Migrating from OpenTracing to OpenTelemetry - Kubernetes Community Days Munic...SonjaChevre
At Tyk, we have recently started our efforts to migrate from OpenTracing to OpenTelemetry. I shared our approach at the Kubernetes Community Days in Munich in October. Here is what we have learned so far. I hope it will be helpful if you are, like us, at the beginning of your observability journey with OpenTelemetry.
See also: https://tyk.io/blog/migrating-from-opentracing-to-opentelemetry/
OpenTelemetry For GitOps: Tracing Deployments from Git Commit to ProductionAndreas Grabner
GitOps, with tools like Argo and Flux, are preferred platform tools managing configuration in cloud native environments. But it is hard to troubleshoot a failed deployment of a complex application as there is no built-in deployment lifecycle observability, standardized hooks nor the concept of an application vs individual workloads.
The CNCF project Keptn addresses those challenges by extending the Kubernetes Pod scheduler to provide OpenTelemetry Traces and Prometheus metrics for end-2-end deployment observability. Keptn introduces automated application-aware pre- and post-deployment lifecycle hooks to enforce dependency checks, send notifications or evaluates SLOs that otherwise need a custom K8s operator.
Join this talk and learn how the Keptn Lifecycle Toolkit (KLT) Operator extends observability into GitOps deployments and how it enables declarative deployment lifecycle orchestration!
TLC2018 Thomas Haver: The Automation Firehose - Be Strategic and TacticalAnna Royzman
Thomas Haver teaches how to automate both strategically and tactically to maximize the benefits of automation - at Test Leadership Congress 2018.
http://testleadershipcongress-ny.com
UI Dev in Big data world using open sourceTech Triveni
He will be sharing his last 10 years of experience in UI Development for Big Data Analytics & ML world using available open-source plethora in the market. How 'UI dev' needs to target big data problems?
Key points to consider while choosing any open-source framework/library for the big data world.
Do you need to write a custom framework or use ready-made open source, when what to choose?
How dev can leverage open source frameworks like Angular, REACT to making big data apps faster?
How you can extend open-source BI tools like Kibana, superset graphana to make UI development tool?
How to show network big data using open source graph libraries?
How to deal with real-time data in Big data UI?
Why use & contribute to open source?
Design UI for future as in Big data world customer problems keep changing with time. Showcasing demo for our real customer's problems, how we achieved using these open source libraries.
Bridging the Gap: from Data Science to ProductionFlorian Wilhelm
A recent but quite common observation in industry is that although there is an overall high adoption of data science, many companies struggle to get it into production. Huge teams of well-payed data scientists often present one fancy model after the other to their managers but their proof of concepts never manifest into something business relevant. The frustration grows on both sides, managers and data scientists.
In my talk I elaborate on the many reasons why data science to production is such a hard nut to crack. I start with a taxonomy of data use cases in order to easier assess technical requirements. Based thereon, my focus lies on overcoming the two-language-problem which is Python/R loved by data scientists vs. the enterprise-established Java/Scala. From my project experiences I present three different solutions, namely 1) migrating to a single language, 2) reimplementation and 3) usage of a framework. The advantages and disadvantages of each approach is presented and general advices based on the introduced taxonomy is given.
Additionally, my talk also addresses organisational as well as problems in quality assurance and deployment. Best practices and further references are presented on a high-level in order to cover all facets of data science to production.
With my talk I hope to convey the message that breakdowns on the road from data science to production are rather the rule than the exception, so you are not alone. At the end of my talk, you will have a better understanding of why your team and you are struggling and what to do about it.
Migrating from OpenTracing to OpenTelemetry - Kubernetes Community Days Munic...SonjaChevre
At Tyk, we have recently started our efforts to migrate from OpenTracing to OpenTelemetry. I shared our approach at the Kubernetes Community Days in Munich in October. Here is what we have learned so far. I hope it will be helpful if you are, like us, at the beginning of your observability journey with OpenTelemetry.
See also: https://tyk.io/blog/migrating-from-opentracing-to-opentelemetry/
OpenTelemetry For GitOps: Tracing Deployments from Git Commit to ProductionAndreas Grabner
GitOps, with tools like Argo and Flux, are preferred platform tools managing configuration in cloud native environments. But it is hard to troubleshoot a failed deployment of a complex application as there is no built-in deployment lifecycle observability, standardized hooks nor the concept of an application vs individual workloads.
