How Linux Processes Your Network Packet - Elazar LeibovichDevOpsDays Tel Aviv
With buzz on eBPF, XDP, bpfilter etc,, it's important to get the basics right. We will show the route of a networ packet from kernel driver to TCP/IP stack to userspace socket and explain how and where it's processed en route.
Modern environment uses a lot of the Linux networking stack capability.
Every docker container requires a dedicated bridge, usually a few iptables entries to expose port, and a dnsmasq daemon, and masquarading to allow internet access.
It is hence important to understand Linux network fundumentals. From the driver interrupt/NAPI, to the network stack, the various filters it passes through and the various hooks you have at your disposal to alter and view the network packets flow.
We will first review the theory, and then present useful tools to apply the theory and debug problems in common situations.
We will survey common containers situations and see how packets move from the hardware to the container's veth.
Building a secure image pipeline with Ansible. Generating secure OS images for OpenShift Virtualization. Creating a immutable image pipeline with Ansible, OpenSCAP, Packer, Molecule and Vagrant. Packaging OS images for consumption to OpenShift Virtualization.
Virtual File System in Linux Kernel
Note: When you view the the slide deck via web browser, the screenshots may be blurred. You can download and view them offline (Screenshots are clear).
How Linux Processes Your Network Packet - Elazar LeibovichDevOpsDays Tel Aviv
With buzz on eBPF, XDP, bpfilter etc,, it's important to get the basics right. We will show the route of a networ packet from kernel driver to TCP/IP stack to userspace socket and explain how and where it's processed en route.
Modern environment uses a lot of the Linux networking stack capability.
Every docker container requires a dedicated bridge, usually a few iptables entries to expose port, and a dnsmasq daemon, and masquarading to allow internet access.
It is hence important to understand Linux network fundumentals. From the driver interrupt/NAPI, to the network stack, the various filters it passes through and the various hooks you have at your disposal to alter and view the network packets flow.
We will first review the theory, and then present useful tools to apply the theory and debug problems in common situations.
We will survey common containers situations and see how packets move from the hardware to the container's veth.
Building a secure image pipeline with Ansible. Generating secure OS images for OpenShift Virtualization. Creating a immutable image pipeline with Ansible, OpenSCAP, Packer, Molecule and Vagrant. Packaging OS images for consumption to OpenShift Virtualization.
Virtual File System in Linux Kernel
Note: When you view the the slide deck via web browser, the screenshots may be blurred. You can download and view them offline (Screenshots are clear).
Configuring an embedded Linux system with a read-only rootfs has many advantages: reduced wear on flash memory; easier to update and trivial factory reset being among them. This presentation shows you how
HKG15-311: OP-TEE for Beginners and Porting ReviewLinaro
HKG15-311: OP-TEE for Beginners and Porting Review
---------------------------------------------------
Speaker: Victor Chong
Date: February 11, 2015
---------------------------------------------------
★ Session Summary ★
Explains the building blocks involved in Security including TrustZone, OP-TEE, Trusted Firmware etc. Goes into detail on how Secure Boot Works.. and Why. Explains how a simple secure Trusted Application interacts with OP-TEE and works. Brief overview on how to port OP-TEE to an ARM platform. Opens discussions for Potential Challenges and Hardware limitations and how they can be overcome.
--------------------------------------------------
★ Resources ★
Pathable: https://hkg15.pathable.com/meetings/250816
Video: https://www.youtube.com/watch?v=Fksx4-bpHRY
Etherpad: http://pad.linaro.org/p/hkg15-311
---------------------------------------------------
★ Event Details ★
Linaro Connect Hong Kong 2015 - #HKG15
February 9-13th, 2015
Regal Airport Hotel Hong Kong Airport
---------------------------------------------------
http://www.linaro.org
http://connect.linaro.org
Advanced Git Techniques: Subtrees, Grafting, and Other Fun StuffAtlassian
Your team has adopted Git, and are happily coding along. But is that all? Can you do more with it? You bet! Join the always-animated Nicola Paolucci to learn advanced techniques for grafting multiple repositories, managing project dependencies with git subtree, splitting commits, and finding the best merge strategy for your staging servers. If you've ever wondered how to collate the histories of different projects, or how to split a sub-directory into it's own project without destroying its history, this session is for you.
