This document provides an overview of new features in NIO 2 and asynchronous I/O in Java. It discusses buffers, channels, selectors, file system APIs, file change notification, and asynchronous operations using futures and completion handlers. The key aspects covered include non-blocking I/O, readiness selection, file locking, memory mapping, and file attributes.
Full recorded presentation at https://www.youtube.com/watch?v=2UfAgCSKPZo for Tetrate Tech Talks on 2022/05/13.
Envoy's support for Kafka protocol, in form of broker-filter and mesh-filter.
Contents:
- overview of Kafka (usecases, partitioning, producer/consumer, protocol);
- proxying Kafka (non-Envoy specific);
- proxying Kafka with Envoy;
- handling Kafka protocol in Envoy;
- Kafka-broker-filter for per-connection proxying;
- Kafka-mesh-filter to provide front proxy for multiple Kafka clusters.
References:
- https://adam-kotwasinski.medium.com/deploying-envoy-and-kafka-8aa7513ec0a0
- https://adam-kotwasinski.medium.com/kafka-mesh-filter-in-envoy-a70b3aefcdef
Get hands-on with security features and best practices to protect your containerized services. Learn to push and verify signed images with Docker Content Trust, and collaborate with delegation roles. Intermediate to advanced level Docker experience recommended, participants will be building and pushing with Docker during the workshop.
Led By Docker Security Experts:
Riyaz Faizullabhoy
David Lawrence
Viktor Stanchev
Experience Level: Intermediate to advanced level Docker experience recommended
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...Flink Forward
Flink Forward San Francisco 2022.
Probably everyone who has written stateful Apache Flink applications has used one of the fault-tolerant keyed state primitives ValueState, ListState, and MapState. With RocksDB, however, retrieving and updating items comes at an increased cost that you should be aware of. Sometimes, these may not be avoidable with the current API, e.g., for efficient event-time stream-sorting or streaming joins where you need to iterate one or two buffered streams in the right order. With FLIP-220, we are introducing a new state primitive: BinarySortedMultiMapState. This new form of state offers you to (a) efficiently store lists of values for a user-provided key, and (b) iterate keyed state in a well-defined sort order. Both features can be backed efficiently by RocksDB with a 2x performance improvement over the current workarounds. This talk will go into the details of the new API and its implementation, present how to use it in your application, and talk about the process of getting it into Flink.
by
Nico Kruber
Apache Pulsar: The Next Generation Messaging and Queuing SystemDatabricks
Apache Pulsar is the next generation messaging and queuing system with unique design trade-offs driven by the need for scalability and durability. Its two layered architecture of separating message storage from serving led to an implementation that unifies the flexibility and the high-level constructs of messaging, queuing and light weight computing with the scalable properties of log storage systems.
Integrating Apache Kafka Into Your Environmentconfluent
Watch this talk here: https://www.confluent.io/online-talks/integrating-apache-kafka-into-your-environment-on-demand
Integrating Apache Kafka with other systems in a reliable and scalable way is a key part of an event streaming platform. This session will show you how to get streams of data into and out of Kafka with Kafka Connect and REST Proxy, maintain data formats and ensure compatibility with Schema Registry and Avro, and build real-time stream processing applications with Confluent KSQL and Kafka Streams.
This session is part 4 of 4 in our Fundamentals for Apache Kafka series.
This presentation was created as an introduction to the Apache NiFi project; to be followed by “Lab 0” of the “Realtime Event Processing in Hadoop with NiFi, Kafka and Storm” tutorial hosted here: http://hortonworks.com/hadoop-tutorial/realtime-event-processing-nifi-kafka-storm/#section_1
Full recorded presentation at https://www.youtube.com/watch?v=2UfAgCSKPZo for Tetrate Tech Talks on 2022/05/13.
Envoy's support for Kafka protocol, in form of broker-filter and mesh-filter.
Contents:
- overview of Kafka (usecases, partitioning, producer/consumer, protocol);
- proxying Kafka (non-Envoy specific);
- proxying Kafka with Envoy;
- handling Kafka protocol in Envoy;
- Kafka-broker-filter for per-connection proxying;
- Kafka-mesh-filter to provide front proxy for multiple Kafka clusters.
