GDPR regulations will affect the way your organization collects and manages customer data in Europe. This will require changes to your business processes along with IT applications and infrastructure updates. In the webinar, 5 Ways to Make Your Postgres GDPR-Ready, you'll discover what you need to do to prepare your Postgres databases for GDPR including:
- An overview of GDPR and its detailed requirements
- Strategies for preparing your Postgres databases for compliance
- Examples of relevant Postgres capabilities, code changes, process modifications, and third-party tools
- Where to turn for the expertise and support you need to succeed
View Now at: https://attendee.gotowebinar.com/register/3457814923722973699
Spark Hadoop Tutorial | Spark Hadoop Example on NBA | Apache Spark Training |...Edureka!
This Edureka Spark Hadoop Tutorial will help you understand how to use Spark and Hadoop together. This Spark Hadoop tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Apache Spark concepts. Below are the topics covered in this tutorial:
1) Spark Overview
2) Hadoop Overview
3) Spark vs Hadoop
4) Why Spark Hadoop?
5) Using Hadoop With Spark
6) Use Case - Sports Analytics (NBA)
A Thorough Comparison of Delta Lake, Iceberg and HudiDatabricks
Recently, a set of modern table formats such as Delta Lake, Hudi, Iceberg spring out. Along with Hive Metastore these table formats are trying to solve problems that stand in traditional data lake for a long time with their declared features like ACID, schema evolution, upsert, time travel, incremental consumption etc.
A Tale of Three Apache Spark APIs: RDDs, DataFrames, and Datasets with Jules ...Databricks
Of all the developers’ delight, none is more attractive than a set of APIs that make developers productive, that are easy to use, and that are intuitive and expressive. Apache Spark offers these APIs across components such as Spark SQL, Streaming, Machine Learning, and Graph Processing to operate on large data sets in languages such as Scala, Java, Python, and R for doing distributed big data processing at scale. In this talk, I will explore the evolution of three sets of APIs-RDDs, DataFrames, and Datasets-available in Apache Spark 2.x. In particular, I will emphasize three takeaways: 1) why and when you should use each set as best practices 2) outline its performance and optimization benefits; and 3) underscore scenarios when to use DataFrames and Datasets instead of RDDs for your big data distributed processing. Through simple notebook demonstrations with API code examples, you’ll learn how to process big data using RDDs, DataFrames, and Datasets and interoperate among them. (this will be vocalization of the blog, along with the latest developments in Apache Spark 2.x Dataframe/Datasets and Spark SQL APIs: https://databricks.com/blog/2016/07/14/a-tale-of-three-apache-spark-apis-rdds-dataframes-and-datasets.html)
Review the latest features released in Neo4j version 4.1 including Cypher, database drivers, clustering, security, and extension libraries like APOC and Spring Data Neo4j!
Building Robust ETL Pipelines with Apache SparkDatabricks
Stable and robust ETL pipelines are a critical component of the data infrastructure of modern enterprises. ETL pipelines ingest data from a variety of sources and must handle incorrect, incomplete or inconsistent records and produce curated, consistent data for consumption by downstream applications. In this talk, we’ll take a deep dive into the technical details of how Apache Spark “reads” data and discuss how Spark 2.2’s flexible APIs; support for a wide variety of datasources; state of art Tungsten execution engine; and the ability to provide diagnostic feedback to users, making it a robust framework for building end-to-end ETL pipelines.
Spark Hadoop Tutorial | Spark Hadoop Example on NBA | Apache Spark Training |...Edureka!
This Edureka Spark Hadoop Tutorial will help you understand how to use Spark and Hadoop together. This Spark Hadoop tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Apache Spark concepts. Below are the topics covered in this tutorial:
1) Spark Overview
2) Hadoop Overview
3) Spark vs Hadoop
4) Why Spark Hadoop?
5) Using Hadoop With Spark
6) Use Case - Sports Analytics (NBA)
A Thorough Comparison of Delta Lake, Iceberg and HudiDatabricks
Recently, a set of modern table formats such as Delta Lake, Hudi, Iceberg spring out. Along with Hive Metastore these table formats are trying to solve problems that stand in traditional data lake for a long time with their declared features like ACID, schema evolution, upsert, time travel, incremental consumption etc.
