Introduction to Aspera software; an extremely high speed file transfer, and streaming technology; faster than 100x for ftp. Replacement of FTP, and rsync.
The document discusses configuration management and how Chef can be used to manage numerous environments, services, and servers across platforms by defining roles, environments, and cookbooks; it also discusses how Chef can be integrated with Jenkins for continuous integration and used to automatically scale application servers in AWS through tools that bridge CloudFormation and Chef.
goployer, 코드 기반의 배포 도구 - 송주영 (beNX) :: AWS Community Day 2020AWSKRUG - AWS한국사용자모임
The document discusses deployment best practices and introduces goployer, an open source deployment tool. It summarizes key aspects of infrastructure as code and modern deployment approaches like blue/green and canary deployments. Goployer supports immutable infrastructure, deployment as code, measurement and testing to enable cost effective and simple deployments. The DevOps Art project aims to share infrastructure code, develop open source tools like Terraform and goployer, and conduct online workshops to foster a proper conceptual understanding of DevOps philosophy and ideal implementations based on that philosophy.
This document discusses infrastructure as code and the HashiCorp ecosystem. Infrastructure as code allows users to define and provision infrastructure through code rather than manual configuration. It can be used to launch, create, change, and downscale infrastructure based on configuration files. Tools like Terraform allow showing what changes will occur before applying them through files like main.tf and variables.tf. Terraform is part of the broader HashiCorp ecosystem of tools.
20ft is a toolkit for building containerized applications simply and securely. It allows building tiny containerized apps that can be configured and managed independently. 20ft uses containers, load balancing, individual firewalls, and snapshot/rollback capabilities to provide a multi-tenant environment with isolation and high availability.
This document discusses how Between, a mobile app for couples, migrated their photo architecture to reduce storage costs by 70%. The old architecture generated and stored multiple thumbnail sizes for each photo, using 6.6 billion thumbnails and 738 TB of storage. The new architecture resizes thumbnails on demand using the fast Skia library, saving the original high resolution photos as smaller WebP files. Migration of 1.1 billion existing photos to the new system took 4 days using Spot instances. This reduced storage usage by 75% to 184 TB and number of S3 objects by 82%, cutting total photo costs by 68%.
Introduction To Streaming Data and Stream Processing with Apache Kafkaconfluent
Slack processes over 1.2 trillion messages written and 3.4 trillion messages read daily across its real-time messaging platform, generating around 1 petabyte of streaming data. With thousands of engineers and tens of thousands of producer processes, Slack relies on Apache Kafka as the commit log for its distributed database to handle its massive scale of real-time messaging.
This document discusses using Kubernetes on AWS and provides tips across three main topics: designing clusters, installation, and operations. For design, it recommends automating as much as possible, properly sizing clusters based on network and server capacities, and using permissions and tags to control access. For installation, it discusses using multiple AWS accounts for access control and tools like Kops to deploy and manage clusters. For operations, it discusses using AWS services for databases and logging instead of running them on Kubernetes, and considerations for custom registries and secrets. The overall message is how to leverage AWS services while deploying and managing Kubernetes clusters at scale.
The document discusses improving Terraform infrastructure management by using modules and remote state. It recommends creating reusable modules for resources like EC2, ECS, and ALB and storing remote state for shared resources like VPC to avoid duplication. Engineers can then easily modify infrastructure by calling modules from a single repo, promoting collaboration and review. Key benefits include less complex creation/updates, easier PR reviews, and allowing any engineer to modify Terraform configs following standards.
The document discusses configuration management and how Chef can be used to manage numerous environments, services, and servers across platforms by defining roles, environments, and cookbooks; it also discusses how Chef can be integrated with Jenkins for continuous integration and used to automatically scale application servers in AWS through tools that bridge CloudFormation and Chef.
goployer, 코드 기반의 배포 도구 - 송주영 (beNX) :: AWS Community Day 2020AWSKRUG - AWS한국사용자모임
The document discusses deployment best practices and introduces goployer, an open source deployment tool. It summarizes key aspects of infrastructure as code and modern deployment approaches like blue/green and canary deployments. Goployer supports immutable infrastructure, deployment as code, measurement and testing to enable cost effective and simple deployments. The DevOps Art project aims to share infrastructure code, develop open source tools like Terraform and goployer, and conduct online workshops to foster a proper conceptual understanding of DevOps philosophy and ideal implementations based on that philosophy.
This document discusses infrastructure as code and the HashiCorp ecosystem. Infrastructure as code allows users to define and provision infrastructure through code rather than manual configuration. It can be used to launch, create, change, and downscale infrastructure based on configuration files. Tools like Terraform allow showing what changes will occur before applying them through files like main.tf and variables.tf. Terraform is part of the broader HashiCorp ecosystem of tools.
20ft is a toolkit for building containerized applications simply and securely. It allows building tiny containerized apps that can be configured and managed independently. 20ft uses containers, load balancing, individual firewalls, and snapshot/rollback capabilities to provide a multi-tenant environment with isolation and high availability.
This document discusses how Between, a mobile app for couples, migrated their photo architecture to reduce storage costs by 70%. The old architecture generated and stored multiple thumbnail sizes for each photo, using 6.6 billion thumbnails and 738 TB of storage. The new architecture resizes thumbnails on demand using the fast Skia library, saving the original high resolution photos as smaller WebP files. Migration of 1.1 billion existing photos to the new system took 4 days using Spot instances. This reduced storage usage by 75% to 184 TB and number of S3 objects by 82%, cutting total photo costs by 68%.
Introduction To Streaming Data and Stream Processing with Apache Kafkaconfluent
Slack processes over 1.2 trillion messages written and 3.4 trillion messages read daily across its real-time messaging platform, generating around 1 petabyte of streaming data. With thousands of engineers and tens of thousands of producer processes, Slack relies on Apache Kafka as the commit log for its distributed database to handle its massive scale of real-time messaging.
