techniques for cyber security analysis and anomaly detection are essential for protecting digital assets. This blog explores these cutting-edge methods, providing a comprehensive overview of their application and importance.
Quality Patents: Patents That Stand the Test of TimeAurora Consulting
Is your patent a vanity piece of paper for your office wall? Or is it a reliable, defendable, assertable, property right? The difference is often quality.
Is your patent simply a transactional cost and a large pile of legal bills for your startup? Or is it a leverageable asset worthy of attracting precious investment dollars, worth its cost in multiples of valuation? The difference is often quality.
Is your patent application only good enough to get through the examination process? Or has it been crafted to stand the tests of time and varied audiences if you later need to assert that document against an infringer, find yourself litigating with it in an Article 3 Court at the hands of a judge and jury, God forbid, end up having to defend its validity at the PTAB, or even needing to use it to block pirated imports at the International Trade Commission? The difference is often quality.
Quality will be our focus for a good chunk of the remainder of this season. What goes into a quality patent, and where possible, how do you get it without breaking the bank?
** Episode Overview **
In this first episode of our quality series, Kristen Hansen and the panel discuss:
⦿ What do we mean when we say patent quality?
⦿ Why is patent quality important?
⦿ How to balance quality and budget
⦿ The importance of searching, continuations, and draftsperson domain expertise
⦿ Very practical tips, tricks, examples, and Kristen’s Musts for drafting quality applications
https://www.aurorapatents.com/patently-strategic-podcast.html
Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
Measuring the Impact of Network Latency at TwitterScyllaDB
Widya Salim and Victor Ma will outline the causal impact analysis, framework, and key learnings used to quantify the impact of reducing Twitter's network latency.
Fluttercon 2024: Showing that you care about security - OpenSSF Scorecards fo...Chris Swan
Have you noticed the OpenSSF Scorecard badges on the official Dart and Flutter repos? It's Google's way of showing that they care about security. Practices such as pinning dependencies, branch protection, required reviews, continuous integration tests etc. are measured to provide a score and accompanying badge.
You can do the same for your projects, and this presentation will show you how, with an emphasis on the unique challenges that come up when working with Dart and Flutter.
The session will provide a walkthrough of the steps involved in securing a first repository, and then what it takes to repeat that process across an organization with multiple repos. It will also look at the ongoing maintenance involved once scorecards have been implemented, and how aspects of that maintenance can be better automated to minimize toil.
UiPath Community Day Kraków: Devs4Devs ConferenceUiPathCommunity
We are honored to launch and host this event for our UiPath Polish Community, with the help of our partners - Proservartner!
We certainly hope we have managed to spike your interest in the subjects to be presented and the incredible networking opportunities at hand, too!
Check out our proposed agenda below 👇👇
08:30 ☕ Welcome coffee (30')
09:00 Opening note/ Intro to UiPath Community (10')
Cristina Vidu, Global Manager, Marketing Community @UiPath
Dawid Kot, Digital Transformation Lead @Proservartner
09:10 Cloud migration - Proservartner & DOVISTA case study (30')
Marcin Drozdowski, Automation CoE Manager @DOVISTA
Pawel Kamiński, RPA developer @DOVISTA
Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner
09:40 From bottlenecks to breakthroughs: Citizen Development in action (25')
Pawel Poplawski, Director, Improvement and Automation @McCormick & Company
Michał Cieślak, Senior Manager, Automation Programs @McCormick & Company
10:05 Next-level bots: API integration in UiPath Studio (30')
Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner
10:35 ☕ Coffee Break (15')
10:50 Document Understanding with my RPA Companion (45')
Ewa Gruszka, Enterprise Sales Specialist, AI & ML @UiPath
11:35 Power up your Robots: GenAI and GPT in REFramework (45')
Krzysztof Karaszewski, Global RPA Product Manager
12:20 🍕 Lunch Break (1hr)
13:20 From Concept to Quality: UiPath Test Suite for AI-powered Knowledge Bots (30')
Kamil Miśko, UiPath MVP, Senior RPA Developer @Zurich Insurance
13:50 Communications Mining - focus on AI capabilities (30')
Thomasz Wierzbicki, Business Analyst @Office Samurai
14:20 Polish MVP panel: Insights on MVP award achievements and career profiling
Kief Morris rethinks the infrastructure code delivery lifecycle, advocating for a shift towards composable infrastructure systems. We should shift to designing around deployable components rather than code modules, use more useful levels of abstraction, and drive design and deployment from applications rather than bottom-up, monolithic architecture and delivery.
