The document discusses using Apache jclouds to interact with cloud databases. It introduces jclouds as a cloud SDK that allows interacting with multiple cloud providers through a common API. It then demonstrates how to use the jclouds database API to create a database instance on Rackspace, create a database, and add a user, providing code examples for each step.
JavaOne 2014: Taming the Cloud Database with jcloudszshoylev
This document provides information and instructions for setting up a project using Apache jclouds to create a database in the cloud. It discusses initializing the necessary APIs from jclouds to interact with cloud database services, and provides code samples for creating a database user, database instance, and connecting to the database to test it. The document also discusses next steps like contributing to jclouds examples projects and documentation.
Taming the Cloud Database with Apache jclouds, ApacheCon Europe 2014zshoylev
This document discusses setting up and using Apache jclouds, an open source multi-cloud library, to create and manage cloud databases. It provides code snippets for initializing the jclouds API, creating a database instance on a cloud provider like Rackspace, and polling the instance status until it is ready. The document also outlines the jclouds architecture and abstractions for cloud database services like Trove, and explains how to add support for new providers.
Why is My Spark Job Failing? by Sandy Ryza of ClouderaData Con LA
Abstract:
You are not a bad person. But your Apache Spark job is failing. It is running out of memory. It is stalled. It is complaining that no executors have registered or spitting out "Filesystem closed" exceptions with lines upon lines of $anon$1's or being consumed by a swarm of locusts the likes of which have not been seen since Moses crossed the Red Sea. Or it's completing -- 20 times as slow as it should reasonably take. Why? In this talk, you'll learn the internals of Spark jobs, the root causes of such ailments, and tuning strategies for avoiding them.
Bio:
Sandy Ryza is a data scientist at Cloudera, an Apache Hadoop committer, and a Spark contributor. Sandy is also the co-author of Advanced Analytics with Spark.
FeedBurner is a feed management provider that has scaled to serve 270,000 feeds and 100 million hits per day. The document discusses FeedBurner's scaling history and the solutions they implemented to address various scalability problems, including using load balancers and health checks, caching with Memcached, batch processing, partitioning tables, and implementing a disaster recovery plan using a "Panic App" to download and synchronize feeds.
Successful Software Development with Apache Cassandrazznate
Adding a new technology to your development process can be challenging, and the distributed nature of Apache Cassandra can make it daunting. However, recent improvements in drivers, utilities and tooling have simplified the process making it easier than ever before to develop software with Apache Cassandra.
In this presentation, we cover essential knowledge for all developers wanting to efficiently create reliable Apache Cassandra based solutions. Topics include:
- Language and Driver selection
- Optimizing Driver configuration
- Productive Developer environments using ccm, Vagrant and DataStax DevCenter
- Creating appropriate test data
- Unit testing
- Automated integration testing
- Test optimization with profiles
New and existing users will come away from this presentation with the necessary knowledge to make their next Apache Cassandra project a success.
Australian OpenStack User Group August 2012: Chef for OpenStackMatt Ray
This document discusses how Chef can be used to deploy and manage OpenStack infrastructure. It provides an overview of Chef's capabilities for infrastructure automation including defining servers, applications, and databases through code and templates. The document also describes the Chef for OpenStack project which provides cookbooks for deploying OpenStack components like Keystone, Glance, Nova, etc. It promotes the community around automating OpenStack deployment and management with Chef.
From common errors seen in running Spark applications, e.g., OutOfMemory, NoClassFound, disk IO bottlenecks, History Server crash, cluster under-utilization to advanced settings used to resolve large-scale Spark SQL workloads such as HDFS blocksize vs Parquet blocksize, how best to run HDFS Balancer to re-distribute file blocks, etc. you will get all the scoop in this information-packed presentation.
This document discusses caching strategies for Rails applications, including:
1. Using Rails caching for queries, pages, assets, and fragments to improve performance.
2. Configuring Cache-Control headers, compression, and CDNs like Fastly for efficient caching.
3. Techniques for caching dynamic content at the edge using surrogate keys and purging cached responses.
JavaOne 2014: Taming the Cloud Database with jcloudszshoylev
This document provides information and instructions for setting up a project using Apache jclouds to create a database in the cloud. It discusses initializing the necessary APIs from jclouds to interact with cloud database services, and provides code samples for creating a database user, database instance, and connecting to the database to test it. The document also discusses next steps like contributing to jclouds examples projects and documentation.
Taming the Cloud Database with Apache jclouds, ApacheCon Europe 2014zshoylev
This document discusses setting up and using Apache jclouds, an open source multi-cloud library, to create and manage cloud databases. It provides code snippets for initializing the jclouds API, creating a database instance on a cloud provider like Rackspace, and polling the instance status until it is ready. The document also outlines the jclouds architecture and abstractions for cloud database services like Trove, and explains how to add support for new providers.
Why is My Spark Job Failing? by Sandy Ryza of ClouderaData Con LA
Abstract:
You are not a bad person. But your Apache Spark job is failing. It is running out of memory. It is stalled. It is complaining that no executors have registered or spitting out "Filesystem closed" exceptions with lines upon lines of $anon$1's or being consumed by a swarm of locusts the likes of which have not been seen since Moses crossed the Red Sea. Or it's completing -- 20 times as slow as it should reasonably take. Why? In this talk, you'll learn the internals of Spark jobs, the root causes of such ailments, and tuning strategies for avoiding them.
Bio:
Sandy Ryza is a data scientist at Cloudera, an Apache Hadoop committer, and a Spark contributor. Sandy is also the co-author of Advanced Analytics with Spark.