A Tale of Three Apache Spark APIs: RDDs, DataFrames, and Datasets with Jules ...Databricks
Of all the developers’ delight, none is more attractive than a set of APIs that make developers productive, that are easy to use, and that are intuitive and expressive. Apache Spark offers these APIs across components such as Spark SQL, Streaming, Machine Learning, and Graph Processing to operate on large data sets in languages such as Scala, Java, Python, and R for doing distributed big data processing at scale. In this talk, I will explore the evolution of three sets of APIs-RDDs, DataFrames, and Datasets-available in Apache Spark 2.x. In particular, I will emphasize three takeaways: 1) why and when you should use each set as best practices 2) outline its performance and optimization benefits; and 3) underscore scenarios when to use DataFrames and Datasets instead of RDDs for your big data distributed processing. Through simple notebook demonstrations with API code examples, you’ll learn how to process big data using RDDs, DataFrames, and Datasets and interoperate among them. (this will be vocalization of the blog, along with the latest developments in Apache Spark 2.x Dataframe/Datasets and Spark SQL APIs: https://databricks.com/blog/2016/07/14/a-tale-of-three-apache-spark-apis-rdds-dataframes-and-datasets.html)
Review the latest features released in Neo4j version 4.1 including Cypher, database drivers, clustering, security, and extension libraries like APOC and Spring Data Neo4j!
Building Robust ETL Pipelines with Apache SparkDatabricks
Stable and robust ETL pipelines are a critical component of the data infrastructure of modern enterprises. ETL pipelines ingest data from a variety of sources and must handle incorrect, incomplete or inconsistent records and produce curated, consistent data for consumption by downstream applications. In this talk, we’ll take a deep dive into the technical details of how Apache Spark “reads” data and discuss how Spark 2.2’s flexible APIs; support for a wide variety of datasources; state of art Tungsten execution engine; and the ability to provide diagnostic feedback to users, making it a robust framework for building end-to-end ETL pipelines.
Operating and Supporting Delta Lake in ProductionDatabricks
Delta lake is widely adopted. There are things to be aware of when dealing with petabytes of data in Delta Lake. These smart decisions can give the best efficiency and increase the adoption of Delta. Best practices like OPTIMIZE, ZORDER have to wisely chosen. We have support stories where we successfully resolved performance issues by applying the right performance strategy. There are a set of common issues or repeated questions from our strategic customers face when using Delta and in this session we cover them and how to address them.
Iceberg: a modern table format for big data (Ryan Blue & Parth Brahmbhatt, Netflix)
Presto Summit 2018 (https://www.starburstdata.com/technical-blog/presto-summit-2018-recap/)
Every business today wants to leverage data to drive strategic initiatives with machine learning, data science and analytics — but runs into challenges from siloed teams, proprietary technologies and unreliable data.
That’s why enterprises are turning to the lakehouse because it offers a single platform to unify all your data, analytics and AI workloads.
Join our How to Build a Lakehouse technical training, where we’ll explore how to use Apache SparkTM, Delta Lake, and other open source technologies to build a better lakehouse. This virtual session will include concepts, architectures and demos.
Here’s what you’ll learn in this 2-hour session:
How Delta Lake combines the best of data warehouses and data lakes for improved data reliability, performance and security
How to use Apache Spark and Delta Lake to perform ETL processing, manage late-arriving data, and repair corrupted data directly on your lakehouse
In this session, Sergio covered the Lakehouse concept and how companies implement it, from data ingestion to insight. He showed how you could use Azure Data Services to speed up your Analytics project from ingesting, modelling and delivering insights to end users.
Neptune is a Graph database, but what is a graph database, when should it be used and how? Come to this sessions and learn about Neptune and the different use cases for graph databases and how it can be used, including demos.
Apache Spark Data Source V2 with Wenchen Fan and Gengliang WangDatabricks
As a general computing engine, Spark can process data from various data management/storage systems, including HDFS, Hive, Cassandra and Kafka. For flexibility and high throughput, Spark defines the Data Source API, which is an abstraction of the storage layer. The Data Source API has two requirements.
1) Generality: support reading/writing most data management/storage systems.
2) Flexibility: customize and optimize the read and write paths for different systems based on their capabilities.
Data Source API V2 is one of the most important features coming with Spark 2.3. This talk will dive into the design and implementation of Data Source API V2, with comparison to the Data Source API V1. We also demonstrate how to implement a file-based data source using the Data Source API V2 for showing its generality and flexibility.
SQL is a popular database language for modern applications, given its flexibility in modelling workloads and how widely it is understood by developers. However, most modern applications running in the clouds require fault tolerance, the ability to scale out and geographic data distribution of data. These are hard to achieve with traditional SQL databases, which is paving the way for distributed SQL databases.
