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1. What are the difficulties in deploying and managing the life cycle of data-heavy application 2. Review of kubernetes landscape w.r.t data-heavy applications 3. Robin approach to orchestrating data-heavy applications
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A Case Study of NoSQL Adoption: What Drove Wordnik Non-Relational?
Wordnik migrated from a MySQL relational database to the non-relational MongoDB database for 5 key reasons: speed, stability, scaling, simplicity, and fitting their object model better. They tested MongoDB extensively, iteratively improving their data mapping and access patterns. The migration was done without downtime by switching between the databases. While inserts were much faster in MongoDB, updates could be slow due to disk I/O. Wordnik addressed this through optimizations like pre-fetching on updates and moving to local storage. Overall, MongoDB was a better fit for Wordnik's large and evolving datasets.
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Video from presentation: https://youtu.be/SoSZdI2lMVQ
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Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a platform designed to address multi-faceted needs by offering multi-function Data Management and analytics to solve the enterprise’s most pressing data and analytic challenges in a streamlined fashion. They need a worry-free experience with the architecture and its components.
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https://segment.com/ - Analytics API and Customer Data Platform
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https://segment.com/docs/ - Documentation of Segment
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Join us for this webinar where Alex Ma of Alluxio, an open-source data orchestration platform, will discuss how a data orchestration approach offers a solution for connecting traditional on-prem data centers and cloud data lakes with other clouds and data centers. With Alluxio’s “zero-copy” burst solution, companies can bridge remote data centers and data lakes with computing frameworks in other locations, enabling them to offload, compute, and leverage the flexibility, scalability, and power of the cloud for their remote data.
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A Case Study of NoSQL Adoption: What Drove Wordnik Non-Relational?
Wordnik migrated from a MySQL relational database to the non-relational MongoDB database for 5 key reasons: speed, stability, scaling, simplicity, and fitting their object model better. They tested MongoDB extensively, iteratively improving their data mapping and access patterns. The migration was done without downtime by switching between the databases. While inserts were much faster in MongoDB, updates could be slow due to disk I/O. Wordnik addressed this through optimizations like pre-fetching on updates and moving to local storage. Overall, MongoDB was a better fit for Wordnik's large and evolving datasets.
Effective use of cloud resources for Data Engineering - Johnson Darkwah
Video from presentation: https://youtu.be/SoSZdI2lMVQ
Processing vast amounts of data in the cloud has long been a nightmare not just for data analysts but also budget owners. We believe that migrating your data engineering workloads to can be beneficial, if you keep in mind some basic architectural principles. Teams processing big data in the cloud should understand and leverage its key attribute. Flexibility.The goal of our keynote is to share our experience and key learnings on how to fully utilize the power that the cloud offers and not go broke. This could be useful for both startups, but also large corporation as we will show examples of how to dramatically lower the cost of infrastructure.
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Estimating the Total Costs of Your Cloud Analytics Platform
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a platform designed to address multi-faceted needs by offering multi-function Data Management and analytics to solve the enterprise’s most pressing data and analytic challenges in a streamlined fashion. They need a worry-free experience with the architecture and its components.
A complete machine learning infrastructure cost for the first modern use case at a midsize to large enterprise will be anywhere from $2M to $14M. Get this data point as you take the next steps on your journey.
When you need more data in less time...
Introduction to Segment, Analytics API and Customer Data Platform. (Demo: Segment, AWS Redshift, Redash, Segment and GTM Alternatives) (Frontend Fighters Edition)
Recommended links:
https://segment.com/ - Analytics API and Customer Data Platform
https://open.segment.com/ - Open Source Projects of Segment
https://segment.com/docs/ - Documentation of Segment
https://redash.io/ - Open Sorce Data Dashboard
https://aws.amazon.com/redshift/ - Data Warehouse Solution
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Slides: Proven Strategies for Hybrid Cloud Computing with Mainframes — From A...
Mainframes continue to perform mission-critical transaction processing and contain massive amounts of core business data. But digital transformation initiatives and cloud computing have created both opportunities and challenges for unlocking and utilizing this data. Qlik and AWS will share some of the proven strategies from successful customer deployments across a range of different mainframe to cloud use cases, including legacy application modernization, data analytics, and data migrations.
In this presentation, you will learn how to:
• Replicate very large volumes of mainframe data in real-time to the cloud
• Automate the creation of analytics-ready data lakes and data warehouses
• Achieve a 30% reduction in cost of compute
Data Lakehouse, Data Mesh, and Data Fabric (r2)
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
Data architecture for modern enterprise
Synopsis: Modern enterprises anticipate business requirements and work proactively to optimise the outcomes. If they don’t renovate or reinvent their data architectures, they lose customers, and market share. So my talk will be in detailing the importance of data architecture, architectural challenges if is not addressed and a case study - the learnings and success story by fixing the issues at the root - at the data storage & access.
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Using “zero-copy” hybrid bursting on remote data to solve data lake analytics capacity and performance problems.
Data scientists want answers on demand. But in today’s enterprise architectures, the reality is that most data remains on-prem, despite the promise of cloud-based analytics. Moving all that data to the cloud has typically not been possible for many reasons including cost, latency, and technical difficulty. So, what if there was a technology that would connect these on-prem environments to any major cloud platform, enabling high-powered computing without the need to move massive amounts of data?
Join us for this webinar where Alex Ma of Alluxio, an open-source data orchestration platform, will discuss how a data orchestration approach offers a solution for connecting traditional on-prem data centers and cloud data lakes with other clouds and data centers. With Alluxio’s “zero-copy” burst solution, companies can bridge remote data centers and data lakes with computing frameworks in other locations, enabling them to offload, compute, and leverage the flexibility, scalability, and power of the cloud for their remote data.
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• Why there is a need for digital modernization?
• What are the characteristics of the innovative data platform?
• What is NoSQL Apache Cassandra?
• How does DataStax innovate the NoSQL data platform?
• What are some of the challenges associated with digital modernization and migration?
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You will learn how to achieve quantifiable results by modernizing your data and analytics stack with a semantic layer that delivers an order of magnitude better query performance, increased data team productivity, lower query compute costs, and improved Speed-to-Insights.
Attend this session to learn about:
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- Making a consistent set of business metrics “analytics-ready” and accessible.
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- Treating “data as a product” and how to drive business value for all consumers.