This document discusses using Kubernetes on AWS and provides tips across three main topics: designing clusters, installation, and operations. For design, it recommends automating as much as possible, properly sizing clusters based on network and server capacities, and using permissions and tags to control access. For installation, it discusses using multiple AWS accounts for access control and tools like Kops to deploy and manage clusters. For operations, it discusses using AWS services for databases and logging instead of running them on Kubernetes, and considerations for custom registries and secrets. The overall message is how to leverage AWS services while deploying and managing Kubernetes clusters at scale.
The document discusses improving Terraform infrastructure management by using modules and remote state. It recommends creating reusable modules for resources like EC2, ECS, and ALB and storing remote state for shared resources like VPC to avoid duplication. Engineers can then easily modify infrastructure by calling modules from a single repo, promoting collaboration and review. Key benefits include less complex creation/updates, easier PR reviews, and allowing any engineer to modify Terraform configs following standards.
This document discusses Contentful Engineering's migration from using AWS alone to using Kubernetes on AWS. Some key points:
1) Contentful migrated to take advantage of Kubernetes' focus on application delivery and open source development model over their previous Chef-based deployment platform.
2) They use Kops to manage Kubernetes clusters on AWS, deploying clusters in the same VPC and using kubenet networking and kube2iam to integrate with AWS services.
3) The migration process involved moving services to Kubernetes deployments and exposing them via LoadBalancer services, and updating service discovery in Route53.
4) Lessons learned include staying up to date with Kubernetes and Kops releases, customizing Kops outputs
Storage Is Not Virtualized Enough - part 1Zhipeng Huang
This document discusses storage function virtualization (SFV) and why storage is not yet virtualized enough. It provides an overview of SFV and how it can enhance NFV by virtualizing storage functions. It also discusses OpenStack SFV and related blueprints to improve storage scheduling and functionality. Finally, it encourages collaboration on SFV-related work beyond just OpenStack through various communication channels and open source projects.
How to use Ansible to automate your applications in AWS. What is Ansible and why is it different? How to control cloud deployments securely and how to control AWS resources using dynamic inventory and tags.
The document discusses scaling infrastructure using Amazon Web Services (AWS). It provides examples of how a vendor could programmatically spin up AWS instances and resources based on customer needs to handle scaling from one customer to thousands. It also describes various AWS services like EC2, EBS, S3, and Glacier for flexible and scalable infrastructure with no long term commitments.
Setup Kubernetes Cluster On AWS Using KOPSSivaprakash
This document provides steps to set up a Kubernetes cluster on AWS using KOPS. It describes installing required tools like kubectl and KOPS, creating an SSH key and Route53 host on AWS, generating a Kubernetes cluster across multiple Availability Zones, and exposing sample applications. Finally, it covers deleting the cluster.
Configuration Management with AWS OpsWorks for Chef AutomateAmazon Web Services
AWS OpsWorks for Chef Automate provides a fully managed Chef server and suite of automation tools that give you workflow automation for continuous deployment, automated testing for compliance and security, and a user interface that gives you visibility into your nodes and their status. The Chef server gives you full stack automation by handling operational tasks such as software and operating system configurations, package installations, database setups, and more. The Chef server centrally stores your configuration tasks and provides them to each node in your compute environment at any scale, from a few nodes to thousands of nodes. OpsWorks for Chef Automate is completely compatible with tooling and cookbooks from the Chef community and automatically registers new nodes with your Chef server.
1. The document discusses AWS services for container orchestration including EKS, Fargate, Docker Swarm, and Mesos. It also discusses using CloudFront and S3 for hosting static assets.
2. Details are provided on migrating from Docker Swarm to EKS on AWS, including using EC2 and Route53. Options for hosting databases like MySQL and PostgreSQL across regions are explored.
3. The benefits of services like EKS, Lambda, and CloudFront are summarized and pricing models for CloudFront are referenced. Moving infrastructure to different regions for latency or redundancy purposes is also briefly discussed.
Automating aws infrastructure and code deployments using Ansible @WebEngageVishal Uderani
In this talk , we’ll cover how and why Ansible was leveraged to automate routine management of EC2 instances/EBS/EIP/ELB etc and why the Ansible approach towards automation is key for code and system deployments across 100’s of nodes and how we achieved this at Webengage. We will provide an overview of the deployment process and give a demonstration as an example
Outlines :
How ansible is a straightforward , easy way to manage multiple cloud resources
Intended Audience :
Previous experience with configuration management systems
Previous experience with AWS and Ansible
This document discusses the history and future of operations (ops) and infrastructure management. It outlines how infrastructure has evolved from single manually configured servers to cloud-based infrastructure with immutable servers. Immutable infrastructure involves replacing servers instead of modifying them, using pre-built machine images. Tools like Packer, Vagrant, and Serf help enable immutable infrastructure by automating the creation of machine images and handling service orchestration outside of images. This approach provides benefits like speed, repeatability, stability and testability compared to traditional mutable infrastructure management.
Consolidate MySQL Shards Into Amazon Aurora Using AWS Database Migration Serv...Amazon Web Services
If you’re running a MySQL database at scale, there’s a good chance you’re sharding your database deployment. Sharding is a useful way to increase the scale of your deployment, but it has drawbacks like higher costs, high administration overheard and lower elasticity. It’s harder to grow or shrink a sharded database deployment to match your traffic patterns. In this session, we will discuss and demonstrate how to use AWS Database Migration Service to consolidate multiple MySQL shards into an Amazon Aurora cluster to reduce cost, improve elasticity and make it easier to manage your database.
Learning Objectives:
Learn how to scale your MySQL database at reduced cost and higher elasticity, by consolidating multiple shards into one Amazon Aurora cluster.