Google Spanner is arguably the world's first truly distributed SQL database. Given its fully decentralized architecture, it delivers higher performance and availability for geo-distributed SQL workloads than other specialized transactional databases such as Amazon Aurora. Now, there are a number of open source derivatives of Google Spanner such as YugaByte DB, CockroachDB and TiDB. This talk will focus on the common architectural paradigms that these databases are built on (using YugaByte DB as an example). Learn about the concepts these databases leverage, how to evaluate if these will meet your needs and the questions to ask to differentiate among these databases.
Linked Open Data Principles, Technologies and ExamplesOpen Data Support
Theoretical and practical introducton to linked data, focusing both on the value proposition, the theory/foundations, and on practical examples. The material is tailored to the context of the EU institutions.
Analyzing Flight Delays with Apache Spark, DataFrames, GraphFrames, and MapR-DBCarol McDonald
Apache Spark GraphX made it possible to run graph algorithms within Spark, GraphFrames integrates GraphX and DataFrames and makes it possible to perform Graph pattern queries without moving data to a specialized graph database.
This presentation will help you get started using Apache Spark GraphFrames Graph Algorithms and Graph Queries with MapR-DB JSON document database.
This session covers how to work with PySpark interface to develop Spark applications. From loading, ingesting, and applying transformation on the data. The session covers how to work with different data sources of data, apply transformation, python best practices in developing Spark Apps. The demo covers integrating Apache Spark apps, In memory processing capabilities, working with notebooks, and integrating analytics tools into Spark Applications.
Presentation / Workshop which will teach you the core patterns, concepts and visualisation options of D3.js (v4). Accompanying exercises can be found here: https://github.com/josdirksen/d3exercises
This is the presentation for the lecture of Dimitar Mitov "Data Analytics with Dremio" (in Bulgarian), part of OpenFest 2022: https://www.openfest.org/2022/bg/full-schedule-bg/
The webinar will review a multi-layered framework for PostgreSQL security, with a deeper focus on limiting access to the database and data, as well as securing the data.
Using the popular AAA (Authentication, Authorization, Auditing) framework we will cover:
- Best practices for authentication (trust, certificate, MD5, Scram, etc).
- Advanced approaches, such as password profiles.
- Deep dive of authorization and data access control for roles, database objects (tables, etc), view usage, row-level security, and data redaction.
- Auditing, encryption, and SQL injection attack prevention.
Note: this session is delivered in French
We will review a multi-layered framework for PostgreSQL security, with a deeper focus on limiting access to the database and data, as well as securing the data. Using the popular AAA (Authentication, Authorization, Auditing) framework we will cover:
Best practices for authentication (trust, certificate, MD5, Scram, etc).
Advanced approaches, such as password profiles.
Deep dive of authorization and data access control for roles, database objects (tables etc), view usage, row level security and data redaction.
Auditing, encryption and SQL injection attack prevention.
Operating and Supporting Delta Lake in ProductionDatabricks
Delta lake is widely adopted. There are things to be aware of when dealing with petabytes of data in Delta Lake. These smart decisions can give the best efficiency and increase the adoption of Delta. Best practices like OPTIMIZE, ZORDER have to wisely chosen. We have support stories where we successfully resolved performance issues by applying the right performance strategy. There are a set of common issues or repeated questions from our strategic customers face when using Delta and in this session we cover them and how to address them.
Iceberg: a modern table format for big data (Ryan Blue & Parth Brahmbhatt, Netflix)
Presto Summit 2018 (https://www.starburstdata.com/technical-blog/presto-summit-2018-recap/)
Every business today wants to leverage data to drive strategic initiatives with machine learning, data science and analytics — but runs into challenges from siloed teams, proprietary technologies and unreliable data.
That’s why enterprises are turning to the lakehouse because it offers a single platform to unify all your data, analytics and AI workloads.
Join our How to Build a Lakehouse technical training, where we’ll explore how to use Apache SparkTM, Delta Lake, and other open source technologies to build a better lakehouse. This virtual session will include concepts, architectures and demos.
Here’s what you’ll learn in this 2-hour session:
How Delta Lake combines the best of data warehouses and data lakes for improved data reliability, performance and security
How to use Apache Spark and Delta Lake to perform ETL processing, manage late-arriving data, and repair corrupted data directly on your lakehouse
In this session, Sergio covered the Lakehouse concept and how companies implement it, from data ingestion to insight. He showed how you could use Azure Data Services to speed up your Analytics project from ingesting, modelling and delivering insights to end users.
Neptune is a Graph database, but what is a graph database, when should it be used and how? Come to this sessions and learn about Neptune and the different use cases for graph databases and how it can be used, including demos.