How to Choose a Software Update Mechanism for Embedded Linux DevicesLeon Anavi
How to Choose a Software Update Mechanism for Embedded Linux Devices
by Leon Anavi, Konsulko Group
Embedded Linux Conference NA 2022 and Open Source Summit NA 2022
Atomic software system update of an embedded Linux device has always been an important part of any product, especially nowadays with the existing large fleets of connected devices and Internet of Things. There are several different widely used in the industry approaches: A/B updates with dual redundant scheme, delta updates, container-based updates and combined strategies. Open source technologies such as Mender, RAUC and libostree based solutions implement these strategies and provide tools to manage updates of multiple devices. What are the advantages and disadvantages? How to choose an appropriate open source solution for a specific project? This session explores a number of different open source Linux software update technologies with practical examples for integrating them using the Yocto Project and OpenEmbedded. In order to better understand the strengths and weaknesses of each technology, we deep dive in various use cases. The talk is appropriate for anyone with basic knowledge about Linux. It will hopefully help managers, engineers and developers better understand the technical challenges and the available open source solutions with which to overcome them easier and faster so that they can focus on the unique core features of their products.
[KubeConEU] Building images efficiently and securely on Kubernetes with BuildKitAkihiro Suda
https://sched.co/MPX5
BuildKit is a modern container image builder that focuses on efficiency and security, mostly known as the backend of Docker 18.06+ and Jessie Frazelle's `img`. (But it is even useful as a standalone tool!)
In this talk, Akihiro Suda, one of founding maintainers of BuildKit, shows practical tips for running BuildKit on Kubernetes clusters.
Introduce Brainf*ck, another Turing complete programming language. Then, try to implement the following from scratch: Interpreter, Compiler [x86_64 and ARM], and JIT Compiler.
Linux Performance Analysis: New Tools and Old SecretsBrendan Gregg
Talk for USENIX/LISA2014 by Brendan Gregg, Netflix. At Netflix performance is crucial, and we use many high to low level tools to analyze our stack in different ways. In this talk, I will introduce new system observability tools we are using at Netflix, which I've ported from my DTraceToolkit, and are intended for our Linux 3.2 cloud instances. These show that Linux can do more than you may think, by using creative hacks and workarounds with existing kernel features (ftrace, perf_events). While these are solving issues on current versions of Linux, I'll also briefly summarize the future in this space: eBPF, ktap, SystemTap, sysdig, etc.
Linux 4.x Tracing: Performance Analysis with bcc/BPFBrendan Gregg
Talk about bcc/eBPF for SCALE15x (2017) by Brendan Gregg. "BPF (Berkeley Packet Filter) has been enhanced in the Linux 4.x series and now powers a large collection of performance analysis and observability tools ready for you to use, included in the bcc (BPF Complier Collection) open source project. BPF nowadays can do system tracing, software defined networks, and kernel fast path: much more than just filtering packets! This talk will focus on the bcc/BPF tools for performance analysis, which make use of other built in Linux capabilities: dynamic tracing (kprobes and uprobes) and static tracing (tracepoints and USDT). There are now bcc tools for measuring latency distributions for file system I/O and run queue latency, printing details of storage device I/O and TCP retransmits, investigating blocked stack traces and memory leaks, and a whole lot more. These lead to performance wins large and small, especially when instrumenting areas that previously had zero visibility. Tracing superpowers have finally arrived, built in to Linux."
