A framework to classify and compare different cloud platforms - including Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS)
Open source big data landscape and possible ITS applicationsSoftwareMill
What is big data, and how open-source big data projects, such as Apache Spark, Kafka and Cassandra can be used in ITS (Intelligent Transport Systems) related projects.
Scylla Summit 2018: Scaling your time series data with NewtsScyllaDB
Today's datasets are growing at an exponential rate. Collection, storage, analysis, and reporting are becoming more challenging, and the results more valued. A decade ago, RRDTool's algorithms were well-suited to our requirements, but they fall short of scaling to current demands. A new direction is needed, one that prioritizes write-optimized storage, and that scales beyond a single host.
This presentation will provide an overview of Newts, a distributed time-series data store based on ScyllaDB, show how it compares to other solutions, and take a look at how it is integrated in OpenNMS.
Migrating Data Pipeline from MongoDB to CassandraDemi Ben-Ari
MongoDB is a great NoSQL database, it’s very flexible and easy to use,
but would it handle massive Read / Write throughput?
actually, what happens when you need to scale everything out and easily?
We will lay out the reasons and the steps of migrating our data pipeline to Apache Cassandra in a short period without having any prior knowledge.
We’ll list our lessons learned as well.
Bio:
Demi Ben-Ari, Sr. Data Engineer @Windward,
I have over 9 years of experience in building various systems both from the field of near real time applications and Big Data distributed systems.
Co-Organizer of the “Big Things” Big Data community:http://somebigthings.com/big-things-intro/
Exploring Alluxio for Daily Tasks at RobinhoodAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Exploring Alluxio for Daily Tasks at Robinhood
Jiawei Zhang, Data Platform Engineer (Robinhood)
Yichuan Huang, Data Platform Engineer (Robinhood)
Grace Lu, Data Platform Engineer (Robinhood)
Wenlong Xiong, Data Platform Engineer (Robinhood)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
MongoDB vs Scylla: Production Experience from Both Dev & Ops Standpoint at Nu...ScyllaDB
MongoDB has become the prominent NoSQL database engine and is now used for a wide variety of use cases because of its flexibility and ease of use for developers, while Scylla, a C++ rewrite of Cassandra, provides benefits through its architectural approach, including getting rid of the JVM and a CPU-level design that gets the most out of your hardware thanks to a CPU level design.
Numberly has been using MongoDB for over a decade and Scylla for over a year in production. The benefits of the Scylla architecture allied to the Cassandra ecosystem fuel a rapid adoption in a very wide range of use cases: from real-time data pipelines and analytics batches processing to web applications database backend.
Learn the motivations of such an adoption trend and why it proves to be successful so far while outlining its limits and why MongoDB is still here to stay!
Open source big data landscape and possible ITS applicationsSoftwareMill
What is big data, and how open-source big data projects, such as Apache Spark, Kafka and Cassandra can be used in ITS (Intelligent Transport Systems) related projects.
Scylla Summit 2018: Scaling your time series data with NewtsScyllaDB
Today's datasets are growing at an exponential rate. Collection, storage, analysis, and reporting are becoming more challenging, and the results more valued. A decade ago, RRDTool's algorithms were well-suited to our requirements, but they fall short of scaling to current demands. A new direction is needed, one that prioritizes write-optimized storage, and that scales beyond a single host.
This presentation will provide an overview of Newts, a distributed time-series data store based on ScyllaDB, show how it compares to other solutions, and take a look at how it is integrated in OpenNMS.
Migrating Data Pipeline from MongoDB to CassandraDemi Ben-Ari
MongoDB is a great NoSQL database, it’s very flexible and easy to use,
but would it handle massive Read / Write throughput?
actually, what happens when you need to scale everything out and easily?
We will lay out the reasons and the steps of migrating our data pipeline to Apache Cassandra in a short period without having any prior knowledge.
We’ll list our lessons learned as well.
Bio:
Demi Ben-Ari, Sr. Data Engineer @Windward,
I have over 9 years of experience in building various systems both from the field of near real time applications and Big Data distributed systems.
