MongoDB Ops Manager is an enterprise-grade end-to-end database management, monitoring, and backup solution. Kubernetes has clearly won the orchestration-platform "wars". In this session we'll take a deep dive on how you can leverage both these technologies to host your MongoDB deployments within your Kubernetes infrastructure whether that's OpenShift, PKS, Azure AKS, or just upstream. This talk will review the core technologies, such as containers, Kubernetes, and MongoDB Ops Manager. You'll also have a chance to see real-live demos of MongoDB running on Kubernetes and managed with MongoDB Ops Manager with the MongoDB Enterprise Kubernetes Operator.
This tutorial covers all parallel replication implementation in MariaDB 10.0 and 10.1 and MySQL 5.6, 5.7 and 8.0 (including how it works in Group Replication).
MySQL and MariaDB have different types of parallel replication. In this tutorial, we present the different implementations that allow us to understand their limitations and tuning parameters. We cover how to make parallel replication faster and what to avoid for maximizing its benefits. We also present tests from Booking.com workloads.
Some of the subjects that are covered are group commit and optimistic parallel replication in MariaDB, the parallelism interval of MySQL and its Write Set optimization, and the ?slowing down the master to speed up the slave? optimization.
After this tutorial, you will know everything you need to implement and tune parallel replication in your environment. But more importantly, we will show how you can test parallel replication benefit in a non-disruptive way before deployment.
Advanced Percona XtraDB Cluster in a nutshell... la suiteKenny Gryp
Percona XtraDB Cluster is a high availability and high scalability solution for MySQL clustering. Percona XtraDB Cluster integrates Percona Server with the Galera synchronous replication library in a single product package which enables you to create a cost-effective MySQL cluster.
Since three years during Percona Live we initiate people to this technology... but what's next ? This tutorial is the continuation. It targets users that already have experience with PXC and want to go further.
This tutorial will cover the following topics:
- monitoring and trending
- problem solving
- limitations, when not to choose for PXC
- how to test ? (benchmark)
- schema changes
- backups
- multi datacenter
- advanced load balancing with HA Pproxy and Maxscale
- fine tune some important variables like galera cache, flow control limit, ...
This talk discusses the core concepts behind the Kubernetes extensibility model. We are going to see how to implement new CRDs, operators and when to use them to automate the most critical aspects of your Kubernetes clusters.
Load Balancing MySQL with HAProxy - SlidesSeveralnines
Agenda:
* What is HAProxy?
* SQL Load balancing for MySQL
* Failure detection using MySQL health checks
* High Availability with Keepalived and Virtual IP
* Use cases: MySQL Cluster, Galera Cluster and MySQL Replication
* Alternative methods: Database drivers with inbuilt cluster support, MySQL proxy, MaxScale, ProxySQL
This tutorial covers all parallel replication implementation in MariaDB 10.0 and 10.1 and MySQL 5.6, 5.7 and 8.0 (including how it works in Group Replication).
MySQL and MariaDB have different types of parallel replication. In this tutorial, we present the different implementations that allow us to understand their limitations and tuning parameters. We cover how to make parallel replication faster and what to avoid for maximizing its benefits. We also present tests from Booking.com workloads.
Some of the subjects that are covered are group commit and optimistic parallel replication in MariaDB, the parallelism interval of MySQL and its Write Set optimization, and the ?slowing down the master to speed up the slave? optimization.
After this tutorial, you will know everything you need to implement and tune parallel replication in your environment. But more importantly, we will show how you can test parallel replication benefit in a non-disruptive way before deployment.
Advanced Percona XtraDB Cluster in a nutshell... la suiteKenny Gryp
Percona XtraDB Cluster is a high availability and high scalability solution for MySQL clustering. Percona XtraDB Cluster integrates Percona Server with the Galera synchronous replication library in a single product package which enables you to create a cost-effective MySQL cluster.
Since three years during Percona Live we initiate people to this technology... but what's next ? This tutorial is the continuation. It targets users that already have experience with PXC and want to go further.
This tutorial will cover the following topics:
- monitoring and trending
- problem solving
- limitations, when not to choose for PXC
- how to test ? (benchmark)
- schema changes
- backups
- multi datacenter
- advanced load balancing with HA Pproxy and Maxscale
- fine tune some important variables like galera cache, flow control limit, ...
This talk discusses the core concepts behind the Kubernetes extensibility model. We are going to see how to implement new CRDs, operators and when to use them to automate the most critical aspects of your Kubernetes clusters.
Load Balancing MySQL with HAProxy - SlidesSeveralnines
Agenda:
* What is HAProxy?