This document provides an overview of Docker, ECS, and how they can be used together on AWS. It defines Docker as application virtualization using containers that package code, runtime, and dependencies. ECS is AWS's container orchestration service that allows running Docker containers across a cluster, providing scheduling, networking, scaling, and reliability. The document outlines key aspects of using ECS including task definitions that specify container configurations, services that maintain a desired number of tasks, and load balancers for exposing applications. It also provides details on how ECS leverages underlying AWS resources and orchestrates tasks and services behind the scenes.
From HashiCorp Korea User Group Meetup
발표자: 김민규(데브시스터즈, 인프라 관리, https://github.com/synthdnb)
발표자: 김도윤(데브시스터즈, 플랫폼 API 서버 개발, https://github.com/solmonk)
발표내용: 팀의 규모가 커지면서 Secret 관리 문제가 조금씩 부각되었습니다. 예를 들면 코드에 커밋되거나, 구전으로 전해지는 Secret들, SSH Key Rotation 등의 문제를 처리하기 위해 많은 노력과 삽질이 필요했습니다. 저희 팀에서 Vault를 통해 이런 문제들을 어떻게 해결했는지 소개하려 합니다.
The talk describes how Yelp deploys Zipkin and integrates it with its 250+ services. It also goes through the challenges faced during scaling it up and how we tuned it up.
- Terraform allows infrastructure teams to more efficiently and agilely provision resources at scale across multiple production datacenters and regions.
- Key benefits include auto-scaling, self-service provisioning of services like Elasticsearch and Cassandra, and reducing new datacenter provisioning from over 12 months to just 2 months.
- Debugging and managing complex Terraform configurations, especially across modules, can currently be challenging due to limitations in Terraform's data handling and interpolation features.
Advanced Data Migration Techniques for Amazon RDS (DAT308) | AWS re:Invent 2013Amazon Web Services
Migrating data from the existing environments to AWS is a key part of the overall migration to Amazon RDS for most customers. Moving data into Amazon RDS from existing production systems in a reliable, synchronized manner with minimum downtime requires careful planning and the use of appropriate tools and technologies. Because each migration scenario is different, in terms of source and target systems, tools, and data sizes, you need to customize your data migration strategy to achieve the best outcome. In this session, we do a deep dive into various methods, tools, and technologies that you can put to use for a successful and timely data migration to Amazon RDS.
PostgreSQL is one of the most loved databases and that is why AWS could not hold back from offering PostgreSQL as RDS. There are some really nice features in RDS which can be good for DBA and inspiring for Enterprises to build resilient solution with PostgreSQL.
Amazon Aurora is a MySQL-compatible relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is disruptive technology in the database space, bringing a new architectural model and distributed systems techniques to provide far higher performance, availability and durability than previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
Return on Ignite 2019: Azure, .NET, A.I. & DataMSDEVMTL
Microsoft provides a global network for Azure including 54 Azure regions, 130k+ miles of fiber and subsea cables, 160+ edge sites, 500+ network partners, and 20k+ peering connections. Azure Arc allows organizations to manage and govern servers, Kubernetes applications, and data services across environments from a single Azure management plane. It enables extending Azure management capabilities to physical and virtual servers anywhere while still using native server management tools locally.
Amazon Aurora is a MySQL-compatible relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is disruptive technology in the database space, bringing a new architectural model and distributed systems techniques to provide far higher performance, availability, and durability than was previously available using conventional monolithic database techniques. In this session, we dive deep into some of the key innovations behind Amazon Aurora, discuss best practices and migration from other databases to Amazon Aurora, and share early customer experiences from the field.
This document discusses Contentful Engineering's migration from using AWS alone to using Kubernetes on AWS. Some key points:
1) Contentful migrated to take advantage of Kubernetes' focus on application delivery and open source development model over their previous Chef-based deployment platform.
2) They use Kops to manage Kubernetes clusters on AWS, deploying clusters in the same VPC and using kubenet networking and kube2iam to integrate with AWS services.
3) The migration process involved moving services to Kubernetes deployments and exposing them via LoadBalancer services, and updating service discovery in Route53.
4) Lessons learned include staying up to date with Kubernetes and Kops releases, customizing Kops outputs
Storage Is Not Virtualized Enough - part 1Zhipeng Huang
This document discusses storage function virtualization (SFV) and why storage is not yet virtualized enough. It provides an overview of SFV and how it can enhance NFV by virtualizing storage functions. It also discusses OpenStack SFV and related blueprints to improve storage scheduling and functionality. Finally, it encourages collaboration on SFV-related work beyond just OpenStack through various communication channels and open source projects.
How to use Ansible to automate your applications in AWS. What is Ansible and why is it different? How to control cloud deployments securely and how to control AWS resources using dynamic inventory and tags.
The document discusses scaling infrastructure using Amazon Web Services (AWS). It provides examples of how a vendor could programmatically spin up AWS instances and resources based on customer needs to handle scaling from one customer to thousands. It also describes various AWS services like EC2, EBS, S3, and Glacier for flexible and scalable infrastructure with no long term commitments.
Setup Kubernetes Cluster On AWS Using KOPSSivaprakash
This document provides steps to set up a Kubernetes cluster on AWS using KOPS. It describes installing required tools like kubectl and KOPS, creating an SSH key and Route53 host on AWS, generating a Kubernetes cluster across multiple Availability Zones, and exposing sample applications. Finally, it covers deleting the cluster.
Configuration Management with AWS OpsWorks for Chef AutomateAmazon Web Services
AWS OpsWorks for Chef Automate provides a fully managed Chef server and suite of automation tools that give you workflow automation for continuous deployment, automated testing for compliance and security, and a user interface that gives you visibility into your nodes and their status. The Chef server gives you full stack automation by handling operational tasks such as software and operating system configurations, package installations, database setups, and more. The Chef server centrally stores your configuration tasks and provides them to each node in your compute environment at any scale, from a few nodes to thousands of nodes. OpsWorks for Chef Automate is completely compatible with tooling and cookbooks from the Chef community and automatically registers new nodes with your Chef server.