References:
- https://adam-kotwasinski.medium.com/deploying-envoy-and-kafka-8aa7513ec0a0
- https://adam-kotwasinski.medium.com/kafka-mesh-filter-in-envoy-a70b3aefcdef
Get hands-on with security features and best practices to protect your containerized services. Learn to push and verify signed images with Docker Content Trust, and collaborate with delegation roles. Intermediate to advanced level Docker experience recommended, participants will be building and pushing with Docker during the workshop.
Led By Docker Security Experts:
Riyaz Faizullabhoy
David Lawrence
Viktor Stanchev
Experience Level: Intermediate to advanced level Docker experience recommended
Introducing BinarySortedMultiMap - A new Flink state primitive to boost your ...Flink Forward
Flink Forward San Francisco 2022.
Probably everyone who has written stateful Apache Flink applications has used one of the fault-tolerant keyed state primitives ValueState, ListState, and MapState. With RocksDB, however, retrieving and updating items comes at an increased cost that you should be aware of. Sometimes, these may not be avoidable with the current API, e.g., for efficient event-time stream-sorting or streaming joins where you need to iterate one or two buffered streams in the right order. With FLIP-220, we are introducing a new state primitive: BinarySortedMultiMapState. This new form of state offers you to (a) efficiently store lists of values for a user-provided key, and (b) iterate keyed state in a well-defined sort order. Both features can be backed efficiently by RocksDB with a 2x performance improvement over the current workarounds. This talk will go into the details of the new API and its implementation, present how to use it in your application, and talk about the process of getting it into Flink.
by
Nico Kruber
Apache Pulsar: The Next Generation Messaging and Queuing SystemDatabricks
Apache Pulsar is the next generation messaging and queuing system with unique design trade-offs driven by the need for scalability and durability. Its two layered architecture of separating message storage from serving led to an implementation that unifies the flexibility and the high-level constructs of messaging, queuing and light weight computing with the scalable properties of log storage systems.
Integrating Apache Kafka Into Your Environmentconfluent
Watch this talk here: https://www.confluent.io/online-talks/integrating-apache-kafka-into-your-environment-on-demand
Integrating Apache Kafka with other systems in a reliable and scalable way is a key part of an event streaming platform. This session will show you how to get streams of data into and out of Kafka with Kafka Connect and REST Proxy, maintain data formats and ensure compatibility with Schema Registry and Avro, and build real-time stream processing applications with Confluent KSQL and Kafka Streams.
This session is part 4 of 4 in our Fundamentals for Apache Kafka series.
This presentation was created as an introduction to the Apache NiFi project; to be followed by “Lab 0” of the “Realtime Event Processing in Hadoop with NiFi, Kafka and Storm” tutorial hosted here: http://hortonworks.com/hadoop-tutorial/realtime-event-processing-nifi-kafka-storm/#section_1
Presentation at Strata Data Conference 2018, New York
The controller is the brain of Apache Kafka. A big part of what the controller does is to maintain the consistency of the replicas and determine which replica can be used to serve the clients, especially during individual broker failure.
Jun Rao outlines the main data flow in the controller—in particular, when a broker fails, how the controller automatically promotes another replica as the leader to serve the clients, and when a broker is started, how the controller resumes the replication pipeline in the restarted broker.
Jun then describes recent improvements to the controller that allow it to handle certain edge cases correctly and increase its performance, which allows for more partitions in a Kafka cluster.
Slides for presentation on ZooKeeper I gave at Near Infinity (www.nearinfinity.com) 2012 spring conference.
The associated sample code is on GitHub at https://github.com/sleberknight/zookeeper-samples
CDC Stream Processing With Apache Flink With Timo Walther | Current 2022HostedbyConfluent
CDC Stream Processing With Apache Flink With Timo Walther | Current 2022
An instant world requires instant decisions at scale. This includes the ability to digest and react to changes in real-time. Thus, event logs such as Apache Kafka can be found in almost every architecture, while databases and similar systems still provide the foundation. Change Data Capture (CDC) has become popular for propagating changes. Nevertheless, integrating all these systems, which often have slightly different semantics, can be a challenge.
