Understanding InfluxDB Basics: Tags, Fields and MeasurementsInfluxData
Is it a table? No, it is much more! Finally understand tags, fields and measurements.
In this session, you will learn how to answer your real-life questions with data stored in InfluxDB. You will see that InfluxDB is more than some tables; it is a window to the world of your data. In particular, the usage of tags, fields and measurements enhances the time series database and helps answer your questions in a convenient and fast way, if you know what to do. Discover tips and tricks to use while implementing InfluxDB.
All topics are addressed in the context of IoT monitoring, predictive maintenance and medical applications.
Learn how ScyllaDB Cloud is moving to serverless, transforming its single tenant deployment model into a multi-tenant architecture based on Kubernetes. Discover the engineering innovation required, and the user value of the new architecture, including use of encryption (both at flight and at rest), performance isolation, and the capability to scale elastically.
How netflix manages petabyte scale apache cassandra in the cloudVinay Kumar Chella
At Netflix, we manage petabytes of data in Apache Cassandra which must be reliably accessible to users in mere milliseconds. To achieve this, we have built sophisticated control planes that turn our persistence layer based on Apache Cassandra into a truly self-driving system. We will start with the user interface that Netflix developers use to interact with their Cassandra databases and dive deep into the automation that powers it all. From cluster creation, through scaling up, to cluster death, complex automation drives large fleets of virtual machines hosted on the AWS cloud. First, we will cover the basics of how Netflix deploys Apache Cassandra. In particular, this begins with how we mold Apache Cassandra to the Netflix philosophy of immutable infrastructure, including managing software and hardware upgrades in the face of ever-failing hardware. Then we will explore the concrete techniques needed for such a massive deployment, specifically pull-based control planes and auto-healing strategies. Next, we will cover how Netflix has automated complex but critical Apache Cassandra maintenance tasks such as continuous snapshot backups and always-on anti-entropy repair for keeping our datasets safe and consistent. Both of these systems have gone through multiple architectural evolutions, and we have learned many lessons along the way. Lastly, we will share some of the ways this has gone wrong, and what you can do to avoid them. We will cover a few case studies of major Cassandra outages at Netflix, their root cause, and what we learned from those incidents. At the end of this talk, we hope that participants leave with concrete understanding of the challenges in running massive scale Apache Cassandra as well as solid advice and techniques for building their own self-driving data persistence layer.
Cloud computing gives you a number of advantages, such as being able to scale your application on demand. As a new business looking to use the cloud, you inevitably ask yourself, "Where do I start?" Join us in this session to understand best practices for scaling your resources from zero to millions of users. We will show you how to best combine different AWS services, make smarter decisions for architecting your application, and best practices for scaling your infrastructure in the cloud.
Understanding InfluxDB Basics: Tags, Fields and MeasurementsInfluxData
Is it a table? No, it is much more! Finally understand tags, fields and measurements.
In this session, you will learn how to answer your real-life questions with data stored in InfluxDB. You will see that InfluxDB is more than some tables; it is a window to the world of your data. In particular, the usage of tags, fields and measurements enhances the time series database and helps answer your questions in a convenient and fast way, if you know what to do. Discover tips and tricks to use while implementing InfluxDB.
All topics are addressed in the context of IoT monitoring, predictive maintenance and medical applications.
Learn how ScyllaDB Cloud is moving to serverless, transforming its single tenant deployment model into a multi-tenant architecture based on Kubernetes. Discover the engineering innovation required, and the user value of the new architecture, including use of encryption (both at flight and at rest), performance isolation, and the capability to scale elastically.