Support en anglais diffusé lors de l'événement 100% IA organisé dans les locaux parisiens d'Iguane Solutions, le mardi 2 juillet 2024 :
- Présentation de notre plateforme IA plug and play : ses fonctionnalités avancées, telles que son interface utilisateur intuitive, son copilot puissant et des outils de monitoring performants.
- REX client : Cyril Janssens, CTO d’ easybourse, partage son expérience d’utilisation de notre plateforme IA plug & play.
Scaling Connections in PostgreSQL Postgres Bangalore(PGBLR) Meetup-2 - MydbopsMydbops
This presentation, delivered at the Postgres Bangalore (PGBLR) Meetup-2 on June 29th, 2024, dives deep into connection pooling for PostgreSQL databases. Aakash M, a PostgreSQL Tech Lead at Mydbops, explores the challenges of managing numerous connections and explains how connection pooling optimizes performance and resource utilization.
Key Takeaways:
* Understand why connection pooling is essential for high-traffic applications
* Explore various connection poolers available for PostgreSQL, including pgbouncer
* Learn the configuration options and functionalities of pgbouncer
* Discover best practices for monitoring and troubleshooting connection pooling setups
* Gain insights into real-world use cases and considerations for production environments
This presentation is ideal for:
* Database administrators (DBAs)
* Developers working with PostgreSQL
* DevOps engineers
* Anyone interested in optimizing PostgreSQL performance
Contact info@mydbops.com for PostgreSQL Managed, Consulting and Remote DBA Services
Quantum Communications Q&A with Gemini LLM. These are based on Shannon's Noisy channel Theorem and offers how the classical theory applies to the quantum world.
How RPA Help in the Transportation and Logistics Industry.pptxSynapseIndia
Revolutionize your transportation processes with our cutting-edge RPA software. Automate repetitive tasks, reduce costs, and enhance efficiency in the logistics sector with our advanced solutions.
5. #MDBLocal
Kubernetes Overview
eksctl create cluster
--name myKubeCluster
--version 1.14
--nodegroup-name standard-workers
--node-type t3.xlarge
--nodes 3
https://eksctl.io/
HA in one command !
6. #MDBLocal
Helm Architecture
Helm 2 - Package Manager for Kubernetes
(Helm 3 is in Beta – “No Tiller”)
● https://helm.sh/ Do not use Helm charts with MongoDB Kubernetes Operator as
upgrades are more complicated with the Helm client
Package Manager for Kubernetes - A useful tool
7. #MDBLocal
Kubernetes Service Catalog
It’s Really this easy….
1. Create resources that define
your application
2. Define the MongoDB Atlas
persistence service it relies
on
3. (Done by MongoDB and
contained in Github repo:
https://github.com/mongodb/
mongodb-atlas-service-
broker )
4. Seamlessly Connect the two
The elegance of simplicity
9. #MDBLocal
The service catalog translates CRD into requests to the Atlas Service
Broker, Provisions resources on your behalf, and injects the
credentials for access back into your containers
Kubernetes Service catalog
Easy Mode
10. #MDBLocal
• Kubernetes Operator are nothing more than a set of application-
specific custom controllers. Controllers have direct access to
Kubernetes API, which means they can monitor the cluster,
change pods/services, scale up/down and call endpoints of the
running applications, all according to custom rules written inside
those controllers.
• MongoDB’s Operator was created as an effort to make databases
easy to manage without locking you to a specific cloud vendor.
The operator, supports automated cluster provisioning, elastic
scalability, auto recovery, logging, monitoring, shard operations,
backup and restore through Ops/Cloud Manager.
• MongoDB Cloud Manger and Kubernetes Operators provides a
cloud-agnostic application deployment and management. The
power of both tools allow us to treat cloud providers like a
commodity, allowing seamless migration between them.
Kubernetes Operators
ü OperatorHub.io – Online
resource to Kubernetes
Operators
ü https://operatorhub.io/operator/
mongodb-enterprise
11. #MDBLocal
• A custom resource is an object that
extends the Kubernetes API or
allows you to introduce your own API
into a project or a cluster.
• A custom resource definition (CRD)
file defines your own object kinds
and lets the API Server handle the
entire lifecycle. Deploying a CRD
into the cluster causes the
Kubernetes API server to begin
serving the specified custom
resource.
CRD’s – Kubernetes Custom Resources and Custom Resource Definitions
API Definition from CDR
• /apis/<spec:group>/<spec:version>/<scope>/*/<names-plural>/...