In this talk, we highlight what it means for Apache Flink to be a general data processor that acts as a data integration hub. Looking under the hood, we demonstrate Flink's SQL engine as a changelog processor that ships with an ecosystem tailored to processing CDC data and maintaining materialized views. We will discuss the semantics of different data sources and how to perform joins or stream enrichment between them. This talk illustrates how Flink can be used with systems such as Kafka (for upsert logging), Debezium, JDBC, and others.
Apache Kafka® is the technology behind event streaming which is fast becoming the central nervous system of flexible, scalable, modern data architectures. Customers want to connect their databases, data warehouses, applications, microservices and more, to power the event streaming platform. To connect to Apache Kafka, you need a connector!
This online talk dives into the new Verified Integrations Program and the integration requirements, the Connect API and sources and sinks that use Kafka Connect. We cover the verification steps and provide code samples created by popular application and database companies. We will discuss the resources available to support you through the connector development process.
This is Part 2 of 2 in Building Kafka Connectors - The Why and How
There are many ways to run high availability with PostgreSQL. Here, we present a template for you to create your own customized, high-availability solution using Python and for maximum accessibility, a distributed configuration store like ZooKeeper or etcd.
Webinar: Detecting row patterns with Flink SQL - Dawid WysakowiczVerverica
Apache Flink is one of the first open source stream processors that was able to address the full spectrum of stream processing applications, ranging from applications with low latency requirements to applications that process millions of events per second. On top of this powerful processing engine, the Flink community built APIs for complex event processing and streaming analytics, namely the CEP library and support for streaming SQL.
Since recently, the Flink community is integrating both APIs by extending Flink SQL to support the MATCH RECOGNIZE clause for row pattern matching that was introduced with the SQL:2016 standard.
I will discuss the new MATCH RECOGNIZE feature and present use cases that benefit from pattern matching support in streaming SQL, such as process monitoring or anomaly detection. I will demonstrate the feature with a few example queries.
Common issues with Apache Kafka® Producerconfluent
Badai Aqrandista, Confluent, Senior Technical Support Engineer
This session will be about a common issue in the Kafka Producer: producer batch expiry. We will be discussing the Kafka Producer internals, its common causes, such as a slow network or small batching, and how to overcome them. We will also be sharing some examples along the way!
https://www.meetup.com/apache-kafka-sydney/events/279651982/
At the beginning of 2021, Shopify Data Platform decided to adopt Apache Flink to enable modern stateful stream-processing. Shopify had a lot of experience with other streaming technologies, but Flink was a great fit due to its state management primitives.
After about six months, Shopify now has a flourishing ecosystem of tools, tens of prototypes from many teams across the company and a few large use-cases in production.
Yaroslav will share a story about not just building a single data pipeline but building a sustainable ecosystem. You can learn about how they planned their platform roadmap, the tools and libraries Shopify built, the decision to fork Flink, and how Shopify partnered with other teams and drove the adoption of streaming at the company.
Event-Driven Messaging and Actions using Apache Flink and Apache NiFiDataWorks Summit
At Comcast, our team has been architecting a customer experience platform which is able to react to near-real-time events and interactions and deliver appropriate and timely communications to customers. By combining the low latency capabilities of Apache Flink and the dataflow capabilities of Apache NiFi we are able to process events at high volume to trigger, enrich, filter, and act/communicate to enhance customer experiences. Apache Flink and Apache NiFi complement each other with their strengths in event streaming and correlation, state management, command-and-control, parallelism, development methodology, and interoperability with surrounding technologies. We will trace our journey from starting with Apache NiFi over three years ago and our more recent introduction of Apache Flink into our platform stack to handle more complex scenarios. In this presentation we will compare and contrast which business and technical use cases are best suited to which platform and explore different ways to integrate the two platforms into a single solution.
Confluent REST Proxy and Schema Registry (Concepts, Architecture, Features)Kai Wähner
High level introduction to Confluent REST Proxy and Schema Registry (leveraging Apache Avro under the hood), two components of the Apache Kafka open source ecosystem. See the concepts, architecture and features.