FeedBurner is a feed management provider that has scaled to serve 270,000 feeds and 100 million hits per day. The document discusses FeedBurner's scaling history and the solutions they implemented to address various scalability problems, including using load balancers and health checks, caching with Memcached, batch processing, partitioning tables, and implementing a disaster recovery plan using a "Panic App" to download and synchronize feeds.
Successful Software Development with Apache Cassandrazznate
Adding a new technology to your development process can be challenging, and the distributed nature of Apache Cassandra can make it daunting. However, recent improvements in drivers, utilities and tooling have simplified the process making it easier than ever before to develop software with Apache Cassandra.
In this presentation, we cover essential knowledge for all developers wanting to efficiently create reliable Apache Cassandra based solutions. Topics include:
- Language and Driver selection
- Optimizing Driver configuration
- Productive Developer environments using ccm, Vagrant and DataStax DevCenter
- Creating appropriate test data
- Unit testing
- Automated integration testing
- Test optimization with profiles
New and existing users will come away from this presentation with the necessary knowledge to make their next Apache Cassandra project a success.
Australian OpenStack User Group August 2012: Chef for OpenStackMatt Ray
This document discusses how Chef can be used to deploy and manage OpenStack infrastructure. It provides an overview of Chef's capabilities for infrastructure automation including defining servers, applications, and databases through code and templates. The document also describes the Chef for OpenStack project which provides cookbooks for deploying OpenStack components like Keystone, Glance, Nova, etc. It promotes the community around automating OpenStack deployment and management with Chef.
From common errors seen in running Spark applications, e.g., OutOfMemory, NoClassFound, disk IO bottlenecks, History Server crash, cluster under-utilization to advanced settings used to resolve large-scale Spark SQL workloads such as HDFS blocksize vs Parquet blocksize, how best to run HDFS Balancer to re-distribute file blocks, etc. you will get all the scoop in this information-packed presentation.
This document discusses caching strategies for Rails applications, including:
1. Using Rails caching for queries, pages, assets, and fragments to improve performance.
2. Configuring Cache-Control headers, compression, and CDNs like Fastly for efficient caching.
3. Techniques for caching dynamic content at the edge using surrogate keys and purging cached responses.
Mitigating Security Threats with Fastly - Joe Williams at Fastly Altitude 2015Fastly
Fastly Altitude - June 25, 2015. Joe Williams, Computer Operator at GitHub discusses using a CDN to mitigate security threats.
Video of the talk: http://fastly.us/Altitude2015_Mitigating-Security-Threats-2
Joe's bio: Joe Williams is a Computer Operator at GitHub, and joined their infrastructure team in August 2013. Joe's passion for distributed systems, queuing theory and automation help keep the lights on. When not behind a computer you can generally find him riding a bicycle around Marin, CA.
Modern tooling to assist with developing applications on FreeBSDSean Chittenden
Discuss a workflow and the tooling for FreeBSD engineers to develop locally on their laptop (OS-X, Windows, or FreeBSD), and push applications to bare metal or the cloud. The tooling required to provide good automation from a developer laptop to production takes time to evolve, however this lecture will jumpstart a series of best practices for FreeBSD engineers who want to see their business applications run on FreeBSD.
The Best and Worst of Cassandra-stress Tool (Christopher Batey, The Last Pick...DataStax
Making sure your Data Model will work on the production cluster after 6 months as well as it does on your laptop is an important skill. It's one that we use every day with our clients at The Last Pickle, and one that relies on tools like the cassandra-stress. Knowing how the data model will perform under stress once it has been loaded with data can prevent expensive re-writes late in the project.
In this talk Christopher Batey, Consultant at The Last Pickle, will shed some light on how to use the cassandra-stress tool to test your own schema, graph the results and even how to extend the tool for your own use cases. While this may be called premature optimisation for a RDBS, a successful Cassandra project depends on it's data model.
About the Speaker
Christopher Batey Consultant / Software Engineer, The Last Pickle
Christopher (@chbatey) is a part time consultant at The Last Pickle where he works with clients to help them succeed with Apache Cassandra as well as a freelance software engineer working in London. Likes: Scala, Haskell, Java, the JVM, Akka, distributed databases, XP, TDD, Pairing. Hates: Untested software, code ownership. You can checkout his blog at: http://www.batey.info
Advanced Apache Cassandra Operations with JMXzznate
Nodetool is a command line interface for managing a Cassandra node. It provides commands for node administration, cluster inspection, table operations and more. The nodetool info command displays node-specific information such as status, load, memory usage and cache details. The nodetool compactionstats command shows compaction status including active tasks and progress. The nodetool tablestats command displays statistics for a specific table including read/write counts, space usage, cache usage and latency.
Spark and Mesos cluster optimization was discussed. The key points were:
1. Spark concepts like stages, tasks, and partitions were explained to understand application behavior and optimization opportunities around shuffling.
2. Application optimization focused on reducing shuffling through techniques like partitioning, reducing object sizes, and optimizing closures.
3. Memory tuning in Spark involved configuring storage and shuffling fractions to control memory usage between user data and Spark's internal data.
4. When running Spark on Mesos, coarse-grained and fine-grained allocation modes were described along with solutions like using Mesos roles to control resource allocation and dynamic allocation in coarse-grained mode.
This document provides instructions for setting up a small 3 node Hadoop cluster on Amazon EC2. It covers configuring EC2 instances, installing Java and Hadoop, configuring the Hadoop nodes and services, and running a sample MapReduce job to validate the cluster. The goal is to provide a simple tutorial for getting started with Hadoop on EC2 for learning purposes.