The CNCF project Keptn addresses those challenges by extending the Kubernetes Pod scheduler to provide OpenTelemetry Traces and Prometheus metrics for end-2-end deployment observability. Keptn introduces automated application-aware pre- and post-deployment lifecycle hooks to enforce dependency checks, send notifications or evaluates SLOs that otherwise need a custom K8s operator.
Join this talk and learn how the Keptn Lifecycle Toolkit (KLT) Operator extends observability into GitOps deployments and how it enables declarative deployment lifecycle orchestration!
TLC2018 Thomas Haver: The Automation Firehose - Be Strategic and TacticalAnna Royzman
Thomas Haver teaches how to automate both strategically and tactically to maximize the benefits of automation - at Test Leadership Congress 2018.
http://testleadershipcongress-ny.com
UI Dev in Big data world using open sourceTech Triveni
He will be sharing his last 10 years of experience in UI Development for Big Data Analytics & ML world using available open-source plethora in the market. How 'UI dev' needs to target big data problems?
Key points to consider while choosing any open-source framework/library for the big data world.
Do you need to write a custom framework or use ready-made open source, when what to choose?
How dev can leverage open source frameworks like Angular, REACT to making big data apps faster?
How you can extend open-source BI tools like Kibana, superset graphana to make UI development tool?
How to show network big data using open source graph libraries?
How to deal with real-time data in Big data UI?
Why use & contribute to open source?
Design UI for future as in Big data world customer problems keep changing with time. Showcasing demo for our real customer's problems, how we achieved using these open source libraries.
Bridging the Gap: from Data Science to ProductionFlorian Wilhelm
A recent but quite common observation in industry is that although there is an overall high adoption of data science, many companies struggle to get it into production. Huge teams of well-payed data scientists often present one fancy model after the other to their managers but their proof of concepts never manifest into something business relevant. The frustration grows on both sides, managers and data scientists.
In my talk I elaborate on the many reasons why data science to production is such a hard nut to crack. I start with a taxonomy of data use cases in order to easier assess technical requirements. Based thereon, my focus lies on overcoming the two-language-problem which is Python/R loved by data scientists vs. the enterprise-established Java/Scala. From my project experiences I present three different solutions, namely 1) migrating to a single language, 2) reimplementation and 3) usage of a framework. The advantages and disadvantages of each approach is presented and general advices based on the introduced taxonomy is given.
Additionally, my talk also addresses organisational as well as problems in quality assurance and deployment. Best practices and further references are presented on a high-level in order to cover all facets of data science to production.
With my talk I hope to convey the message that breakdowns on the road from data science to production are rather the rule than the exception, so you are not alone. At the end of my talk, you will have a better understanding of why your team and you are struggling and what to do about it.
Automation: The Good, The Bad and The Ugly with DevOpsGuys - AppD Summit EuropeAppDynamics
A cornerstone of the DevOps philosophy, investment in automation at all stages across the SDLC has increased over recent years. Automation promises velocity and reduced errors, helps foster repeatable processes, and removes the need for long hours on dull, repetitive tasks. So what’s not to like? The downside of automation is that unless applied at the right place in your SDLC it can make a bad process worse. Automation also raises questions around job security, the need for re-skilling in other areas, and tool sprawl if different teams each choose their preferred technology. This session will outline:
-A short chronology of where automation has impacted the modern software stack
-Where it makes the most sense to automate (by identifying your key constraints)
-Best practices for adopting automation and how to identify where it’s working — and where it isn’t
For more information, visit: www.appdynamics.com
DevOpsGuys - DevOps Automation - The Good, The Bad and The UglyDevOpsGroup
DevOpsGuys - DevOps Automation - The Good, The Bad and The Ugly gives an overview of the strengths and weaknesses of DevOps automation, tips on developing your automation strategy, and a high level overview of automation options across the DevOps toolchain.
Unlocking the Power of ChatGPT and AI in Testing - NextSteps, presented by Ap...Applitools
Gain insights into the practical applications of ChatGPT, Bard, and other AI-based technological advancements, including GitHub CoPilot and Applitools Self-Healing Cloud, in this session with Anand Bagmar. Through specific use cases, Anand demonstrates how to enhance test automation processes—making them faster, more stable, and easier to implement.
Session recording and more info at applitools.com
Uncover how these tools can revolutionize your testing strategies and stay ahead of the curve in the ever-evolving world of test automation.