API Proxy Stub
• /apis/mongodb.com/v1/namespaces/mongodb/mongodb/studentcluster
Repo: https://github.com/mongodb/mongodb-enterprise-kubernetes
Reference: crds.yaml
13. #MDBLocal
MongoDB Kubernetes Architectural Alternatives
Hybrid Cloud or Cloud
● MongoDb Open
Service Broker
● Cloud Manager
Best Practice -- depends on requirements
On-Premise - Air gapped
● MongoDB Kubernetes
Operator
14. #MDBLocal
MongoDB Cloud Manager
Intelligent Agents are the Key
● MongoDB Agents using
Automation on each
MongoDB host can maintain
your MongoDB deployments.
Cloud Manager
● Automation Agents can
add hosts, deploy and
upgrade new and existing
clusters.
● Same look and feel as
On-Premise MongoDB
Ops Manager
Works Anywhere – Used with MongoDB Operator
15. #MDBLocal
MongoDB Ops Manager
• Deploy and upgrade your
system. Reliably perform the tasks
that you have performed manually
in the past.
• Scale your MongoDB
application. Dynamically resize
capacity by adding shards and
replica set members
• Deliver point-in-time recovery and
scheduled backups. Restore to
any point in time.
• Monitor and get performance
alerts. Track over 100 key metrics.
• Improve Query Performance for
slow queries, recommends new
indexing strategy
For your data center - Used with
MongoDB Operator
17. #MDBLocal
MongoDB Open Service Broker or MongoDB Operator
Considerations
● Where is the database hosted? In Kubernetes Cluster or outside of Kubernetes cluster?
● Is there time/budget for maintenance tasks, like backups, patching and scaling (up and
down)
● Pods are transient, so the likelihood of database application restarts or failovers is higher
● Databases that are storing more transient and caching layers are better fits for
Kubernetes
● Enterprise Ops Manager – You do it all, set up Automation and Backup MongoDB
Clusters, Set all configuration options, Load Balance Ops Manager GUI
● Cloud Manager – We do it, point and click “Hosted Ops Manager” – Mongo Clusters in
Kubernetes
Containerization Data layer -- finally getting traction
18. #MDBLocal
But, I can set up MongoDB Myself
● Who should own the technical debt?
● The people that wrote the database, and know the internals …
● Or, My company that has an expertise in the area of <Fill in your application Domain>
● What is businesses biggest complaint of IT/Project Management/Development
● We want it now, we want it faster (Plus we want you to read our minds – right!!!!)
● We all like to be good stewards of our companies money, but are we?
● MongoDB handles all the system maintenance, both Atlas and Cloud Manager
● Help is a support ticket call away – seriously, these people are REALLY good!
● Free is not free, Yes, it is perfect for Dev Clusters, great for experiments, great for
learning, then there are those wonderful people that love us, that we are taking time
away from, perhaps unnecessarily.
Considerations
20. #MDBLocal
#! /usr/bin/env bash
eksctl create cluster
--name service-cluster
--version 1.13
--nodegroup-name standard-workers
--node-type t3.xlarge
--nodes 3
# Get External IP – Atlas and Cloud Manager are Secure by Default
kubectl get nodes -o jsonpath='{$.items[*].status.addresses[?(@.type=="ExternalIP")].address }'
echo "Be sure to add external IPs to API Whitelist..."
21. #MDBLocal
API Secrets
● Both Open Service
Broker and Operator
Uses API Public and
Private Key
● Both Use Organization
ID
● However, format and
locations of data are
different
But they are different …
26. #MDBLocal
#! /usr/bin/env bash
#
# Register the Atlas Open Service Broker with the Kubernetes Service Catalog
#
kubectl apply -f service-broker.yaml -n atlas
svcat get brokers -n atlas
##
# Check our Work
##
svcat describe broker atlas-service-broker -n atlas
# Deploy ReplicaSet
#
kubectl apply -f replica-set.yaml
# How is the deployment going
svcat describe instance my-atlas-cluster -n atlas
27. #MDBLocal
Service Options
ClusterServiceBroker
● An Atlas Open Service Broker instance that is registered as a ClusterServiceBroker is available to the
entire Kubernetes cluster. When you deploy a Atlas replica set or sharded cluster, you must use the
associated clusterServiceClass and clusterServicePlan resources.
ServiceBroker
● An Atlas Open Service Broker instance that is registered as a ServiceBroker is available to only a single
namespace within the Kubernetes cluster. When you deploy a Atlas replica set or sharded cluster, you
must use the serviceClass and servicePlan resources scoped to the same namespace.
39. #MDBlocal
Every session you rate enters you into a drawing for a
$200 gift card and TWO passes to MongoDB World 2020!
Using MongoDB Services in
Kubernetes: Any Platform
https://www.surveymonkey.com/r/QRCJHVP