Deploying VMware vCloud Hybrid Service with Puppet - PuppetConf 2013Puppet
The document discusses automating the deployment of a VMware vCloud Hybrid Service (vCHS) using Puppet. It describes using Puppet to deploy and configure the various vCHS components through their respective APIs, including vCenter, vShield, and vCloud Director. It addresses challenges in automating these components and proposes treating everything as a native Puppet resource, with a "transport" resource to handle connecting to the different component APIs over SSH or REST.
Caching the Uncacheable: Leveraging Your CDN to Cache Dynamic ContentFastly
June 25, 2014. Hooman Beheshti, VP Technology at Fastly, discusses how using a real-time, modern CDN that provides instant cache invalidation and real-time analytics allows for instantaneous control over dynamic content caching. In this session, he looks at the challenges CDNs face with dynamic content and how you can use programmatic means to fully integrate your applications with your CDN.
Building an Impenetrable ZooKeeper - Kathleen Tingjaxconf
ZooKeeper is the unsung hero. Although a critical component, ZooKeeper is often noticed only after it’s missing. In this presentation, we'll talk about how to efficiently resolve some of the common issues that can cause ZooKeeper’s unavailability. An impenetrable ZooKeeper makes for a healthy cluster. ZooKeeper provides reliable and timely coordination of processes.
Production Readiness Strategies in an Automated WorldSean Chittenden
This document discusses strategies for making a software service production ready. It begins by outlining the typical software life cycle from idea to production. It then discusses some of the organizational prerequisites needed for a production service, including standardized terminology, naming conventions, and rules for incident response. The document also provides examples of what to include in a production readiness checklist, such as an overview of the service, its consumers, release process, health metrics, and quality metrics.
Stupid Boot Tricks: using ipxe and chef to get to boot management blissmacslide
Jason Cook discusses his experience setting up boot infrastructure for Fastly's caching clusters. He outlines how they moved from using existing tools like Cobbler and Razor to building their own solution called Donner using iPXE to boot machines over HTTP. Donner uses Chef to store machine metadata and configuration which allows the boot process to install operating systems, configure networking, and run Chef on first boot to provision machines.
This document discusses MySQL Sandbox, a tool for quickly installing and testing multiple MySQL database servers on a single machine. The tool allows users to install MySQL servers from binaries in seconds, set up replication topologies easily, and customize server configurations. MySQL Sandbox provides an easy way to test MySQL features without having to manually configure each database instance.
Tips for going fast in a slow world: Michael May at OSCON 2015Fastly
Fastly engineer Michael May at OSCON 2015: When it comes to caching, we fall into two categories – those who make phat stacks of cache money and those who suffer from cache anxiety. We know caching aggressively improves performance; however, advanced caching strategies for event-driven content or user-specific content are often neglected for fear of complexity or lack of understanding. In this talk, we’ll cover HTTP caching, old and new strategies for caching historically ‘uncacheable’ content, and secret features of HTTP accelerators like Varnish. Whether you’re already stacking cache or just seeking a prescription for one, you’ll leave with a deeper understanding of caching and accelerating applications that you can take and apply to your Rails, Django, etc. apps.
This document provides tips and examples for creating shell scripts to automate database administration tasks. It recommends using shell scripts because shell is available everywhere and shell scripting is powerful and fast to write. It then provides several tips for writing robust shell scripts, such as using configuration files, running commands in parallel, and creating shortcuts. The document includes examples of scripts for installing MySQL replication across multiple servers and testing that replication is working.
Description of some of the elements that go in to creating a PostgreSQL-as-a-Service for organizations with many teams and a diverse ecosystem of applications and teams.
Building highly scalable website requires to understand the core building blocks of your applicative environment. In this talk we dive into Jahia core components to understand how they interact and how by (1) respecting a few architectural practices and (2) fine tuning Jahia components and the JVM, you will be able to build a highly scalable service
How To Set Up SQL Load Balancing with HAProxy - SlidesSeveralnines
We continuously see great interest in MySQL load balancing and HAProxy, so we thought it was about time we organised a live webinar on the topic! Here is the replay of that webinar!
As most of you will know, database clusters and load balancing go hand in hand.
Once your data is distributed and replicated across multiple database nodes, a load balancing mechanism helps distribute database requests, and gives applications a single database endpoint to connect to.
Instance failures or maintenance operations like node additions/removals, reconfigurations or version upgrades can be masked behind a load balancer. This provides an efficient way of isolating changes in the database layer from the rest of the infrastructure.
In this webinar, we cover the concepts around the popular open-source HAProxy load balancer, and show you how to use it with your SQL-based database clusters. We also discuss HA strategies for HAProxy with Keepalived and Virtual IP.
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
Out of the box replication in postgres 9.4(pg confus)Denish Patel
This document contains notes from a presentation on PostgreSQL replication. It discusses write-ahead logs (WAL), replication history in PostgreSQL from versions 7.0 to 9.4, how to set up basic replication, tools for backups and monitoring replication, and demonstrates setting up replication without third party tools using pg_basebackup, replication slots, and pg_receivexlog. It also includes contact information for the presenter and an invitation to join the PostgreSQL Slack channel.
A empresa de tecnologia anunciou um novo smartphone com câmera de alta resolução, tela grande e bateria de longa duração por um preço acessível. O aparelho tem como objetivo atrair mais consumidores para a marca e aumentar sua participação no competitivo mercado de smartphones.
Mitigating Security Threats with Fastly - Joe Williams at Fastly Altitude 2015Fastly
Fastly Altitude - June 25, 2015. Joe Williams, Computer Operator at GitHub discusses using a CDN to mitigate security threats.