Intro to GitOps with Weave GitOps, Flagger and LinkerdWeaveworks
You may not think of "GitOps" and "service mesh" together – but maybe you should! These two wildly different technologies are each enormously capable independently, and combined they deliver far more than the sum of their parts: a single Git commit can control workflows customized for your exact situation by taking advantage of the service mesh's ability to measure and manipulate traffic anywhere in your application's call graph, and you can rest easy knowing that Git is preserving the complete configuration for your entire application every step of the way.
See how these technologies can work together to tackle complex problems in cloud-native applications.
What you’ll get out of this:
* Understand what GitOps and service meshes can - and can't - do for you.
* Understand basic operations with GitOps and Linkerd.
* Understand the basics of continuous deployment with Weave GitOps and Linkerd.
Mindtree provides devops service that builds continuous delivery capabilities with tool choices through a DevSecOps maturity assessment framework. Click here to know more.
Machine Learning is increasingly being used by companies as a disruptor or providing a USP. This means that Machine Learning models need to cope with being a critical part of solutions and if those solutions use PCI-DSS or PII then the models must be highly secure.
In addition, if a Machine Learning model is part of your USP then you will want to protect it. Also, the EU AI Regulation and UK AI Strategy means that AI is becoming increasingly regulated. This means you need to be able to prove what model made a prediction and why it made it by providing auditability and explainabilty.
In this talk we go over these issues and how to address them including using AWS and how to implement development best practices.
Everyone heard about Kubernetes. Everyone wants to use this tool. However, sometimes we forget about security, which is essential throughout the container lifecycle.
Therefore, our journey with Kubernetes security should begin in the build stage when writing the code becomes the container image.
Kubernetes provides innate security advantages, and together with solid container protection, it will be invincible.
During the sessions, we will review all those features and highlight which are mandatory to use. We will discuss the main vulnerabilities which may cause compromising your system.
Contacts:
LinkedIn - https://www.linkedin.com/in/vshynkar/
GitHub - https://github.com/sqerison
-------------------------------------------------------------------------------------
Materials from the video:
The policies and docker files examples:
https://gist.github.com/sqerison/43365e30ee62298d9757deeab7643a90
The repo with the helm chart used in a demo:
https://github.com/sqerison/argo-rollouts-demo
Tools that showed in the last section:
https://github.com/armosec/kubescape
https://github.com/aquasecurity/kube-bench
https://github.com/controlplaneio/kubectl-kubesec
https://github.com/Shopify/kubeaudit#installation
https://github.com/eldadru/ksniff
Further learning.
A book released by CISA (Cybersecurity and Infrastructure Security Agency):
https://media.defense.gov/2021/Aug/03/2002820425/-1/-1/1/CTR_KUBERNETES%20HARDENING%20GUIDANCE.PDF
O`REILLY Kubernetes Security:
https://kubernetes-security.info/
O`REILLY Container Security:
https://info.aquasec.com/container-security-book
Thanks for watching!
How to Build Your Own Test Automation Framework?Dmitry Buzdin
Even though there are plenty of open source tools on the market every company needs to put them together and create a test automation framework on top. Best practices of doing that are quite well-known in industry and it is important to learn them before building your own framework. We will go through the core building blocks of test automation frameworks and how they are playing together. You will learn how to assemble your test automation toolchain out of open source libraries and how to integrate them together. The session will be heavily biased towards Java platform.
A selection of short stories where Azure DevOps saved the baconMatteo Emili
Session I held at MK.NET, where I introduced the services of Azure DevOps starting from real-world stories of usage or uncommon scenarios where it proved massively beneficial
Observe and command your fleets across any kubernetes with weave git opsWeaveworks
Modern day deployments can often resemble the chaos of navigating the high seas with poor visibility and the dangers of unexpected events. Dev and test environments, running test data sets and feature flags in the public cloud, and production being served from a self-managed site that securely hosts client data can all be a challenge without full observability and control.
In this webinar, we show how you can reliably expand your Kubernetes footprint with Weave GitOps. Confidently observe and control your fleets, all from a single pane of glass across any environment.
Join this webinar to learn how to:
Control the health and propagation of customized clusters
Easily assign and secure clusters across multiple teams for multiple purposes
Observe all actions across all environments all from within Git
Understand managing all deployments across your cluster and fleets
Let’s consider a world, not in the distant future but in the present, to feature a unique testing environment. A testing environment is completely separated from an organization’s other sandboxes. This environment for testing will allow everyone to test almost everything in production. The idea behind this testing environment is to accumulate valuable data that will help your production team make significant improvements. And that’s the secret ingredient? Feature Flags!
