An outline of how Moneytree uses Amazon SWF to coordinate our backend aggregation workflow. Focuses on how to run a large scale distributed system with a few developers while still sleeping at night.
Introduction to Big Data & Big Data 1.0 SystemPetr Novotný
Big Data, a recent phenomenon. Everyone talks about it, but do you really know what Big Data is? Join our four-part series about Big Data and you will get answers to your questions!
We will cover Introduction to Big Data and available platforms which we can use to deal with Big Data. And in the end, we are going to give you an insight into the possible future of dealing with Big Data.
Today we will start with a brief introduction to Big Data. We will talk about how Big Data is generated, where we can apply it and also about the first world-wide famous platform of BigData 1.0 System, which is Hadoop.
#CHEDTEB
www.chedteb.eu
Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.
everyone need to some storage and data.this big data is increase the data capacity and processing power.
Big Data may well be the Next Big Thing in the IT world.
• Big data burst upon the scene in the first decade of the 21st century.
• The first organizations to embrace it were online and startup firms. Firms like Google, eBay, LinkedIn, and Facebook were built around big data from the beginning.
• Like many new information technologies, big data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings.
Introduction to Big Data & Big Data 1.0 SystemPetr Novotný
Big Data, a recent phenomenon. Everyone talks about it, but do you really know what Big Data is? Join our four-part series about Big Data and you will get answers to your questions!
We will cover Introduction to Big Data and available platforms which we can use to deal with Big Data. And in the end, we are going to give you an insight into the possible future of dealing with Big Data.
Today we will start with a brief introduction to Big Data. We will talk about how Big Data is generated, where we can apply it and also about the first world-wide famous platform of BigData 1.0 System, which is Hadoop.
#CHEDTEB
www.chedteb.eu
Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.
everyone need to some storage and data.this big data is increase the data capacity and processing power.
Big Data may well be the Next Big Thing in the IT world.
• Big data burst upon the scene in the first decade of the 21st century.
• The first organizations to embrace it were online and startup firms. Firms like Google, eBay, LinkedIn, and Facebook were built around big data from the beginning.
• Like many new information technologies, big data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings.
1.Introduction
2.Overview
3.Why Big Data
4.Application of Big Data
5.Risks of Big Data
6.Benefits & Impact of Big Data
7.Conclusion
‘Big Data’ is similar to ‘small data’, but bigger in size
But having data bigger it requires different approaches:
Techniques, tools and architecture
An aim to solve new problems or old problems in a better
way
Big Data generates value from the storage and processing
of very large quantities of digital information that cannot be
analyzed with traditional computing techniques.
Big Data refers to the bulk amount of data while Hadoop is a framework to process this data.
There are various technologies and fields under Big Data. Big Data finds its applications in various areas like healthcare, military and various other fields.
http://www.techsparks.co.in/thesis-topics-in-big-data-and-hadoop/
Big Data Analytics: Applications and Opportunities in On-line Predictive Mode...BigMine
Talk by Usama Fayyad at BigMine12 at KDD12.
Virtually all organizations are having to deal with Big Data in many contexts: marketing, operations, monitoring, performance, and even financial management. Big Data is characterized not just by its size, but by its Velocity and its Variety for which keeping up with the data flux, let alone its analysis, is challenging at best and impossible in many cases. In this talk I will cover some of the basics in terms of infrastructure and design considerations for effective an efficient BigData. In many organizations, the lack of consideration of effective infrastructure and data management leads to unnecessarily expensive systems for which the benefits are insufficient to justify the costs. We will refer to example frameworks and clarify the kinds of operations where Map-Reduce (Hadoop and and its derivatives) are appropriate and the situations where other infrastructure is needed to perform segmentation, prediction, analysis, and reporting appropriately – these being the fundamental operations in predictive analytics. We will thenpay specific attention to on-line data and the unique challenges and opportunities represented there. We cover examples of Predictive Analytics over Big Data with case studies in eCommerce Marketing, on-line publishing and recommendation systems, and advertising targeting: Special focus will be placed on the analysis of on-line data with applications in Search, Search Marketing, and targeting of advertising. We conclude with some technical challenges as well as the solutions that can be used to these challenges in social network data.
Big Data: The 6 Key Skills Every Business NeedsBernard Marr
Here are the 6 most important skills businesses require to address their big data needs.It is based on this blog post http://ow.ly/EQUhb by Bernard Marr.
Big Data for beginners, the main points you need to know. Simple answers to: What is Big Data? What are the benefits of Big Data? What is the future of Big Data?
Detailed description of big data, with the characteristics of it. What are the limitations of the traditional systems? Where we are using big data? And also the applications of big data.