Co-Organizer of the “Big Things” Big Data community:http://somebigthings.com/big-things-intro/
Exploring Alluxio for Daily Tasks at RobinhoodAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Exploring Alluxio for Daily Tasks at Robinhood
Jiawei Zhang, Data Platform Engineer (Robinhood)
Yichuan Huang, Data Platform Engineer (Robinhood)
Grace Lu, Data Platform Engineer (Robinhood)
Wenlong Xiong, Data Platform Engineer (Robinhood)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
MongoDB vs Scylla: Production Experience from Both Dev & Ops Standpoint at Nu...ScyllaDB
MongoDB has become the prominent NoSQL database engine and is now used for a wide variety of use cases because of its flexibility and ease of use for developers, while Scylla, a C++ rewrite of Cassandra, provides benefits through its architectural approach, including getting rid of the JVM and a CPU-level design that gets the most out of your hardware thanks to a CPU level design.
Numberly has been using MongoDB for over a decade and Scylla for over a year in production. The benefits of the Scylla architecture allied to the Cassandra ecosystem fuel a rapid adoption in a very wide range of use cases: from real-time data pipelines and analytics batches processing to web applications database backend.
Learn the motivations of such an adoption trend and why it proves to be successful so far while outlining its limits and why MongoDB is still here to stay!
ClustrixDB: how distributed databases scale outMariaDB plc
ClustrixDB, now part of MariaDB, is a fully distributed and transactional RDBMS for applications with the highest scalability requirements. In this session Robbie Mihalyi, VP of Engineering for ClustrixDB, provides an introduction to ClustrixDB, followed by an in-depth technical overview of its architecture, with a focus on distributed storage, transactions and query processing – and its unique approach to index partitioning.
DynomiteDB is a high performance Dynamo layer that adds data replication and sharding to Redis and other single-server storage engines, plus the ability to scale linearly, high availability via a shared nothing architecture with no single point of failure (SPOF), and support for 1000+ node clusters that span multiple data centers.
SQL, NoSQL, Distributed SQL: Choose your DataStore carefullyMd Kamaruzzaman
In modern Software Development and Software Architecture, selecting the right DataStore is one of the most challenging and important task. In this presentation, I have summarized the major DataStores and the decision criteria to select the right DataStore according to the use case.
Presto talk @ Global AI conference 2018 Bostonkbajda
Presented at Global AI Conference in Boston 2018:
http://www.globalbigdataconference.com/boston/global-artificial-intelligence-conference-106/speaker-details/kamil-bajda-pawlikowski-62952.html
Presto, an open source distributed SQL engine, is widely recognized for its low-latency queries, high concurrency, and native ability to query multiple data sources. Proven at scale in a variety of use cases at Facebook, Airbnb, Netflix, Uber, Twitter, LinkedIn, Bloomberg, and FINRA, Presto experienced an unprecedented growth in popularity in both on-premises and cloud deployments in the last few years. Presto is really a SQL-on-Anything engine in a single query can access data from Hadoop, S3-compatible object stores, RDBMS, NoSQL and custom data stores. This talk will cover some of the best use cases for Presto, recent advancements in the project such as Cost-Based Optimizer and Geospatial functions as well as discuss the roadmap going forward.
HBaseCon2017 Splice Machine as a Service: Multi-tenant HBase using DCOS (Meso...HBaseCon
The talk will go through the following topics and experiences.
1. Container Strategy and Implementation for HBase.
2. Resource Management inside a containerized environment.
3. Network Isolation and Policy Management (Project Calico)
4. Orchestration Structure using DCOS Commons
5. Internal and External Load Balancing using Marathon Load Balancer.
6. Auto-scaling of HBase
7. AWS Deployment learnings.
This talk will be interesting to developers and administrators who are attempting to automate the deployment of HBase and HDFS in containers.
by John Leach and Daniel Gomez Ferro of Splice Machine
How Alibaba Cloud scaled ApsaraDB with MariaDB MaxScaleMariaDB plc
ApsaraDB is the leading cloud database in China with millions of database instances are running on it. However, the diversity and complexity of the mission-critical applications using it brought a huge challenge to ApsaraDB, scalability – a long-time pain point. To solve the problem, in middle of 2018 and after a careful evaluation, an elegant solution was found in MariaDB MaxScale. So far, the deep synergy of MariaDB MaxScale and ApsaraDB has proved very successful as thousands of high-demand customers of ApsaraDB are benefiting from a much-improved experience. In this presentation, we are going to share following topics:
- How ApsaraDB is using MariaDB MaxScale
- Best practices when leveraging MariaDB MaxScale with ApsaraDB
- Next steps and future plans for for MariaDB MaxScale and ApsaraDB
In 2018's user conference keynote MariaDB CEO, Michael Howard, announced an initiative to build a MariaDB DBaaS platform. In this session, the DBaaS team shares how MariaDB is approaching DBaaS, then discusses the role of containers and Kubernetes, the need for infrastructure-agnostic provisioning, support for day-two operations and enterprise requirements for large-scale DBaaS deployments.
