Introduction to Apache Kafka and Confluent... and why they matterconfluent
Milano Apache Kafka Meetup by Confluent (First Italian Kafka Meetup) on Wednesday, November 29th 2017.
Il talk introduce Apache Kafka (incluse le APIs Kafka Connect e Kafka Streams), Confluent (la società creata dai creatori di Kafka) e spiega perché Kafka è un'ottima e semplice soluzione per la gestione di stream di dati nel contesto di due delle principali forze trainanti e trend industriali: Internet of Things (IoT) e Microservices.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
HDFS has several strengths: horizontally scale its IO bandwidth and scale its storage to petabytes of storage. Further, it provides very low latency metadata operations and scales to over 60K concurrent clients. Hadoop 3.0 recently added Erasure Coding. One of HDFS’s limitations is scaling a number of files and blocks in the system. We describe a radical change to Hadoop’s storage infrastructure with the upcoming Ozone technology. It allows Hadoop to scale to tens of billions of files and blocks and, in the future, to every larger number of smaller objects. Ozone fundamentally separates the namespace layer and the block layer allowing new namespace layers to be added in the future. Further, the use of RAFT protocol has allowed the storage layer to be self-consistent. We show how this technology helps a Hadoop user and also what it means for evolving HDFS in the future. We will also cover the technical details of Ozone.
Speaker: Sanjay Radia, Chief Architect, Founder, Hortonworks
Graph Computing with JanusGraph. Presented at Cleveland Big Data Mega Meetup on September 11, 2017. https://www.meetup.com/Cleveland-Hadoop/events/241553826/
Dell Technologies è un’esclusiva famiglia di aziende che offre alle organizzazioni l’infrastruttura necessaria per costruire il loro futuro digitale, favorire l’IT Transformation e proteggere le loro risorse più importanti: le informazioni.
In particolare per il settore dell’Education di livello superiore, Dell EMC ha studiato un catalogo di soluzioni in aree quali:
Converged Infrastructure
Storage e Protection dei dati
Servizi di didattica digitale
In questo ciclo di webinar illustreremo le soluzioni Dell EMC più all'avanguardia, attualmente oggetto di studio da parte della Fondazione CRUI per un possibile contratto in convenzione.
ScyllaDB recently launched our Scylla Cloud database as a service, which combines the speed and power of the Scylla NoSQL database with the ease of a fully managed cloud service. Scylla Cloud relieves your team of day-to-day cluster management so you can focus on creating modern, interactive applications that respond to queries in milliseconds.
Join us for an overview of Scylla Cloud, including a live demo of how to launch and connect to a cluster, how to create and query a table, and how to run a few operations, all in minutes.
Apache Kafka vs. Integration Middleware (MQ, ETL, ESB)Kai Wähner
Learn the differences between an event-driven streaming platform and middleware like MQ, ETL and ESBs – including best practices and anti-patterns, but also how these concepts and tools complement each other in an enterprise architecture.
Extract-Transform-Load (ETL) is still a widely-used pattern to move data between different systems via batch processing. Due to its challenges in today’s world where real time is the new standard, an Enterprise Service Bus (ESB) is used in many enterprises as integration backbone between any kind of microservice, legacy application or cloud service to move data via SOAP / REST Web Services or other technologies. Stream Processing is often added as its own component in the enterprise architecture for correlation of different events to implement contextual rules and stateful analytics. Using all these components introduces challenges and complexities in development and operations.
This session discusses how teams in different industries solve these challenges by building a native streaming platform from the ground up instead of using ETL and ESB tools in their architecture. This allows to build and deploy independent, mission-critical streaming real time application and microservices. The architecture leverages distributed processing and fault-tolerance with fast failover, no-downtime rolling deployments and the ability to reprocess events, so you can recalculate output when your code changes. Integration and Stream Processing are still key functionality but can be realized in real time natively instead of using additional ETL, ESB or Stream Processing tools.
ASE Performance and Tuning Parameters Beyond the cfg FileSAP Technology
The ASE configuration file contains a long list of changeable parameters, but many parameter still exists outside of the main configuration file. This session will be a discussion of hidden gems in other places that can make performance better for queries, networking, and system administration.
The document discusses best practices for using Neo4j drivers. It recommends connecting with neo4j+s:// for security and routing context. Drivers should verify connectivity before queries and reuse a single driver instance. Transactions should use explicit functions and parameters to avoid overloading servers. Bookmarks provide causal consistency by allowing queries to read their own writes.
ksqlDB: A Stream-Relational Database Systemconfluent
Speaker: Matthias J. Sax, Software Engineer, Confluent
ksqlDB is a distributed event streaming database system that allows users to express SQL queries over relational tables and event streams. The project was released by Confluent in 2017 and is hosted on Github and developed with an open-source spirit. ksqlDB is built on top of Apache Kafka®, a distributed event streaming platform. In this talk, we discuss ksqlDB’s architecture that is influenced by Apache Kafka and its stream processing library, Kafka Streams. We explain how ksqlDB executes continuous queries while achieving fault tolerance and high vailability. Furthermore, we explore ksqlDB’s streaming SQL dialect and the different types of supported queries.