Big Data Tutorial | What Is Big Data | Big Data Hadoop Tutorial For Beginners...Simplilearn
This presentation about Big Data will help you understand how Big Data evolved over the years, what is Big Data, applications of Big Data, a case study on Big Data, 3 important challenges of Big Data and how Hadoop solved those challenges. The case study talks about Google File System (GFS), where you’ll learn how Google solved its problem of storing increasing user data in early 2000. We’ll also look at the history of Hadoop, its ecosystem and a brief introduction to HDFS which is a distributed file system designed to store large volumes of data and MapReduce which allows parallel processing of data. In the end, we’ll run through some basic HDFS commands and see how to perform wordcount using MapReduce. Now, let us get started and understand Big Data in detail.
Below topics are explained in this Big Data presentation for beginners:
1. Evolution of Big Data
2. Why Big Data?
3. What is Big Data?
4. Challenges of Big Data
5. Hadoop as a solution
6. MapReduce algorithm
7. Demo on HDFS and MapReduce
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
This short slide deck provides a quick description of what logmatic does to help companies extract value from their logs with an effortless & powerful tool.
2011 06 15 velocity conf from visible ops to dev ops finalGene Kim
My presentation called "Creating the Dev/Test/PM/Ops Supertribe: From Visible Ops To DevOps"
2011 Velocity Conference:
http://velocityconf.com/velocity2011/public/schedule/detail/21123
1.Introduction
2.Overview
3.Why Big Data
4.Application of Big Data
5.Risks of Big Data
6.Benefits & Impact of Big Data
7.Conclusion
‘Big Data’ is similar to ‘small data’, but bigger in size
But having data bigger it requires different approaches:
Techniques, tools and architecture
An aim to solve new problems or old problems in a better
way
Big Data generates value from the storage and processing
of very large quantities of digital information that cannot be
analyzed with traditional computing techniques.
Big Data refers to the bulk amount of data while Hadoop is a framework to process this data.
There are various technologies and fields under Big Data. Big Data finds its applications in various areas like healthcare, military and various other fields.
http://www.techsparks.co.in/thesis-topics-in-big-data-and-hadoop/
Big Data Analytics: Applications and Opportunities in On-line Predictive Mode...BigMine
Talk by Usama Fayyad at BigMine12 at KDD12.
Virtually all organizations are having to deal with Big Data in many contexts: marketing, operations, monitoring, performance, and even financial management. Big Data is characterized not just by its size, but by its Velocity and its Variety for which keeping up with the data flux, let alone its analysis, is challenging at best and impossible in many cases. In this talk I will cover some of the basics in terms of infrastructure and design considerations for effective an efficient BigData. In many organizations, the lack of consideration of effective infrastructure and data management leads to unnecessarily expensive systems for which the benefits are insufficient to justify the costs. We will refer to example frameworks and clarify the kinds of operations where Map-Reduce (Hadoop and and its derivatives) are appropriate and the situations where other infrastructure is needed to perform segmentation, prediction, analysis, and reporting appropriately – these being the fundamental operations in predictive analytics. We will thenpay specific attention to on-line data and the unique challenges and opportunities represented there. We cover examples of Predictive Analytics over Big Data with case studies in eCommerce Marketing, on-line publishing and recommendation systems, and advertising targeting: Special focus will be placed on the analysis of on-line data with applications in Search, Search Marketing, and targeting of advertising. We conclude with some technical challenges as well as the solutions that can be used to these challenges in social network data.
Big Data: The 6 Key Skills Every Business NeedsBernard Marr
Here are the 6 most important skills businesses require to address their big data needs.It is based on this blog post http://ow.ly/EQUhb by Bernard Marr.
Big Data for beginners, the main points you need to know. Simple answers to: What is Big Data? What are the benefits of Big Data? What is the future of Big Data?
Detailed description of big data, with the characteristics of it. What are the limitations of the traditional systems? Where we are using big data? And also the applications of big data.
Big Data Tutorial | What Is Big Data | Big Data Hadoop Tutorial For Beginners...Simplilearn
This presentation about Big Data will help you understand how Big Data evolved over the years, what is Big Data, applications of Big Data, a case study on Big Data, 3 important challenges of Big Data and how Hadoop solved those challenges. The case study talks about Google File System (GFS), where you’ll learn how Google solved its problem of storing increasing user data in early 2000. We’ll also look at the history of Hadoop, its ecosystem and a brief introduction to HDFS which is a distributed file system designed to store large volumes of data and MapReduce which allows parallel processing of data. In the end, we’ll run through some basic HDFS commands and see how to perform wordcount using MapReduce. Now, let us get started and understand Big Data in detail.