Talk for SCaLE13x. Video: https://www.youtube.com/watch?v=_Ik8oiQvWgo . Profiling can show what your Linux kernel and appliacations are doing in detail, across all software stack layers. This talk shows how we are using Linux perf_events (aka "perf") and flame graphs at Netflix to understand CPU usage in detail, to optimize our cloud usage, solve performance issues, and identify regressions. This will be more than just an intro: profiling difficult targets, including Java and Node.js, will be covered, which includes ways to resolve JITed symbols and broken stacks. Included are the easy examples, the hard, and the cutting edge.
Objectif général : Acquérir les connaissances nécessaires à la programmation avec le langage Python
Objectifs opérationnels :
- Mémoriser des données primitives
- Traiter des données
- Communiquer avec l’extérieur
- Contrôler le flux d’exécution des instructions
- Mémoriser des données composites
- Découper et réutiliser du code
A presentation delivered by Arctiq, onsite in Toronto, on Mar 1, 2017. The presentation discusses Ansible as an automation tool for Linux, Windows, and network devices. Reach out if you would like more information www.arctiq.ca
Configuring an embedded Linux system with a read-only rootfs has many advantages: reduced wear on flash memory; easier to update and trivial factory reset being among them. This presentation shows you how
HKG15-311: OP-TEE for Beginners and Porting ReviewLinaro
HKG15-311: OP-TEE for Beginners and Porting Review
---------------------------------------------------
Speaker: Victor Chong
Date: February 11, 2015
---------------------------------------------------
★ Session Summary ★
Explains the building blocks involved in Security including TrustZone, OP-TEE, Trusted Firmware etc. Goes into detail on how Secure Boot Works.. and Why. Explains how a simple secure Trusted Application interacts with OP-TEE and works. Brief overview on how to port OP-TEE to an ARM platform. Opens discussions for Potential Challenges and Hardware limitations and how they can be overcome.
--------------------------------------------------
★ Resources ★
Pathable: https://hkg15.pathable.com/meetings/250816
Video: https://www.youtube.com/watch?v=Fksx4-bpHRY
Etherpad: http://pad.linaro.org/p/hkg15-311
---------------------------------------------------
★ Event Details ★
Linaro Connect Hong Kong 2015 - #HKG15
February 9-13th, 2015
Regal Airport Hotel Hong Kong Airport
---------------------------------------------------
http://www.linaro.org
http://connect.linaro.org
Advanced Git Techniques: Subtrees, Grafting, and Other Fun StuffAtlassian
Your team has adopted Git, and are happily coding along. But is that all? Can you do more with it? You bet! Join the always-animated Nicola Paolucci to learn advanced techniques for grafting multiple repositories, managing project dependencies with git subtree, splitting commits, and finding the best merge strategy for your staging servers. If you've ever wondered how to collate the histories of different projects, or how to split a sub-directory into it's own project without destroying its history, this session is for you.
How to Choose a Software Update Mechanism for Embedded Linux DevicesLeon Anavi
How to Choose a Software Update Mechanism for Embedded Linux Devices
by Leon Anavi, Konsulko Group
Embedded Linux Conference NA 2022 and Open Source Summit NA 2022
Atomic software system update of an embedded Linux device has always been an important part of any product, especially nowadays with the existing large fleets of connected devices and Internet of Things. There are several different widely used in the industry approaches: A/B updates with dual redundant scheme, delta updates, container-based updates and combined strategies. Open source technologies such as Mender, RAUC and libostree based solutions implement these strategies and provide tools to manage updates of multiple devices. What are the advantages and disadvantages? How to choose an appropriate open source solution for a specific project? This session explores a number of different open source Linux software update technologies with practical examples for integrating them using the Yocto Project and OpenEmbedded. In order to better understand the strengths and weaknesses of each technology, we deep dive in various use cases. The talk is appropriate for anyone with basic knowledge about Linux. It will hopefully help managers, engineers and developers better understand the technical challenges and the available open source solutions with which to overcome them easier and faster so that they can focus on the unique core features of their products.