How netflix manages petabyte scale apache cassandra in the cloudVinay Kumar Chella
At Netflix, we manage petabytes of data in Apache Cassandra which must be reliably accessible to users in mere milliseconds. To achieve this, we have built sophisticated control planes that turn our persistence layer based on Apache Cassandra into a truly self-driving system. We will start with the user interface that Netflix developers use to interact with their Cassandra databases and dive deep into the automation that powers it all. From cluster creation, through scaling up, to cluster death, complex automation drives large fleets of virtual machines hosted on the AWS cloud. First, we will cover the basics of how Netflix deploys Apache Cassandra. In particular, this begins with how we mold Apache Cassandra to the Netflix philosophy of immutable infrastructure, including managing software and hardware upgrades in the face of ever-failing hardware. Then we will explore the concrete techniques needed for such a massive deployment, specifically pull-based control planes and auto-healing strategies. Next, we will cover how Netflix has automated complex but critical Apache Cassandra maintenance tasks such as continuous snapshot backups and always-on anti-entropy repair for keeping our datasets safe and consistent. Both of these systems have gone through multiple architectural evolutions, and we have learned many lessons along the way. Lastly, we will share some of the ways this has gone wrong, and what you can do to avoid them. We will cover a few case studies of major Cassandra outages at Netflix, their root cause, and what we learned from those incidents. At the end of this talk, we hope that participants leave with concrete understanding of the challenges in running massive scale Apache Cassandra as well as solid advice and techniques for building their own self-driving data persistence layer.
Cloud computing gives you a number of advantages, such as being able to scale your application on demand. As a new business looking to use the cloud, you inevitably ask yourself, "Where do I start?" Join us in this session to understand best practices for scaling your resources from zero to millions of users. We will show you how to best combine different AWS services, make smarter decisions for architecting your application, and best practices for scaling your infrastructure in the cloud.
CI/CD Pipeline Security: Advanced Continuous Delivery Best Practices: Securit...Amazon Web Services
CI/CD Pipeline Security: Advanced Continuous Delivery Best Practices: Security Week at the San Francisco Loft
Continuous delivery (CD) enables teams to be more agile and quickens the pace of innovation. Too often, however, teams adopt CD without putting the right safety mechanisms in place. In this talk, we discuss opportunities for you to transform your software release process into a safer one. We explore various DevOps best practices, showcasing sample applications and code with AWS CodePipeline and AWS CodeDeploy. We discuss how to set up delivery pipelines with nonproduction testing stages, failure cases, rollbacks, redundancy, canary testing and blue/green deployments, and monitoring. We'll discuss continuous delivery practices for deploying to Amazon EC2, AWS Lambda, and Containers (such as Amazon ECS or AWS Fargate).
Level: 200
Speaker: Leo Zhadanovsky - Principal Solutions Architect, Cloudstart, AWS
In this session we’ll take a high-level overview of AWS Lambda, a serverless compute platform that has changed the way that developers around the world build applications. We’ll explore how Lambda works under the hood, the capabilities it has, and how it is used. By the end of this talk you’ll know how to create Lambda based applications and deploy and manage them easily.
Speaker: Chris Munns - Principal Developer Advocate, AWS Serverless Applications, AWS
Apache Hadoop and Spark on AWS: Getting started with Amazon EMR - Pop-up Loft...Amazon Web Services
Amazon EMR is a managed service that makes it easy for customers to use big data frameworks and applications like Apache Hadoop, Spark, and Presto to analyze data stored in HDFS or on Amazon S3, Amazon’s highly scalable object storage service. In this session, we will introduce Amazon EMR and the greater Apache Hadoop ecosystem, and show how customers use them to implement and scale common big data use cases such as batch analytics, real-time data processing, interactive data science, and more. Then, we will walk through a demo to show how you can start processing your data at scale within minutes.
Casandra is a open-source, distributed, highly scalable and fault-tolerant database. It is a best choice for managing structured, semi-structured or unstructured data at a large amount.
Model serving made easy using Kedro pipelines - Mariusz Strzelecki, GetInDataGetInData
If you want to stay up to date, subscribe to our newsletter here: https://bit.ly/3tiw1I8
Presentation from the performance given by Mariusz during the Data Science Summit ML Edition.
Author: Mariusz Strzelecki
Linkedin: https://www.linkedin.com/in/mariusz-strzelecki/
___
Company:
Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets.
Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries.
https://getindata.com
Luigi Brochard from Lenovo presented this deck at the Switzerland HPC Conference.