Below topics are explained in this Big Data presentation for beginners:
1. Evolution of Big Data
2. Why Big Data?
3. What is Big Data?
4. Challenges of Big Data
5. Hadoop as a solution
6. MapReduce algorithm
7. Demo on HDFS and MapReduce
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
This short slide deck provides a quick description of what logmatic does to help companies extract value from their logs with an effortless & powerful tool.
2011 06 15 velocity conf from visible ops to dev ops finalGene Kim
My presentation called "Creating the Dev/Test/PM/Ops Supertribe: From Visible Ops To DevOps"
2011 Velocity Conference:
http://velocityconf.com/velocity2011/public/schedule/detail/21123
Big Data Day LA 2016/ Big Data Track - Rapid Analytics @ Netflix LA (Updated ...Data Con LA
This talk explores how Netflix equips its engineers with the freedom to find and introduce the right software for the job - even if it isn't used anywhere else in-house. Examples include how Netflix has enabled analysts to fluidly switch between MPP RDBMS and an auto-scaling Presto cluster, how Spark + NoSQL stores are used when deploying data sets to internal web apps, and how data scientists are enabled to work in the ML framework of their choosing and deploy models as a service.
The session outlines why IT operations teams need to be "SharePoint operational ready" by ensuring that when project teams handover solutions built using SharePoint, these can be supported using existing support tools and processes. The session covers IT operational management frameworks and how/why IT teams should plan to add SharePoint to their operational management duties. The session will cover roles, responsibilities and skills required in IT teams to be able to help the business manage and operate a SharePoint platform after "go-live". The session will look at some of the challenges and possible actions to overcome these in order to provide a stable and robust SharePoint operational management platform.
Join Panaya and a select few Salesforce Techincal Architects as we discuss best practices for maintaining and building healthy Salesforce architecture for your business.
Building a Compliance System for your BusinessSarah Sajedi
All businesses need to manage compliance tasks - audits, inspections, permits, etc. - here's how to build a compliance management system for your business.
Everything You Need to Know About RPA in 30 MinutesHelpSystems
Robotic process automation (RPA) is a term now heard across enterprises large and small. While there’s no doubt that RPA has become a popular part of many business’s automation strategies, there’s still a lot of confusion out there about what robotic process automation really is and what it can do for your organization.
If you’re hearing terms like digital workforce, software robot, and automation center of excellence, but aren’t sure what it all means, this webinar is for you. Watch to learn about the advantages of automation with RPA, real-life robotic process automation use cases, and common RPA terminology.
This RPA webinar also dives into topics like:
-What makes robotic process automation so popular
-Strategies for taking the first steps with RPA
-Avoiding common pitfalls when getting started
At Netflix, we've spent a lot of time thinking about how we can make our analytics group move quickly. Netflix's Data Engineering & Analytics organization embraces the company's culture of "Freedom & Responsibility".
How does a company with a $40 billion market cap and $6 billion in annual revenue keep their data teams moving with the agility of a tiny company?
How do hundreds of data engineers and scientists make the best decisions for their projects independently, without the analytics environment devolving into chaos?
We'll talk about how Netflix equips its business intelligence and data engineers with:
the freedom to leverage cloud-based data tools - Spark, Presto, Redshift, Tableau and others - in ways that solve our most difficult data problems
the freedom to find and introduce right software for the job - even if it isn't used anywhere else in-house
the freedom to create and drop new tables in production without approval
the freedom to choose when a question is a one-off, and when a question is asked often enough to require a self-service tool
the freedom to retire analytics and data processes whose value doesn't justify their support costs
Speaker Bios
Monisha Kanoth is a Senior Data Architect at Netflix, and was one of the founding members of the current streaming Content Analytics team. She previously worked as a big data lead at Convertro (acquired by AOL) and as a data warehouse lead at MySpace.
Jason Flittner is a Senior Business Intelligence Engineer at Netflix, focusing on data transformation, analysis, and visualization as part of the Content Data Engineering & Analytics team. He previously led the EC2 Business Intelligence team at Amazon Web Services and was a business intelligence engineer with Cisco.
Chris Stephens is a Senior Data Engineer at Netflix. He previously served as the CTO at Deep 6 Analytics, a machine learning & content analytics company in Los Angeles, and on the data warehouse teams at the FOX Audience Network and Anheuser-Busch.
At Netflix, we've spent a lot of time thinking about how we can make our analytics group move quickly. Netflix's Data Engineering & Analytics organization embraces the company's culture of "Freedom & Responsibility".
How does a company with a $40 billion market cap and $6 billion in annual revenue keep their data teams moving with the agility of a tiny company?