[KubeConEU] Building images efficiently and securely on Kubernetes with BuildKitAkihiro Suda
https://sched.co/MPX5
BuildKit is a modern container image builder that focuses on efficiency and security, mostly known as the backend of Docker 18.06+ and Jessie Frazelle's `img`. (But it is even useful as a standalone tool!)
In this talk, Akihiro Suda, one of founding maintainers of BuildKit, shows practical tips for running BuildKit on Kubernetes clusters.
Introduce Brainf*ck, another Turing complete programming language. Then, try to implement the following from scratch: Interpreter, Compiler [x86_64 and ARM], and JIT Compiler.
Linux Performance Analysis: New Tools and Old SecretsBrendan Gregg
Talk for USENIX/LISA2014 by Brendan Gregg, Netflix. At Netflix performance is crucial, and we use many high to low level tools to analyze our stack in different ways. In this talk, I will introduce new system observability tools we are using at Netflix, which I've ported from my DTraceToolkit, and are intended for our Linux 3.2 cloud instances. These show that Linux can do more than you may think, by using creative hacks and workarounds with existing kernel features (ftrace, perf_events). While these are solving issues on current versions of Linux, I'll also briefly summarize the future in this space: eBPF, ktap, SystemTap, sysdig, etc.
Linux 4.x Tracing: Performance Analysis with bcc/BPFBrendan Gregg
Talk about bcc/eBPF for SCALE15x (2017) by Brendan Gregg. "BPF (Berkeley Packet Filter) has been enhanced in the Linux 4.x series and now powers a large collection of performance analysis and observability tools ready for you to use, included in the bcc (BPF Complier Collection) open source project. BPF nowadays can do system tracing, software defined networks, and kernel fast path: much more than just filtering packets! This talk will focus on the bcc/BPF tools for performance analysis, which make use of other built in Linux capabilities: dynamic tracing (kprobes and uprobes) and static tracing (tracepoints and USDT). There are now bcc tools for measuring latency distributions for file system I/O and run queue latency, printing details of storage device I/O and TCP retransmits, investigating blocked stack traces and memory leaks, and a whole lot more. These lead to performance wins large and small, especially when instrumenting areas that previously had zero visibility. Tracing superpowers have finally arrived, built in to Linux."
Talk for SCaLE13x. Video: https://www.youtube.com/watch?v=_Ik8oiQvWgo . Profiling can show what your Linux kernel and appliacations are doing in detail, across all software stack layers. This talk shows how we are using Linux perf_events (aka "perf") and flame graphs at Netflix to understand CPU usage in detail, to optimize our cloud usage, solve performance issues, and identify regressions. This will be more than just an intro: profiling difficult targets, including Java and Node.js, will be covered, which includes ways to resolve JITed symbols and broken stacks. Included are the easy examples, the hard, and the cutting edge.
Objectif général : Acquérir les connaissances nécessaires à la programmation avec le langage Python
Objectifs opérationnels :
- Mémoriser des données primitives
- Traiter des données
- Communiquer avec l’extérieur
- Contrôler le flux d’exécution des instructions
- Mémoriser des données composites
- Découper et réutiliser du code
A presentation delivered by Arctiq, onsite in Toronto, on Mar 1, 2017. The presentation discusses Ansible as an automation tool for Linux, Windows, and network devices. Reach out if you would like more information www.arctiq.ca
Talk given at DomCode meetup in Utrecht (August 2014) on different frameworks to do asynchronous I/O y Python, with a strong focus on asyncio (PEP-3156).
Python Performance Profiling: The Guts And The Gloryemptysquare
Your Python program is too slow, and you need to optimize it. Where do you start? With the right tools, you can optimize your code where it counts. We’ll explore the guts of the Python profiler “Yappi” to understand its features and limitations. We’ll learn how to find the maximum performance wins with minimum effort.