1. The document discusses AWS services for container orchestration including EKS, Fargate, Docker Swarm, and Mesos. It also discusses using CloudFront and S3 for hosting static assets.
2. Details are provided on migrating from Docker Swarm to EKS on AWS, including using EC2 and Route53. Options for hosting databases like MySQL and PostgreSQL across regions are explored.
3. The benefits of services like EKS, Lambda, and CloudFront are summarized and pricing models for CloudFront are referenced. Moving infrastructure to different regions for latency or redundancy purposes is also briefly discussed.
Automating aws infrastructure and code deployments using Ansible @WebEngageVishal Uderani
In this talk , we’ll cover how and why Ansible was leveraged to automate routine management of EC2 instances/EBS/EIP/ELB etc and why the Ansible approach towards automation is key for code and system deployments across 100’s of nodes and how we achieved this at Webengage. We will provide an overview of the deployment process and give a demonstration as an example
Outlines :
How ansible is a straightforward , easy way to manage multiple cloud resources
Intended Audience :
Previous experience with configuration management systems
Previous experience with AWS and Ansible
This document discusses the history and future of operations (ops) and infrastructure management. It outlines how infrastructure has evolved from single manually configured servers to cloud-based infrastructure with immutable servers. Immutable infrastructure involves replacing servers instead of modifying them, using pre-built machine images. Tools like Packer, Vagrant, and Serf help enable immutable infrastructure by automating the creation of machine images and handling service orchestration outside of images. This approach provides benefits like speed, repeatability, stability and testability compared to traditional mutable infrastructure management.
Consolidate MySQL Shards Into Amazon Aurora Using AWS Database Migration Serv...Amazon Web Services
If you’re running a MySQL database at scale, there’s a good chance you’re sharding your database deployment. Sharding is a useful way to increase the scale of your deployment, but it has drawbacks like higher costs, high administration overheard and lower elasticity. It’s harder to grow or shrink a sharded database deployment to match your traffic patterns. In this session, we will discuss and demonstrate how to use AWS Database Migration Service to consolidate multiple MySQL shards into an Amazon Aurora cluster to reduce cost, improve elasticity and make it easier to manage your database.
Learning Objectives:
Learn how to scale your MySQL database at reduced cost and higher elasticity, by consolidating multiple shards into one Amazon Aurora cluster.
This document provides an overview of Docker, ECS, and how they can be used together on AWS. It defines Docker as application virtualization using containers that package code, runtime, and dependencies. ECS is AWS's container orchestration service that allows running Docker containers across a cluster, providing scheduling, networking, scaling, and reliability. The document outlines key aspects of using ECS including task definitions that specify container configurations, services that maintain a desired number of tasks, and load balancers for exposing applications. It also provides details on how ECS leverages underlying AWS resources and orchestrates tasks and services behind the scenes.
From HashiCorp Korea User Group Meetup
발표자: 김민규(데브시스터즈, 인프라 관리, https://github.com/synthdnb)
발표자: 김도윤(데브시스터즈, 플랫폼 API 서버 개발, https://github.com/solmonk)
발표내용: 팀의 규모가 커지면서 Secret 관리 문제가 조금씩 부각되었습니다. 예를 들면 코드에 커밋되거나, 구전으로 전해지는 Secret들, SSH Key Rotation 등의 문제를 처리하기 위해 많은 노력과 삽질이 필요했습니다. 저희 팀에서 Vault를 통해 이런 문제들을 어떻게 해결했는지 소개하려 합니다.
The talk describes how Yelp deploys Zipkin and integrates it with its 250+ services. It also goes through the challenges faced during scaling it up and how we tuned it up.
- Terraform allows infrastructure teams to more efficiently and agilely provision resources at scale across multiple production datacenters and regions.
- Key benefits include auto-scaling, self-service provisioning of services like Elasticsearch and Cassandra, and reducing new datacenter provisioning from over 12 months to just 2 months.
- Debugging and managing complex Terraform configurations, especially across modules, can currently be challenging due to limitations in Terraform's data handling and interpolation features.
Advanced Data Migration Techniques for Amazon RDS (DAT308) | AWS re:Invent 2013Amazon Web Services
Migrating data from the existing environments to AWS is a key part of the overall migration to Amazon RDS for most customers. Moving data into Amazon RDS from existing production systems in a reliable, synchronized manner with minimum downtime requires careful planning and the use of appropriate tools and technologies. Because each migration scenario is different, in terms of source and target systems, tools, and data sizes, you need to customize your data migration strategy to achieve the best outcome. In this session, we do a deep dive into various methods, tools, and technologies that you can put to use for a successful and timely data migration to Amazon RDS.
PostgreSQL is one of the most loved databases and that is why AWS could not hold back from offering PostgreSQL as RDS. There are some really nice features in RDS which can be good for DBA and inspiring for Enterprises to build resilient solution with PostgreSQL.
Amazon Aurora is a MySQL-compatible relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is disruptive technology in the database space, bringing a new architectural model and distributed systems techniques to provide far higher performance, availability and durability than previously available using conventional monolithic database techniques. In this session, we will do a deep-dive into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
Return on Ignite 2019: Azure, .NET, A.I. & DataMSDEVMTL
Microsoft provides a global network for Azure including 54 Azure regions, 130k+ miles of fiber and subsea cables, 160+ edge sites, 500+ network partners, and 20k+ peering connections. Azure Arc allows organizations to manage and govern servers, Kubernetes applications, and data services across environments from a single Azure management plane. It enables extending Azure management capabilities to physical and virtual servers anywhere while still using native server management tools locally.