* SQL Load balancing for MySQL
* Failure detection using MySQL health checks
* High Availability with Keepalived and Virtual IP
* Use cases: MySQL Cluster, Galera Cluster and MySQL Replication
* Alternative methods: Database drivers with inbuilt cluster support, MySQL proxy, MaxScale, ProxySQL
Almost Perfect Service Discovery and Failover with ProxySQL and OrchestratorJean-François Gagné
Of course there is no such thing as perfect service discovery, and we will see why in the talk. However, the way ProxySQL is deployed in this case minimizes the risk for split-brains, and this is why I qualify it as almost perfect. But let’s step back a little...
MySQL alone is not a high availability solution. To provide resilience to primary failure, other components need to be integrated with MySQL. At MessageBird, these additional components are ProxySQL and Orchestrator. In this talk, we describe how ProxySQL is architectured to provide close to perfect Service Discovery and how this, combined with Orchestrator, allows for automatic failover. The talk presents the details of the integration of MySQL, ProxySQL and Orchestrator in Google Cloud (and it would be easy to re-implement a similar architecture at other cloud vendors or on-premises). We will also cover lessons learned for the 2 years this architecture has been in production. Come to this talk to learn more about MySQL high availability, ProxySQL and Orchestrator.
리눅스 pacemaker 기반의 High Availaiblity 구성방법에 대해 설명합니다. pacemaker를 사용하는 다른 리눅스 기반도 구성이 가능합니다.
Pacemaker 기반 Linux High Availability 입문용으로는 적합하지 않을 수 있습니다. Pacemaker 기반 Linux High Availability를 한 번도 설치 및 구성을 하지 않은 리눅스 관리자라면 설치 문서를 먼저 참고하십시오.
RHEL7 및 CentOS 7을 중심으로 레드햇 계열의 리눅스에 적합한 내용으로 작성되었습니다.
MySQL Group Replication - Ready For Production? (2018-04)Kenny Gryp
At the end of 2016, Oracle released a new Plugin called MySQL Group Replication, which is a new MySQL replication method that aims to provide better High Availability, and built-in failover with consistency guarantees.
I evaluated the initial GA versions back in early 2017. I presented my initial findings with several best practices and concerns with the current implementation which made me state that Group Replication was not quite ready yet.
(https://www.slideshare.net/Grypyrg/my-sql-group-replication)
(Un)lucky as I was, a large part of the attendees were Oracle developers and the months after this, many of these bugs and missing features were implemented in both MySQL 8.0 as well as backported to MySQL 5.7. (Thank you!)
This is a followup presentation on my previous analysis, where I will look into the changes since and re-evaluate the readiness of Group Replication for production usage and provide my insights and opinion on the state of GR.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
Comparing Next-Generation Container Image Building ToolsAkihiro Suda
http://sched.co/EaYe
Until recently, running `docker build` against Dockerfile had been the only way to build container images.
However, lots of opensource software are being proposed as successors/alternatives to `docker build`:
- BuildKit (Moby Project / Docker)
- img (Jessica Frazelle / Microsoft)
- Buildah (Project Atomic / Red Hat)
- umoci & Orca (SUSE)
- Bazel (Google)
- OpenShift S2I (Red Hat)
Akihiro Suda compares these new tools' advantages and disadvantages.
His evaluation basis would include but not be limited to:
- Performance (Cache efficiency, Concurrency, Distributed Execution)
- Secret management, e.g. SSH and AWS keys
- Support for non-Dockerfile
- Non-root execution
- UI & UX
- Governance of the community
He also proposes a unified interface for using these tools with Kubernetes in a vendor-neutral way.
[오픈소스컨설팅]Day #1 MySQL 엔진소개, 튜닝, 백업 및 복구, 업그레이드방법Ji-Woong Choi
MySQL 소개
간략한 소개
version history
MySQL 사용처
제품 군 변화
시장 변화
MySQL 구성
MySQL 클라이언트 / 서버 개념
클라이언트 프로그램
MySQL 설치
MySQL 버전
MySQL 설치
MySQL 환경 설정
환경설정, 변수 설정
MySQL 스토리지 엔진 소개
MySQL tuning 소개 및 방법
데이터 백업/복구 방법
백업
복구
MySQL Upgrade
An Operator is an application that encodes the domain knowledge of the application and extends the Kubernetes API through custom resources. They enable users to create, configure, and manage their applications. Operators have been around for a while now, and that has allowed for patterns and best practices to be developed.
In this talk, Lili will explain what operators are in the context of Kubernetes and present the different tools out there to create and maintain operators over time. She will end by demoing the building of an operator from scratch, and also using the helper tools available out there.
MySQL InnoDB Cluster: High Availability Made Easy!Vittorio Cioe
InnoDB Cluster represents the present and the future of High-Availability technologies for MySQL! It has been developed to remove from the discussion all the "BUT" which used to arised when we were speaking about high-availability with MySQL. Now, with quasi-automated deployment, fully automated failover and conflict resolution, designing, implementing and maintaing your highly-available MySQL infrastructure is a really no-stress operation!