Apache Spark Data Source V2 with Wenchen Fan and Gengliang WangDatabricks
As a general computing engine, Spark can process data from various data management/storage systems, including HDFS, Hive, Cassandra and Kafka. For flexibility and high throughput, Spark defines the Data Source API, which is an abstraction of the storage layer. The Data Source API has two requirements.
1) Generality: support reading/writing most data management/storage systems.
2) Flexibility: customize and optimize the read and write paths for different systems based on their capabilities.
Data Source API V2 is one of the most important features coming with Spark 2.3. This talk will dive into the design and implementation of Data Source API V2, with comparison to the Data Source API V1. We also demonstrate how to implement a file-based data source using the Data Source API V2 for showing its generality and flexibility.
SQL is a popular database language for modern applications, given its flexibility in modelling workloads and how widely it is understood by developers. However, most modern applications running in the clouds require fault tolerance, the ability to scale out and geographic data distribution of data. These are hard to achieve with traditional SQL databases, which is paving the way for distributed SQL databases.
Google Spanner is arguably the world's first truly distributed SQL database. Given its fully decentralized architecture, it delivers higher performance and availability for geo-distributed SQL workloads than other specialized transactional databases such as Amazon Aurora. Now, there are a number of open source derivatives of Google Spanner such as YugaByte DB, CockroachDB and TiDB. This talk will focus on the common architectural paradigms that these databases are built on (using YugaByte DB as an example). Learn about the concepts these databases leverage, how to evaluate if these will meet your needs and the questions to ask to differentiate among these databases.
Linked Open Data Principles, Technologies and ExamplesOpen Data Support
Theoretical and practical introducton to linked data, focusing both on the value proposition, the theory/foundations, and on practical examples. The material is tailored to the context of the EU institutions.
Analyzing Flight Delays with Apache Spark, DataFrames, GraphFrames, and MapR-DBCarol McDonald
Apache Spark GraphX made it possible to run graph algorithms within Spark, GraphFrames integrates GraphX and DataFrames and makes it possible to perform Graph pattern queries without moving data to a specialized graph database.
This presentation will help you get started using Apache Spark GraphFrames Graph Algorithms and Graph Queries with MapR-DB JSON document database.
This session covers how to work with PySpark interface to develop Spark applications. From loading, ingesting, and applying transformation on the data. The session covers how to work with different data sources of data, apply transformation, python best practices in developing Spark Apps. The demo covers integrating Apache Spark apps, In memory processing capabilities, working with notebooks, and integrating analytics tools into Spark Applications.
Presentation / Workshop which will teach you the core patterns, concepts and visualisation options of D3.js (v4). Accompanying exercises can be found here: https://github.com/josdirksen/d3exercises
This is the presentation for the lecture of Dimitar Mitov "Data Analytics with Dremio" (in Bulgarian), part of OpenFest 2022: https://www.openfest.org/2022/bg/full-schedule-bg/
The webinar will review a multi-layered framework for PostgreSQL security, with a deeper focus on limiting access to the database and data, as well as securing the data.
Using the popular AAA (Authentication, Authorization, Auditing) framework we will cover:
- Best practices for authentication (trust, certificate, MD5, Scram, etc).
- Advanced approaches, such as password profiles.
- Deep dive of authorization and data access control for roles, database objects (tables, etc), view usage, row-level security, and data redaction.
- Auditing, encryption, and SQL injection attack prevention.
Note: this session is delivered in French
We will review a multi-layered framework for PostgreSQL security, with a deeper focus on limiting access to the database and data, as well as securing the data. Using the popular AAA (Authentication, Authorization, Auditing) framework we will cover:
Best practices for authentication (trust, certificate, MD5, Scram, etc).
Advanced approaches, such as password profiles.
Deep dive of authorization and data access control for roles, database objects (tables etc), view usage, row level security and data redaction.
Auditing, encryption and SQL injection attack prevention.
Ethyca CodeDriven - Data Privacy Compliance for Engineers & Data TeamsCillian Kieran
A presentation at FirstMark's CodeDriven event in AWS Loft in New York on how to think about Data Privacy Compliance if you work in engineering, data or product teams.
The webinar will review a multi-layered framework for PostgreSQL security, with a deeper focus on limiting access to the database and data, as well as securing the data.
Using the popular AAA (Authentication, Authorization, Auditing) framework we will cover:
- Best practices for authentication (trust, certificate, MD5, Scram, etc).
- Advanced approaches, such as password profiles.
- Deep dive of authorization and data access control for roles, database objects (tables, etc), view usage, row-level security, and data redaction.