Oracle Real Application Clusters 19c- Best Practices and Internals- EMEA Tour...Sandesh Rao
In this session, I will cover under-the-hood features that power Oracle Real Application Clusters (Oracle RAC) 19c specifically around Cache Fusion and Service management. Improvements in Oracle RAC helps in integration with features such as Multitenant and Data Guard. In fact, these features benefit immensely when used with Oracle RAC. Finally we will talk about changes to the broader Oracle RAC Family of Products stack and the algorithmic changes that helps quickly detect sick/dead nodes/instances and the reconfiguration improvements to ensure that the Oracle RAC Databases continue to function without any disruption
Apache Flink is a popular stream computing framework for real-time stream computing. Many stream compute algorithms require trailing data in order to compute the intended result. One example is computing the number of user logins in the last 7 days. This creates a dilemma where the results of the stream program are incomplete until the runtime of the program exceeds 7 days. The alternative is to bootstrap the program using historic data to seed the state before shifting to use real-time data.
This talk will discuss alternatives to bootstrap programs in Flink. Some alternatives rely on technologies exogenous to the stream program, such as enhancements to the pub/sub layer, that are more generally applicable to other stream compute engines. Other alternatives include enhancements to Flink source implementations. Lyft is exploring another alternative using orchestration of multiple Flink programs. The talk will cover why Lyft pursued this alternative and future directions to further enhance bootstrapping support in Flink.
Speaker
Gregory Fee, Principal Engineer, Lyft
Open Device Programmability: Hands-on Intro to RESTCONF (and a bit of NETCONF)Cisco DevNet
In this small group, hands-on workshop session you'll learn how to write your first Python application that uses YANG, NETCONF and , RESTCONF to access operational and configuration data on a device.
Watch the DevNet 2044 replay from the Cisco Live On-Demand Library at: https://www.ciscolive.com/online/connect/sessionDetail.ww?SESSION_ID=92725&backBtn=true
Check out more and register for Cisco DevNet: http://ow.ly/jCNV3030OfS
Basically everything you need to get started on your Zookeeper training, and setup apache Hadoop high availability with QJM setup with automatic failover.
Presentation at Strata Data Conference 2018, New York
The controller is the brain of Apache Kafka. A big part of what the controller does is to maintain the consistency of the replicas and determine which replica can be used to serve the clients, especially during individual broker failure.
Jun Rao outlines the main data flow in the controller—in particular, when a broker fails, how the controller automatically promotes another replica as the leader to serve the clients, and when a broker is started, how the controller resumes the replication pipeline in the restarted broker.
Jun then describes recent improvements to the controller that allow it to handle certain edge cases correctly and increase its performance, which allows for more partitions in a Kafka cluster.
Slides for presentation on ZooKeeper I gave at Near Infinity (www.nearinfinity.com) 2012 spring conference.
The associated sample code is on GitHub at https://github.com/sleberknight/zookeeper-samples
CDC Stream Processing With Apache Flink With Timo Walther | Current 2022HostedbyConfluent
CDC Stream Processing With Apache Flink With Timo Walther | Current 2022
An instant world requires instant decisions at scale. This includes the ability to digest and react to changes in real-time. Thus, event logs such as Apache Kafka can be found in almost every architecture, while databases and similar systems still provide the foundation. Change Data Capture (CDC) has become popular for propagating changes. Nevertheless, integrating all these systems, which often have slightly different semantics, can be a challenge.
In this talk, we highlight what it means for Apache Flink to be a general data processor that acts as a data integration hub. Looking under the hood, we demonstrate Flink's SQL engine as a changelog processor that ships with an ecosystem tailored to processing CDC data and maintaining materialized views. We will discuss the semantics of different data sources and how to perform joins or stream enrichment between them. This talk illustrates how Flink can be used with systems such as Kafka (for upsert logging), Debezium, JDBC, and others.
Apache Kafka® is the technology behind event streaming which is fast becoming the central nervous system of flexible, scalable, modern data architectures. Customers want to connect their databases, data warehouses, applications, microservices and more, to power the event streaming platform. To connect to Apache Kafka, you need a connector!
This online talk dives into the new Verified Integrations Program and the integration requirements, the Connect API and sources and sinks that use Kafka Connect. We cover the verification steps and provide code samples created by popular application and database companies. We will discuss the resources available to support you through the connector development process.
This is Part 2 of 2 in Building Kafka Connectors - The Why and How
There are many ways to run high availability with PostgreSQL. Here, we present a template for you to create your own customized, high-availability solution using Python and for maximum accessibility, a distributed configuration store like ZooKeeper or etcd.