EFK Stack이란 ElasticSearch, Fluentd, Kibana라는 오픈소스의 조합으로, 방대한 양의 데이터를 신속하고 실시간으로 수집/저장/분석/시각화 할 수 있는 솔루션입니다. 특히 컨테이너 환경에서 로그 수집을 위해 주로 사용되는 기술 스택입니다.
Elasitc Stack에 대한 소개와 EFK Stack 설치 방법에 대해 설명합니다.
WSO2Con US 2015 Kubernetes: a platform for automating deployment, scaling, an...Brian Grant
Kubernetes can run application containers on clusters of physical or virtual machines.
It can also do much more than that.
Kubernetes satisfies a number of common needs of applications running in production, such as co-locating helper processes, mounting storage systems, distributing secrets, application health checking, replicating application instances, horizontal auto-scaling, load balancing, rolling updates, and resource monitoring.
However, even though Kubernetes provides a lot of functionality, there are always new scenarios that would benefit from new features. Ad hoc orchestration that is acceptable initially often requires robust automation at scale. Application-specific workflows can be streamlined to accelerate developer velocity.
This is why Kubernetes was also designed to serve as a platform for building an ecosystem of components and tools to make it easier to deploy, scale, and manage applications. The Kubernetes control plane is built upon the same APIs that are available to developers and users, implementing resilient control loops that continuously drive the current state towards the desired state. This design has enabled Apache Stratos and a number of other Platform as a Service and Continuous Integration and Deployment systems to build atop Kubernetes.
This presentation introduces Kubernetes’s core primitives, shows how some of its better known features are built on them, and introduces some of the new capabilities that are being added.
Optimizing MariaDB for maximum performanceMariaDB plc
When it comes to optimizing the performance of a database, DBAs have to look at everything from the OS to the network. In this session, MariaDB Enterprise Architect Manjot Singh shares best practices for getting the most out of MariaDB. He highlights recommended OS settings, important configuration and tuning parameters, options for improving replication and clustering performance and features such as query result caching.
At Pinterest, the ProxySQL infrastructure fronts numerous heterogeneous databases. Due to the high number of unique configurations and dynamic nature of cloud deployments, it’s a challenge to reliably provision, change, auto-scale, and monitor ProxySQL servers. Applying Infrastructure as Code principles using Terraform, we made it possible to manage such a large fleet of ProxySQL instances confidently. Come learn how we automated provisioning, testing, and monitoring of ProxySQL at scale.
Extending kubernetes with CustomResourceDefinitionsStefan Schimanski
The Kubernetes API provides a number of proven patterns to build distributed systems. More and more 3rd-party components are built on-top of Kubernetes and these patterns, providing their own resources stored in the cluster. In this presentation we will discuss CustomResourcesDefinitions and how they can extend the Kubernetes API in a quasi-native way. We look at the features, limits and their future.
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
In the era of Microservices, Cloud Computing and Serverless architecture, it’s useful to understand Kubernetes and learn how to use it. However, the official Kubernetes documentation can be hard to decipher, especially for newcomers. In this book, I will present a simplified view of Kubernetes and give examples of how to use it for deploying microservices using different cloud providers, including Azure, Amazon, Google Cloud and even IBM.
Almost Perfect Service Discovery and Failover with ProxySQL and OrchestratorJean-François Gagné
Of course there is no such thing as perfect service discovery, and we will see why in the talk. However, the way ProxySQL is deployed in this case minimizes the risk for split-brains, and this is why I qualify it as almost perfect. But let’s step back a little...
MySQL alone is not a high availability solution. To provide resilience to primary failure, other components need to be integrated with MySQL. At MessageBird, these additional components are ProxySQL and Orchestrator. In this talk, we describe how ProxySQL is architectured to provide close to perfect Service Discovery and how this, combined with Orchestrator, allows for automatic failover. The talk presents the details of the integration of MySQL, ProxySQL and Orchestrator in Google Cloud (and it would be easy to re-implement a similar architecture at other cloud vendors or on-premises). We will also cover lessons learned for the 2 years this architecture has been in production. Come to this talk to learn more about MySQL high availability, ProxySQL and Orchestrator.
리눅스 pacemaker 기반의 High Availaiblity 구성방법에 대해 설명합니다. pacemaker를 사용하는 다른 리눅스 기반도 구성이 가능합니다.
Pacemaker 기반 Linux High Availability 입문용으로는 적합하지 않을 수 있습니다. Pacemaker 기반 Linux High Availability를 한 번도 설치 및 구성을 하지 않은 리눅스 관리자라면 설치 문서를 먼저 참고하십시오.
RHEL7 및 CentOS 7을 중심으로 레드햇 계열의 리눅스에 적합한 내용으로 작성되었습니다.