Delivered as plenary at USENIX LISA 2013. video here: https://www.youtube.com/watch?v=nZfNehCzGdw and https://www.usenix.org/conference/lisa13/technical-sessions/plenary/gregg . "How did we ever analyze performance before Flame Graphs?" This new visualization invented by Brendan can help you quickly understand application and kernel performance, especially CPU usage, where stacks (call graphs) can be sampled and then visualized as an interactive flame graph. Flame Graphs are now used for a growing variety of targets: for applications and kernels on Linux, SmartOS, Mac OS X, and Windows; for languages including C, C++, node.js, ruby, and Lua; and in WebKit Web Inspector. This talk will explain them and provide use cases and new visualizations for other event types, including I/O, memory usage, and latency.
PHP Apps on the Move - Migrating from In-House to Cloud RightScale
RightScale Conference NYC 2012 -- PHP Apps on the Move - Migrating from In-House to Cloud
Kent Mitchell - Sr. Director, Product Management, Zend
It’s a common problem: How to move your PHP system to the cloud without completely overhauling your app. Most existing systems and applications were not designed for the level of elasticity the cloud brings. But many of those apps can still take advantage of all that the cloud offers - while requiring very few modifications.
In this session, we will discuss how one customer leveraged the off-the-shelf capabilities of RightScale and Zend to migrate from a fixed, non-scalable traditional architecture to an elastic, high-availability cloud architecture. Join us for a deeper look at this auto-scaling PaaS solution specifically designed to make it easier for you to deploy and manage cloud-based, highly available PHP server clusters.
The Anatomy of the Idea is a short introduction to ideation - the process of generating ideas. How do we create ideas? Or better yet, how do we create great ideas?
If you're interested in how to improve your ideation, visit Crinid.com for tips, techniques and inspiration.
Thank you for reading,
- Rick van der Wal
http://www.crinid.com
Software transactional memory. pure functional approachAlexander Granin
Slides for C++ Russia 2018
I'm presenting my `cpp_stm_free` library: composable monadic STM for C++ on Free monads for lock-free concurrent programming.
package algs13;
import stdlib.*;
import java.util.Iterator;
import java.util.NoSuchElementException;
/* ***********************************************************************
* Compilation: javac Queue.java
* Execution: java Queue < input.txt
* Data files: http://algs4.cs.princeton.edu/13stacks/tobe.txt
*
* A generic queue, implemented using a linked list.
*
* % java Queue < tobe.txt
* to be or not to be (2 left on queue)
*
*************************************************************************/
/**
* The <tt>Queue</tt> class represents a first-in-first-out (FIFO)
* queue of generic items.
* It supports the usual <em>enqueue</em> and <em>dequeue</em>
* operations, along with methods for peeking at the top item,
* testing if the queue is empty, and iterating through
* the items in FIFO order.
* <p>
* All queue operations except iteration are constant time.
* <p>
* For additional documentation, see <a href="http://algs4.cs.princeton.edu/13stacks">Section 1.3</a> of
* <i>Algorithms, 4th Edition</i> by Robert Sedgewick and Kevin Wayne.
*/
public class Queue<T> implements Iterable<T> {
private int N; // number of elements on queue
private Node<T> first; // beginning of queue
private Node<T> last; // end of queue
// helper linked list class
private static class Node<T> {
public Node() { }
public T item;
public Node<T> next;
}
/**
* Create an empty queue.
*/
public Queue() {
first = null;
last = null;
N = 0;
}
/**
* Is the queue empty?
*/
public boolean isEmpty() {
return first == null;
}
/**
* Return the number of items in the queue.
*/
public int size() {
return N;
}
/**
* Return the item least recently added to the queue.
* @throws java.util.NoSuchElementException if queue is empty.
*/
public T peek() {
if (isEmpty()) throw new NoSuchElementException("Queue underflow");
return first.item;
}
/**
* Add the item to the queue.