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What if all members of your software development team from Project Managers, Business Analysts, Testing and documentation members could create and modify web applications and web services? With traditional SQL solutions this was difficult because of the need to convert web pages to objects, objects to tables as well as the reverse functions. But now with native XML databases and drag-and-drop forms builders, data can flow from the XML model of a web form to the database and back again without translation. This radically simpler process combined with standardized query languages makes it easier for non-programmers to build and maintain their own applications and web services.
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We’ll describe some use cases as examples of a broad range of modern use cases that need a platform. We will describe some popular valid technology stacks that enterprises use in accomplishing these modern use cases of customer churn, predictive analytics, fraud detection, and supply chain management.
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Many organizations are turning to predictive analytics to increase their bottom line and efficiency and, therefore, competitive advantage. It can make the difference between business success or failure.
Fraudulent activity detection is exponentially more effective when risk actions are taken immediately (i.e., stop the fraudulent transaction), instead of after the fact. Fast digestion of a wide network of risk exposures across the network is required in order to minimize adverse outcomes.
Supply chain leaders are under constant pressure to reduce overall supply chain management (SCM) costs while maintaining a flexible and diverse supplier ecosystem. They will leverage IoT, sensors, cameras, and blockchain. Major investments in advanced analytics, warehouse relocation, and automation, both in distribution centers and stores, will be essential for survival.
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The Shifting Landscape of Data Integration
This document discusses the shifting landscape of data integration. It begins with an introduction by William McKnight, who is described as the "#1 Global Influencer in Data Warehousing". The document then discusses how challenges in data integration are shifting from dealing with volume, velocity and variety to dealing with dynamic, distributed and diverse data in the cloud. It also discusses IDC's view that this shift is occurring from the traditional 3Vs to the 3Ds. The rest of the document discusses Matillion, a vendor that provides a modern solution for cloud data integration challenges.
Optimizing for Costs in the Cloud
This document discusses optimizing costs when using cloud computing resources. It provides several strategies for reducing costs including using only the resources needed, turning off unused resources, optimizing based on time of day or year, leveraging auto scaling, and using spot instances. It also discusses using application services like load balancers, queues, and notifications to optimize costs compared to running those services on EC2 instances. Overall the key strategies discussed are rightsizing resources, auto scaling, using reserved instances analysis, architecting for spot instances, and leveraging serverless application services.
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Caserta Concepts, Datameer and Microsoft shared their combined knowledge and a use case on big data, the cloud and deep analytics. Attendes learned how a global leader in the test, measurement and control systems market reduced their big data implementations from 18 months to just a few.
Speakers shared how to provide a business user-friendly, self-service environment for data discovery and analytics, and focus on how to extend and optimize Hadoop based analytics, highlighting the advantages and practical applications of deploying on the cloud for enhanced performance, scalability and lower TCO.
Agenda included:
- Pizza and Networking
- Joe Caserta, President, Caserta Concepts - Why are we here?
- Nikhil Kumar, Sr. Solutions Engineer, Datameer - Solution use cases and technical demonstration
- Stefan Groschupf, CEO & Chairman, Datameer - The evolving Hadoop-based analytics trends and the role of cloud computing
- James Serra, Data Platform Solution Architect, Microsoft, Benefits of the Azure Cloud Service
- Q&A, Networking
For more information on Caserta Concepts, visit our website: http://casertaconcepts.com/
Data Architecture PowerPoint Presentation Slides
Use this Data Architecture PowerPoint Presentation Slides to explain important technologies of data architecture. Principles of data architecture can be well explained using these PPT slides. There are many templates provided in this PowerPoint complete deck such as NoSQL databases, real-time streaming platforms, dockers and containers, containers repositories, container orchestration, microservices, functions as a service, principles of data architecture, view data as a shared asset, ensure security and access controls, data architecture, big data architecture, etc. All the templates are designed by our team of experts after an in-depth study of the topic. These templates are completely editable. The presenter can change font, text, and color. It also contains additional slides like mission, puzzle, timeline, target, Venn, idea pie chart, bar graph, area chart helps you to illustrate the concept in a professional manner. Download this data system presentation graphics to present your work smarty and precisely. Ideas acquire a definite form due to our Data Architecture Powerpoint Presentation Slides. It will all begin to jell.
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Integrating data across systems has been a perpetual challenge. Unfortunately, the current technology-focused solutions have not helped IT to improve its dismal project success statistics. Data warehouses, BI implementations, and general analytical efforts achieve the same levels of success as other IT projects – approximately 1/3rd are considered successes when measured against price, schedule, or functionality objectives. The first step is determining the appropriate analysis approach to the data system integration challenge. The second step is understanding the strengths and weaknesses of various approaches. Turns out that proper analysis at this stage makes actual technology selection far more accurate. Only when these are accomplished can proper matching between problem and capabilities be achieved as the third step and true business value be delivered. This webinar will illustrate that good systems development more often depends on at least three data management disciplines in order to provide a solid foundation.
Takeaways:
Data system integration challenge analysis
Understanding of a range of data system-integration technologies including
Problem space (BI, Analytics, Big Data), Data (Warehousing, Vault, Cube) and alternative approaches (Virtualization, Linked Data, Portals, Meta-models)
Understanding foundational data warehousing & BI concepts based on the Data Management Body of Knowledge (DMBOK)
How to utilize data warehousing & BI in support of business strategy
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The Business Data Lake is a new approach to information management, analytics and reporting that better matches the culture of business and better enables organizations to truly leverage the value of their information.
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Data lakes & data warehouses, whether on-premises or in the cloud promise to provide a centralized, cost-effective and scalable foundation for modern analytics. However, organisations continue to struggle to deliver accurate, current and analytics-ready data sets in a timely fashion. Traditional ingestion tools weren’t designed to handle hundreds or even thousands of data sources and the lack of lineage forces data consumers to manually aggregate information from sources they trust. In this session, you’ll learn how to future-proof your modern data environment to meet the needs of the business for the long term. We'll examine how to overcome common challenges, the related must-have technology solutions in the data lake/ data warehousing world, using real-world success stories and even a few architecture tips from industry experts.
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Big Data Analytics on the Cloud
Caserta Concepts, Datameer and Microsoft shared their combined knowledge and a use case on big data, the cloud and deep analytics. Attendes learned how a global leader in the test, measurement and control systems market reduced their big data implementations from 18 months to just a few.