MySQL Group Replication - Ready For Production? (2018-04)Kenny Gryp
At the end of 2016, Oracle released a new Plugin called MySQL Group Replication, which is a new MySQL replication method that aims to provide better High Availability, and built-in failover with consistency guarantees.
I evaluated the initial GA versions back in early 2017. I presented my initial findings with several best practices and concerns with the current implementation which made me state that Group Replication was not quite ready yet.
(https://www.slideshare.net/Grypyrg/my-sql-group-replication)
(Un)lucky as I was, a large part of the attendees were Oracle developers and the months after this, many of these bugs and missing features were implemented in both MySQL 8.0 as well as backported to MySQL 5.7. (Thank you!)
This is a followup presentation on my previous analysis, where I will look into the changes since and re-evaluate the readiness of Group Replication for production usage and provide my insights and opinion on the state of GR.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
Comparing Next-Generation Container Image Building ToolsAkihiro Suda
http://sched.co/EaYe
Until recently, running `docker build` against Dockerfile had been the only way to build container images.
However, lots of opensource software are being proposed as successors/alternatives to `docker build`:
- BuildKit (Moby Project / Docker)
- img (Jessica Frazelle / Microsoft)
- Buildah (Project Atomic / Red Hat)
- umoci & Orca (SUSE)
- Bazel (Google)
- OpenShift S2I (Red Hat)
Akihiro Suda compares these new tools' advantages and disadvantages.
His evaluation basis would include but not be limited to:
- Performance (Cache efficiency, Concurrency, Distributed Execution)
- Secret management, e.g. SSH and AWS keys
- Support for non-Dockerfile
- Non-root execution
- UI & UX
- Governance of the community
He also proposes a unified interface for using these tools with Kubernetes in a vendor-neutral way.
[오픈소스컨설팅]Day #1 MySQL 엔진소개, 튜닝, 백업 및 복구, 업그레이드방법Ji-Woong Choi
MySQL 소개
간략한 소개
version history
MySQL 사용처
제품 군 변화
시장 변화
MySQL 구성
MySQL 클라이언트 / 서버 개념
클라이언트 프로그램
MySQL 설치
MySQL 버전
MySQL 설치
MySQL 환경 설정
환경설정, 변수 설정
MySQL 스토리지 엔진 소개
MySQL tuning 소개 및 방법
데이터 백업/복구 방법
백업
복구
MySQL Upgrade
An Operator is an application that encodes the domain knowledge of the application and extends the Kubernetes API through custom resources. They enable users to create, configure, and manage their applications. Operators have been around for a while now, and that has allowed for patterns and best practices to be developed.
In this talk, Lili will explain what operators are in the context of Kubernetes and present the different tools out there to create and maintain operators over time. She will end by demoing the building of an operator from scratch, and also using the helper tools available out there.
MySQL InnoDB Cluster: High Availability Made Easy!Vittorio Cioe
InnoDB Cluster represents the present and the future of High-Availability technologies for MySQL! It has been developed to remove from the discussion all the "BUT" which used to arised when we were speaking about high-availability with MySQL. Now, with quasi-automated deployment, fully automated failover and conflict resolution, designing, implementing and maintaing your highly-available MySQL infrastructure is a really no-stress operation!
EFK Stack이란 ElasticSearch, Fluentd, Kibana라는 오픈소스의 조합으로, 방대한 양의 데이터를 신속하고 실시간으로 수집/저장/분석/시각화 할 수 있는 솔루션입니다. 특히 컨테이너 환경에서 로그 수집을 위해 주로 사용되는 기술 스택입니다.
Elasitc Stack에 대한 소개와 EFK Stack 설치 방법에 대해 설명합니다.
WSO2Con US 2015 Kubernetes: a platform for automating deployment, scaling, an...Brian Grant
Kubernetes can run application containers on clusters of physical or virtual machines.
It can also do much more than that.
Kubernetes satisfies a number of common needs of applications running in production, such as co-locating helper processes, mounting storage systems, distributing secrets, application health checking, replicating application instances, horizontal auto-scaling, load balancing, rolling updates, and resource monitoring.
However, even though Kubernetes provides a lot of functionality, there are always new scenarios that would benefit from new features. Ad hoc orchestration that is acceptable initially often requires robust automation at scale. Application-specific workflows can be streamlined to accelerate developer velocity.
This is why Kubernetes was also designed to serve as a platform for building an ecosystem of components and tools to make it easier to deploy, scale, and manage applications. The Kubernetes control plane is built upon the same APIs that are available to developers and users, implementing resilient control loops that continuously drive the current state towards the desired state. This design has enabled Apache Stratos and a number of other Platform as a Service and Continuous Integration and Deployment systems to build atop Kubernetes.
This presentation introduces Kubernetes’s core primitives, shows how some of its better known features are built on them, and introduces some of the new capabilities that are being added.