- Auditing, encryption, and SQL injection attack prevention.
Note: this session is delivered in German
Speaker:
Borys Neselovskyi, Sales Engineer, EDB
Creating a Multi-Layered Secured Postgres DatabaseEDB
Join EDB’s SVP of Product Development and Support, Marc Linster in this webinar, he discusses the process of creating a multi-layered security architecture for your Postgres database.
During this session, we will cover:
- Aspects of Data Security
- Authentication, Authorization & Auditing
- Multiple Layers of Security
Learn security best practices for managing your Postgres databases.
Improve IT Security and Compliance with Mainframe Data in SplunkPrecisely
Avoid security blind spots with an enterprise-wide view.
If your organization relies on Splunk as its security nerve center, you can’t afford to leave out your mainframes.
They work with the rest of your IT infrastructure to support critical business applications–and they need to be
viewed in that wider context to address potential security blind spots.
Although the importance of including mainframe data in Splunk is undeniable, many organizations have left it out
because Splunk doesn’t natively support IBM Z® environments. Learn how Precisely Ironstream can help with a
straight-forward, powerful approach for integrating your mainframe security data into Splunk, and making it actionable
once it’s there.
Database Auditing Essentials... or... Who did what to which data when and how?
The combination of increasing government regulation and the need for securing corporate data has driven up the need to track who is accessing data in our corporate databases. This presentation discusses these drivers as well as presenting the requirements for auditing data access in corporate databases.
The goal of this presentation is to review the regulations impacting the need to audit, and then to discuss in detail the kinds of things that may need to be audited, along with the several ways of accomplishing this.
How Cloudera SDX can aid GDPR compliance 6.21.18Cloudera, Inc.
In this webinar, we will cover:
Technical capabilities required in your data platform including metadata classification on ingest, column-level lineage, fine-grained authorization, encryption, and more
How a shared data experience can facilitate the safe handling of metadata
Ways to enable your data platform for GDPR success
GDPR Compliance Made Easy with Data VirtualizationDenodo
Companies should be gearing up for May 25, 2018 when the General Data Protection Regulation (GDPR) comes into effect. GPDR will affect how businesses that serve the European Union collect, use and transfer data, forcing them to provide specific reasons and need for the personal data they gather and prove their compliance with the principles established by the regulation.
The regulation is already creating many challenges for companies, including:
• Ensuring secure access to most current data, whether on or off-premise
• Consistent security across all data sources
• Data access audit
• Ability to provide data lineage
This webinar aims to demonstrate how data virtualization has surfaced as a straight-forward solution to many of the challenges and questions brought on by the GDPR. It will also include a case study of how Asurion already achieved the desired level of security with data virtualization.
Watch the webinar in full to learn more about the benefits of using data virtualization to smoothly comply with the GDPR: http://ow.ly/1kzk30bRw3i
The GDPR requires organizations — both “data controllers” and “data processors” — to strengthen their data protection and security measures to protect the personally identifiable information (PII) of EU citizens, and to demonstrate their compliance at any time. See how Quest solutions can help make it easier to ensure that your customer on-premises, cloud or hybrid environment meets GDPR compliance requirements.
Join Storage Switzerland and Tegile Systems for our on demand webinar, “How to Design Primary Storage for GDPR,” to learn how design primary storage architectures in the GDPR era. The data center now has three realities to deal with.
Kangaroot EDB Webinar Best Practices in Security with PostgreSQLKangaroot
The webinar will review a multi-layered framework for PostgreSQL security, with a deeper focus on limiting access to the database and data, as well as securing the data.
Using the popular AAA (Authentication, Authorisation, Auditing) framework EnterpriseDB will cover:
- Best practices for authentication (trust, certificate, MD5, Scram, etc).
- Advanced approaches, such as password profiles.
- Deep dive of authorisation and data access control for roles, database objects (tables, etc), view usage, row-level security, and data redaction.
- Auditing, encryption, and SQL injection attack prevention
Cloud Migration Paths: Kubernetes, IaaS, or DBaaSEDB
Moving to the cloud is hard, and moving Postgres databases to the cloud is even harder. Public cloud or private cloud? Infrastructure as a Service (IaaS), or Platform as a Service (PaaS)? Kubernetes for the application, or for the database and the application? This talk will juxtapose self-managed Kubernetes and container-based database solutions, Postgres deployments on IaaS, and Postgres DBaaS solutions of which EDB’s DBaaS BigAnimal is the latest example.