Video of the talk: http://fastly.us/Altitude2015_Mitigating-Security-Threats-2
Joe's bio: Joe Williams is a Computer Operator at GitHub, and joined their infrastructure team in August 2013. Joe's passion for distributed systems, queuing theory and automation help keep the lights on. When not behind a computer you can generally find him riding a bicycle around Marin, CA.
Modern tooling to assist with developing applications on FreeBSDSean Chittenden
Discuss a workflow and the tooling for FreeBSD engineers to develop locally on their laptop (OS-X, Windows, or FreeBSD), and push applications to bare metal or the cloud. The tooling required to provide good automation from a developer laptop to production takes time to evolve, however this lecture will jumpstart a series of best practices for FreeBSD engineers who want to see their business applications run on FreeBSD.
The Best and Worst of Cassandra-stress Tool (Christopher Batey, The Last Pick...DataStax
Making sure your Data Model will work on the production cluster after 6 months as well as it does on your laptop is an important skill. It's one that we use every day with our clients at The Last Pickle, and one that relies on tools like the cassandra-stress. Knowing how the data model will perform under stress once it has been loaded with data can prevent expensive re-writes late in the project.
In this talk Christopher Batey, Consultant at The Last Pickle, will shed some light on how to use the cassandra-stress tool to test your own schema, graph the results and even how to extend the tool for your own use cases. While this may be called premature optimisation for a RDBS, a successful Cassandra project depends on it's data model.
About the Speaker
Christopher Batey Consultant / Software Engineer, The Last Pickle
Christopher (@chbatey) is a part time consultant at The Last Pickle where he works with clients to help them succeed with Apache Cassandra as well as a freelance software engineer working in London. Likes: Scala, Haskell, Java, the JVM, Akka, distributed databases, XP, TDD, Pairing. Hates: Untested software, code ownership. You can checkout his blog at: http://www.batey.info
Advanced Apache Cassandra Operations with JMXzznate
Nodetool is a command line interface for managing a Cassandra node. It provides commands for node administration, cluster inspection, table operations and more. The nodetool info command displays node-specific information such as status, load, memory usage and cache details. The nodetool compactionstats command shows compaction status including active tasks and progress. The nodetool tablestats command displays statistics for a specific table including read/write counts, space usage, cache usage and latency.
Spark and Mesos cluster optimization was discussed. The key points were:
1. Spark concepts like stages, tasks, and partitions were explained to understand application behavior and optimization opportunities around shuffling.
2. Application optimization focused on reducing shuffling through techniques like partitioning, reducing object sizes, and optimizing closures.
3. Memory tuning in Spark involved configuring storage and shuffling fractions to control memory usage between user data and Spark's internal data.
4. When running Spark on Mesos, coarse-grained and fine-grained allocation modes were described along with solutions like using Mesos roles to control resource allocation and dynamic allocation in coarse-grained mode.
This document provides instructions for setting up a small 3 node Hadoop cluster on Amazon EC2. It covers configuring EC2 instances, installing Java and Hadoop, configuring the Hadoop nodes and services, and running a sample MapReduce job to validate the cluster. The goal is to provide a simple tutorial for getting started with Hadoop on EC2 for learning purposes.
Deploying VMware vCloud Hybrid Service with Puppet - PuppetConf 2013Puppet
The document discusses automating the deployment of a VMware vCloud Hybrid Service (vCHS) using Puppet. It describes using Puppet to deploy and configure the various vCHS components through their respective APIs, including vCenter, vShield, and vCloud Director. It addresses challenges in automating these components and proposes treating everything as a native Puppet resource, with a "transport" resource to handle connecting to the different component APIs over SSH or REST.
Caching the Uncacheable: Leveraging Your CDN to Cache Dynamic ContentFastly
June 25, 2014. Hooman Beheshti, VP Technology at Fastly, discusses how using a real-time, modern CDN that provides instant cache invalidation and real-time analytics allows for instantaneous control over dynamic content caching. In this session, he looks at the challenges CDNs face with dynamic content and how you can use programmatic means to fully integrate your applications with your CDN.
Building an Impenetrable ZooKeeper - Kathleen Tingjaxconf
ZooKeeper is the unsung hero. Although a critical component, ZooKeeper is often noticed only after it’s missing. In this presentation, we'll talk about how to efficiently resolve some of the common issues that can cause ZooKeeper’s unavailability. An impenetrable ZooKeeper makes for a healthy cluster. ZooKeeper provides reliable and timely coordination of processes.
Production Readiness Strategies in an Automated WorldSean Chittenden
This document discusses strategies for making a software service production ready. It begins by outlining the typical software life cycle from idea to production. It then discusses some of the organizational prerequisites needed for a production service, including standardized terminology, naming conventions, and rules for incident response. The document also provides examples of what to include in a production readiness checklist, such as an overview of the service, its consumers, release process, health metrics, and quality metrics.
Stupid Boot Tricks: using ipxe and chef to get to boot management blissmacslide
Jason Cook discusses his experience setting up boot infrastructure for Fastly's caching clusters. He outlines how they moved from using existing tools like Cobbler and Razor to building their own solution called Donner using iPXE to boot machines over HTTP. Donner uses Chef to store machine metadata and configuration which allows the boot process to install operating systems, configure networking, and run Chef on first boot to provision machines.
This document discusses MySQL Sandbox, a tool for quickly installing and testing multiple MySQL database servers on a single machine. The tool allows users to install MySQL servers from binaries in seconds, set up replication topologies easily, and customize server configurations. MySQL Sandbox provides an easy way to test MySQL features without having to manually configure each database instance.