Optimizing MariaDB for maximum performanceMariaDB plc
When it comes to optimizing the performance of a database, DBAs have to look at everything from the OS to the network. In this session, MariaDB Enterprise Architect Manjot Singh shares best practices for getting the most out of MariaDB. He highlights recommended OS settings, important configuration and tuning parameters, options for improving replication and clustering performance and features such as query result caching.
At Pinterest, the ProxySQL infrastructure fronts numerous heterogeneous databases. Due to the high number of unique configurations and dynamic nature of cloud deployments, it’s a challenge to reliably provision, change, auto-scale, and monitor ProxySQL servers. Applying Infrastructure as Code principles using Terraform, we made it possible to manage such a large fleet of ProxySQL instances confidently. Come learn how we automated provisioning, testing, and monitoring of ProxySQL at scale.
Extending kubernetes with CustomResourceDefinitionsStefan Schimanski
The Kubernetes API provides a number of proven patterns to build distributed systems. More and more 3rd-party components are built on-top of Kubernetes and these patterns, providing their own resources stored in the cluster. In this presentation we will discuss CustomResourcesDefinitions and how they can extend the Kubernetes API in a quasi-native way. We look at the features, limits and their future.
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
In the era of Microservices, Cloud Computing and Serverless architecture, it’s useful to understand Kubernetes and learn how to use it. However, the official Kubernetes documentation can be hard to decipher, especially for newcomers. In this book, I will present a simplified view of Kubernetes and give examples of how to use it for deploying microservices using different cloud providers, including Azure, Amazon, Google Cloud and even IBM.
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.
In Apache Cassandra Lunch #41: Apache Cassandra Lunch #41: Cassandra on Kubernetes - Docker/Kubernetes/Helm Part 1, we discuss Cassandra on Kubernetes and give an introduction to Docker, Kubernetes, and Helm.
Accompanying Blog: https://blog.anant.us/apache-cassandra-lunch-41-cassandra-on-kubernetes-docker-kubernetes-helm-part-1/
Accompanying YouTube: https://youtu.be/-I8cKQO_Qr0
Sign Up For Our Newsletter: http://eepurl.com/grdMkn
Join Cassandra Lunch Weekly at 12 PM EST Every Wednesday: https://www.meetup.com/Cassandra-DataStax-DC/events/
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Follow Us and Reach Us At:
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MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...MongoDB
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
Mastering Kubernetes - Basics and Advanced Concepts using Example Projectwajrcs
Kubernetes is one of the most important pillars of modern IT environments. However, working with Kubernetes continues to present companies with challenges - not least due to a rapidly growing ecosystem and complex application scenarios. With the full-day online conference Mastering Kubernetes, you will learn about the latest trends in container orchestration and how to use Kubernetes in practice. You will master the most important tools and techniques of the cloud-native world around Kubernetes!
1. Basic Understanding
2. Installation
3. Basic components
4. Advanced components
5. Example project
#Kubernetes #CloudComputing #Training #CICD #Docker #Networking
This presentation covers how app deployment model evolved from bare metal servers to Kubernetes World.
In addition to theoretical information, you will find free KATACODA workshops url to perform practices to understand the details of the each topics.
DevOps Days Boston 2017: Real-world Kubernetes for DevOpsAmbassador Labs
DevOps Days Boston 2017
Microservices is an increasingly popular approach to building cloud-native applications. Dozens of new technologies that streamline adopting microservices development such as Docker, Kubernetes, and Envoy have been released over the past few years. But how do you actually use these technologies together to develop, deploy, and run microservices?
In this presentation, we’ll cover the nuances of deploying containerized applications on Kubernetes, including creating a Kubernetes manifest, debugging and logging, and how to build an automated continuous deployment pipeline. Then, we’ll do a brief tour of some of the advanced concepts related to microservices, including service mesh, canary deployments, resilience, and security.
Dev opsec dockerimage_patch_n_lifecyclemanagement_kanedafromparis
Lors de cette présentation, nous allons dans un premier temps rappeler la spécificité de docker par rapport à une VM (PID, cgroups, etc) parler du système de layer et de la différence entre images et instances puis nous présenterons succinctement kubernetes.
Ensuite, nous présenterons un processus « standard » de propagation d’une version CI/CD (développement, préproduction, production) à travers les tags docker.
Enfin, nous parlerons des différents composants constituant une application docker (base-image, tooling, librairie, code).
Une fois cette introduction réalisée, nous parlerons du cycle de vie d’une application à travers ses phases de développement, BAU pour mettre en avant que les failles de sécurité en période de développement sont rapidement corrigées par de nouvelles releases, mais pas nécessairement en BAU où les releases sont plus rares. Nous parlerons des diverses solutions (jfrog Xray, clair, …) pour le suivie des automatique des CVE et l’automatisation des mises à jour. Enfin, nous ferons un bref retour d’expérience pour parler des difficultés rencontrées et des propositions d’organisation mises en oeuvre.