Speakers shared how to provide a business user-friendly, self-service environment for data discovery and analytics, and focus on how to extend and optimize Hadoop based analytics, highlighting the advantages and practical applications of deploying on the cloud for enhanced performance, scalability and lower TCO.
Agenda included:
- Pizza and Networking
- Joe Caserta, President, Caserta Concepts - Why are we here?
- Nikhil Kumar, Sr. Solutions Engineer, Datameer - Solution use cases and technical demonstration
- Stefan Groschupf, CEO & Chairman, Datameer - The evolving Hadoop-based analytics trends and the role of cloud computing
- James Serra, Data Platform Solution Architect, Microsoft, Benefits of the Azure Cloud Service
- Q&A, Networking
For more information on Caserta Concepts, visit our website: http://casertaconcepts.com/
Slides: Migrate BI Dashboards to Run Directly on a Cloud Data Lake in Five Ea...
While BI dashboards are great at democratizing analytics in organizations, the architecture that traditionally powers them has hidden consequences that have serious impacts on the business.
This architecture is based on a 30-year-old paradigm that requires many different systems, ETL jobs, and copies of data in data marts, data warehouses, and BI extracts. One downside of many is that it takes many days if not weeks to answer a different business question with this architecture. The negative consequences are further multiplied by the tens, hundreds, or even thousands of dashboards needed to run a data-driven organization.
Now, there’s a straightforward way to overcome these challenges that many organizations are already taking advantage of, an open cloud data lake architecture and Dremio
Join Jason Hughes, Technical Director at Dremio, for this webinar to learn how you can migrate BI dashboards to Dremio to quickly provide interactive dashboards to data consumers without the issues of the traditional architecture — and finally deliver the benefits always promised by BI.
What you’ll learn:
• Why BI dashboards’ traditional architecture implemented at scale causes many issues, which hinder the very insights it promises.
• How a Dremio-powered cloud data lake architecture eliminates or mitigates the negative consequences of the traditional approach.
• Step-by-step instructions for migrating a BI dashboard to run directly on a cloud data lake, both a self-contained example and your own dashboards.
Containerized Hadoop beyond Kubernetes
Partha Seetala is the CTO of Robin Systems, which provides a Kubernetes platform for running big data, NoSQL, database, and AI/ML workloads. Robin addresses challenges with containerizing these applications, such as resource management and storage and networking issues. Robin's solution allows applications to drive infrastructure configuration for improved user experience with capabilities like one-click provisioning, scaling, cloning, backup, and migration of applications across clouds.
MySQL Cluster Scaling to a Billion Queries
MySQL Cluster is a distributed database that provides extreme scalability, high availability, and real-time performance. It uses an auto-sharding and auto-replicating architecture to distribute data across multiple low-cost servers. Key benefits include scaling reads and writes, 99.999% availability through its shared-nothing design with no single point of failure, and real-time responsiveness. It supports both SQL and NoSQL interfaces to enable complex queries as well as high-performance key-value access.
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Join Principal Strategy Architect Ankit Patel to discuss the digital modernization journey many enterprises have taken from relational to NoSQL databases. In this webinar we will discuss the following:
• Why there is a need for digital modernization?
• What are the characteristics of the innovative data platform?
• What is NoSQL Apache Cassandra?
• How does DataStax innovate the NoSQL data platform?
• What are some of the challenges associated with digital modernization and migration?
How to Use a Semantic Layer on Big Data to Drive AI & BI Impact
Learn about using a semantic layer to make data accessible and how to accelerate the business impact of AI and BI at your organization.
This session will offer practical advice on how to drive AI & BI business outcomes with an effective data strategy that leverages a semantic layer.
You will learn how to achieve quantifiable results by modernizing your data and analytics stack with a semantic layer that delivers an order of magnitude better query performance, increased data team productivity, lower query compute costs, and improved Speed-to-Insights.
Attend this session to learn about:
- Gaining business alignment and reducing data prep for your AI and BI teams.
- Making a consistent set of business metrics “analytics-ready” and accessible.
- Accelerating end-to-end query performance while optimizing cloud resources.
- Treating “data as a product” and how to drive business value for all consumers.
Agile NoSQL With XRX
What if all members of your software development team from Project Managers, Business Analysts, Testing and documentation members could create and modify web applications and web services? With traditional SQL solutions this was difficult because of the need to convert web pages to objects, objects to tables as well as the reverse functions. But now with native XML databases and drag-and-drop forms builders, data can flow from the XML model of a web form to the database and back again without translation. This radically simpler process combined with standardized query languages makes it easier for non-programmers to build and maintain their own applications and web services.
Platforming the Major Analytic Use Cases for Modern Engineering
We’ll describe some use cases as examples of a broad range of modern use cases that need a platform. We will describe some popular valid technology stacks that enterprises use in accomplishing these modern use cases of customer churn, predictive analytics, fraud detection, and supply chain management.
In many industries, to achieve top-line growth, it is imperative that companies get the most out of existing customer relationships. Customer churn use cases are about generating high levels of profitable customer satisfaction through the use of knowledge generated from corporate and external data to help drive a more positive customer experience (CX).
Many organizations are turning to predictive analytics to increase their bottom line and efficiency and, therefore, competitive advantage. It can make the difference between business success or failure.
Fraudulent activity detection is exponentially more effective when risk actions are taken immediately (i.e., stop the fraudulent transaction), instead of after the fact. Fast digestion of a wide network of risk exposures across the network is required in order to minimize adverse outcomes.
Supply chain leaders are under constant pressure to reduce overall supply chain management (SCM) costs while maintaining a flexible and diverse supplier ecosystem. They will leverage IoT, sensors, cameras, and blockchain. Major investments in advanced analytics, warehouse relocation, and automation, both in distribution centers and stores, will be essential for survival.
Enable Better Decision Making with Power BI Visualizations & Modern Data Estate
Self-service BI empowers users to reach analytic outputs through data visualizations and reporting tools. Solution Architect and Cloud Solution Specialist, James McAuliffe, will be taking you through a journey of Azure's Modern Data Estate.
The technology of the business data lake
The Pivotal Business Data Lake provides a flexible blueprint to meet your business's future information and analytics needs while avoiding the pitfalls of typical EDW implementations. Pivotal’s products will help you overcome challenges like reconciling corporate and local needs, providing real-time access to all types of data, integrating data from multiple sources and in multiple formats, and supporting ad hoc analysis.