Die 10 besten PostgreSQL-Replikationsstrategien für Ihr UnternehmenEDB
Dieses Webinar hilft Ihnen, die Unterschiede zwischen den verschiedenen Replikationsansätzen zu verstehen, die Anforderungen der jeweiligen Strategie zu erkennen und sich über die Möglichkeiten klar zu werden, was mit jeder einzelnen zu erreichen ist. Damit werden Sie hoffentlich eher in der Lage sein, herauszufinden, welche PostgreSQL-Replikationsarten Sie wirklich für Ihr System benötigen.
- Wie physische und logische Replikation in PostgreSQL funktionieren
- Unterschiede zwischen synchroner und asynchroner Replikation
- Vorteile, Nachteile und Herausforderungen bei der Multi-Master-Replikation
- Welche Replikationsstrategie für unterschiedliche Use-Cases besser geeignet ist
Referent:
Borys Neselovskyi, Regional Sales Engineer DACH, EDB
------------------------------------------------------------
For more #webinars, visit http://bit.ly/EDB-Webinars
Download free #PostgreSQL whitepapers: http://bit.ly/EDB-Whitepapers
Read our #Postgres Blog http://bit.ly/EDB-Blogs
Follow us on Facebook at http://bit.ly/EDB-FB
Follow us on Twitter at http://bit.ly/EDB-Twitter
Follow us on LinkedIn at http://bit.ly/EDB-LinkedIn
Reach us via email at marketing@enterprisedb.com
Cuando busca alternativas a Oracle en la nube, hacer el cambio puede parecer un trabajo duro. Entendemos que la migración involucra más que solo la base de datos. La compatibilidad es un punto clave, especialmente cuando se consideran los recursos que posiblemente ya haya invertido en Oracle, como por ejemplo el código de aplicación específico de Oracle.Este seminario web explorará las opciones y las principales consideraciones al pasar de las bases de datos de Oracle a la nube.
- Revisión detallada de las ofertas de bases de datos disponibles en la nube
- Factores críticos que se deben considerar considerar para elegir la oferta en la nube más adecuada
- Cómo la experiencia de EDB con PostgreSQL puede ayudarlo en su decisión
- Demostración de BigAnimal de EDB
Présentateur:
Sergio Romera, Senior Sales Engineer EMEA, EDB
------------------------------------------------------------
For more #webinars, visit http://bit.ly/EDB-Webinars
Download free #PostgreSQL whitepapers: http://bit.ly/EDB-Whitepapers
Read our #Postgres Blog http://bit.ly/EDB-Blogs
Follow us on Facebook at http://bit.ly/EDB-FB
Follow us on Twitter at http://bit.ly/EDB-Twitter
Follow us on LinkedIn at http://bit.ly/EDB-LinkedIn
Reach us via email at marketing@enterprisedb.com
Database come PostgreSQL non possono girare su Kubernetes. Questo è il ritornello che sentiamo continuamente, ma al tempo stesso la motivazione per noi di EDB di abbattere questo muro, una volta per tutte.
In questo webinar parleremo della nostra avventura finora per portare PostgreSQL su Kubernetes. Scopri perché crediamo che fare benchmark di storage e del database prima di andare in produzione porti a una più sana e longeva vita di un DBMS, anche su Kubernetes.
Condivideremo il nostro processo, i risultati fin qui ottenuti e sveleremo i nostri piani per il futuro con Cloud Native PostgreSQL.
Las Variaciones de la Replicación de PostgreSQLEDB
Replicación física, replicación lógica, síncrona, asíncrona, multi-maestro, escalabilidad horizontal, etc. Son muchos los términos asociados con la replicación de bases de datos. En esta charla revisaremos los conceptos fundamentales detrás de cada variación de la replicación de PostgreSQL, y en qué casos conviene usar una o la otra. La presentación incluye una parte práctica con demostraciones aunque no será un tutorial sobre como configurar un cluster. El enfoque está en entender cada variación para elegir la mejor dependiendo del caso de uso.
Cosas que aprenderán:
- Cómo funciona la replicación física en PostgreSQL
- Cómo funciona la replicación lógica en PostgreSQL
- Diferencias entre replicación síncrona y asíncrona
- Qué es replicación multi-maestro
NoSQL and Spatial Database Capabilities using PostgreSQLEDB
PostgreSQL is an object-relational database system. NoSQL on the other hand is a non-relational database and is document-oriented. Learn how the PostgreSQL database gives one the flexible options to combine NoSQL workloads with the relational query power by offering JSON data types. With PostgreSQL, new capabilities can be developed and plugged into the database as required.