Cette présentation bien qu’illustrée par des implémentations techniques est principalement organisationnelle.
Stateful, Stateless and Serverless - Running Apache Kafka® on Kubernetesconfluent
Speakers: Joe Beda, Co-founder and CTO, Heptio + Gwen Shapira, Principal Data Architect, Confluent
With the rapid adoption of microservices, there is a growing need for solutions to manage deployment, resources and data for fleets of microservices. Kubernetes is a resource management framework for containers that is rapidly growing in popularity. Apache Kafka is a streaming platform that makes data accessible to the edges of an organization. It's no wonder the question of running Kafka on Kubernetes keeps coming up!
In this online talk, Joe Beda, CTO of Heptio and co-creator of Kubernetes, and Gwen Shapira, principal data architect at Confluent and Kafka PMC member, will help you navigate through the hype, address frequently asked questions and deliver critical information to help you decide if running Kafka on Kubernetes is the right approach for your organization.
You will:
-Get an introduction to the basic concepts you need to know as you plan to deploy services on Kubernetes.
-Learn which parts of the Kafka ecosystem fit Kubernetes like a glove, and which require special attention.
-Pick up useful tips for getting started.
-See why Confluent Platform for Kubernetes is the simplest solution to deploying and orchestrating Kafka on Kubernetes, using container images and a Kubernetes operator.
Watch the recording: https://videos.confluent.io/watch/yoZcuazDjDDTcj1sRnaD3J?.
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB
During this talk we'll navigate through a customer's journey as they migrate an existing MongoDB deployment to MongoDB Atlas. While the migration itself can be as simple as a few clicks, the prep/post effort requires due diligence to ensure a smooth transfer. We'll cover these steps in detail and provide best practices. In addition, we’ll provide an overview of what to consider when migrating other cloud data stores, traditional databases and MongoDB imitations to MongoDB Atlas.
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
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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: 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.
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
Query performance should be the unsung hero of an application, but without proper configuration, can become a constant headache. When used properly, MongoDB provides extremely powerful querying capabilities. In this session, we'll discuss concepts like equality, sort, range, managing query predicates versus sequential predicates, and best practices to building multikey indexes.
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
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 .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.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Dominate Social Media with TubeTrivia AI’s Addictive Quiz Videos.pdf
MongoDB Ops Manager + Kubernetes
1. opsmanager-kubernetes
December 8, 2018
1 MongoDB Enterprise Kubernetes Operator
1.1 Agenda
• High level overview of Kubernetes
• Kubernetes Cluster vs MongoDB Cluster
• Statefull vs Stateless Replication
• Kubernetes Operators
• Ops Manager Kubernetes Operator
• Build a local cluster along the way
1.2 > whoami
{
"name": "Norberto Leite",
"position": "Lead Engineer",
"team": "Curriculum, Engineering"
}
Norberto Leite
1
2. mflix front page
1.2.1 [@nleite](https://twitter.com/nleite)
1.2.2 Disclaimer
This is a buzzword intensive presentation but by no means intended to trick you into
thinking I’m a very smart person! Buzzwords just sound nice when put together...
1.2.3 But before we get started ....
replace this image
1.2.4 MongoDB Developer Courses
https://university.mongodb.com/
2
3. M220 MongoDB University Courses
Kubernetes Logo
1.3 Kubernetes
1.3.1 Kubernetes Vendor Ecosystem
https://blog.spotinst.com/2018/05/20/kubernetes-ecosystem/
1.3.2 Definition
Kubernetes is an open-source container-orchestration system for automating deployment, scaling
and management of containerized applications. It was originally designed by Google and is now
maintained by the Cloud Native Computing Foundation
Kubernetes Objects
• pods
• replicasets
• persistentvolumeclaims
• persistentvolumes
• nodes
• storageclasses
• clusters
• ...
https://kubernetes.io/docs/concepts/overview/working-with-objects/kubernetes-objects/
1.3.3 Kubernetes is for Containers => Virginia is for Lovers
Kubernetes is an open-source container-orchestration system for automating deployment, scal-
ing and management of containerized applications. It was originally designed by Google and
3
5. is now maintained by the Cloud Native Computing Foundation
Kubernetes uses containers. Well, we can say that kubernetes loves containers. Deploys and
manages containers and containerized applications
Kubernetes has standardized the container definition on the Docker format.
1.3.4 Container Definition
cat mflix/Dockerfile
# base image of mflix container
FROM java:8
# port number the container exposes
EXPOSE 90000
# make the jar file available in the container image
COPY mflix-1.0-SNAPSHOT.jar ./mflix-1.0-SNAPSHOT.jar
# application run command
CMD ["java", "-jar", "./mflix-1.0-SNAPSHOT.jar"]
In this file we can see an example of a Docker image file. Sets the instructions to load, expose
and execute containarized applications or instances.