Enterprise Architecture vs. Data Architecture
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
The Shifting Landscape of Data Integration
This document discusses the shifting landscape of data integration. It begins with an introduction by William McKnight, who is described as the "#1 Global Influencer in Data Warehousing". The document then discusses how challenges in data integration are shifting from dealing with volume, velocity and variety to dealing with dynamic, distributed and diverse data in the cloud. It also discusses IDC's view that this shift is occurring from the traditional 3Vs to the 3Ds. The rest of the document discusses Matillion, a vendor that provides a modern solution for cloud data integration challenges.
Optimizing for Costs in the Cloud
This document discusses optimizing costs when using cloud computing resources. It provides several strategies for reducing costs including using only the resources needed, turning off unused resources, optimizing based on time of day or year, leveraging auto scaling, and using spot instances. It also discusses using application services like load balancers, queues, and notifications to optimize costs compared to running those services on EC2 instances. Overall the key strategies discussed are rightsizing resources, auto scaling, using reserved instances analysis, architecting for spot instances, and leveraging serverless application services.
Benefits of the Azure Cloud
Caserta Concepts, Datameer and Microsoft shared their combined knowledge and a use case on big data, the cloud and deep analytics. Attendes learned how a global leader in the test, measurement and control systems market reduced their big data implementations from 18 months to just a few.
Speakers shared how to provide a business user-friendly, self-service environment for data discovery and analytics, and focus on how to extend and optimize Hadoop based analytics, highlighting the advantages and practical applications of deploying on the cloud for enhanced performance, scalability and lower TCO.
Agenda included:
- Pizza and Networking
- Joe Caserta, President, Caserta Concepts - Why are we here?
- Nikhil Kumar, Sr. Solutions Engineer, Datameer - Solution use cases and technical demonstration
- Stefan Groschupf, CEO & Chairman, Datameer - The evolving Hadoop-based analytics trends and the role of cloud computing
- James Serra, Data Platform Solution Architect, Microsoft, Benefits of the Azure Cloud Service
- Q&A, Networking
For more information on Caserta Concepts, visit our website: http://casertaconcepts.com/
Data Architecture PowerPoint Presentation Slides
Use this Data Architecture PowerPoint Presentation Slides to explain important technologies of data architecture. Principles of data architecture can be well explained using these PPT slides. There are many templates provided in this PowerPoint complete deck such as NoSQL databases, real-time streaming platforms, dockers and containers, containers repositories, container orchestration, microservices, functions as a service, principles of data architecture, view data as a shared asset, ensure security and access controls, data architecture, big data architecture, etc. All the templates are designed by our team of experts after an in-depth study of the topic. These templates are completely editable. The presenter can change font, text, and color. It also contains additional slides like mission, puzzle, timeline, target, Venn, idea pie chart, bar graph, area chart helps you to illustrate the concept in a professional manner. Download this data system presentation graphics to present your work smarty and precisely. Ideas acquire a definite form due to our Data Architecture Powerpoint Presentation Slides. It will all begin to jell.
Cloud Economics
This document discusses the economics of cloud computing. While cost reduction is often seen as a primary benefit of cloud adoption, public cloud is not always cheaper than traditional hosting. There are factors to consider like total cost of ownership, transformation costs, and an organization's position in the IT lifecycle. Public cloud costs more per usage unit due to short commitments, but exploiting variable demand patterns through scaling can reduce costs. The optimal approach depends on an application's demand graph shape - periodic, spiked, or cyclical usage may benefit most from a hybrid cloud model.
Power BI Advanced Data Modeling Virtual Workshop
Join CCG and Microsoft for a virtual workshop, hosted by Solution Architect, Doug McClurg, to learn how to create professional, frustration-free data models that engage your customers.
Data-Ed Online Presents: Data Warehouse Strategies
Integrating data across systems has been a perpetual challenge. Unfortunately, the current technology-focused solutions have not helped IT to improve its dismal project success statistics. Data warehouses, BI implementations, and general analytical efforts achieve the same levels of success as other IT projects – approximately 1/3rd are considered successes when measured against price, schedule, or functionality objectives. The first step is determining the appropriate analysis approach to the data system integration challenge. The second step is understanding the strengths and weaknesses of various approaches. Turns out that proper analysis at this stage makes actual technology selection far more accurate. Only when these are accomplished can proper matching between problem and capabilities be achieved as the third step and true business value be delivered. This webinar will illustrate that good systems development more often depends on at least three data management disciplines in order to provide a solid foundation.
Takeaways:
Data system integration challenge analysis
Understanding of a range of data system-integration technologies including
Problem space (BI, Analytics, Big Data), Data (Warehousing, Vault, Cube) and alternative approaches (Virtualization, Linked Data, Portals, Meta-models)
Understanding foundational data warehousing & BI concepts based on the Data Management Body of Knowledge (DMBOK)
How to utilize data warehousing & BI in support of business strategy
Future of Analytics: Drivers of Change
Scott Fairbanks, Senior BI Consultant at CCG, demonstrates the key differentiators between traditional warehouse architectures and new cloud technologies. Learn the key competitors in the cloud space, and what elements separates them in terms of linking analytic solutions.
The principles of the business data lake
The Business Data Lake is a new approach to information management, analytics and reporting that better matches the culture of business and better enables organizations to truly leverage the value of their information.
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEED
Data lakes & data warehouses, whether on-premises or in the cloud promise to provide a centralized, cost-effective and scalable foundation for modern analytics. However, organisations continue to struggle to deliver accurate, current and analytics-ready data sets in a timely fashion. Traditional ingestion tools weren’t designed to handle hundreds or even thousands of data sources and the lack of lineage forces data consumers to manually aggregate information from sources they trust. In this session, you’ll learn how to future-proof your modern data environment to meet the needs of the business for the long term. We'll examine how to overcome common challenges, the related must-have technology solutions in the data lake/ data warehousing world, using real-world success stories and even a few architecture tips from industry experts.
Pivotal deep dive_on_pivotal_hd_world_class_hdfs_platform
The document discusses Pivotal HD, a Hadoop distribution from Pivotal. It provides an overview of key features of Pivotal HD 2.0 including improved support for real-time analytics using Gemfire XD, enhanced machine learning and SQL capabilities, and integration with the Isilon storage platform. The presentation highlights how Pivotal HD can help customers build a "data lake" to store all of their data and gain insights to create new data-driven services and applications.