The most significant pain point for any production/testing environment is deciding if the idea is genius or foolish. Feature flags help you directly deploy your applications’ new versions and features into a production environment in miniature batches.
What are feature flags?
Feature flags is a coming-up-age software engineering method that allows developers to continually integrate into the primary’ trunk.’ With feature flags, developers can ship incomplete features into the production state. These features will be dormant till they are ready to be worked upon. Feature flags also play a quintessential role in software development and delivery. When the feature in development is complete, the code can be activated on demand. Read more about blog: https://cloudzenix.com/an-introduction-to-feature-flags/
Empowering developers and operators through Gitlab and HashiCorpMitchell Pronschinske
Companies digitally transforming themselves into modern, software-defined businesses are building their foundation on cloud native solutions like GitLab and Hashicorp. Together, GitLab, Terraform, and Vault are empowering organizations to be more iterative, flexible, and secure. Join us in this session to learn more about how GitLab and Hashicorp are lowering the barrier of entry into industrializing the application development and delivery process across the entire application lifecycle.
I am an instructor of the MLOps workshop for some anonymous startup incubation program where the objectives are (1) to orchestrate and deploy updates to the application and the deep learning model in a unified way. (2) To design a DevOps pipeline to coordinate retrieving the latest best model from the model registry, packaging the web application, deploying the web application and inferencing web service.
Automation: The Good, The Bad and The Ugly with DevOpsGuys - AppD Summit EuropeAppDynamics
A cornerstone of the DevOps philosophy, investment in automation at all stages across the SDLC has increased over recent years. Automation promises velocity and reduced errors, helps foster repeatable processes, and removes the need for long hours on dull, repetitive tasks. So what’s not to like? The downside of automation is that unless applied at the right place in your SDLC it can make a bad process worse. Automation also raises questions around job security, the need for re-skilling in other areas, and tool sprawl if different teams each choose their preferred technology. This session will outline:
-A short chronology of where automation has impacted the modern software stack
-Where it makes the most sense to automate (by identifying your key constraints)
-Best practices for adopting automation and how to identify where it’s working — and where it isn’t
For more information, visit: www.appdynamics.com
DevOpsGuys - DevOps Automation - The Good, The Bad and The UglyDevOpsGroup
DevOpsGuys - DevOps Automation - The Good, The Bad and The Ugly gives an overview of the strengths and weaknesses of DevOps automation, tips on developing your automation strategy, and a high level overview of automation options across the DevOps toolchain.
Unlocking the Power of ChatGPT and AI in Testing - NextSteps, presented by Ap...Applitools
Gain insights into the practical applications of ChatGPT, Bard, and other AI-based technological advancements, including GitHub CoPilot and Applitools Self-Healing Cloud, in this session with Anand Bagmar. Through specific use cases, Anand demonstrates how to enhance test automation processes—making them faster, more stable, and easier to implement.
Session recording and more info at applitools.com
Uncover how these tools can revolutionize your testing strategies and stay ahead of the curve in the ever-evolving world of test automation.
Intro to GitOps with Weave GitOps, Flagger and LinkerdWeaveworks
You may not think of "GitOps" and "service mesh" together – but maybe you should! These two wildly different technologies are each enormously capable independently, and combined they deliver far more than the sum of their parts: a single Git commit can control workflows customized for your exact situation by taking advantage of the service mesh's ability to measure and manipulate traffic anywhere in your application's call graph, and you can rest easy knowing that Git is preserving the complete configuration for your entire application every step of the way.
See how these technologies can work together to tackle complex problems in cloud-native applications.
What you’ll get out of this:
* Understand what GitOps and service meshes can - and can't - do for you.
* Understand basic operations with GitOps and Linkerd.
* Understand the basics of continuous deployment with Weave GitOps and Linkerd.
Mindtree provides devops service that builds continuous delivery capabilities with tool choices through a DevSecOps maturity assessment framework. Click here to know more.
Machine Learning is increasingly being used by companies as a disruptor or providing a USP. This means that Machine Learning models need to cope with being a critical part of solutions and if those solutions use PCI-DSS or PII then the models must be highly secure.
In addition, if a Machine Learning model is part of your USP then you will want to protect it. Also, the EU AI Regulation and UK AI Strategy means that AI is becoming increasingly regulated. This means you need to be able to prove what model made a prediction and why it made it by providing auditability and explainabilty.
In this talk we go over these issues and how to address them including using AWS and how to implement development best practices.
Everyone heard about Kubernetes. Everyone wants to use this tool. However, sometimes we forget about security, which is essential throughout the container lifecycle.