Big Data in 200 km/h | AWS Big Data Demystified #1.3 Omid Vahdaty
What we're about
A while ago I entered the challenging world of Big Data. As an engineer, at first, I was not so impressed with this field. As time went by, I realised more and more, The technological challenges in this area are too great to master by one person. Just look at the picture in this articles, it only covers a small fraction of the technologies in the Big Data industry…
Consequently, I created a meetup detailing all the challenges of Big Data, especially in the world of cloud. I am using AWS infrastructure to answer the basic questions of anyone starting their way in the big data world.
how to transform data (TXT, CSV, TSV, JSON) into Parquet, ORCwhich technology should we use to model the data ? EMR? Athena? Redshift? Spectrum? Glue? Spark? SparkSQL?how to handle streaming?how to manage costs?Performance tips?Security tip?Cloud best practices tips?
Some of our online materials:
Website:
https://big-data-demystified.ninja/
Youtube channels:
https://www.youtube.com/channel/UCzeGqhZIWU-hIDczWa8GtgQ?view_as=subscriber
https://www.youtube.com/channel/UCMSdNB0fGmX5dXI7S7Y_LFA?view_as=subscriber
Meetup:
https://www.meetup.com/AWS-Big-Data-Demystified/
https://www.meetup.com/Big-Data-Demystified
Facebook Group :
https://www.facebook.com/groups/amazon.aws.big.data.demystified/
Facebook page (https://www.facebook.com/Amazon-AWS-Big-Data-Demystified-1832900280345700/)
Audience:
Data Engineers
Data Science
DevOps Engineers
Big Data Architects
Solution Architects
CTO
VP R&D
Building tiered data stores using aesop to bridge sql and no sql systemsRegunath B
Slides from my talk on building tiered data stores using Aesop to bridge SQL and NoSQL data stores. Aesop is a pub-sub like change data capture and propagation system.
Scylla Summit 2022: New AWS Instances Perfect for ScyllaDBScyllaDB
In this talk AWS’ Ken Krupa, Head of Specialized Solutions Architecture, will describe the architecture and capabilities of two new AWS EC2 instance types perfect for data-intensive storage and IO-heavy workloads like ScyllaDB: the Intel-based I4i and the Graviton2-based I4g series.
The Intel Xeon Ice Lake-based I4i series provides unparalleled raw horsepower for your most demanding workloads. Meanwhile, the Graviton2-powered I4g instances provide lower cost per storage on a power-efficient platform to deploy your cloud-native applications.
Ken will also describe the AWS Nitro SSD, a new form of high-speed NVMe storage with a Flash Translation Layer built with Nitro controllers, which powers both of these instance families.
ScyllaDB VP of Product Tzach Livyatan will then share benchmarking results showing how ScyllaDB behaves under load on these two instance types, providing maximum system utility and efficiency.
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
Platform as a Service (PaaS) - A cloud service for Developers Ravindra Dastikop
Cloud Computing offers three fundamental categories of Services- namely IaaS, PaaS and SaaS. In this presentation, Platform as a Service is discussed. PaaS is a service aimed at developers and it enables them to design, develop and deploy applications on Cloud platforms
ClustrixDB: how distributed databases scale outMariaDB plc
ClustrixDB, now part of MariaDB, is a fully distributed and transactional RDBMS for applications with the highest scalability requirements. In this session Robbie Mihalyi, VP of Engineering for ClustrixDB, provides an introduction to ClustrixDB, followed by an in-depth technical overview of its architecture, with a focus on distributed storage, transactions and query processing – and its unique approach to index partitioning.
DynomiteDB is a high performance Dynamo layer that adds data replication and sharding to Redis and other single-server storage engines, plus the ability to scale linearly, high availability via a shared nothing architecture with no single point of failure (SPOF), and support for 1000+ node clusters that span multiple data centers.