Amazon Aurora is a MySQL-compatible relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is disruptive technology in the database space, bringing a new architectural model and distributed systems techniques to provide far higher performance, availability, and durability than was previously available using conventional monolithic database techniques. In this session, we dive deep into some of the key innovations behind Amazon Aurora, discuss best practices and migration from other databases to Amazon Aurora, and share early customer experiences from the field.
This document provides an overview of IBM's Bluemix DBaaS SQL Database service. It offers a fully managed SQL database service powered by DB2. The service provides automatic backups, high availability, data encryption and masking capabilities. It also integrates with other Bluemix services like DataWorks, Cloudant and dashDB and provides sensitive data reporting capabilities suitable for PCI audits.
An Irish electrical service company, Avonmore Electrical, partnered with a Turkish coil manufacturer, Coil Partners, to refurbish a wind turbine generator made by a Swiss manufacturer for a wind farm in Scotland. Avonmore was looking to enter the wind energy market and found Coil Partners through their membership in the European Association of Electrical Services. Coil Partners could provide high quality coils at a lower cost due to their operations in Turkey. Avonmore and Coil Partners worked through cultural and logistical challenges to successfully complete the refurbishment project, and hope to continue their partnership to expand into new markets.
The document discusses building a healthier burger option by finding alternatives to the existing bun and cheese that contain fewer calories, fat, and carbohydrates. It shows that switching to an alternative bun that has 140 calories, 2g of fat, and 27g of carbohydrates compared to 260 calories, 5g of fat, and 45g of carbohydrates in the original bun. Similarly, an alternative cheese with 70 calories, 4g of fat and 1g of carbohydrates rather than 125 calories, 9g of fat and 1g of carbohydrates in the original cheese allows the new burger to have fewer total calories at 410 compared to 585 in the original, and less total fat and carbohydrates.
Vijay Kumar Digoria is seeking a career opportunity. He has over 10 years of experience working in electronics and telecommunications as a service engineer for Amara Raja Batteries and as a technical assistant for Rajasthan Electronics. He holds a Diploma in Electronics and Telecommunication Engineering and a B.A. degree. His skills include computer literacy, teamwork, leadership, and he has strong technical abilities in equipment maintenance, repair, and project experience with power electronics.
The document discusses how the film opening challenges and develops conventions of real media products in the drama genre. It uses techniques like natural lighting, relatable settings, realistic costumes, and close-up shots of the main character to draw in the target teenage audience. While most drama films use continuity editing and stable shots, this opening challenges conventions with cross-fades, handheld shots, and unfocused images to convey the feeling that the character is "slipping away." It also includes a voiceover and slow, sad music to set the reflective mood.
The document discusses the organizational structure of the University of Cambridge in the United Kingdom. It is divided into six schools - Arts and Humanities, Biological Sciences, Clinical Medicine, Humanities and Social Sciences, Physical Sciences, and Technology - which group related faculties and units together. Some famous historical figures who studied at Cambridge include Isaac Newton, Lord Byron, and Charles Darwin, and the great Russian scientist Ivan Pavlov received a toy dog as a gift from students during his time working there.
This document appears to be a product catalog listing various styles of printed fabrics including the names Flower Fista, High Chic, and Lattice followed by descriptions of the print and stripe options for each style. The listings include style names, color options, and item numbers ranging from 10 to 60.
Jacob P. Voyles is a United States Marine with 5 years of experience who has expertise leading security teams and managing operations. He has supervised training and equipment for over 960 Marines. Voyles also has experience leading security teams to prevent tampering with nuclear weapons and conducting patrols and operations involving nuclear weapons. He has various qualifications, certifications, and a secret security clearance.
This presentation captures the screenshot of hybrid DevOps which automates deployment of OSGI application to (1) on-premise build-verification-test environment running WebSphere Liberty profile, and then (2) promote to cloud-based Bluemix environment
The document provides a list of 9 items that should not be posted online for privacy and safety reasons. It cautions against posting photos, one's schedule, gossip about others, details about get-togethers, one's school, address, phone number, birthday, or sharing one's current location. Examples are given of how oversharing personal information online could enable identity theft, cyberbullying or unwanted contact from strangers.
[Lucas Films] Using a Perforce Proxy with Alternate TransportsPerforce
The document discusses using a Perforce proxy with an alternate transport like UDP to overcome high latency or low bandwidth networks between global sites. It describes how a Perforce proxy caches files to improve transfer speeds but is traditionally limited by TCP/IP. The author details using Aspera Sync to mirror the Perforce server to the proxy at much higher speeds of 20-25 MB/s over UDP, improving a 1GB file transfer from 4 hours to just minutes. This solution leverages the stateless nature of the proxy and removes the dependence on TCP/IP for large data sharing between remote offices.
White Paper: Scaling Servers and Storage for Film AssetsPerforce
Pixar's use of Perforce grew from one server with one code depot to over 90 servers storing all types of assets across multiple depots. They had to address scaling issues related to server architecture, storage growth, and monitoring as their infrastructure and data increased. Some techniques used to manage this growth included using file type specifications to automatically purge generated data, migrating unnecessary data out of Perforce, de-duplicating files, running servers virtually, and administering servers across multiple depots using a "superp4" script.
Deploying Apache Flume to enable low-latency analyticsDataWorks Summit
The driving question behind redesigns of countless data collection architectures has often been, ?how can we make the data available to our analytical systems faster?? Increasingly, the go-to solution for this data collection problem is Apache Flume. In this talk, architectures and techniques for designing a low-latency Flume-based data collection and delivery system to enable Hadoop-based analytics are explored. Techniques for getting the data into Flume, getting the data onto HDFS and HBase, and making the data available as quickly as possible are discussed. Best practices for scaling up collection, addressing de-duplication, and utilizing a combination streaming/batch model are described in the context of Flume and Hadoop ecosystem components.