"Lenovo has developed an open source HPC software stack for system management with GUI support. This enables customers to more efficiently manage their clusters by making it simple and easy for both the system administrator and end users.This talk will present this initiative, show a demo and present future evolutions."
Watch the video presentation:
https://www.youtube.com/watch?v=xqwLul_hA28
See more talks in the Swiss Conference Video Gallery: http://insidehpc.com/2016-swiss-hpc-conference/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Auto scaling using Amazon Web Services ( AWS )Harish Ganesan
In this article i would like to share some of the insights on AWS Auto Scaling in following perspectives:
• Need for Auto Scaling
• How AWS Auto scaling can help to handle the various load volatility scenarios
• How to configure an Auto scaling policy in AWS
• Things to remember before Scaling out and down
• Understand the intricacies while integrating Auto scaling with other Amazon Web Services
• Risks involved in AWS Auto scaling
Presented at #H2OWorld 2017 in Mountain View, CA.
Enjoy the video: https://youtu.be/42Oo8TOl85I.
Learn more about H2O.ai: https://www.h2o.ai/.
Follow @h2oai: https://twitter.com/h2oai.
- - -
Abstract:
In recent years, the demand for machine learning experts has outpaced the supply, despite the surge of people entering the field. To address this gap, there have been big strides in the development of user-friendly machine learning software that can be used by non-experts. Although H2O has made it easier for practitioners to train and deploy machine learning models at scale, there is still a fair bit of knowledge and background in data science that is required to produce high-performing machine learning models. Deep Neural Networks in particular, are notoriously difficult for a non-expert to tune properly. In this presentation, we provide an overview of the field of "Automatic Machine Learning" and introduce the new AutoML functionality in H2O. H2O's AutoML provides an easy-to-use interface which automates the process of training a large, comprehensive selection of candidate models and a stacked ensemble model which, in most cases, will be the top performing model in the AutoML Leaderboard. H2O AutoML is available in all the H2O interfaces including the h2o R package, Python module and the Flow web GUI. We will also provide simple code examples to get you started using AutoML.
Erin's Bio:
Erin is a Statistician and Machine Learning Scientist at H2O.ai. She is the main author of H2O Ensemble. Before joining H2O, she was the Principal Data Scientist at Wise.io and Marvin Mobile Security (acquired by Veracode in 2012) and the founder of DataScientific, Inc. Erin received her Ph.D. in Biostatistics with a Designated Emphasis in Computational Science and Engineering from University of California, Berkeley. Her research focuses on ensemble machine learning, learning from imbalanced binary-outcome data, influence curve based variance estimation and statistical computing. She also holds a B.S. and M.A. in Mathematics.
Alexei Vladishev - Zabbix - Monitoring Solution for EveryoneZabbix
Paris Zabbix User Group Meetup 2016
June 23, 2016
1. Open Source
2. Zabbix Architecture
3. Data Collection
4. Problem Detection
5. Problem Forecasting / Trend Prediction
6. Lifecycle and Support Policy
CI/CD Pipeline Security: Advanced Continuous Delivery Best Practices: Securit...Amazon Web Services
CI/CD Pipeline Security: Advanced Continuous Delivery Best Practices: Security Week at the San Francisco Loft
Continuous delivery (CD) enables teams to be more agile and quickens the pace of innovation. Too often, however, teams adopt CD without putting the right safety mechanisms in place. In this talk, we discuss opportunities for you to transform your software release process into a safer one. We explore various DevOps best practices, showcasing sample applications and code with AWS CodePipeline and AWS CodeDeploy. We discuss how to set up delivery pipelines with nonproduction testing stages, failure cases, rollbacks, redundancy, canary testing and blue/green deployments, and monitoring. We'll discuss continuous delivery practices for deploying to Amazon EC2, AWS Lambda, and Containers (such as Amazon ECS or AWS Fargate).