SQL, NoSQL, Distributed SQL: Choose your DataStore carefullyMd Kamaruzzaman
In modern Software Development and Software Architecture, selecting the right DataStore is one of the most challenging and important task. In this presentation, I have summarized the major DataStores and the decision criteria to select the right DataStore according to the use case.
Presto talk @ Global AI conference 2018 Bostonkbajda
Presented at Global AI Conference in Boston 2018:
http://www.globalbigdataconference.com/boston/global-artificial-intelligence-conference-106/speaker-details/kamil-bajda-pawlikowski-62952.html
Presto, an open source distributed SQL engine, is widely recognized for its low-latency queries, high concurrency, and native ability to query multiple data sources. Proven at scale in a variety of use cases at Facebook, Airbnb, Netflix, Uber, Twitter, LinkedIn, Bloomberg, and FINRA, Presto experienced an unprecedented growth in popularity in both on-premises and cloud deployments in the last few years. Presto is really a SQL-on-Anything engine in a single query can access data from Hadoop, S3-compatible object stores, RDBMS, NoSQL and custom data stores. This talk will cover some of the best use cases for Presto, recent advancements in the project such as Cost-Based Optimizer and Geospatial functions as well as discuss the roadmap going forward.
HBaseCon2017 Splice Machine as a Service: Multi-tenant HBase using DCOS (Meso...HBaseCon
The talk will go through the following topics and experiences.
1. Container Strategy and Implementation for HBase.
2. Resource Management inside a containerized environment.
3. Network Isolation and Policy Management (Project Calico)
4. Orchestration Structure using DCOS Commons
5. Internal and External Load Balancing using Marathon Load Balancer.
6. Auto-scaling of HBase
7. AWS Deployment learnings.
This talk will be interesting to developers and administrators who are attempting to automate the deployment of HBase and HDFS in containers.
by John Leach and Daniel Gomez Ferro of Splice Machine
How Alibaba Cloud scaled ApsaraDB with MariaDB MaxScaleMariaDB plc
ApsaraDB is the leading cloud database in China with millions of database instances are running on it. However, the diversity and complexity of the mission-critical applications using it brought a huge challenge to ApsaraDB, scalability – a long-time pain point. To solve the problem, in middle of 2018 and after a careful evaluation, an elegant solution was found in MariaDB MaxScale. So far, the deep synergy of MariaDB MaxScale and ApsaraDB has proved very successful as thousands of high-demand customers of ApsaraDB are benefiting from a much-improved experience. In this presentation, we are going to share following topics:
- How ApsaraDB is using MariaDB MaxScale
- Best practices when leveraging MariaDB MaxScale with ApsaraDB
- Next steps and future plans for for MariaDB MaxScale and ApsaraDB
In 2018's user conference keynote MariaDB CEO, Michael Howard, announced an initiative to build a MariaDB DBaaS platform. In this session, the DBaaS team shares how MariaDB is approaching DBaaS, then discusses the role of containers and Kubernetes, the need for infrastructure-agnostic provisioning, support for day-two operations and enterprise requirements for large-scale DBaaS deployments.
Big Data in 200 km/h | AWS Big Data Demystified #1.3 Omid Vahdaty
What we're about
A while ago I entered the challenging world of Big Data. As an engineer, at first, I was not so impressed with this field. As time went by, I realised more and more, The technological challenges in this area are too great to master by one person. Just look at the picture in this articles, it only covers a small fraction of the technologies in the Big Data industry…
Consequently, I created a meetup detailing all the challenges of Big Data, especially in the world of cloud. I am using AWS infrastructure to answer the basic questions of anyone starting their way in the big data world.
how to transform data (TXT, CSV, TSV, JSON) into Parquet, ORCwhich technology should we use to model the data ? EMR? Athena? Redshift? Spectrum? Glue? Spark? SparkSQL?how to handle streaming?how to manage costs?Performance tips?Security tip?Cloud best practices tips?