Tips for going fast in a slow world: Michael May at OSCON 2015Fastly
Fastly engineer Michael May at OSCON 2015: When it comes to caching, we fall into two categories – those who make phat stacks of cache money and those who suffer from cache anxiety. We know caching aggressively improves performance; however, advanced caching strategies for event-driven content or user-specific content are often neglected for fear of complexity or lack of understanding. In this talk, we’ll cover HTTP caching, old and new strategies for caching historically ‘uncacheable’ content, and secret features of HTTP accelerators like Varnish. Whether you’re already stacking cache or just seeking a prescription for one, you’ll leave with a deeper understanding of caching and accelerating applications that you can take and apply to your Rails, Django, etc. apps.
This document provides tips and examples for creating shell scripts to automate database administration tasks. It recommends using shell scripts because shell is available everywhere and shell scripting is powerful and fast to write. It then provides several tips for writing robust shell scripts, such as using configuration files, running commands in parallel, and creating shortcuts. The document includes examples of scripts for installing MySQL replication across multiple servers and testing that replication is working.
Description of some of the elements that go in to creating a PostgreSQL-as-a-Service for organizations with many teams and a diverse ecosystem of applications and teams.
Building highly scalable website requires to understand the core building blocks of your applicative environment. In this talk we dive into Jahia core components to understand how they interact and how by (1) respecting a few architectural practices and (2) fine tuning Jahia components and the JVM, you will be able to build a highly scalable service
How To Set Up SQL Load Balancing with HAProxy - SlidesSeveralnines
We continuously see great interest in MySQL load balancing and HAProxy, so we thought it was about time we organised a live webinar on the topic! Here is the replay of that webinar!
As most of you will know, database clusters and load balancing go hand in hand.
Once your data is distributed and replicated across multiple database nodes, a load balancing mechanism helps distribute database requests, and gives applications a single database endpoint to connect to.
Instance failures or maintenance operations like node additions/removals, reconfigurations or version upgrades can be masked behind a load balancer. This provides an efficient way of isolating changes in the database layer from the rest of the infrastructure.
In this webinar, we cover the concepts around the popular open-source HAProxy load balancer, and show you how to use it with your SQL-based database clusters. We also discuss HA strategies for HAProxy with Keepalived and Virtual IP.
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
Out of the box replication in postgres 9.4(pg confus)Denish Patel
This document contains notes from a presentation on PostgreSQL replication. It discusses write-ahead logs (WAL), replication history in PostgreSQL from versions 7.0 to 9.4, how to set up basic replication, tools for backups and monitoring replication, and demonstrates setting up replication without third party tools using pg_basebackup, replication slots, and pg_receivexlog. It also includes contact information for the presenter and an invitation to join the PostgreSQL Slack channel.
A empresa de tecnologia anunciou um novo smartphone com câmera de alta resolução, tela grande e bateria de longa duração por um preço acessível. O aparelho tem como objetivo atrair mais consumidores para a marca e aumentar sua participação no competitivo mercado de smartphones.
This document discusses different types of wireless network security protocols and configurations for local area networks (LANs). It describes WEP, WPA, PSK, TKIP, and AES security protocols, explaining their purpose and differences. It also outlines three configurations for connecting devices like computers and an Xbox in a LAN, either through wired or wireless connections using a router.
This document describes PLANET, a system for massively parallel learning of tree ensembles using MapReduce. PLANET can build decision trees on very large datasets in a scalable way. It uses a master node to control the process and MapReduce jobs to handle tasks like finding the best splits when data is too large to fit in memory. PLANET supports techniques like bagging and boosting to build ensembles of trees for better predictive performance. Evaluation shows PLANET can efficiently learn from large datasets and complex models. Future work includes improving support for sampling and high-cardinality categorical attributes.
Structure of taxation and classification of taxesshaik moin
Tax is a compulsory payment to the government and can be direct or indirect. Direct taxes have an immediate burden on the taxpayer, like income and wealth taxes. Indirect taxes are collected by intermediaries and included in the price, like sales tax. Governments in India levy various direct and indirect taxes. The central government levies income, wealth, customs, excise and service taxes. State governments levy professional, entertainment, VAT and state excise duties. Local governments levy property, water and sewerage taxes. Direct taxes are more equitable but also more complex and unpopular. Indirect taxes are more convenient but also more inflationary and expensive to collect.
The niche in the market: The case of Belgian WinesJonas De Maere
Belgian wines have a very small share of less than 0.1% of the Belgian wine market, which is dominated by imports, primarily from France. Total Belgian wine production meets only about 0.1% of domestic consumption. To distinguish Belgian wines in this saturated market and justify their higher average price of €11 per bottle, producers need to focus on quality and terroir, educate consumers, and promote through competitions and tastings to build legitimacy and awareness. The marketing strategy of Belgian Wines Ltd. emphasizes developing the brand through understanding local markets and consumers and choosing appropriate marketing mix elements like price, placement in shops and restaurants, and promotional activities.
This document is a glossary containing vocabulary words organized into categories including animals, professions, rooms and objects, clothing, and transportation. The animals category lists creatures such as goldfish, snakes, sharks, and whales. Professions include occupations like photographer, doctor, chef, and engineer. Rooms and objects contain terms for interior spaces and furnishings. Clothing features items of dress like jackets, pants, dresses and accessories. Transportation covers vehicles and modes of transit.
The document describes Skill Accelerator, a new approach to intensive training that provides interactive training and coaching to improve skills and performance. It offers both generic and customized delivery options including online, in-person, and through a team learning and simulation approach (TLSA). Skill Accelerator covers various skills like sales, customer service, and leadership. It works in three phases - training, coaching, and simulation/debriefing. The coaching session can integrate customized or standard business simulations to test and embed learning while developing critical thinking. Skill Accelerator is a flexible platform that challenges professionals and helps organizations capture and share knowledge.