Therefore, our journey with Kubernetes security should begin in the build stage when writing the code becomes the container image.
Kubernetes provides innate security advantages, and together with solid container protection, it will be invincible.
During the sessions, we will review all those features and highlight which are mandatory to use. We will discuss the main vulnerabilities which may cause compromising your system.
Contacts:
LinkedIn - https://www.linkedin.com/in/vshynkar/
GitHub - https://github.com/sqerison
-------------------------------------------------------------------------------------
Materials from the video:
The policies and docker files examples:
https://gist.github.com/sqerison/43365e30ee62298d9757deeab7643a90
The repo with the helm chart used in a demo:
https://github.com/sqerison/argo-rollouts-demo
Tools that showed in the last section:
https://github.com/armosec/kubescape
https://github.com/aquasecurity/kube-bench
https://github.com/controlplaneio/kubectl-kubesec
https://github.com/Shopify/kubeaudit#installation
https://github.com/eldadru/ksniff
Further learning.
A book released by CISA (Cybersecurity and Infrastructure Security Agency):
https://media.defense.gov/2021/Aug/03/2002820425/-1/-1/1/CTR_KUBERNETES%20HARDENING%20GUIDANCE.PDF
O`REILLY Kubernetes Security:
https://kubernetes-security.info/
O`REILLY Container Security:
https://info.aquasec.com/container-security-book
Thanks for watching!
How to Build Your Own Test Automation Framework?Dmitry Buzdin
Even though there are plenty of open source tools on the market every company needs to put them together and create a test automation framework on top. Best practices of doing that are quite well-known in industry and it is important to learn them before building your own framework. We will go through the core building blocks of test automation frameworks and how they are playing together. You will learn how to assemble your test automation toolchain out of open source libraries and how to integrate them together. The session will be heavily biased towards Java platform.
A selection of short stories where Azure DevOps saved the baconMatteo Emili
Session I held at MK.NET, where I introduced the services of Azure DevOps starting from real-world stories of usage or uncommon scenarios where it proved massively beneficial
Observe and command your fleets across any kubernetes with weave git opsWeaveworks
Modern day deployments can often resemble the chaos of navigating the high seas with poor visibility and the dangers of unexpected events. Dev and test environments, running test data sets and feature flags in the public cloud, and production being served from a self-managed site that securely hosts client data can all be a challenge without full observability and control.
In this webinar, we show how you can reliably expand your Kubernetes footprint with Weave GitOps. Confidently observe and control your fleets, all from a single pane of glass across any environment.
Join this webinar to learn how to:
Control the health and propagation of customized clusters
Easily assign and secure clusters across multiple teams for multiple purposes
Observe all actions across all environments all from within Git
Understand managing all deployments across your cluster and fleets
Let’s consider a world, not in the distant future but in the present, to feature a unique testing environment. A testing environment is completely separated from an organization’s other sandboxes. This environment for testing will allow everyone to test almost everything in production. The idea behind this testing environment is to accumulate valuable data that will help your production team make significant improvements. And that’s the secret ingredient? Feature Flags!
The most significant pain point for any production/testing environment is deciding if the idea is genius or foolish. Feature flags help you directly deploy your applications’ new versions and features into a production environment in miniature batches.
What are feature flags?
Feature flags is a coming-up-age software engineering method that allows developers to continually integrate into the primary’ trunk.’ With feature flags, developers can ship incomplete features into the production state. These features will be dormant till they are ready to be worked upon. Feature flags also play a quintessential role in software development and delivery. When the feature in development is complete, the code can be activated on demand. Read more about blog: https://cloudzenix.com/an-introduction-to-feature-flags/
Empowering developers and operators through Gitlab and HashiCorpMitchell Pronschinske
Companies digitally transforming themselves into modern, software-defined businesses are building their foundation on cloud native solutions like GitLab and Hashicorp. Together, GitLab, Terraform, and Vault are empowering organizations to be more iterative, flexible, and secure. Join us in this session to learn more about how GitLab and Hashicorp are lowering the barrier of entry into industrializing the application development and delivery process across the entire application lifecycle.
I am an instructor of the MLOps workshop for some anonymous startup incubation program where the objectives are (1) to orchestrate and deploy updates to the application and the deep learning model in a unified way. (2) To design a DevOps pipeline to coordinate retrieving the latest best model from the model registry, packaging the web application, deploying the web application and inferencing web service.
Cleaning Up the Dirt of the Nineties - How New Protocols are Modernizing the WebSteffen Gebert
About HTTP/2, QUIC, and Multipath TCP.