*/
public void enqueue(T item) {
Node<T> oldlast = last;
last = new Node<>();
last.item = item;
last.next = null;
if (isEmpty()) first = last;
else oldlast.next = last;
N++;
}
/**
* Remove and return the item on the queue least recently added.
* @throws java.util.NoSuchElementException if queue is empty.
*/
public T dequeue() {
if (isEmpty()) throw new NoSuchElementException("Queue underflow");
T item = first.item;
first = first.next;
N--;
if (isEmpty()) last = null;
return item;
}
/**
* Return string representation.
*/
public String toString() {
StringBuilder s = new StringBuilder();
for (T item : this)
s.append(item + " ");
return s.toString();
}
// check internal invariants
private static <T> boolean check(Queue<T> that) {
int N = that.N;
Queue.Node<T> first = that.first;
Queue.Node<T> last = that.last;
if (N == 0) {
if (first != null) return false;
if (last != null) return false;
}
else if (N == 1) {
if (f.
JVM Mechanics: Understanding the JIT's TricksDoug Hawkins
In this talk, we'll walkthrough how the JIT optimizes a piece Java code step-by-step. In doing so, you'll learn some of the amazing feats of optimization that JVMs can perform, but also some surprisingly simple things that prevent your code from running fast.
In Class AssignmetzCST280W13a-1.pdfCST 280 In-Class Pract.docxbradburgess22840
In Class Assignmetz/CST280W13a-1.pdf
CST 280 In-Class Practice – Week 13
Manually determine the configuration of the priority queue (stored as a heap) created
by the following operations. Trace the following logic and define the output:
enqueue(7);
enqueue(17);
enqueue(2);
enqueue(5);
enqueue(22);
enqueue(19);
enqueue(6);
enqueue(11);
enqueue(13);
write the queue contents
dequeue and write front item
enqueue(15);
enqueue(8);
dequeue and write front item
dequeue and write front item
enqueue(24);
enqueue(14);
write the queue contents
Part 2
Then, verify the output by implementing the algorithm by rewriting the priority
queue demonstration program discussed in class. Files needed:
testPQueue.cpp pqType.h heap.cpp
Deliverables
• This cover sheet (with your names on it)
• Driver source code and output for verification program exectution.
In Class Assignmetz/CST280W13b.pdf
CST 280 In-Class Practice – Week 13
Use this page as a worksheet to sketch the progression of the elements up to the first
split for the QuickSort algorithm. Use the middle array element as the split value:
15 34 99 42 11 41 66 23 55 93 48
Next, access the file quickSort.cpp from the course web page. Tailor the program
by entering the array values above in place of the integer values used for an in-class
demonstration. Be sure to adjust the index range to match the size of this array.
Remember that the parameters to the QuickSort algorithm are starting and ending index
values, not the size of the array.
Next, insert code to demonstrate the state of the array after the first split. This should
verify what you did by hand above. Insert the following code at various points within
the partition function to “see” the array at various stages of processing:
for (int i = start; i <= end; i++) // <== ADD
cout << set[i] << ' ';
cout << endl;
Insert the code at these positions:
int partition(int set[], int start, int end)
{
int pivotValue, pivotIndex, mid;
mid = (start + end) / 2;
swap(set[start], set[mid]);
pivotIndex = start;
pivotValue = set[start];
ç HERE
for (int scan = start + 1; scan <= end; scan++)
{
if (set[scan] < pivotValue)
{
pivotIndex++;
swap(set[pivotIndex], set[scan]);
}
ç HERE
}
swap(set[start], set[pivotIndex]);
ç HERE
return pivotIndex;
}
Finally, identify the line that matches what you concluded above.
Deliverables:
Deliver the following for this assignment:
• This work sheet with a sketch of the array first split
• Program source code with required change
• Program output demonstrating array configuration after first split .