This document appears to be a list of students' results from the Grade 8 exams administered by the Punjab Examination Commission in 2013. It includes the roll numbers, names, and total scores of 401 students who took the exam at GHSS City Muslim Town (M-1) in Faisalabad. The scores are either numerical values or indicators like "FAIL" to show if a student passed or failed the exam.
Reflexes are rapid, involuntary motor responses to stimuli that can involve peripheral nerves and the spinal cord or higher brain centers. There are several types of reflexes classified by their anatomical location, number of synapses involved, or whether they produce flexion or extension responses. Muscle spindles and Golgi tendon organs are proprioceptors that provide feedback to the central nervous system to regulate muscle tone and reflexes like the stretch reflex and Golgi tendon reflex. Abnormal muscle tone like spasticity or rigidity can result from upper motor neuron disorders that disrupt the inhibitory pathways controlling motor neurons.
A Theoretical Analysis of the Tenets of Multinational Enterprise (MNE)Claretta Webb
In this paper, we analyzed the basic tenets of multinational enterprise (MNE) from a theoretical perspective, shedding light on the growing significance of MNEs in today’s global economy. The concept of MNE has been reviewed. We examined two theories of MNE – the trade theory and the transaction cost or internalization theory, in line with emerging global trends. We conclude that no single theory can explain MNE, rather, a combination of theories.
1. The document discusses a model for distributing Galaxy data across multiple storage resources including local storage, network-attached storage, and cloud-based storage.
2. It proposes integrating user-owned cloud-based storage to allow for unlimited storage and easier joint data analysis across Galaxy instances and third-party applications.
3. The model is transparent to end-users and involves uploading and downloading data between Galaxy histories and cloud storage using a tool called CloudBridge.
Running your Java EE 6 applications in the Cloud (FISL 12)Arun Gupta
This document discusses running Java EE 6 applications in the cloud. It provides an overview of Java EE 6 and demonstrates how to deploy Java EE 6 applications on various cloud platforms including Amazon Web Services, RightScale, Microsoft Azure, and Joyent. The document also discusses the Java EE 7 specification and upcoming GlassFish Server distributions.
Deploying windows containers with kubernetesBen Hall
The document discusses deploying Windows containers with Kubernetes. It covers building Windows containers, deploying containers on Kubernetes, and operating Kubernetes. Specifically, it shows how to:
- Build a Windows container with SQL Server using Docker
- Deploy a .NET Core app container to Kubernetes and expose it using a load balancer
- Scale the deployment to multiple replicas and observe traffic distribution
- Perform rolling updates to deploy new versions of the application
This document discusses using Windows Server AppFabric to scale the data tier of web applications. It describes the typical challenges of scaling a web application's data tier, such as databases becoming saturated and services slowing down. It then introduces Windows Server AppFabric as a solution, which provides a distributed in-memory cache that can be shared across servers and services. This allows caching data across multiple machines, reducing database load and eliminating duplicate requests. It provides examples of how AppFabric can be used to cache reference data, integrate with sessions, and support optimistic/pessimistic locking for shared resources.
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Oracle provides Java EE 6 application servers and databases that can run on various cloud platforms including Amazon Web Services, RightScale, Microsoft Azure, and Joyent. These cloud platforms offer virtual servers, storage, databases and additional services that allow flexible deployment of Java EE 6 applications in public, private and hybrid cloud environments. Pricing models vary between platforms and include consumption-based or commitment-based options.
Running your Java EE 6 Applications in the CloudArun Gupta
This document discusses running Java EE 6 applications in the cloud. It provides an overview of Java EE 6 and demonstrates deploying applications to various cloud platforms including Amazon Web Services, RightScale, Microsoft Azure, and Joyent. It also compares these platforms and discusses how Java EE can evolve to better support cloud computing.
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My talk in Bessemer VP R&D / CTO yearly event (Jan 2020).
The presentation discusses major concept in resilience testing and MyHeritage's path to Chaos Engineering.
Running your Java EE 6 applications in the Cloud @ Silicon Valley Code Camp 2010Arun Gupta
Arun Gupta presented on running Java EE 6 applications in the cloud. He discussed Java EE 6 support on various cloud platforms including Amazon, RightScale, Elastra, and Joyent. He also compared features of different cloud vendors and how Java EE can evolve to better support cloud computing. Gupta concluded that Java EE 6 applications can easily be deployed to various clouds and GlassFish provides a feature-rich implementation of Java EE 6.
JavaOne India 2011 - Running your Java EE 6 Apps in the CloudArun Gupta
This document discusses running Java EE 6 applications in the cloud. It provides an overview of deploying Java EE 6 applications to various cloud platforms including Amazon Web Services, RightScale, Microsoft Azure, and Joyent. It also discusses the Java EE 7 specification and how it will further support cloud deployments with a focus on multi-tenancy and elasticity. Lastly, it outlines the GlassFish Server distributions for both open source and commercial use on private and public clouds.
Running your Java EE 6 Apps in the Cloud - JavaOne India 2011Arun Gupta
This document discusses running Java EE 6 applications in the cloud. It provides an overview of deploying Java EE 6 applications to various cloud platforms including Amazon Web Services, RightScale, Microsoft Azure, and Joyent. It also discusses the Java EE 7 specification and how it will further support cloud deployments with a focus on multi-tenancy and elasticity. Lastly, it outlines the GlassFish Server distributions for both open source and commercial use on private and public clouds.