Some of our online materials:
Website:
https://big-data-demystified.ninja/
Youtube channels:
https://www.youtube.com/channel/UCzeGqhZIWU-hIDczWa8GtgQ?view_as=subscriber
https://www.youtube.com/channel/UCMSdNB0fGmX5dXI7S7Y_LFA?view_as=subscriber
Meetup:
https://www.meetup.com/AWS-Big-Data-Demystified/
https://www.meetup.com/Big-Data-Demystified
Facebook Group :
https://www.facebook.com/groups/amazon.aws.big.data.demystified/
Facebook page (https://www.facebook.com/Amazon-AWS-Big-Data-Demystified-1832900280345700/)
Audience:
Data Engineers
Data Science
DevOps Engineers
Big Data Architects
Solution Architects
CTO
VP R&D
Building tiered data stores using aesop to bridge sql and no sql systemsRegunath B
Slides from my talk on building tiered data stores using Aesop to bridge SQL and NoSQL data stores. Aesop is a pub-sub like change data capture and propagation system.
Scylla Summit 2022: New AWS Instances Perfect for ScyllaDBScyllaDB
In this talk AWS’ Ken Krupa, Head of Specialized Solutions Architecture, will describe the architecture and capabilities of two new AWS EC2 instance types perfect for data-intensive storage and IO-heavy workloads like ScyllaDB: the Intel-based I4i and the Graviton2-based I4g series.
The Intel Xeon Ice Lake-based I4i series provides unparalleled raw horsepower for your most demanding workloads. Meanwhile, the Graviton2-powered I4g instances provide lower cost per storage on a power-efficient platform to deploy your cloud-native applications.
Ken will also describe the AWS Nitro SSD, a new form of high-speed NVMe storage with a Flash Translation Layer built with Nitro controllers, which powers both of these instance families.
ScyllaDB VP of Product Tzach Livyatan will then share benchmarking results showing how ScyllaDB behaves under load on these two instance types, providing maximum system utility and efficiency.
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
Platform as a Service (PaaS) - A cloud service for Developers Ravindra Dastikop
Cloud Computing offers three fundamental categories of Services- namely IaaS, PaaS and SaaS. In this presentation, Platform as a Service is discussed. PaaS is a service aimed at developers and it enables them to design, develop and deploy applications on Cloud platforms
There is no doubt that Openstack represents one of the massive industry alignment towards the Open source cloud, Some even touting it to be the linux of cloud computing. But is it “THE” perfect solution ?
Vanilla Openstack is a “Myth”
The choice of Openstack as part of your cloud strategy purely depends on the kind of workload and the add-on features.
Openstack can be a serious contender especially for fresh deployments and applications that are being architected for cloud. But as the environment gets diverse(legacy integrations) Openstack can be tricky to integrate and maintain
One might require a vendor based Cloud management platform especially when the cloud strategy involves public clouds(AWS, Azure, GCE) and migration of application services across
No doubt it is fully open source, but it comes with learning curve, release cycles, Vendor specific driver integrations etc.
Interesting developments with respect to containers, docker, Kubernetes, Mesosphere etc will challenge Openstack
Openstack will no doubt will grow mature over next couple of years, until then, the hunt for the CMP continues...
Topics of interest :
to build a true hyper converged cloud ?
as an enterprise cloud management platform ?
public cloud ? (as a CSP)
Telco carrier grade cloud ?
VNF, MANO and SDN integrations
Apache Stratos - Building a PaaS using OSGi and EquinoxPaul Fremantle
Apache Stratos is a PaaS built on top of Equinox and OSGi. Stratos runs all kinds of workloads including Java, OSGi, Tomcat apps, PHP, Node.js, MySQL, Mongo, Cassandra and others.
This session is an introduction to Stratos which will cover:
- How to get started
- Deploying on Amazon AWS and OpenStack Clouds
- Workloads Stratos supports
- Why and how Equinox is used
- Multi-tenancy and security
- Elastic scaling
- How Stratos compares to other PaaS systems
The session will include live demontrations of Stratos.
The session is aimed at those interested in PaaS models, as well as those with a strong interest in OSGi runtimes and Equinox.