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptxJoão Esperancinha
These are the slides of the presentation I gave at the JetBrains HQ by the RAI in Amsterdam named "Decoding Kotlin - Your Guide to Solving the Mysterious in Kotlin". I want to express a big thank you to Xebia and JetBrains for the opportunity. I gave this presentation on the 24th of April 2024.
Slides from the talk I gave at the FOSDEM 2021 main stage on how we scaled Jitsi Meet during the pandemic to deal with the load.
https://fosdem.org/2021/schedule/event/jitsi_scaling/
Slides from the talk given at FOSDEM 2019 on how Jitsi Meet was brought from the web to mobile and how we built a native SDK using React Native.
Video: https://fosdem.org/2019/schedule/event/jitsi_mobile_webrtc/
Slides from my talk at OpenSIPS Summit 2017 and KamailioWorld 2017, showing the capabilities of Jitsi Meet, and a novel way for doing SIP video room integration.
Video at KamailioWorld: https://www.youtube.com/watch?v=TGloLKOrvmo
Dangerous Demo at KamailioWorld: https://www.youtube.com/watch?v=d0zHiLkHDyY&feature=youtu.be&t=3589
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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
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
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.
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.
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/
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.
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.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
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.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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.
4. Greenlet API
greenlet(func, parent=None): creates a greenlet to
run ‘func’
greenlet.switch(*args, **kw): switches execution to
the target greenlet, the first time
func(*args, **kw) will be executed
greenlet.throw([typ, [val, [tb]]]): switches execution
to the target greenlet and raises the specified
exception (GreenletExit by default)
6. How does it work?
Organized in a tree structure
Each greenlet has a ‘parent’, except main
When a greenlet dies, control is switched to its parent
Execution order isn’t always obvious
A glorified GOTO?!
7. How does it work? (II)
greenlet2
greenlet1
greenlet3
greenlet5
greenlet4
8. How does it work? (III)
‘Stack switching’
Non portable asm code
Copy stack slices on the heap
State is saved and restored when switching
CPU registers
Current Python frame, recursion depth and exception
state
9.
10.
11.
12.
13. Enter PyPy
New shiny and fast implementation of Python
Vast amount of fairy-dust covered unicorns
included
Includes an implementation of greenlet
Implemented on top of “continulet” objects
14. import _continuation
Continulets are one-shot continuations
Switching code is a standalone C library: stacklet
rpython/translator/c/src/stacklet/
15. Continulet API
continulet(func, *args, **kw): create a continulet
object which will call fun(cont, *args, **kw)
continulet.switch(value=None, to=None): start the
continulet or activate the previously suspended
one. If to is specified a ‘double switch’ is
performed
continulet.throw(type, value=None, tb=None,
to=None): similar to switch, but raise the given
exception after the switch is done
16. Stacklet
Tiny library implementing one-shot continuations
for C
Single C file (~400 lines) + per-platform asm
Supports x86, x86_64 and ARM
Nice and simple API
17. Stacklet API
stacklet_newthread(): creates a new thread handle
stacklet_new(thread_handle, run_func, run_arg):
calls run(arg) in a new stacklet, starts immediately
stacklet_switch(target): switches execution to
target stacklet
20. Using greenlet
Too low level, it’s usually used through a
framework
gevent, eventlet, evergreen *, gruvi *, ...
In these frameworks, switching happens through a
“hub”
*: these frameworks use python-fibers now
22. Undoing callbacks
import greenlet
# ...
def foo_async(cb):
call cb(result, error) eventually
pass
def foo_sync():
current = greenlet.getcurrent()
def cb(result, error):
if error is not None:
current.throw(Exception(error))
else:
current.switch(result)
foo_async(cb)
return hub.switch()
23. import fibers
shameless
plug!
Micro-threadling library API inspired by Python
threads and greenlet
Uses stacklet underneath
Works on CPython and PyPy
On PyPy it uses continulets
github.com/saghul/python-fibers
Or pip install fibers