Big Data Analytics on the Cloud
Caserta Concepts, Datameer and Microsoft shared their combined knowledge and a use case on big data, the cloud and deep analytics. Attendes learned how a global leader in the test, measurement and control systems market reduced their big data implementations from 18 months to just a few.
Speakers shared how to provide a business user-friendly, self-service environment for data discovery and analytics, and focus on how to extend and optimize Hadoop based analytics, highlighting the advantages and practical applications of deploying on the cloud for enhanced performance, scalability and lower TCO.
Agenda included:
- Pizza and Networking
- Joe Caserta, President, Caserta Concepts - Why are we here?
- Nikhil Kumar, Sr. Solutions Engineer, Datameer - Solution use cases and technical demonstration
- Stefan Groschupf, CEO & Chairman, Datameer - The evolving Hadoop-based analytics trends and the role of cloud computing
- James Serra, Data Platform Solution Architect, Microsoft, Benefits of the Azure Cloud Service
- Q&A, Networking
For more information on Caserta Concepts, visit our website: http://casertaconcepts.com/
Slides: Migrate BI Dashboards to Run Directly on a Cloud Data Lake in Five Ea...
While BI dashboards are great at democratizing analytics in organizations, the architecture that traditionally powers them has hidden consequences that have serious impacts on the business.
This architecture is based on a 30-year-old paradigm that requires many different systems, ETL jobs, and copies of data in data marts, data warehouses, and BI extracts. One downside of many is that it takes many days if not weeks to answer a different business question with this architecture. The negative consequences are further multiplied by the tens, hundreds, or even thousands of dashboards needed to run a data-driven organization.
Now, there’s a straightforward way to overcome these challenges that many organizations are already taking advantage of, an open cloud data lake architecture and Dremio
Join Jason Hughes, Technical Director at Dremio, for this webinar to learn how you can migrate BI dashboards to Dremio to quickly provide interactive dashboards to data consumers without the issues of the traditional architecture — and finally deliver the benefits always promised by BI.
What you’ll learn:
• Why BI dashboards’ traditional architecture implemented at scale causes many issues, which hinder the very insights it promises.
• How a Dremio-powered cloud data lake architecture eliminates or mitigates the negative consequences of the traditional approach.
• Step-by-step instructions for migrating a BI dashboard to run directly on a cloud data lake, both a self-contained example and your own dashboards.
Mais procurados (20)
How to Use a Semantic Layer on Big Data to Drive AI & BI Impact
How to Use a Semantic Layer on Big Data to Drive AI & BI Impact
Platforming the Major Analytic Use Cases for Modern Engineering
Platforming the Major Analytic Use Cases for Modern Engineering
Enable Better Decision Making with Power BI Visualizations & Modern Data Estate
Enable Better Decision Making with Power BI Visualizations & Modern Data Estate
Data-Ed Online Presents: Data Warehouse Strategies
Data-Ed Online Presents: Data Warehouse Strategies
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEED
THE FUTURE OF DATA: PROVISIONING ANALYTICS-READY DATA AT SPEED
Pivotal deep dive_on_pivotal_hd_world_class_hdfs_platform
Pivotal deep dive_on_pivotal_hd_world_class_hdfs_platform
Slides: Migrate BI Dashboards to Run Directly on a Cloud Data Lake in Five Ea...
Slides: Migrate BI Dashboards to Run Directly on a Cloud Data Lake in Five Ea...
Semelhante a Deliver Big Data, Database and AI/ML as-a-Service anywhere
Containerized Hadoop beyond Kubernetes
Partha Seetala is the CTO of Robin Systems, which provides a Kubernetes platform for running big data, NoSQL, database, and AI/ML workloads. Robin addresses challenges with containerizing these applications, such as resource management and storage and networking issues. Robin's solution allows applications to drive infrastructure configuration for improved user experience with capabilities like one-click provisioning, scaling, cloning, backup, and migration of applications across clouds.
MySQL Cluster Scaling to a Billion Queries
MySQL Cluster is a distributed database that provides extreme scalability, high availability, and real-time performance. It uses an auto-sharding and auto-replicating architecture to distribute data across multiple low-cost servers. Key benefits include scaling reads and writes, 99.999% availability through its shared-nothing design with no single point of failure, and real-time responsiveness. It supports both SQL and NoSQL interfaces to enable complex queries as well as high-performance key-value access.
SQL and NoSQL in SQL Server
This document discusses SQL and NoSQL approaches to scaling databases. It describes how social networks and other large-scale websites use techniques like sharding and messaging to partition data across many databases. It also discusses how SQL Server is adopting NoSQL paradigms like flexible schemas and federated sharding to provide scalability. The document aims to educate about scaling databases and how SQL Server is evolving to support both SQL and NoSQL approaches.
Cloud Computing & Scaling Web Apps
The presentation discussed moving applications to the cloud for scalability, flexibility and pay-as-you-go pricing, noting key differences between RSAWEBCloud and AWS; challenges for developers include optimizing applications for production environments and handling scaling which requires separating concerns like data types and using caching, load balancing, and autoscaling tools.
Azure and cloud design patterns
The document discusses cloud computing and designing applications for scalability and availability in the cloud. It covers key considerations for moving to the cloud like design for failure, building loosely coupled systems, implementing elasticity, and leveraging different storage options. It also discusses challenges like application scalability and availability and how to address them through patterns like caching, partitioning, and implementing elasticity. The document uses examples like MapReduce to illustrate how to build applications that can scale horizontally across infrastructure in the cloud.
Distributed Database Design Decisions to Support High Performance Event Strea...
Event streaming architectures launched a reexamination of applications and systems architectures across the board. We live in a world where answers are needed now in a constant real-time flow. Yet beyond the event streaming system itself, what are the corequisites to ensure our large scale distributed database systems can keep pace with this always-on, always-current real time flow of data? What are the requirements and expectations for this next tech cycle?
Riak at Engine Yard Cloud
The document discusses using Riak, an open source NoSQL database, in the cloud to provide highly available and fault tolerant storage for applications. It describes how the authors' application struggled with availability when hosted on AWS, and their research led them to choose Riak as a solution. Riak provides features like consistent hashing, hinted handoff, and active anti-entropy that allow it to scale linearly and remain available even during failures or added/reduced nodes. The document provides guidance on deploying a Riak cluster in the cloud, including choosing instance types, sizing the cluster, disabling swap, using the right filesystem and scheduler, and monitoring and scaling the cluster over time.