Attend this webinar to learn:
- The new features and capabilities in PostgreSQL for new workloads, requiring greater flexibility in the data model
- NoSQL with JSON, Hstore and its performance and features for enterprises
- Spatial SQL - advanced features in PostGIS application with PostGIS extension
"Why use PgBouncer? It’s a lightweight, easy to configure connection pooler and it does one job well. As you’d expect from a talk on connection pooling, we’ll give a brief summary of connection pooling and why it increases efficiency. We’ll look at when not to use connection pooling, and we’ll demonstrate how to configure PgBouncer and how it works. But. Did you know you can also do this? 1. Scaling PgBouncer PgBouncer is single threaded which means a single instance of PgBouncer isn’t going to do you much good on a multi-threaded and/or multi-CPU machine. We’ll show you how to add more PgBouncer instances so you can use more than one thread for easy scaling. 2. Read-write / read only routing Using different pgBouncer databases you can route read-write traffic to the primary database and route read-only traffic to a number of standby databases. 3. Load balancing When we use multiple PgBouncer instances, load balancing comes for free. Load balancing can be directed to different standbys, and weighted according to ratios of load. 4. Silent failover You can perform silent failover during promotion of a new primary (assuming you have a VIP/DNS etc that always points to the primary). 5. And even: DoS prevention and protection from “badly behaved” applications! By using distinct port numbers you can provide database connections which deal with sudden bursts of incoming traffic in very different ways, which can help prevent the database from becoming swamped during high activity periods. You should leave the presentation wondering if there is anything PgBouncer can’t do."
In this talk I'll discuss how we can combine the power of PostgreSQL with TensorFlow to perform data analysis. By using the pl/python3 procedural language we can integrate machine learning libraries such as TensorFlow with PostgreSQL, opening the door for powerful data analytics combining SQL with AI. Typical use-cases might involve regression analysis to find relationships in an existing dataset and to predict results based on new inputs, or to analyse time series data and extrapolate future data taking into account general trends and seasonal variability whilst ignoring noise. Python is an ideal language for building custom systems to do this kind of work as it gives us access to a rich ecosystem of libraries such as Pandas and Numpy, in addition to TensorFlow itself.
Practical Partitioning in Production with PostgresEDB
Has your table become too large to handle? Have you thought about chopping it up into smaller pieces that are easier to query and maintain? What if it's in constant use? An introduction to the problems that can arise and how PostgreSQL's partitioning features can help, followed by a real-world scenario of partitioning an existing huge table on a live system. We will be looking at the problems caused by having very large tables in your database and how declarative table partitioning in Postgres can help. Also, how to perform dimensioning before but also after creating huge tables, partitioning key selection, the importance of upgrading to get the latest Postgres features and finally we will dive into a real-world scenario of having to partition an existing huge table in use on a production system.
There have been plenty of “explaining EXPLAIN” type talks over the years, which provide a great introduction to it. They often also cover how to identify a few of the more common issues through it. EXPLAIN is a deep topic though, and to do a good introduction talk, you have to skip over a lot of the tricky bits. As such, this talk will not be a good introduction to EXPLAIN, but instead a deeper dive into some of the things most don’t cover. The idea is to start with some of the more complex and unintuitive calculations needed to work out the relationships between operations, rows, threads, loops, timings, buffers, CTEs and subplans. Most popular tools handle at least several of these well, but there are cases where they don’t that are worth being conscious of and alert to. For example, we’ll have a look at whether certain numbers are averaged per-loop or per-thread, or both. We’ll also cover a resulting rounding issue or two to be on the lookout for. Finally, some per-operation timing quirks are worth looking out for where CTEs and subqueries are concerned, for example CTEs that are referenced more than once. As time allows, we can also look at a few rarer issues that can be spotted via EXPLAIN, as well as a few more gotchas that we’ve picked up along the way. This includes things like spotting when the query is JIT, planning, or trigger time dominated, spotting the signs of table and index bloat, issues like lossy bitmap scans or index-only scans fetching from the heap, as well as some things to be aware of when using auto_explain.
Internet of Things is a currently a burgeoning market, and is often associated with specialized data-stores. However PostgreSQL is just as capable at this use-case and can offer some compelling advantages. We’ll explore ways to store IoT data in PostgreSQL covering various ways to store and structure this kind of data. How range types and differing types of indexes can be of use. Also taking a quick look at some extensions designed for this use case. Then looking at powerful SQL features which can really help when analyzing IoT data streams, and how the power of a real SQL database can be a key advantage.