Webinar: Detecting row patterns with Flink SQL - Dawid WysakowiczVerverica
Apache Flink is one of the first open source stream processors that was able to address the full spectrum of stream processing applications, ranging from applications with low latency requirements to applications that process millions of events per second. On top of this powerful processing engine, the Flink community built APIs for complex event processing and streaming analytics, namely the CEP library and support for streaming SQL.
Since recently, the Flink community is integrating both APIs by extending Flink SQL to support the MATCH RECOGNIZE clause for row pattern matching that was introduced with the SQL:2016 standard.
I will discuss the new MATCH RECOGNIZE feature and present use cases that benefit from pattern matching support in streaming SQL, such as process monitoring or anomaly detection. I will demonstrate the feature with a few example queries.
Common issues with Apache Kafka® Producerconfluent
Badai Aqrandista, Confluent, Senior Technical Support Engineer
This session will be about a common issue in the Kafka Producer: producer batch expiry. We will be discussing the Kafka Producer internals, its common causes, such as a slow network or small batching, and how to overcome them. We will also be sharing some examples along the way!
https://www.meetup.com/apache-kafka-sydney/events/279651982/
At the beginning of 2021, Shopify Data Platform decided to adopt Apache Flink to enable modern stateful stream-processing. Shopify had a lot of experience with other streaming technologies, but Flink was a great fit due to its state management primitives.
After about six months, Shopify now has a flourishing ecosystem of tools, tens of prototypes from many teams across the company and a few large use-cases in production.
Yaroslav will share a story about not just building a single data pipeline but building a sustainable ecosystem. You can learn about how they planned their platform roadmap, the tools and libraries Shopify built, the decision to fork Flink, and how Shopify partnered with other teams and drove the adoption of streaming at the company.
Event-Driven Messaging and Actions using Apache Flink and Apache NiFiDataWorks Summit
At Comcast, our team has been architecting a customer experience platform which is able to react to near-real-time events and interactions and deliver appropriate and timely communications to customers. By combining the low latency capabilities of Apache Flink and the dataflow capabilities of Apache NiFi we are able to process events at high volume to trigger, enrich, filter, and act/communicate to enhance customer experiences. Apache Flink and Apache NiFi complement each other with their strengths in event streaming and correlation, state management, command-and-control, parallelism, development methodology, and interoperability with surrounding technologies. We will trace our journey from starting with Apache NiFi over three years ago and our more recent introduction of Apache Flink into our platform stack to handle more complex scenarios. In this presentation we will compare and contrast which business and technical use cases are best suited to which platform and explore different ways to integrate the two platforms into a single solution.
Confluent REST Proxy and Schema Registry (Concepts, Architecture, Features)Kai Wähner
High level introduction to Confluent REST Proxy and Schema Registry (leveraging Apache Avro under the hood), two components of the Apache Kafka open source ecosystem. See the concepts, architecture and features.
Oracle Real Application Clusters 19c- Best Practices and Internals- EMEA Tour...Sandesh Rao
In this session, I will cover under-the-hood features that power Oracle Real Application Clusters (Oracle RAC) 19c specifically around Cache Fusion and Service management. Improvements in Oracle RAC helps in integration with features such as Multitenant and Data Guard. In fact, these features benefit immensely when used with Oracle RAC. Finally we will talk about changes to the broader Oracle RAC Family of Products stack and the algorithmic changes that helps quickly detect sick/dead nodes/instances and the reconfiguration improvements to ensure that the Oracle RAC Databases continue to function without any disruption
Apache Flink is a popular stream computing framework for real-time stream computing. Many stream compute algorithms require trailing data in order to compute the intended result. One example is computing the number of user logins in the last 7 days. This creates a dilemma where the results of the stream program are incomplete until the runtime of the program exceeds 7 days. The alternative is to bootstrap the program using historic data to seed the state before shifting to use real-time data.
This talk will discuss alternatives to bootstrap programs in Flink. Some alternatives rely on technologies exogenous to the stream program, such as enhancements to the pub/sub layer, that are more generally applicable to other stream compute engines. Other alternatives include enhancements to Flink source implementations. Lyft is exploring another alternative using orchestration of multiple Flink programs. The talk will cover why Lyft pursued this alternative and future directions to further enhance bootstrapping support in Flink.