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...
Lookout is a mobile cybersecurity company that ingests telemetry data from hundreds of millions of mobile devices to provide security scanning and apply corporate policies. They were facing scaling issues with their existing data pipeline and storage as the number of devices grew. They decided to use Apache Kafka and Confluent Platform for scalable data ingestion and ScyllaDB as the persistent store. Testing showed the new architecture could handle their target of 1 million devices with low latency and significantly lower costs compared to their previous DynamoDB-based solution. Key learnings included improving Kafka's default partitioner and working through issues during proof of concept testing with ScyllaDB.
Resume
Vittal Dadi has over 12 years of experience as an Oracle Database Administrator. He is certified in Oracle 10g RAC and Oracle 11g. He has expertise in performance tuning, backup/recovery, high availability configurations like RAC and Data Guard, and database migrations. He has worked with various versions of Oracle on Linux, Solaris, AIX, HP-UX, and Windows platforms.
Travel & Leisure Platform Department's tech info
The document discusses the Travel & Leisure Platform Dept and its responsibilities related to data and platform management. It provides an overview of the technical stack including private/public clouds, databases, containers, and automation/monitoring tools. It then discusses recent projects involving business continuity, containerization, alert integration, and automation. Finally, it describes open roles for a DBA and DevOps position and their responsibilities related to database provisioning, backup/recovery, infrastructure as code, and providing platforms and tools for developers.
인메모리 클러스터링 아키텍처
This document discusses in-memory data grids and JBoss Infinispan. It begins with an overview of in-memory data grids, their uses for caching, performance boosting, scalability, and high availability. It then discusses Infinispan specifically, describing it as an open-source, distributed in-memory key-value data grid and cache. The document outlines Infinispan's architecture, features like persistence, transactions, querying, distributed execution, and map-reduce capabilities. It also provides a case study on using Infinispan for session clustering in a web application.
OpenEBS Technical Workshop - KubeCon San Diego 2019
The document summarizes an OpenEBS technical workshop that will take place at KubeCon on November 18th in San Diego. It introduces Container Attached Storage (CAS) and OpenEBS as solutions for running stateful applications on Kubernetes. It discusses how OpenEBS addresses challenges with managing stateful applications on Kubernetes and keeping storage agile. It also provides overviews of the OpenEBS architecture, including pluggable storage engines like cStor and Jiva, and components like the Node Device Manager.
Jcon2020 keynote-high-performance-java-cloud-native
Java has been the leading programming language for more than 20 years. However, many people still believe that Java is complex, heavyweight, and memory-hungry. Today, other languages and especially modern serverless approaches seem to overtake Java more and more. What are the plans for Java, is Java also suited for the cloud, what is coming next and, why should I continue to use Java in the future? Good news: The holy grail is already found! With GraalVM and a new generation of microservices frameworks such as Micronaut, a completely new Java technology stack is emerging that will replace Java as we know it so far and bring Java to a completely new level and establish it in the cloud. Developing native applications with Java, Java as fast as C, app start in milliseconds, minimal memory footprint, and database access up to 1000 times faster. This is not a vision - it is already possible today. In this session, you will learn everything about the Java technology stack of the future and how you can use it to develop lightweight and at the same time ultra-fast in-memory cloud-native applications and microservices in Java. While watching our incredible performance demo, you better fasten your seatbelt.
Clustering van IT-componenten
Clustering can provide high availability and scalability. Shared nothing architectures are best for achieving both high availability and scalability together. Oracle Real Application Cluster (RAC) offers advantages over alternative Oracle clustering configurations, but its scalability is limited. The cost-effectiveness of using RAC in a redundant array of inexpensive servers configuration is small due to its limited scalability. Alternatives may be more suitable depending on specific needs and requirements.
Sanjay resume 2019_post
This document provides a summary of Sanjay Arya's qualifications and work experience. It includes over 24 years of experience in database administration, cloud computing, and software development. Recent work has focused on Oracle and AWS cloud administration, including database migration, backup/recovery, and database replication between Oracle and SQL Server. Previous roles involved administration of Oracle RAC, Exadata, high availability clusters, disaster recovery, and storage administration.
Run Cloud Native MySQL NDB Cluster in Kubernetes
The more your database aligns with Cloud Native principles such as resilience, scaling, auto-healing and data consistency across all nodes, the better it also runs as DBaaS in Kubernetes. I walk through running databases in Kubernetes and demos manual deployment and deployment with an NDB operator.
This talk was given at the MySQL Dev Room FOSDEM 2021.
Ai tour 2019 Mejores Practicas en Entornos de Produccion Big Data Open Source...
En esta presentacion mostramos las buenas practicas en la implementacion de Big Data Open Source usando HDInsight
Understand the Cloud Computing and the future career possibilities
The document provides information about cloud computing and AWS services. It discusses the benefits of cloud computing such as scalability, fault tolerance, and pay-as-you-go pricing. It also summarizes several AWS services including EC2 for compute, S3 for storage, RDS for databases, and VPC for networking. The document emphasizes that cloud computing allows on-demand access to resources over the internet and reduces upfront costs.
Microsoft Openness Mongo DB
This document discusses Microsoft's support for open source tools and NoSQL databases on the Azure platform. It provides examples of various open source technologies supported, such as Linux, Hadoop, Java, PHP, and Node.js. It then discusses how Azure provides solutions for large-scale social networking and e-commerce applications through patterns like data sharding, caching layers, and messaging. Azure aims to provide high availability, elastic scale, and support for flexible data models and processing paradigms to meet the needs of NoSQL and big data applications.
Designing Stateful Apps for Cloud and Kubernetes
Almost all applications have some kind of state. Some data processing apps and databases have huge amounts of state. How do we navigate a cloud-based world of containers where stateless and functions-as-a-service is all the rage? As a long-time architect, designer, and developer of very stateful apps (databases and data processing apps), I’d like to take you on a journey through the modern cloud world and Kubernetes, offering helpful design patterns, considerations, tips, and where things are going. How is Kubernetes shaking up stateful app design?
Semelhante a Deliver Big Data, Database and AI/ML as-a-Service anywhere (20)
Distributed Database Design Decisions to Support High Performance Event Strea...
Distributed Database Design Decisions to Support High Performance Event Strea...
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...
Scaling Security on 100s of Millions of Mobile Devices Using Apache Kafka® an...