How do hundreds of data engineers and scientists make the best decisions for their projects independently, without the analytics environment devolving into chaos?
We'll talk about how Netflix equips its business intelligence and data engineers with:
the freedom to leverage cloud-based data tools - Spark, Presto, Redshift, Tableau and others - in ways that solve our most difficult data problems
the freedom to find and introduce right software for the job - even if it isn't used anywhere else in-house
the freedom to create and drop new tables in production without approval
the freedom to choose when a question is a one-off, and when a question is asked often enough to require a self-service tool
the freedom to retire analytics and data processes whose value doesn't justify their support costs
Mission: IT operations for a good night's sleepwwwally
IT Admins are responding to incidents on a day-to-day basis, but management wants to shift to service monitoring. The biggest mismatch there is the maturity level and misconception that technology will fix the GAP. We know that’s not true! Walter Eikenboom shows you how to get from component monitoring to LOB application monitoring with Microsoft System Center 2012 - Operations Manager SP1 and changing the operational paradigm to a private cloud service connecting System Center Orchestrator and System Center Service Manager 2012, creating processes to get your infrastructure to a private cloud. All set and sleep tight!
Similar to Moneytree - Data Aggregation with SWF (20)
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
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.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
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.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
2. Who Am I?
Ross Sharrott
Founder & CTO of Moneytree
American
10 Years in Japan (Feb 24!)
Previously Senior IT Manager
Love distributed architectures in the
cloud
10. 1 Account / Many Statements
But we had a problem…
To determine a CC balance, we need
information from multiple statements
We needed a post statement process
Download
Data
Process
Statements
Post Process
Statements
Store Data +
Additional
Information
12. Queue Falls Down
I know…I’ll use a queue!
Queues are linear
Where are we in the process?
Logged in yet? Processing data?
What do you do when a job fails?
How do you relate jobs to one workflow?
13. Enter SWF
AWS Managed Service
Coordinates Workflows / Maintains
history
Provides multiple queues called Task
Lists
Handle decision points with Deciders
Perform tasks with Activity Workers
15. SWF World – A Restaurant
Decider – does nothing, makes decisions
Workflow Starter – takes orders
Activity Worker – makes food
Activity Worker – distributes food
SWF – maintains history, distributes
tasks
16. Activity Worker
Very similar to any queue worker
Handles a specific task
Polls a Task List to get new info
Reports activity success or failure
Puts results in a DB or on S3, etc.
17. Workflow Decider
Uses workflow history to make decisions
Schedules tasks
Handles rescheduling failures & timeouts
Reacts to external events (Signals)
Reacts to completion events
20. 1 Day of Work
Yesterday:
70,000 Workflows
Average Completion Time: 1 Minute
575,000 Decision Tasks
146,000 Statements Processed
70,000 Aggregation Tasks
70,000 Post Process Tasks
22. How To Sleep At Night
Make Workers Scalable
Avoid SWF API Throttling
Expect Failures
Measure Everything
23. Make Workers Scalable
Separate concerns into individual
workers
Scale each worker process individually
Automate scaling your workers
Make workers idempotent
You can always try again
24. Avoid API Throttling
Don’t call GetWorkflowHistory
Stress test your implementation
Limits are by Region, not domain!
Get your limits raised
We hit limits on day 1
Use exponential retry
Have a circuit breaker
25. Expect Failures
Cloud = Failures
Dyno / EC2 instance restarts
Network & Service outages
Don’t wait for failed processes
Use aggressive timeouts
Use heartbeats for long processes
26. Monitor Everything
Use Performance Monitoring
10x increase in performance = 10x workers
New Relic & Cloudwatch
Centralize Logging
Cloud resources disappear w/their logs
Papertrail / Logentries
Log Everything & Setup Alerts
If you don’t log it, you can’t fix it
27. Sleep At Night
Make Workers Scalable
Avoid SWF API Throttling
Expect Failures
Measure Everything
28. Thank You!
Moneytree is hiring!
iOS Developers
API Developers / AWS Dev Ops
Technology Ninjas
Ross Sharrott Founder / CTO
rsharrott@moneytree.jp
@moneytreejp
Editor's Notes
Manager – does nothing, makes decisionsWaitress – takes ordersCook – makes foodHall Staff – delivers foodPOS System – maintains history, distributes tasks
Long Poll SWF for new decisions. Monitors a single decision task list.
Top Level is simpleBut…We can fail to login or need additional informationWe can fail to process a statement
Decider to handle the WorkflowData Aggregation Activity WorkerStatement Processing Activity WorkerPost Processing Activity WorkerShare Data via S3