Download of PDF file recommended (Slideshare screws backgrounds up)
Talk at the TYPO3camp Vienna
Vienna, Austria, 06.-08.05.2016
Interner Git-Power-Workshop am Lehrstuhl für Informatik III
Dauer: 2,45 h
Teilnehmer hatten die Gelegenheit, Gelerntes direkt am eigenen Laptop auszuprobieren.
Neuigkeiten aus dem TYPO3-Projekt - der aktuelle Stand von TYPO3 CMS 6.0, TYPO3 Neos und TYPO3 Flow.
Vortrag auf der 1. CMS Night Nürnberg, im Rahmen der Nürnberg Web Week
Nürnberg, 23.10.2012
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
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
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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.
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/
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.
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!
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
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.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
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.
14. 14
Evaluation Key and Evaluation Context
@StGebert
§ Evaluation Context
• Information available at that time and
potentially helpful
§ Evaluation Key
• Uniquely identifies the “unit”
• Often user ID, but depends
• Allows individual targeting
• Used for percentage-based allocation
§ Some platforms allow percentage based
on attrributes
16. Server SDK Client SDK
16
@StGebert
SDK Types
§ Flag information for all users
§ Local decision based on all flag
information available locally
§ Fetched on init and later updated
§ Usually not charged per user*
§ Flags specific for this user
§ Calls Evaluation API of platform to
retrieve results
§ Fetched on init and later updated
§ Charged per user
* except split.io
21. Startup Failure Runtime failure
21
@StGebert
Resiliency
§ Unable to connect
• Don’t abort application start
• Serve default values
• Retry connection
§ Unable to connect
• Serve stale flag data
• Retry connection
§ Feature flag not found
• Serve default value
22. 22
Testing Code with Feature Flags
@StGebert
§ Unit tests
• Function for old and new
• Mocking SDK calls
• Test data sources
• Reading flags from file
§ Integration tests
• Reading flags from file
• Test data sources
• Separate environment (that nobody screws up)
23. 23
There is more..
@StGebert
§ Lambda and Proxies
§ Feature flag organisation and cleanup
§ Automated canary deployment
• Analysis of test vs. control group
• Self-destructing flags
24. 24
OpenFeature
@StGebert
§ Like OpenTelemetry for feature management
§ Goal: One API and SDK for all platforms
§ I’ve been mostly using OF terminology
§ Recommended read for getting familiar
https://github.com/open-feature/spec/blob/main/specification/glossary.md
https://github.com/open-feature/research/tree/main/research
26. 26
Cellular IoT Connectivity Anywhere in the World
180 countries
540 networks
2G, 3G, 4G, 5G
LTE-M, NB-IoT
Pay-as-you go pricing
with data pooling
@StGebert
28. EMnify’s IoT Communications Cloud
28
CU STOMER
IOT STACK S &
AP P LICATION S
EMNIFY IoT COMMUNICATIONS CLOUD
Authentication
Mobility
Management
Messaging
Identity
Lifecycle
Management
Policy Control Diagnostics
SIM Logistics Statistics
NET WORK SERVI C ES BUSI NESS SERVI C ES
Packet
Gateway Data Streams
Cloud Connect
VPN
REGIONAL Breakout
Event & Metering Streams
R ADIO
ACCESS
N ETW OR K S
2-5G, LPWAN
Edge Computing
IP Datagrams
Address Allocation
Secure DNS
Packet Inspection
On premise
GLOBALLY DI ST RI BUT ED DATA T RANSPORT
API
NEW
EMNI F Y
P ROGRAMMABLE
SI M
CU S T OMER
IOT DEVICE
33. 33
Further Material
§ Feature Toggles: The Good, The Bad, and The Ugly (Andy Davies, DevoxxUK)
https://www.youtube.com/watch?v=r7VI5x2XKXw
§ Self-Destructing Feature Flags (Jamie Gaskins, SREcon22 Americas)
https://www.youtube.com/watch?v=NPbXFZvCmZs
§ Production Oriented Development (Paul Osman)
https://paulosman.me/2019/12/30/production-oriented-development/
§ Feature Toggles (aka Feature Flags) (Pete Hodgson)
https://martinfowler.com/articles/feature-toggles.html
@StGebert
34. Summary
34
@StGebert
Each of them will help you
Differ in advanved features
Picked LaunchDarkly
Extremely easy and
promising journey
Experimentation
OpenFeature
Platforms Outlook
EMnify