Level: 200
Speaker: Leo Zhadanovsky - Principal Solutions Architect, Cloudstart, AWS
In this session we’ll take a high-level overview of AWS Lambda, a serverless compute platform that has changed the way that developers around the world build applications. We’ll explore how Lambda works under the hood, the capabilities it has, and how it is used. By the end of this talk you’ll know how to create Lambda based applications and deploy and manage them easily.
Speaker: Chris Munns - Principal Developer Advocate, AWS Serverless Applications, AWS
Apache Hadoop and Spark on AWS: Getting started with Amazon EMR - Pop-up Loft...Amazon Web Services
Amazon EMR is a managed service that makes it easy for customers to use big data frameworks and applications like Apache Hadoop, Spark, and Presto to analyze data stored in HDFS or on Amazon S3, Amazon’s highly scalable object storage service. In this session, we will introduce Amazon EMR and the greater Apache Hadoop ecosystem, and show how customers use them to implement and scale common big data use cases such as batch analytics, real-time data processing, interactive data science, and more. Then, we will walk through a demo to show how you can start processing your data at scale within minutes.
Casandra is a open-source, distributed, highly scalable and fault-tolerant database. It is a best choice for managing structured, semi-structured or unstructured data at a large amount.
Model serving made easy using Kedro pipelines - Mariusz Strzelecki, GetInDataGetInData
If you want to stay up to date, subscribe to our newsletter here: https://bit.ly/3tiw1I8
Presentation from the performance given by Mariusz during the Data Science Summit ML Edition.
Author: Mariusz Strzelecki
Linkedin: https://www.linkedin.com/in/mariusz-strzelecki/
___
Company:
Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets.
Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries.
https://getindata.com
Luigi Brochard from Lenovo presented this deck at the Switzerland HPC Conference.
"Lenovo has developed an open source HPC software stack for system management with GUI support. This enables customers to more efficiently manage their clusters by making it simple and easy for both the system administrator and end users.This talk will present this initiative, show a demo and present future evolutions."
Watch the video presentation:
https://www.youtube.com/watch?v=xqwLul_hA28
See more talks in the Swiss Conference Video Gallery: http://insidehpc.com/2016-swiss-hpc-conference/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Auto scaling using Amazon Web Services ( AWS )Harish Ganesan
In this article i would like to share some of the insights on AWS Auto Scaling in following perspectives:
• Need for Auto Scaling
• How AWS Auto scaling can help to handle the various load volatility scenarios
• How to configure an Auto scaling policy in AWS
• Things to remember before Scaling out and down
• Understand the intricacies while integrating Auto scaling with other Amazon Web Services
• Risks involved in AWS Auto scaling
Presented at #H2OWorld 2017 in Mountain View, CA.
Enjoy the video: https://youtu.be/42Oo8TOl85I.
Learn more about H2O.ai: https://www.h2o.ai/.
Follow @h2oai: https://twitter.com/h2oai.
- - -
Abstract:
In recent years, the demand for machine learning experts has outpaced the supply, despite the surge of people entering the field. To address this gap, there have been big strides in the development of user-friendly machine learning software that can be used by non-experts. Although H2O has made it easier for practitioners to train and deploy machine learning models at scale, there is still a fair bit of knowledge and background in data science that is required to produce high-performing machine learning models. Deep Neural Networks in particular, are notoriously difficult for a non-expert to tune properly. In this presentation, we provide an overview of the field of "Automatic Machine Learning" and introduce the new AutoML functionality in H2O. H2O's AutoML provides an easy-to-use interface which automates the process of training a large, comprehensive selection of candidate models and a stacked ensemble model which, in most cases, will be the top performing model in the AutoML Leaderboard. H2O AutoML is available in all the H2O interfaces including the h2o R package, Python module and the Flow web GUI. We will also provide simple code examples to get you started using AutoML.
Erin's Bio:
Erin is a Statistician and Machine Learning Scientist at H2O.ai. She is the main author of H2O Ensemble. Before joining H2O, she was the Principal Data Scientist at Wise.io and Marvin Mobile Security (acquired by Veracode in 2012) and the founder of DataScientific, Inc. Erin received her Ph.D. in Biostatistics with a Designated Emphasis in Computational Science and Engineering from University of California, Berkeley. Her research focuses on ensemble machine learning, learning from imbalanced binary-outcome data, influence curve based variance estimation and statistical computing. She also holds a B.S. and M.A. in Mathematics.