The Docker images are hiearchical, this means that we can compose images uppon each other,
inheriting the configuration and image setup
In this example we are creating a container image using as baseline a Java image.
1.3.5 Image vs Container
An image determines what and how to run, using/inherinting which requierements and the de-
fault configuration of a containerized application
A container is the the runtime execution of a built Docker image.
5
7. kubernetes_definition
1.3.6 Image vs Container Diagram
https://stackoverflow.com/questions/23735149/what-is-the-difference-between-a-
docker-image-and-a-container
1.3.7 Kubernetes Manages Containers
Kubernetes is an open-source container-orchestration system for automating deployment,
scaling and management of containerized applications. It was originally designed by Google
and is now maintained by the Cloud Native Computing Foundation
Aside from running containers, Kubernetes is also capable of defining the rules of when to
start/stop containers, how containers communicate with one another, how we scale deployments,
how to upgrade versions of containers, how to provide HA and fault-tolerance and where to place
different containers into different nodes / machines.
1.4 Kubernetes Architecture
On a high level, kubernetes can be represented by something similar to this diagram.
For each Kubernetes cluster, we will have master node, which holds a set of important compo-
nents of the architecture:
• kube-scheduler
• kube-control-manager
• kube-apiserver
• etcd
• kubelet
• kube-proxy
Each of these I’ll provide the relevant links for the exact function within a k8s cluster, however
the names of these components are pretty self explanatory. The unusual one, that might be a bit
more criptic in terms of meaning, given that the name might mean very different things, is etcd,
7
8. Kubernetes Architecture
which is an HA key value store, that Kubernetes uses for all cluster data. You can think of etcd as
the config server in a MongoDB sharded cluster, which may or may not be set to run within the
master node at all. It can run on it’s own separate node.
You will find all the relevant links at the end of this presentation.
But in essence, the master node runs a fair amount of different processes.
https://github.com/kubernetes/community/blob/master/contributors/design-
proposals/architecture/architecture.md#the-kubernetes-node
1.4.1 Multi-master Kubernetes with kubeadm
Given the previous diagram, you might been thinking
this Kubernetes cluster thing does not seem to be too scalable, how in this day an age
does a cluster have only one master.
Well, fear not, kubernetes does have a way to avoid single points of failure using kubeadm.
This is out-of-scope for this talk, but keep in mind that this alone can be setup in several different
architectures.
Bottom line is that kubernetes can be set to run in an HA mode.
1.4.2 Kubernetes Node
Kubernetes is a cluster, therefore > there will be dragons!
Not really, but there will be nodes. Aside from the previously aluded Master node, or several
of these master nodes, k8s also has worker nodes, previously known as minions
K8s nodes can have serveral different specs. We can compose a k8s cluster with physical,
virtual and cloud server nodes. Although, like in any systems archicture, consistency tends to be
benefitial on the long term, a k8s cluster can be composed by a very diverse set of server instance
specs. | Each node is composed with the necessary processes to run pods. Each has a container
runtime, generally docker, to allow the nodes to deploy and run containers.
8
10. POD Diagram
1.4.3 Kubernetes POD
https://kubernetes.io/docs/concepts/workloads/pods/pod/
A POD is the smallest deployable unit of computing in Kubernetes.
Can be composed of one or several different containers, a group of containers, and allows the
definition of shared network and storage, and how to run the set of containers that compose the
POD.
1.4.4 Kubernetes ReplicaSet - Across Nodes
https://kubernetes.io/docs/concepts/workloads/controllers/replicaset/
Kubernetes allows for pods to be fault tolerant and highly available. This managed via Repli-
caSes (familiar name!)
We can define PODs replica sets across nodes
10
11. replica set single node
1.4.5 Kubernetes ReplicaSet - Single Node
Or within a single node. This is model that we are going to setup today.
1.4.6 Kubernetes Service
https://kubernetes.io/docs/concepts/services-networking/service/
Services are a speciall type of POD that that other PODs relly on to operate. Now, by default
PODs are mortal and get resurected dynamically, and they subject to constant change in terms of
their deployment composition, number of replica nodes etc. This can cause issues to other PODs
if those rely in some guarantees and pre-defined configuration.
A Kubernetes Service is an abstraction which defines a logical set of PODs and a policy by
which to access them. You find Services as relliable and consistent PODs to support other PODs.
11
12. ops manager diagram
1.5 Ops Manager / Cloud Manager
MongoDB Ops Manager is a MongoDB on-prem solution for managing MongoDB Cluster deploy-
ments. Allows for an holistic management of all things related with MongoDB
• updates
• scaling up and down
• user management and integration
• node deployment
• role management
Across you datacenter.