These slides were presented at the Red Hat "Achieving True Integration Agility with Microservices, Containers and API's" workshop in Santa Clara on 10/26
Scenic City Summit (2021): Real-Time Streaming in any and all clouds, hybrid...Timothy Spann
Scenic city summit real-time streaming in any and all clouds, hybrid and beyond
24-September-2021. Scenic City Summit. Virtual. Real-Time Streaming in Any and All Clouds, Hybrid and Beyond
Apache Pulsar, Apache NiFi, Apache Flink
StreamNative
Tim Spann
https://sceniccitysummit.com/
Big data conference europe real-time streaming in any and all clouds, hybri...Timothy Spann
Biography
Tim Spann is a Principal DataFlow Field Engineer at Cloudera where he works with Apache NiFi, MiniFi, Pulsar, Apache Flink, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a senior solutions architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
Talk
Real-Time Streaming in Any and All Clouds, Hybrid and Beyond
Today, data is being generated from devices and containers living at the edge of networks, clouds and data centers. We need to run business logic, analytics and deep learning at the scale and as events arrive.
Tools:
Apache Flink, Apache Pulsar, Apache NiFi, MiNiFi, DJL.ai Apache MXNet.
References:
https://www.datainmotion.dev/2019/11/introducing-mm-flank-apache-flink-stack.html
https://www.datainmotion.dev/2019/08/rapid-iot-development-with-cloudera.html
https://www.datainmotion.dev/2019/09/powering-edge-ai-for-sensor-reading.html
https://www.datainmotion.dev/2019/05/dataworks-summit-dc-2019-report.html
https://www.datainmotion.dev/2019/03/using-raspberry-pi-3b-with-apache-nifi.html
Source Code: https://github.com/tspannhw/MmFLaNK
FLiP Stack
StreamNative
OpenShift is Red Hat's Platform-as-a-Service (PaaS) that lets developers quickly develop, host, and scale Docker container-based applications. OpenShift enables a uniform and standardised approach to container management across all hosting options including AWS/EC2 and other private/public cloud and on/off-premise variants. At this session, you will learn how Red Hat's enterprise clients are using OpenShift to enable their digital transformation initiatives. Examples will cover how realising a hybrid cloud strategy can simplify and reduce the risk of migrating and transitioning application workloads to containers in the cloud.
Alex Smith, Solutions Architect, Amazon Web Services, ASEAN
Stephen Bylo, Senior Solution Architect, Red Hat Asia Pacific Pte Ltd
First steps into developing an application as a suite of small services, and analysis of tools and architecture approaches to be used.
Topics covered:
1) What is a micro service architecture
2)Advantages in code procedures, team dynamics and scaling
3) How container services such as docker assist in its implementation
4) How to deploy code in a micro services architecture
5) Container Management tools and resource efficiency (mesos, kubernetes, aws container service)
6) Scaling up
By PeoplePerHour team
presented by CTO Spyros Lambrinidis & Senior DevOps Panagiotis Moustafellos @ Docker Athens Meetup 18/02/2015
QCon SF 2014 - Create and Deploy APIs using Web IDEs, Open Source Frameworks ...Restlet
This presentation explains how to develop a Web API in Java using (JAX-RS or Restlet API)
make an up-to-date web API documentation available online during crafting
manage access to this web API, including client SDKs generation, access management, firewall and analytics.
We will demonstrate how Restlet Platform provides a comprehensive solution combining the best of open source (Restlet Framework) and PaaS (Restlet APISpark) to solve web API needs.
Private, Managed, Public - All Things WSO2 CloudWSO2
To view recording of this webinar please use the below URL:
http://wso2.com/library/webinars/2015/06/private-managed-public-all-things-wso2-cloud/
During the session, you will learn:
Why customers choose WSO2 Managed Cloud, WSO2 Public Cloud or Private Cloud environments
What unique and differentiating private cloud capabilities are delivered by Apache Stratos 4.1, WSO2 Private PaaS, WSO2 App Factory, WSO2 App Cloud, and WSO2 API Cloud
How customers are structuring private cloud deployments and achieving business benefits
Similar to Accion Labs - Cloud in practice - Cloud computing platforms (20)
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
5. Cloud Computing Layers
Software
(SaaS)
Platform
(PaaS)
Infrastructure
(IaaS)
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6. Infrastructure
(IaaS)
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● Servers
● Blade Servers
● HPC
● KVM Console Servers
● Routers
● Switches
● Cables
● SAN Storage
● SSD SAN Storage
● Virtual Tape Libs
● NAS
Users
System
Engineers
Physical Machines
Network
Hardware
Storage Devices
Examples
● Server providers like IBM,
HP, Dell etc.
● Hosting providers like
Rackspace offer servers
on rent
Examples
● Network equipment
providers like Cisco,
Avaya, Motorola etc.