I would like you to join me on our journey from a complex, multi instance Oracle topology to a single logical database in PostgreSQL. Each technology and architectural decision point will be discussed describing how we arrived at our destination. There are five keys areas that will be covered: - Target architecture - Migration of database objects (tables, indexes, views, synonyms, etc) - Migration of database code (packages, functions, procedures, triggers) - Application tier - Migration of Data - with minimal downtime during cutover The target architecture is a BDR cluster, where the physical data model and data stored is different between the logical standbys and the lead master/shadow master. Will discuss how this allowed for the simplification of the topology, and the benefits this delivered. Before you go there, yes I know PostgreSQL does no have synonyms, but an alternative approach was needed. There is a significant amount of business logic in the database tier all of which needed to be translated into database code. Will look at the tools and extensions available to reproduce the functionality in PostgreSQL. Look at common non-ISO standard SQL embedded in the application tier, along with jdbc challenges. Finally a look at some of the data movement tools available. Full disclosure, we are still on the journey but have learnt a lot on the way.
The proposed talk will go through several questions. The first obvious one is why would I bother learn CLI when I can do whatever I need with a GUI tool?
We'll try to answer why knowing CLI is a MUST for some people (like Postgres DBAs, for example) whereas it's only a bonus for others (like data scientists, for example).
Then we'll go through the basics about 101 (how to connect to, interactive mode versus not interactive more, how to set psql environment to work comfortably and so on...)
The last part will be about tips and tricks that will make anyone's journey with psql more effective and enjoyable. I'm looking for the "TIL" effect in people's eyes.
EDB 13 - New Enhancements for Security and Usability - APJEDB
Database security is always of paramount importance to all organizations. In this webinar, we will explore the security, usability, and portability updates of the latest version of the EDB database server and tools.
Join us in this webinar to learn:
- The new security features such as SCRAM and the encryption of database passwords and traffic between Failover Manager agents
- Usability updates that automate partitioning, verify backup integrity, and streamline the management of failover and backups
- Portability improvements that simplify running PostgreSQL across on-premise and cloud environments
Dans ce webinar, nous allons parler des différences entre une sauvegarde physique et une sauvegarde logique. Nous allons lister les avantages et inconvénients, les principales considérations et les outils disponibles pour les deux méthodes.
- Perte de données
- Exports logiques
- Standbys
- WALs et Recovery
- Snapshots VM/Disques
- Sauvegardes physique
- Conclusion
Vieni a scoprire Cloud Native PostgreSQL (CNP), l’operatore per Kubernetes, direttamente da coloro che lo hanno ideato e lo sviluppano in EDB.
CNP facilita l’integrazione di database PostgreSQL con le tue applicazioni all’interno di cluster Kubernetes e OpenShift Container Platform di RedHat, grazie alla sua gestione automatica dell’architettura primario/standby che include: self-healing, failover, switchover, rolling update, backup, ecc.
Durante il webinar affronteremo i seguenti punti:
- DevOps e Cloud Native
- Introduzione a Cloud Native PostgreSQL
- Architetture
- Caratteristiche principali
- Esempi di uso e configurazione
- Kubernetes, Storage e Postgres
- Demo
- Conclusioni
New enhancements for security and usability in EDB 13EDB
EDB 13 enhances our flagship database server and tools. This webinar will explore its security, usability, and portability updates. Join us to learn how EDB 13 can help you improve your PostgreSQL productivity and data protection.
Webinar highlights include:
- New security features such as SCRAM and the encryption of database passwords and traffic between Failover Manager agents
- Usability updates that automate partitioning, verify backup integrity and streamline the management of failover and backups
- Portability improvements that simplify running PostgreSQL across on-premise and cloud environments
EDB Cloud Native Postgres includes database container images and a Kubernetes Operator that manage the lifecycle of a database from deployment to operations. This Kubernetes Operator for Postgres is written by EDB entirely from scratch in the Go language and relies exclusively on the Kubernetes API.
Attend this webinar to learn about:
- DevOps & Cloud Native
- Overview of Cloud Native Postgres
- Storage for Postgres workloads in Kubernetes
- Using Cloud Native Postgres
- Demo
This webinar will give an overview of the typical use of EDB Postgres Advanced Server and EDB tools for a smart city project, developed in a city with more than 2.2 million people. The main goal of this project is to achieve a 24/7 uninterrupted service with zero data loss and without any service interruption.
During the session, we will explore the project architecture and we will discuss what specific tools were used, and how these tools help manage DBAs’ daily tasks. We will also discuss what type of data is critical for a smart city project.
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
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.
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.
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
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/
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
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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