And there are several particular aspects of a MongoDB Cluster that need care and attention,
something that ops manager takes care of in a very efficient way.
1.5.1 Cloud / Ops Manager - Monitoring
1.5.2 Cloud / Ops Manager - Automation
1.5.3 Cloud / Ops Manager - Backup
1.5.4 Cloud / Ops Manager Agents
1.6 Kubernetes Cluster vs MongoDB Cluster
There are several similar notions and definitions between a Kubernetes cluster and a MongoDB
cluster.
But the devil is in the details and in the functionality of each of these clusters.
1.6.1 Cluster Concepts
• MongoDB Replica Set
• Kubernetes Replica Set
• MongoDB Node
• Kubernetes Node
12
17. Kubernetes Nodes vs MongoDB Nodes
1.6.2 Kubernetes Node vs MongoDB Node
1.6.3 MongoDB Nodes in a Kubernetes Node
1.6.4 Kubernetes ReplicaSet vs MongoDB ReplicaSet
While there purpose for each of the replica set notions is to provide fault tollerance, these are
pretty distinct.
In a POD replication, the definition of the containers is replicate has defined, either to a differ-
ent pod running in the same node or accross different nodes.
In a MongoDB Replica Set, the fault tollerance and HA is also associated with a dynamic intra
replica set rules and options. All nodes of a MongoDB Replica set share the exact same data, they
follow a replication protocol and respond to workloads as a single shared state. This is generally
not the case in a Kubernetes Replica Set.
A nice way to distinguish these two different replica sets is to think in terms of Kubernetes
replica sets as redundancy of application instances/containers, while a MongoDB replica set as-
sures redundancy and HA of data, regardless of the specification of the instance that supports that
service, although all nodes only run a mongodb binary.
1.7 Stateless vs Statefull
One important aspect to keep in mind around cluster management, in particular scalability of
clusters, concernes state and state management.
In generall, container technology is extremely efficient scalling out stateless applications and
systems. This as to do with the fact that state, data, adds density to the scalability. It tends to be
more complicated to manage data then intances.
And this where Kubernetes, via persistent volumes, allows containers scallability to be better
aligned, not perfect with the notion of scaling systems that rely and manage state.
17
20. All Together Now
Getting a system that excels at data management, like mongodb , combined with the scalabilty
offered by kubernetes is a very appealing solution for ops professionals.
1.8 Kubernetes Operator
An Operator is a method of packaging, deploying and managing a Kubernetes appli-
cation. A Kubernetes application is an application that is both deployed on Kubernetes
and managed using the Kubernetes APIs and kubectl tooling.
https://coreos.com/operators/
1.9 MongoDB Enterprise Kubernetes Operator (beta)
The Operator enables easy deploys of MongoDB into Kubernetes clusters, using our
management, monitoring and backup platforms, Ops Manager and Cloud Manager.
By installing this integration, you will be able to deploy MongoDB instances with a
single simple command.
https://github.com/mongodb/mongodb-enterprise-kubernetes
1.9.1 MongoDB Enterprise Kubernetes - Main Benefits
• Quick, declarative definition of what MongoDB services you want
• Auto-healing, using Kubernetes reliability features
• Easy to scale up / scale down
1.10 All Together Now!
https://upload.wikimedia.org/wikipedia/en/c/cd/All_Together_Now_cover.jpg
1.11 Kubernetes + Cloud/Ops Manager
Step 1 - Create Kubernetes Cluster and Cloud/Ops Manager Instance
Step 2 - Install Enterprise Kubernetes Operator
Step 3 - Apply Deployment
Step 4 - Setup Deployment PODs and Agents
Step 5 - Cluster Up and Running Managed by Cloud/Ops Manager
20
24. typical kubernetes cluster image
1.12 Let’s do it!
1.12.1 Typical Image of a Kubernetes Cluster
http://johnmclaughlin.info/learn-kubernetes-using-minikube-docker-macos/
In many different presentations and content out there, in the interwebs, you will see this typical
image of big container ship and lots of containers in it.
Which is nice.
1.12.2 This is what we are going to do today ;)
http://www.simplyorganized.me/2017/05/video-professional-organizers-
organized-fridge-freezer.html
However, in the majority of cases, what you end up setting up is a small set of fridge contain-
ers. That’s exactly what we are going to do today.
1.13 Recap
• Basic overview of Kubernetes components and architecture
• How to locally install a Kubernetes cluster
• How to deploy containarized applications in Kubernetes
• How to deploy and manage a MongoDB Cluster in Kubernetes
• How to integrate Ops Manager | Cloud Manager with Kubernetes
1.13.1 References and Glossory
• kubectl documentation
• kubernetes node
• kubeadm documentation
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