OpenEBS Technical Workshop - KubeCon San Diego 2019
OpenEBS Technical Workshop - KubeCon San Diego 2019
Jcon2020 keynote-high-performance-java-cloud-native
Jcon2020 keynote-high-performance-java-cloud-native
Ai tour 2019 Mejores Practicas en Entornos de Produccion Big Data Open Source...
Ai tour 2019 Mejores Practicas en Entornos de Produccion Big Data Open Source...
Understand the Cloud Computing and the future career possibilities
Understand the Cloud Computing and the future career possibilities
Último
Preparing Non - Technical Founders for Engaging a Tech Agency
Preparing non-technical founders before engaging a tech agency is crucial for the success of their projects. It starts with clearly defining their vision and goals, conducting thorough market research, and gaining a basic understanding of relevant technologies. Setting realistic expectations and preparing a detailed project brief are essential steps. Founders should select a tech agency with a proven track record and establish clear communication channels. Additionally, addressing legal and contractual considerations and planning for post-launch support are vital to ensure a smooth and successful collaboration. This preparation empowers non-technical founders to effectively communicate their needs and work seamlessly with their chosen tech agency.Visit our site to get more details about this. Contact us today www.ishtechnologies.com.au
Webinar On-Demand: Using Flutter for Embedded
Flutter is a popular open source, cross-platform framework developed by Google. In this webinar we'll explore Flutter and its architecture, delve into the Flutter Embedder and Flutter’s Dart language, discover how to leverage Flutter for embedded device development, learn about Automotive Grade Linux (AGL) and its consortium and understand the rationale behind AGL's choice of Flutter for next-gen IVI systems. Don’t miss this opportunity to discover whether Flutter is right for your project.
Safelyio Toolbox Talk Softwate & App (How To Digitize Safety Meetings)
Consistent toolbox talks are critical for maintaining workplace safety, as they provide regular opportunities to address specific hazards and reinforce safe practices.
These brief, focused sessions ensure that safety is a continual conversation rather than a one-time event, which helps keep safety protocols fresh in employees' minds. Studies have shown that shorter, more frequent training sessions are more effective for retention and behavior change compared to longer, infrequent sessions.
Engaging workers regularly, toolbox talks promote a culture of safety, empower employees to voice concerns, and ultimately reduce the likelihood of accidents and injuries on site.
The traditional method of conducting safety talks with paper documents and lengthy meetings is not only time-consuming but also less effective. Manual tracking of attendance and compliance is prone to errors and inconsistencies, leading to gaps in safety communication and potential non-compliance with OSHA regulations. Switching to a digital solution like Safelyio offers significant advantages.
Safelyio automates the delivery and documentation of safety talks, ensuring consistency and accessibility. The microlearning approach breaks down complex safety protocols into manageable, bite-sized pieces, making it easier for employees to absorb and retain information.
This method minimizes disruptions to work schedules, eliminates the hassle of paperwork, and ensures that all safety communications are tracked and recorded accurately. Ultimately, using a digital platform like Safelyio enhances engagement, compliance, and overall safety performance on site. https://safelyio.com/
Oracle Database 19c New Features for DBAs and Developers.pptx
Oracle Database 19c New Features for DBAs and Developers. This video you can watch from my youtube channel at https://youtu.be/m-F-mZA3MkU
The Key to Digital Success_ A Comprehensive Guide to Continuous Testing Integ...
In today's business landscape, digital integration is ubiquitous, demanding swift innovation as a necessity rather than a luxury. In a fiercely competitive market with heightened customer expectations, the timely launch of flawless digital products is crucial for both acquisition and retention—any delay risks ceding market share to competitors.
Hand Rolled Applicative User Validation Code Kata
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.
All you need to know about Spring Boot and GraalVM
All you need to know about Spring Boot and GraalVM 🐰
How Can Hiring A Mobile App Development Company Help Your Business Grow?
ToXSL Technologies is an award-winning Mobile App Development Company in Dubai that helps businesses reshape their digital possibilities with custom app services. As a top app development company in Dubai, we offer highly engaging iOS & Android app solutions. https://rb.gy/necdnt
Malibou Pitch Deck For Its €3M Seed Round
French start-up Malibou raised a €3 million Seed Round to develop its payroll and human resources
management platform for VSEs and SMEs. The financing round was led by investors Breega, Y Combinator, and FCVC.
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留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
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Oracle 23c New Features For DBAs and Developers.pptx
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
Measures in SQL (SIGMOD 2024, Santiago, Chile)
SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
Liberarsi dai framework con i Web Component.pptx
In Italian
Presentazione sulle feature e l'utilizzo dei Web Component nell sviluppo di pagine e applicazioni web. Racconto delle ragioni storiche dell'avvento dei Web Component. Evidenziazione dei vantaggi e delle sfide poste, indicazione delle best practices, con particolare accento sulla possibilità di usare web component per facilitare la migrazione delle proprie applicazioni verso nuovi stack tecnologici.
Project Management: The Role of Project Dashboards.pdf
Project management is a crucial aspect of any organization, ensuring that projects are completed efficiently and effectively. One of the key tools used in project management is the project dashboard, which provides a comprehensive view of project progress and performance. In this article, we will explore the role of project dashboards in project management, highlighting their key features and benefits.
8 Best Automated Android App Testing Tool and Framework in 2024.pdf
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.
J-Spring 2024 - Going serverless with Quarkus, GraalVM native images and AWS ...
Presented at NLJUG's J-Spring 2024.