Aspera on demand for AWS (S3 inc) overviewBhavik Vyas
Aspera provides high-speed file transfer software and technologies. According to the document:
- Aspera was founded in 2004 and is headquartered in Emeryville, CA. It has 95 employees and over 1,200 customers.
- Aspera's core technology is the fasp protocol, which uses innovative techniques to maximize transfer speeds over any network distance or conditions. It outperforms other transfer methods.
- When transferring data over long distances, TCP performance degrades significantly but fasp transfers maintain high speeds. This makes it crucial for applications involving "Big Data" transfers.
- The document discusses running Hive/Spark on S3 object storage using S3A committers and running HBase on NFS file storage instead of HDFS. This separates compute and storage and avoids HDFS operations and complexity. S3A committers allow fast, atomic writes to S3 without renaming files. Benchmark results show the magic committer is faster than the file committer for S3 writes. HBase performance tests show FlashBlade NFS providing low latency for random reads/writes compared to Amazon EFS.
Delivering on the promise of the cloud for digital media, aspera on demandAmazon Web Services
Aspera's software portfolio includes products for distributing large digital files at high speeds, collaborating on file sharing and exchanges, and automating workflows. Key products are the Enterprise Server for file transfers, faspex for secure collaboration, and Orchestrator for designing and managing automated workflows. Aspera's patented fasp transport technology provides fast, reliable data delivery over any network conditions.
From limited Hadoop compute capacity to increased data scientist efficiencyAlluxio, Inc.
Alluxio Tech Talk
Oct 17, 2019
Speaker:
Alex Ma, Alluxio
Want to leverage your existing investments in Hadoop with your data on-premise and still benefit from the elasticity of the cloud?
Like other Hadoop users, you most likely experience very large and busy Hadoop clusters, particularly when it comes to compute capacity. Bursting HDFS data to the cloud can bring challenges – network latency impacts performance, copying data via DistCP means maintaining duplicate data, and you may have to make application changes to accomodate the use of S3.
“Zero-copy” hybrid bursting with Alluxio keeps your data on-prem and syncs data to compute in the cloud so you can expand compute capacity, particularly for ephemeral Spark jobs.
Data Orchestration Platform for the CloudAlluxio, Inc.
This document discusses using a hybrid cloud approach with data orchestration to enable analytics workloads on data stored both on-premises and in the cloud. It outlines reasons for a hybrid approach including reducing time to production and leveraging cloud flexibility. It then describes alternatives like lift-and-shift or compute-driven approaches and their issues. Finally, it introduces a data orchestration platform that can cache and tier data intelligently while enabling analytics frameworks to access both on-premises and cloud-based data with low latency.
This document provides an introduction to Apache Kafka. It begins with an overview of Kafka as a distributed messaging system that is real-time, scalable, low latency, and fault tolerant. It then covers key concepts such as topics, partitions, producers, consumers, and replication. The document explains how Kafka achieves fast reads and writes through its design and use of disk flushing and replication for durability. It also discusses how Kafka can be used to build real-time systems and provides examples like connected cars. Finally, it introduces Apache Metron as an example of a cyber security solution built on Kafka.
Accelerating Analytics with EMR on your S3 Data LakeAlluxio, Inc.
- Alluxio provides a data caching layer for analytics frameworks like Spark running on AWS EMR, addressing challenges of using S3 directly like inconsistent performance and expensive metadata operations.
- It mounts S3 as a unified filesystem and caches frequently used data in memory across workers for faster queries while continuously syncing data to S3.
- Alluxio's multi-tier storage enables data to be accessed locally from remote locations like S3 using intelligent policies to promote and demote data between memory, SSDs and disks.
Using FLiP with InfluxDB for EdgeAI IoT at Scale 2022Timothy Spann
Using FLiP with InfluxDB for EdgeAI IoT at Scale 2022
https://adtmag.com/webcasts/2021/12/influxdata-february-10.aspx?tc=page0
Using FLiP with InfluxDB for EdgeAI IoT at Scale
Date: Thursday, February 10th at 11am PT / 2pm ET
Join this webcast as Timothy from StreamNative takes you on a hands-on deep-dive using Pulsar, Apache NiFi + Edge Flow Manager + MiniFi Agents with Apache MXNet, OpenVino, TensorFlow Lite, and other Deep Learning Libraries on the actual edge devices including Raspberry Pi with Movidius 2, Google Coral TPU and NVidia Jetson Nano.
The team runs deep learning models on the edge devices, sends images, and captures real-time GPS and sensor data. Their low-coding IoT applications provide easy edge routing, transformation, data acquisition and alerting before they decide what data to stream in real-time to their data space. These edge applications classify images and sensor readings in real-time at the edge and then send Deep Learning results to Flink SQL and Apache NiFi for transformation, parsing, enrichment, querying, filtering and merging data to InfluxDB.
In this session you will learn how to:
Build an end-to-end streaming edge app
Pull messages from Pulsar topics and persists the messages to InfluxDB
Build a data stream for IoT with NiFi and InfluxDB
Use Apache Flink + Apache Pulsar
Timothy Spann, Developer Advocate, StreamNative
Tim Spann is a Developer Advocate at StreamNative where he works with Apache NiFi, MiniFi, Kafka, Apache Flink, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a senior solutions architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
Using FLiP with influxdb for edgeai iot at scale 2022Timothy Spann
https://adtmag.com/webcasts/2021/12/influxdata-february-10.aspx?tc=page0
FLiP Stack (Apache Flink, Apache Pulsar, Apache NiFi, Apache Spark) with Influx DB for Edge AI and IoT workloads at scale
Tim Spann
Developer Advocate
StreamNative
datainmotion.dev
OSS EU: Deep Dive into Building Streaming Applications with Apache PulsarTimothy Spann
OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. If there’s a preferred language that the attendees pick, we will focus only on that one. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics. We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript. After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
apache pulsar
This document provides an overview of Hadoop and related Apache projects. It begins with an introduction to Hadoop, explaining why it was created and who uses it. It then discusses HDFS and its goals of storing huge datasets across commodity hardware. Key components of HDFS like the NameNode, DataNodes and block placement are explained. The document also covers MapReduce and provides a word count example. Finally, it briefly introduces related Apache projects like Pig, HBase and Hive that build upon Hadoop.