● Hosting providers offer
bundled network services
Examples
● Storage equipment
providers like Dell, NEC,
EMC etc.
● Hosting providers offer
storage on rent
7. Infrastructure
(IaaS)
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● Virtual computing
units
● Pool of resources
from different servers
● Automatic load
balancing, higher
availability
● Decouples virtual
networks from
network hardware
● Provides higher
utilization, flexibility
● Easier management
of resources
● Decouples storage
volumes from physical
hardware
● Caching,
snapshotting, high
availability
● IO optimization
independent of
computing resources
Users
Infrastructure
Engineers
Virtual Machines
Software Defined
Network (SDN)
Software Defined
Storage (SDS)
Examples
● Open Stack Nova
● Amazon EC2
● MS Windows Azure
● Google Compute Engine
● IBM SmartCloud
● VMware vSphere
Examples
● Open Stack Neutron
● Vmware Nicira (NSX)
Examples
● Open Stack Cinder
● Vmware Virtual SAN
8. Platform
(PaaS)
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● Containers for running
applications
● Compiled applications
along with run-time
support libraries can
be deployed
● Isolated, self-described
● Infrastructure agnostic
● Routing messages
between app
containers, storage
systems & external
systems
● Routing, queueing,
scheduling
● Load balancing
● Storage and retrieval
of objects
● No mounting
partitioning, formatting
● HTTP API for store
and retrieve
Users
DevOps
Engineers
Application
Containers
Routing,
Messaging
Object Storage
Examples
● Docker
● Dyno
● CloudFoundry Warden
● Google Imctfy
Examples
● CloudFoundry
Messaging/NATS
● Heroku Routing Layer
● CloudFoundry Router
Examples
● Open Stack Swift
● Amazon S3
● Ceph Storage
9. Platform
(PaaS)
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● Uses Application
Containers
● Runtime support (e.g.
JVM for Java,
Interpreters for
Python, PHP, Node.js,
Grails etc.)
● Middleware (e.g.
Tomcat, Spring)
● Provides
communication
among applications
● Routing,
Transformations,
Queuing
● Enterprise Service
Bus
● Ready-to-use
database as a service
● Relational, key-value,
column-oriented
database
● Availability and
scalability
Users
Professional
Developers
Application
Platforms
Integration
Platforms
Database
Platforms
Examples
● CloudFoundry Buildpacks
● Google App Engine
● Heroku Buildpacks
Examples
● TIBCO Cloud Bus
● WS02 StratosLive
● Windows Azure BizTalk
Services
Examples
● Amazon SimpleDB,
DynamoDB, RDS,
Redshift
● Object Rocket
(MongoDB, Riak)
● Windows Azure SQL
10. Software
(SaaS)
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● Computing
components, APIs
● Can be orchestrated
to build or extend
applications
● Can be customized
with configuration, or
Domain-specific
Languages (DSLs)
● Communication APIs
● Can be utilized to
provide pre-built
communication
services to
applications
● Customized using
configuration or DSLs
● Prebuilt storage
services
● Big data as a service
● Provides value-added
services such as
ready analytics tools
Users
Enterprise
Developers
Application
Components
Communication
Components
Storage
Components
Examples
● Force.com
● Google Prediction API
● Hubspot API
● Zuora API
● MuleSoft Anypoint
Connectors
Examples
● Amazon Simple Email
Service
● Twilio, Voxeo APIs for
unified communications
Examples
● Dropbox API
● Qlikview
● SAP Business Objects BI
On Demand
● TIBCO Silver Spotfire
11. Software
(SaaS)
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● Ready-to-use software applications
● Web and mobile interface
Users
● 3-tier architecture
● Typically multi-tenant
● Whole range from consumer to enterprise
applications
● Different licensing and payment options
End Users
● Software Applications
Examples
● Salesforce.com, hubspot.com, zuora.com,
netsuite.com, wordpress.com
● oracle on-demand, SAP on-demand
● Wordpress.org, Drupal, Liferay, SugarCRM,
Compiere.com
22. Platform
(PaaS)
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Analytical
Compute Grid
Data Warehouse
As a Service
SQL
Column Database
(Cassandra)
Ralational Database
(PostgreSQL)
HDFS
(Hadoop+Hive)
Data Source Index
(Mapping/Cassandra)
ODBC
JDBC
Management
API