Troubleshooting Tips from a Docker Support EngineerJeff Anderson
The document discusses various troubleshooting techniques for Docker including using tools like socat and curl to characterize networking and TLS issues, checking container processes and permissions, using volumes to store persistent data, and resolving issues with incorrect localhost references between containers. It also provides examples of troubleshooting issues with a Minecraft server, Ruby application, and Nginx proxy configuration.
Troubleshooting Tips from a Docker Support Engineer - Jeff Anderson, DockerDocker, Inc.
Docker makes everything easier. But even with the easiest platforms, sometimes you run into problems. In this session, you'll learn first hand from someone whose job is helping customers fix these problems. Using Docker and Docker Data Center, you can keep your apps running smoothly with minimal downtime. In this session, you'll learn how to apply your troubleshooting skills in the Docker ecosystem, including: 1. Identification and characterization of the problem. 2. Command line tools to inspect networking and namespaces. 3. Applying these skills to your workloads on OSS Docker and on DDC.
This document discusses asynchronous I/O in Java and Scala using the Play Framework. It describes how LinkedIn uses a service-oriented architecture with hundreds of services making requests to each other. It then covers how Play supports non-blocking I/O using asynchronous code, promises, and futures to allow parallel requests without blocking threads. Key points covered include using map and flatMap to transform promises and futures, handling errors and timeouts, and the benefits of non-blocking I/O for scalability.
Monitoring Docker at Scale - Docker San Francisco Meetup - August 11, 2015Datadog
In this session I showed building a multi-container app from beginning to end, using Docker, Docker-Machine, Docker-Compose and everything in between. You can even try it out yourself using the link in the deck to a repo on GitHub.
If you're not familiar with Docker yet, here is your chance to catch up: a quick overview of the Open Source Docker Engine, and its associated services delivered through the Docker Hub. It also includes Jérôme will also discuss the new features of Docker 1.0, and briefly explain how you can run and maintain Docker on Azure. In addition, an Azure team member will demonstrate how deploy docker to Azure. The presentation will be followed by a Q&A session!
Running your Java EE 6 applications in the CloudArun Gupta
The document discusses running Java EE applications in the cloud using platforms like Amazon Web Services, RightScale, Microsoft Azure, and Joyent. It provides an overview of deploying Java EE applications on each platform, including how to configure and manage applications on Amazon EC2 and S3, deploy using RightScripts on RightScale, publish to Microsoft Azure using Visual Studio, and the language and server options for Joyent. The document also touches on pricing models and some considerations for evolving Java EE for cloud platforms.
Similar to Taming the Cloud Database with Apache jclouds (20)
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
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These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
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Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
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- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
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5th Power Grid Model Meet-up
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Power Grid Model
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2. Introductions
Taming the Cloud Database with Apache jclouds http://j.
mp/acjdb14
2
➢ Zack Shoylev
➢ irc: zacksh twitter: @zackshoylev
freenode #jclouds
Also email!
3. Introductions
Taming the Cloud Database with Apache jclouds http://j.
mp/acjdb14
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Developer Relations Group
https://developer.rackspace.com/support/
4. Goals
Taming the Cloud Database with Apache jclouds http://j.
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➢ jclouds
➢ Create a database in the cloud
➢ Abstractions and how to contribute
8. The Cloud
Taming the Cloud Database with Apache jclouds http://j.
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➢ Public cloud (external provider)
➢ Private cloud (internal deployment)
➢ Hybrid cloud
➢ Public + Private
Rackspace
example
9. The Cloud
Taming the Cloud Database with Apache jclouds http://j.
mp/acjdb14
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Your
System
S
D
K
Cloud
AP
I
VM
VM
VM
➢ This can be an application server
➢ Or your home machine
➢ Or belong to one of your end users
➢ Or a cloud VM
➢ Or a smartphone
jclouds
10. The Cloud
Taming the Cloud Database with Apache jclouds http://j.
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➢ Advantages
➢ Metered pricing (pay as you go)
➢ Project scalability (unlimited)
➢ Safer (offsite/redundant)
➢ Economies of scale
➢ Expertise
➢ Support
11. The Cloud
Taming the Cloud Database with Apache jclouds http://j.
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➢ Disadvantages
➢ Less hardware control
➢ Provider-controlled downtime
➢ Virtualization (efficiency)
➢ Provider lock-in
➢ Provider-specific apis/sdks/features
➢ Expensive to switch clouds or deploy locally
➢ jclouds minimizes this disadvantage
12. The Cloud
Taming the Cloud Database with Apache jclouds http://j.
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➢ Can’t someone else do it?
13. The Cloud
Taming the Cloud Database with Apache jclouds http://j.
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➢ Database specific advantages
➢ Optimized by provider
➢ Settings
➢ Container virtualization
➢ Automated software updates
➢ Redundant data storage
➢ Backup
➢ Migration
➢ Support
14. OpenStack
Taming the Cloud Database with Apache jclouds http://j.
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➢ Cloud OS
➢ Open-sourced by Rackspace and NASA
(2010)
➢ Free
➢ Supported
➢ AT&T, HP, IBM, Red Hat, Rackspace, Dell, Cisco,
Intel, VMware, …
15. jclouds
Taming the Cloud Database with Apache jclouds http://j.
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➢ Cloud SDK
➢ Apache project
➢ Java (and Clojure)
➢ Easy
➢ Portable
➢ Cloud-agnostic
➢ Community
➢ Open source
16. jclouds
Taming the Cloud Database with Apache jclouds http://j.
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➢ HTTP requests, responses, retries
➢ Authentication and re-authentication
➢ Pagination
➢ Polling
➢ Rate limits
➢ Retries
➢ Abstractions
➢ Logging
➢ Less code
25. Logging
Taming the Cloud Database with Apache jclouds http://j.