This document provides an overview of Hadoop and related Apache projects. It begins with an introduction to Hadoop, explaining why it was created and who uses it. It then discusses HDFS and its goals, architecture, and functions. Next, it covers MapReduce, providing examples and explaining features like locality optimizations. Finally, it briefly introduces related subprojects like Pig, HBase, Hive, and Zookeeper that build upon Hadoop.
This document provides an overview of Hadoop and related Apache projects. It begins with an introduction to Hadoop, explaining why it was created and who uses it. It then discusses HDFS and its goals of storing huge datasets across commodity hardware. Key components of HDFS like the NameNode, DataNodes and block placement are described. The document also covers MapReduce and provides an example word count algorithm. Finally, it briefly introduces related Apache projects like Pig, HBase, Hive and Zookeeper that build upon Hadoop.
Dancing Elephants - Efficiently Working with Object Stores from Apache Spark ...DataWorks Summit
This document discusses challenges and solutions for using object storage with Apache Spark and Hive. It covers:
- Eventual consistency issues in object storage and lack of atomic operations
- Improving performance of object storage connectors through caching, optimized metadata operations, and consistency guarantees
- Techniques like S3Guard and committers that address consistency and correctness problems with output commits in object storage
This document discusses accelerating Spark workloads on Amazon S3 using Alluxio. It describes the challenges of running Spark interactively on S3 due to its eventual consistency and expensive metadata operations. Alluxio provides a data caching layer that offers strong consistency, faster performance, and API compatibility with HDFS and S3. It also allows data outside of S3 to be analyzed. The document demonstrates how to bootstrap Alluxio on an AWS EMR cluster to accelerate Spark workloads running on S3.
Hopsworks - The Platform for Data-Intensive AIQAware GmbH
Hopsworks is a platform for data-intensive AI projects that provides:
1. End-to-end machine learning pipelines from data ingestion to model serving.
2. A feature store for organizing machine learning data.
3. Distributed deep learning using multiple GPUs for faster training.
The document discusses Hadoop integration with cloud storage. It describes the Hadoop-compatible file system architecture, which allows applications to work with different storage systems transparently. Recent enhancements to the S3A connector for Amazon S3 are discussed, including performance improvements and support for encryption. Benchmark results show significant performance gains for Hive queries running on S3A compared to earlier versions. Upcoming work on consistency, output committers, and abstraction layers is outlined to further improve object store integration.
This describes the two-speed delivery issue of enterprise mobility. It explains the flow of delivery stages for IBM MobileFirst, to implement the DevOps.
This is part 1 (of 3 series). The coming part 2 & 3 will explain the DevOps for differnt mobile app patterns.
Mobile-first development prioritizes building applications for mobile devices first before desktop. Mobile backend as a service (MBaaS) provides SDKs, APIs and services to develop mobile apps. It allows for loosely coupled distributed architectures with cloud hosting. Common tasks with MBaaS include defining RESTful APIs, configuring push notifications, performing testing and security scans.
The document discusses adopting a mobile-first strategy for enterprise mobility. It recommends the IBM MobileFirst Platform as a mobile backend that is suited for quick development using open standards and supports both building and buying mobile apps. It also lists 15 factors for customers to consider in the build vs buy decision for their mobile applications.
Introduction to IBM Bluemix Presence Insight - cloud-based location-based service, for retailers, airport, or hospital, etc. This backend engine to process the sensor, or beacon data, for event (entry, exit, dwell) detection, and integrate backend application (e.g. CRM)
UrbanCode Deploy is a web application that automates application deployment to address congestion problems. It manages the full application delivery process, including installing executables, migrating data, deploying vendor applications and middleware, and promoting applications across environments from development to production. UrbanCode Deploy provides a tamper-proof artifact repository for versioned application binaries and configurations to enable automated, repeatable deployments with zero downtime using techniques like blue-green deployment.
DevOps is an approach to speed up application delivery through automation. It involves continuous integration, deployment automation, and test automation. Continuous integration involves frequent builds and automated unit testing. Deployment automation enables fast, reliable, and continuous deployment to servers. Test automation includes unit, smoke, integration, UI, static code analysis, and security testing. DevOps principles include fast failure, continuous delivery, automated and repeatable processes, building once, keeping deployed binaries and versioning, and separating development and operations duties. The DevOps toolchain manages software configuration, application deployment, builds, packaging, delta deployment, zero-downtime deployment, rollbacks, cleanups, and is maintained by operations.
Bluemix MBasS provides a mobile backend as a service platform that can save developers time and money compared to building their own backend infrastructure from scratch. It offers various services including a NoSQL database, push notifications, user authentication, security, and tools for testing, analytics and improving app quality. These services allow for loosely coupled and distributed mobile app architectures without needing to deal with complex middleware configurations and implementations.
Bluemix is an IBM platform that allows users to quickly build and deploy applications using various open source technologies like Java, JavaScript, Ruby, PHP, and Python. It provides a platform-as-a-service model that saves time and money by eliminating the need to install middleware, operating systems, or infrastructure. Users can extend their applications functionality by integrating various IBM services around areas like Watson, mobile, DevOps, data, cloud integration, big data, security, and IoT. Bluemix also provides auto-scaling capabilities and tools to help with the full software development lifecycle.