Speaker
Gregory Fee, Principal Engineer, Lyft
Open Device Programmability: Hands-on Intro to RESTCONF (and a bit of NETCONF)Cisco DevNet
In this small group, hands-on workshop session you'll learn how to write your first Python application that uses YANG, NETCONF and , RESTCONF to access operational and configuration data on a device.
Watch the DevNet 2044 replay from the Cisco Live On-Demand Library at: https://www.ciscolive.com/online/connect/sessionDetail.ww?SESSION_ID=92725&backBtn=true
Check out more and register for Cisco DevNet: http://ow.ly/jCNV3030OfS
Basically everything you need to get started on your Zookeeper training, and setup apache Hadoop high availability with QJM setup with automatic failover.
Laboratory 04 Circularly Linked ListDownload the following files.docxfestockton
Laboratory 04: Circularly Linked List
Download the following files:
Lab04Files.zip
//provided, completed files
CLGUI.h
CLGUI.cpp
CircularList.h
CircularListIterator.h
Circular List Navigation
The main reason to use a circularly (doubly) linked list is the fact that it is fast to move from the end of the list to the beginning of the list in either direction. However, to use this speed, you must first determine the number of steps to get to the destination index using next links vs. using prev links. Complete the
find(int index)
method in CircularList.h to make this determination.
Circular List Removal
Complete the
remove(int index)
method in CircularList.h. To get to the requested index, call the find method. Removing the last item in the list is a special case. Set loc_pos to the removal location (set loc_pos to 0 if the last item is removed). Remember to delete nodes as appropriate, but not data.
The below class interfaces are defined in the namespace
CSC2110
.
String methods
String(const char* text) //constructor
void displayString()
int length()
const char* getText()
int a_to_i()
float a_to_f()
String* i_to_a(int number) //static method
String* f_to_a(float number) //static method
int find(char delimiter, int start) //find the index of a particular character
String* substr(int start, int end)
int compare(String* other)
char charAt(int index) //0-based
Tokens methods
Tokens(String* str, char delimiter) //destructor does not delete the individual tokens
String* getToken(int index)
int getNumTokens()
void displayTokens()
ReadFile methods
ReadFile(const char* file_name)
String* readLine()
bool eof()
void close()
WriteFile methods
WriteLine(String* file_name)
void writeLine(String* line)
void close()
Random methods (use getRandom first)
static Random* getRandom()
int getRandomInt(int lower, int upper)
float getRandomFloat(float lower, float upper)
Keyboard methods (use getKeyboard first)
static Keyboard* getKeyboard() //call this first
int readInt(string prompt)
int getValidatedInt(string prompt, int min, int max)
double readDouble(string prompt)
double getValidatedDouble(string prompt, double min, double max)
String* readString(string prompt)
Integer/Double methods
Integer(int val)/Double(double val)
int getValue()/double getValue()
CD methods
CD(String* artist, String* title, int year, int rating, int num_tracks)
void displayCD() //display the current state of the CD
String* getKey()
void addSong(String* title, String* length)
static int compare_items(CD* one, CD* two) //define how to compare CDs (in this case, by title)
static int compare_keys(String* sk, CD* cd)
static ListArray* readCDs(const char* file_name) //read in all of the CDs from a text file
Song methods
Song(String* title, String* length)
void displaySong()
.
В своей презентации “С++ 11 usage experience: Move semantic”, Дмитрий Гурин, bp GlobalLogic, рассказывает о части нововведений нового стандарта C++, особенностях работы с объектами rvalue и lvalue, а также особенностями использования функций std::move и std::forward. В конце доклада — полезные советы по оптимизации кода с применением возможностей нового стандарта С++.
Напомним, Embedded Kyiv TechTalk состоялся 14 декабря 2013 года.
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.
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.
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.
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.
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.
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.
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.
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
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.