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国外毕业证学位证成绩单办理方法：
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教育部文凭学历认证认证的用途：
如果您计划在国内发展那么办理国内教育部认证是必不可少的。事业性用人单位如银行国企公务员在您应聘时都会需要您提供这个认证。其他私营 #外企企业无需提供！办理教育部认证所需资料众多且烦琐所有材料您都必须提供原件我们凭借丰富的经验帮您快速整合材料让您少走弯路。
实体公司专业为您服务如有需要请联系我: 微信95270640奈一次次令他失望山娃今年岁上五年级识得很多字从走出小屋开始山娃就知道父亲的家和工地共有一个很动听的名字——天河工地的底层空空荡荡很宽阔很凉爽在地上铺上报纸和水泥袋父亲和工人们中午全睡在地上地面坑坑洼洼山娃曾多次绊倒过也曾有长铁钉穿透凉鞋刺在脚板上但山娃不怕工地上也常有五六个从乡下来的小学生他们的父母亲也是高楼上的建筑工人小伙伴来自不同省份都操着带有浓重口音的普通话可不知为啥山娃不仅很快与他们熟识了
GreenCode-A-VSCode-Plugin--Dario-Jurisic
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如何办理(hull学位证书)英国赫尔大学毕业证硕士文凭原版一模一样
原版定制【微信:bwp0011】《(hull学位证书)英国赫尔大学毕业证硕士文凭》【微信:bwp0011】成绩单 、雅思、外壳、留信学历认证永久存档查询，采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信bwp0011】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信bwp0011】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
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Deliver Big Data, Database and AI/ML as-a-Service anywhere
- 1. Ravikumar Alluboyina, Tushar Doshi Robin Systems Deliver Big Data, Database and AI/ML as-a-Service anywhere
- 2. Who are we? SAMPLE CUSTOMER DEPLOYMENTS 11 billion security events ingested and analyzed a day (Elasticsearch, Logstash, Kibana, Kafka) 6 Petabytes under active management in a single Robin cluster (Cloudera, Impala, Kafka, Druid) 400 Oracle RAC databases managed by a single Robin cluster (Oracle, Oracle RAC) We have solved some fundamental problems to enable containers and Kubernetes for running complex Big Data, NoSQL, Database and AI/ML workloads Robin is The Kubernetes platform for big data, databases and AI/ML
- 3. What are the challenges with deployment of Big Data, NoSQL and Databases?
- 5. DN1 DN2 DN3 Node fault tolerance Compute anti-affinity
- 6. DN1 DN2DN3 Rack fault tolerance Compute anti-affinity Location Awareness Rack / DC
- 8. DN1 DN2DN3 Storage fault tolerance Compute anti-affinity Location Awareness Rack / DC Storage & Compute Affinity
- 9. DN1 DN2DN3 ZK2ZK1 ZK3 Storage performance Compute anti-affinity Location Awareness Rack / DC Storage & Compute Affinity
- 10. DN1 DN2DN3 ZK2ZK1 ZK3 Workload types and QoS enforcement Compute anti-affinity Location Awareness Rack / DC Storage & Compute Affinity IO patterns QoS
- 11. DN1 DN2DN3 ZK2ZK1 ZK3 CM Unprotected components Compute anti-affinity Location Awareness Rack / DC Storage & Compute Affinity IO patterns QoS
- 12. Compute anti-affinity DN1 DN2DN3 Location Awareness Rack / DC Storage & Compute Affinity ZK2ZK1 ZK3 IO patterns QoS CM High Availability Storage replication and failover
- 13. Compute anti-affinity DN1 DN2DN3 Location Awareness Rack / DC Storage & Compute Affinity ZK2ZK1 ZK3 IO patterns QoS CM High Availability Complete deployment NM NMGW GW HBase Hive Kudu KuduKudu KuduM KuduM KuduM Solr
- 14. Big data deployment and management challenges Storage & Compute Affinity Location Awareness Rack / DC Compute anti-affinity Scale-out compute and storageStorage workload types (IO patterns / QoS) High Availability Data Protection (Backup / DR) Snapshot / Rollback
- 16. Storage and Networking challenges › Latest 2018 CNCF: 48% say Storage is a big challenge, 44% say Networking is a challenge in Kubernetes › There are 27 Storage vendors and 21 Network vendors providing Storage & Networking solutions for containers and Kubernetes1 1 https://github.com/cncf/landscape Despite so many vendor solutions, why is it still a challenge for so many people? Storage vendors Network vendors
- 17. Challenges with containers Incomplete cgroups virtualization causes many Big Data and Databases to misbehave CPU › Contiguous core IDs, CPU ID mapping (Kudu), accurate threads:cores mapping (DB) › NUMA aware assignment (HANA) Memory: › JVM sees entire host memory even if you cap the memory for container (Any JVM app) › Memory allocation inconsistencies (hugepages, shared page cache) (Oracle) Storage › Apps that need raw block devices need correct WWNs management (e.g., Oracle, MapR) › blkio cgroups setting is useless to avoid noisy neighbor problems (All apps) Confidential – Restricted Distribution
- 18. Time to reframe our thinking Let applications drive infrastructure to meet user requirements (in this model application workflows configure Kubernetes, Networking and Storage)
- 19. Robin is The Kubernetes platform for big data, databases and AI/ML www.robin.io 1-click Provision 1-click Scale 1-click QoS Control 1-click Snapshots 1-click Clones 1-click Backup 1-click Upgrade 1-click Migrate
- 20. Robin Software Stack Virtual Networking App-aware Storage Robin’s built-in enterprise-grade storage stack Snapshots, Clones, QoS, Replication, Backup, Data rebalancing, Tiering, Thin-provisioning, Encryption, Compression Built-in flexible networking OVS, Calico, VLAN, Overlay networking, Persistent IPs Application Workflow Manager Kubernetes 1-click application Deploy, Snapshot, Clone, Scale, Upgrade, Backup Application workflows configure Kubernetes, Storage & Networking Works anywhere On-Prem (Bare Metal, VM) or Public-CloudCONFIDENTIAL – RESTRICTED DISTRIBUTION
- 21. Converged NodesCompute-only Nodes Storage-only Nodes Robin Software Stack Robin application-aware scale-out storage Robin’s built-in enterprise-grade storage stack Snapshots, Clones, QoS, Replication, Backup, Data rebalancing, Tiering, Thin-provisioning, Encryption, Compression Application-aware Networking Robin Agent Kublet K8S Master Robin RCM Built-in flexible networking OVS, Calico, VLAN, Overlay networking, Persistent IPs kubectl, helmrobin Robin programs Kubernetes StatefulSets, Persistent Volumes, Claims, Services, etc., are auto-created to meet application needs GPUGPU TensorFlowKafkaMongo Spark Hortonworks Oracle RAC Elastic Search Robin Agent Kublet Works any where On-Prem (Bare Metal, VM) or Public-Cloud Install to deploying apps in 15 minutes Kublet CONFIDENTIAL – RESTRICTED DISTRIBUTION
- 22. Enough talk.. Demo time …
- 24. Robin is The Kubernetes platform for big data, databases and AI/ML www.robin.io 1-click Provision 1-click Scale 1-click QoS Control 1-click Snapshots 1-click Clones 1-click Backup 1-click Upgrade 1-click Migrate