Alexei Vladishev - Zabbix - Monitoring Solution for EveryoneZabbix
Paris Zabbix User Group Meetup 2016
June 23, 2016
1. Open Source
2. Zabbix Architecture
3. Data Collection
4. Problem Detection
5. Problem Forecasting / Trend Prediction
6. Lifecycle and Support Policy
Opportunistic job sharing for mobile cloud computingijccsa
Cloud Computing is the evolution of new business era which is covered with many of technologies.These
technology are taking advantage of economies of scale and multi tenancy which are used to decrees the
cost of information technology resources. Many of the organization are eager to reduce their computing
cost through the means of virtualization. This demand of reducing the computing cost and time has led to
the innovation of Cloud Computing. Itenhanced computing through improved deployment and
infrastructure costs and processing time. Mobile computing & its applications in smart phones enable a
new, rich user experience. Due to extreme usage of limited resources in smart phones it create problems
which are battery problems, memory space and CPU. To solve this problem, we propose a dynamic mobile
cloud computing architecture framework to use global resources instead of local resources. In this
proposed framework the usefulness of job sharing workload at runtime reduces the load at the local client
and the dynamic throughput time of the job through Wi-Fi Connectivity.
IDENTICAL PROGRAMMING LANGUAGES IN CLOUD COMPUTING PROJECTS
EMINENT RESEARCH IDEAS IN CLOUD COMPUTING PROJECTS
NOTICEABLE RESEARCH TOPICS IN CLOUD COMPUTING PROJECTS
International Journal on Cloud Computing: Services and Architecture (IJCCSA)ijccsa
Cloud computing helps enterprises transform business and technology. Companies have begun to look for solutions that would help reduce their infrastructures costs and improve profitability. Cloud computing is becoming a foundation for benefits well beyond IT cost savings. Yet, many business leaders are concerned about cloud security, privacy, availability, and data protection. To discuss and address these issues, we invite researches who focus on cloud computing to shed more light on this emerging field.
Cloud computing is an internet-based computing technology, where shared re-sources
such as software, platform, storage and information are provided to customers on demand.
Cloud computing is a computing platform for sharing resources that include infrastructures,
software, applications, and business processes. The exact definition of cloud computing is A
large-scale distributed computing paradigm that is driven by economies of scale, in which a
pool of abstracted, virtualized, dynamically scalable, managed computing power, storage,
platforms, and services are delivered on demand to external customers over the Internet .
Cloud computing is a releasing individual and institutions from the traditional cvcle of buying-using-maintaining-upgrading IT resourcs - both hardware and software. Instead it is making IT resource accessible from anywhere and at proportions as required by the end user. Here is a brief introduction to this new transformation
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
2. 2
The latest Cloud Computing Projects master thesis Topics are highlighted below,
EFFECTUAL TOPICS IN CLOUD
COMPUTING PROJECTS
1
Optimal Workload Allocation towards
Power consumption and balanced delay
2
Network Paradigm for Mobile Cloud
Computing of Predictive Offloading
3
UAV Mounted Cloudlet with Mobile
Cloud Computing
4
Design issues, optimization and
challenges of HetNets and Intercloud
Task scheduling and joint optimal pricing
in mobile cloud computing
5
3. 1 2
3 4
5
TYPICAL TOOLS AND SOFTWARE
IN CLOUD COMPUTING
Hereby we have listed down the Cloud Computing Tools and Software in the master thesis,
4. 4
Cloud Infrastructure Management
PIVOTAL RESEARCH IN CLOUD
COMPUTING THESIS
Let us discuss about the research based on the Cloud Computing Technology,
1 Eucalyptus
2 Google Apps
Google Calendar, Talk etc.
3 Amazon web services
Amazon EC2 and Amazon S3
4 Microsoft Online Services
Office communications online