7. NIO Features Channel and Buffers File locking Memory Mapped Files Scatter and Gather Channel to Channel Transfer Non-Blocking Sockets Multiplexed I/O
10. Buffer Basic Operations: Creating Filling and Draining Flipping and Rewind Marking Comparing Duplicating
11. Creating public static XXXBuffer allocate (int capacity) public static XXXBuffer wrap (XXX [] array) public static XXXBuffer wrap (XXX [] array, int offset,int length) For e.g. CharBuffer charBuffer= CharBuffer.allocate(10); char [] charArray = new char [10]; CharBuffercharbuffer = CharBuffer.wrap (charArray ); CharBuffercharbuffer = CharBuffer.wrap (charArray, 2, 7);
12. Filling and Draining XXXBuffer put (XXX b); XXXBuffer put (int index, XXX b); XXX get( ); XXX get(int index); XXXBufferput (XXX[] src); XXXBuffer put(XXX [] src, int offset, int length); XXXBuffer get(XXX[] dest); XXXBuffer get(XXX [] dest, int offset, int length);
13. Flipping and Rewind Manually Flipping a Buffer: buffer.limit(buffer.position( )).position(0) API provides Flip and rewind method: Buffer flip() Buffer rewind()
14. Marking Buffer mark() Buffer reset() For e.g buffer.position(2).mark( ).position(4);
41. Readiness Selection Socket channels can be check for readiness A single thread can monitor a large number of socket Steps to do readiness selection Create a Selector instance Register one or more non-blocking channels with it Implement a infinite loop and wait for events Get the selected keys list and iterate the keys Process the events. Remove the key from the list
49. SeekableByteChannel A byte channel that maintains a current position and allows the position to be changed. Key Methods SeekableByteChannel position(long newPosition) SeekableByteChannel truncate(long size)
50. NetworkChannel & MulticastChanneljava.nio.channels NetworkChannels: All the network-oriented channels implements the new NetworkChannel interface We can easily bind the channel socket, set and query for socket options MulticastChannels: We can send and receive IP datagrams from a complete group Implement by DatagramChannel and AsynchronousDatagramChannel
51. Pathjava.nio.file Locates a file using a system dependent path Defines methods to access and manipulate paths Defines methods to access files
52. Creating a Path // Microsoft Windows Path p1 = Paths.get("C:homejoefoo"); // Solaris syntax Path path = Paths.get("/home/joe/foo"); Path p4 = FileSystems.getDefault().getPath("/users/sally");
58. Walk File Tree Walk a file tree rooted at a given starting file Implement FileVisitor interface Initiate the process by calling anyone of the below method of java.nio.file.FilesClass walkFileTree(Path start, FileVisitor<? super Path> visitor) walkFileTree(Path start, Set<FileVisitOption> options, intmaxDepth, FileVisitor<? super Path> visitor)
61. File Change Notification Looking for file changes in FileSystem Using the native event facility whenever available Steps required to implement a watch service Create a WatchService "watcher" for the file system. For each directory that you want monitored, register it with the watcher. Implement an infinite loop to wait for incoming events Retrieve the key from the watcher's queue. Process all the events associated with the Key. Reset the key, and resume waiting for events. Close the service
64. WatchKeyjava.nio.file WatchKey represents registration of a watchable object with a WatchService. Key Methods: List<WatchEvent<?>> pollEvents() Watchable watchable() boolean reset() boolean isValid() void cancel()
65. File Attributesjava.nio.file.attribute Meta-data associated with file Generalized metadata API Fetch a file's attributes in one bulk operation Map<String,Object> readAttributes(Path, String, LinkOption...) <A extends BasicFileAttributes> readAttributes(Path, Class<A>, LinkOption...) Grouping of related attributes and Views to access the attribute groups.
68. Asynchronous I/Ojava.nio.channels They provide asynchronous operations for both sockets and files. All operations work in non-blocking mode. All the asynchronous I/O operations have one of two forms : The first one returns a java.util.concurrent.Future that represent the pending result The second one is created using a CompletionHandler.
70. CompletionHandler Future result = channel.read(buffer, 100, buffer, new CompletionHandler(){ public void completed(Integer result, ByteBuffer buffer){ //Compute the result } public void failed(Throwable exception, ByteBuffer buffer){ // Handle the error } });
71. References: Java NIO by Ron Hitchens Publisher: O’Reilly http://java.sun.com/developer/technicalArticles/javase/nio/ http://download.oracle.com/javase/tutorial/essential/io/index.html