8 Best Automated Android App Testing Tool and Framework in 2024.pdfkalichargn70th171
Regarding mobile operating systems, two major players dominate our thoughts: Android and iPhone. With Android leading the market, software development companies are focused on delivering apps compatible with this OS. Ensuring an app's functionality across various Android devices, OS versions, and hardware specifications is critical, making Android app testing essential.
SMS API Integration in Saudi Arabia| Best SMS API ServiceYara Milbes
Discover the benefits and implementation of SMS API integration in the UAE and Middle East. This comprehensive guide covers the importance of SMS messaging APIs, the advantages of bulk SMS APIs, and real-world case studies. Learn how CEQUENS, a leader in communication solutions, can help your business enhance customer engagement and streamline operations with innovative CPaaS, reliable SMS APIs, and omnichannel solutions, including WhatsApp Business. Perfect for businesses seeking to optimize their communication strategies in the digital age.
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdfVALiNTRY360
Salesforce Healthcare CRM, implemented by VALiNTRY360, revolutionizes patient management by enhancing patient engagement, streamlining administrative processes, and improving care coordination. Its advanced analytics, robust security, and seamless integration with telehealth services ensure that healthcare providers can deliver personalized, efficient, and secure patient care. By automating routine tasks and providing actionable insights, Salesforce Healthcare CRM enables healthcare providers to focus on delivering high-quality care, leading to better patient outcomes and higher satisfaction. VALiNTRY360's expertise ensures a tailored solution that meets the unique needs of any healthcare practice, from small clinics to large hospital systems.
For more info visit us https://valintry360.com/solutions/health-life-sciences
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
Most important New features of Oracle 23c for DBAs and Developers. You can get more idea from my youtube channel video from https://youtu.be/XvL5WtaC20A
Unveiling the Advantages of Agile Software Development.pdfbrainerhub1
Learn about Agile Software Development's advantages. Simplify your workflow to spur quicker innovation. Jump right in! We have also discussed the advantages.
UI5con 2024 - Keynote: Latest News about UI5 and it’s EcosystemPeter Muessig
Learn about the latest innovations in and around OpenUI5/SAPUI5: UI5 Tooling, UI5 linter, UI5 Web Components, Web Components Integration, UI5 2.x, UI5 GenAI.
Recording:
https://www.youtube.com/live/MSdGLG2zLy8?si=INxBHTqkwHhxV5Ta&t=0
Artificia Intellicence and XPath Extension FunctionsOctavian Nadolu
The purpose of this presentation is to provide an overview of how you can use AI from XSLT, XQuery, Schematron, or XML Refactoring operations, the potential benefits of using AI, and some of the challenges we face.
E-commerce Development Services- Hornet DynamicsHornet Dynamics
For any business hoping to succeed in the digital age, having a strong online presence is crucial. We offer Ecommerce Development Services that are customized according to your business requirements and client preferences, enabling you to create a dynamic, safe, and user-friendly online store.
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
Zoom is a comprehensive platform designed to connect individuals and teams efficiently. With its user-friendly interface and powerful features, Zoom has become a go-to solution for virtual communication and collaboration. It offers a range of tools, including virtual meetings, team chat, VoIP phone systems, online whiteboards, and AI companions, to streamline workflows and enhance productivity.
SOCRadar's Aviation Industry Q1 Incident Report is out now!
The aviation industry has always been a prime target for cybercriminals due to its critical infrastructure and high stakes. In the first quarter of 2024, the sector faced an alarming surge in cybersecurity threats, revealing its vulnerabilities and the relentless sophistication of cyber attackers.
SOCRadar’s Aviation Industry, Quarterly Incident Report, provides an in-depth analysis of these threats, detected and examined through our extensive monitoring of hacker forums, Telegram channels, and dark web platforms.
WWDC 2024 Keynote Review: For CocoaCoders AustinPatrick Weigel
Overview of WWDC 2024 Keynote Address.
Covers: Apple Intelligence, iOS18, macOS Sequoia, iPadOS, watchOS, visionOS, and Apple TV+.
Understandable dialogue on Apple TV+
On-device app controlling AI.
Access to ChatGPT with a guest appearance by Chief Data Thief Sam Altman!
App Locking! iPhone Mirroring! And a Calculator!!
Hand Rolled Applicative User ValidationCode KataPhilip Schwarz
Could you use a simple piece of Scala validation code (granted, a very simplistic one too!) that you can rewrite, now and again, to refresh your basic understanding of Applicative operators <*>, <*, *>?
The goal is not to write perfect code showcasing validation, but rather, to provide a small, rough-and ready exercise to reinforce your muscle-memory.
Despite its grandiose-sounding title, this deck consists of just three slides showing the Scala 3 code to be rewritten whenever the details of the operators begin to fade away.
The code is my rough and ready translation of a Haskell user-validation program found in a book called Finding Success (and Failure) in Haskell - Fall in love with applicative functors.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
11. ##Reasons for Aspera
-Fast & secure
-Best utilization of bandwidth
-Handle unreliable/high latency
network
-Handle large single file
-Handle many, small-files
-SDK
12. ##Reference: FIFA
World Cup 2014
-Near ‘zero deplay’ video
experience
-Live broadcast for 24
different camera angles
-Streamed live for
simultaneous matches
-Delivered to multiple
devices and format
And that’s where C-Cast, the product I’m responsible for, brings all its benefits.
Just think about being in front of your television, watching your favorite team.
You have your tablet in your hands, and between 1 and 2 minutes after an event occured, a new item appears in the list, with the ability to make your own replays from, in this case, up to 24 camera angles
I like this example… for once our small country can beat the United States of America