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// This module is responsible for enabling logging
Iterable<Module> modules = ImmutableSet.<Module> of(new SLF4JLoggingModule());
ComputeServiceContext context = ContextBuilder.newBuilder(provider)
.credentials(username, apiKey)
.modules(modules) // don't forget to add the modules to your context!
.buildView(ComputeServiceContext.class);
logback.xml
<configuration scan="false">
…
<appender name="WIREFILE" class="ch.qos.logback.core.FileAppender">
<file>target/test-data/jclouds-wire.log</file>
<encoder>
<Pattern>%d %-5p [%c] [%thread] %m%n</Pattern>
</encoder>
</appender>
26. Java Project
Taming the Cloud Database with Apache jclouds http://j.
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Skeleton
Project
Create User
Create Instance
Initialize API
Create Database
Test Connection
Cleanup
27. Initialize
Taming the Cloud Database with Apache jclouds http://j.
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private final TroveApi troveApi;
troveApi = ContextBuilder
.newBuilder("rackspace-clouddatabases-
us")
.credentials(username, apiKey)
.buildApi(TroveApi.class);
28. Architecture
Taming the Cloud Database with Apache jclouds http://j.
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Cloud Databases
Trove
jclouds-database
Increasing level of
abstraction
Provider
settings:
Endpoint, etc.
Implementation
code
Abstraction
s
29. Architecture
Taming the Cloud Database with Apache jclouds http://j.
mp/acjdb14
29
Cloud Databases
Trove
jclouds-database
Increasing level of
abstraction
Provider
settings:
Endpoint, etc.
Implementation
code
Abstraction
s
Not implemented
30. Initialize
Taming the Cloud Database with Apache jclouds http://j.
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private final FlavorApi flavorApi;
flavorApi = troveApi.getFlavorApiForZone(ZONE);
32. Java Project
Taming the Cloud Database with Apache jclouds http://j.
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Skeleton
Project
Create User
Create Instance
Initialize API
Create Database
Test Connection
Cleanup
33. Create Instance
Taming the Cloud Database with Apache jclouds http://j.
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Flavor flavor = Iterables.getFirst(flavorApi.list(), null);
…
Instance instance = instanceApi.create(flavorId, size, name);
flavor.getId()
Volume size in
GB
34. Create Instance
Taming the Cloud Database with Apache jclouds http://j.
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Instance updatedInstance = awaitAvailable(instance, instanceApi);
35. Create Instance
Taming the Cloud Database with Apache jclouds http://j.
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Instance updatedInstance = awaitAvailable(instance, instanceApi);
Polls status, waits until ready. Will not retry by
itself!
37. Actual Code
Taming the Cloud Database with Apache jclouds http://j.
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Utils.
getWorkingInstance(
String zone,
String name,
String flavorId,
int size)
38. Java Project
Taming the Cloud Database with Apache jclouds http://j.
mp/acjdb14
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Skeleton
Project
Create User
Create Instance
Initialize API
Create Database
Test Connection
Cleanup
39. Create Database
Taming the Cloud Database with Apache jclouds http://j.
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troveApi = ContextBuilder.newBuilder(PROVIDER)
.credentials(username, apiKey)
.buildApi(TroveApi.class);
instanceApi = troveApi.getInstanceApiForZone(ZONE);
databaseApi = troveApi
.getDatabaseApiForZoneAndInstance(ZONE,getInstance().getId());
getSomeApiForXandYandZ – fairly common in jclouds
40. Create Database
Taming the Cloud Database with Apache jclouds http://j.
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boolean result = databaseApi.create(NAME);
41. Java Project
Taming the Cloud Database with Apache jclouds http://j.
mp/acjdb14
41
Skeleton
Project
Create User
Create Instance
Initialize API
Create Database
Test Connection
Cleanup
42. Create User
Taming the Cloud Database with Apache jclouds http://j.
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userApi = troveApi
.getUserApiForZoneAndInstance(ZONE, instance.getId());
boolean result = userApi.create(UNAME, PASSWORD, DBNAME);
User name
User password
Database
name
43. Java Project
Taming the Cloud Database with Apache jclouds http://j.
mp/acjdb14
43
Skeleton
Project
Create User
Create Instance
Initialize API
Create Database
Test Connection
Cleanup
44. Test Connection
Taming the Cloud Database with Apache jclouds http://j.
mp/acjdb14
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Load balancer needed!
CreateLoadBalancer createLB = CreateLoadBalancer.
builder()
.name(NAME)
.protocol("MYSQL")
.port(3306)
.algorithm(LoadBalancer.Algorithm.RANDOM)
.nodes(addNodes)
.virtualIPType(VirtualIP.Type.PUBLIC)
.build();
45. Test Connection
Taming the Cloud Database with Apache jclouds http://j.
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loadBalancer = lbApi.create(createLB);
46. Test Connection
Taming the Cloud Database with Apache jclouds http://j.
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StringBuilder connString = new StringBuilder();
connString.append("jdbc:mysql://");
connString
.append(getVirtualIPv4(getLb().getVirtualIPs()));
connString.append("/");
connString.append(DBNAME); connString.append("?
user=");
connString.append(UNAME);
connString.append("&password=");
connString.append(PASSWORD);
47. Test Connection
Taming the Cloud Database with Apache jclouds http://j.
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Connection conn =
DriverManager.getConnection(connString.toString());
48. Test Connection
Taming the Cloud Database with Apache jclouds http://j.
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Statement stmt = conn.createStatement();
ResultSet rs = stmt.executeQuery("SELECT 3+5");
rs.first();
System.out.format(" 3+5 is %s%n", rs.getInt(1));