Matthias J. Sax is a software engineer at Confluent working on ksqlDB. He mainly contributes to Kafka Streams, Apache Kafka's stream processing library, which serves as ksqlDB's execution engine. Furthermore, he helps evolve ksqlDB's "streaming SQL" language. In the past, Matthias also contributed to Apache Flink and Apache Storm and he is an Apache committer and PMC member. Matthias holds a Ph.D. from Humboldt University of Berlin, where he studied distributed data stream processing systems.
https://db.cs.cmu.edu/events/quarantine-db-talk-2020-confluent-ksqldb-a-stream-relational-database-system/
Applying DevOps to Databricks can be a daunting task. In this talk this will be broken down into bite size chunks. Common DevOps subject areas will be covered, including CI/CD (Continuous Integration/Continuous Deployment), IAC (Infrastructure as Code) and Build Agents.
We will explore how to apply DevOps to Databricks (in Azure), primarily using Azure DevOps tooling. As a lot of Spark/Databricks users are Python users, will will focus on the Databricks Rest API (using Python) to perform our tasks.
This document discusses using the Cloud Adoption Framework (CAF) Terraform modules to create Azure landing zones. It begins with an introduction to Azure landing zones and their purpose. It then discusses everything-as-code and using Terraform to deploy environments. The remainder of the document focuses on the benefits of using the CAF Terraform modules, including consistency, maintainability, reusability, and delivering value. It provides an overview of the core principles and fundamental building blocks of the CAF modules. Finally, it demonstrates how to get started with the CAF Terraform landing zones.
This document discusses reliability guarantees in Apache Kafka. It explains that Kafka provides reliability through replication of data across multiple brokers. It describes concepts like in-sync replicas, unclean leader election, and how to configure replication factor and minimum in-sync replicas. The document also covers best practices for producers like setting acks to all, and for consumers like committing offsets manually and handling rebalances. It emphasizes the importance of monitoring for errors, lag, and data reconciliation to ensure reliability.
The document provides an overview of Red Hat OpenShift Container Platform, including:
- OpenShift provides a fully automated Kubernetes container platform for any infrastructure.
- It offers integrated services like monitoring, logging, routing, and a container registry out of the box.
- The architecture runs everything in pods on worker nodes, with masters managing the control plane using Kubernetes APIs and OpenShift services.
- Key concepts include pods, services, routes, projects, configs and secrets that enable application deployment and management.
The document discusses Oracle Managed File Transfer (MFT), which provides a centralized solution for managing large file transfers and integrations. It saves organizations time and money by consolidating disparate partner solutions into a single platform. Oracle MFT integrates with other Oracle products to provide easy installation and deployment. Traditional file transfer systems are inefficient and insecure, while Oracle MFT allows for centralized management, monitoring, security and prevents disruptions to business operations.
A basic introductory slide set on Kubernetes: What does Kubernetes do, what does Kubernetes not do, which terms are used (Containers, Pods, Services, Replica Sets, Deployments, etc...) and how basic interaction with a Kubernetes cluster is done.
NOVA SQL User Group - Azure Synapse Analytics Overview - May 2020Timothy McAliley
Jim Boriotti presents an overview and demo of Azure Synapse Analytics, an integrated data platform for business intelligence, artificial intelligence, and continuous intelligence. Azure Synapse Analytics includes Synapse SQL for querying with T-SQL, Synapse Spark for notebooks in Python, Scala, and .NET, and Synapse Pipelines for data workflows. The demo shows how Azure Synapse Analytics provides a unified environment for all data tasks through the Synapse Studio interface.
This document compares and contrasts the cloud platforms AWS, Azure, and GCP. It provides information on each platform's pillars of cloud services, regions and availability zones, instance types, databases, serverless computing options, networking, analytics and machine learning services, development tools, security features, and pricing models. Speakers then provide more details on their experience with each platform, highlighting key products, differences between the platforms, and positives and negatives of each from their perspective.
This document provides an overview of Apache Kafka. It discusses Kafka's key capabilities including publishing and subscribing to streams of records, storing streams of records durably, and processing streams of records as they occur. It describes Kafka's core components like producers, consumers, brokers, and clustering. It also outlines why Kafka is useful for messaging, storing data, processing streams in real-time, and its high performance capabilities like supporting multiple producers/consumers and disk-based retention.
Databricks is a Software-as-a-Service-like experience (or Spark-as-a-service) that is a tool for curating and processing massive amounts of data and developing, training and deploying models on that data, and managing the whole workflow process throughout the project. It is for those who are comfortable with Apache Spark as it is 100% based on Spark and is extensible with support for Scala, Java, R, and Python alongside Spark SQL, GraphX, Streaming and Machine Learning Library (Mllib). It has built-in integration with many data sources, has a workflow scheduler, allows for real-time workspace collaboration, and has performance improvements over traditional Apache Spark.
The document discusses SPARC SuperCluster, a platform for database and middleware consolidation that provides maximum performance. It consists of SPARC T4 servers, Exadata storage servers, ZFS storage appliances, and other components engineered to work together. Implementing SPARC SuperCluster can significantly reduce costs through server consolidation compared to other solutions. It also offers built-in virtualization, Solaris operating system advantages for cloud computing, and lower TCO through better performance and simplified management.
Apache Kafka vs. Integration Middleware (MQ, ETL, ESB)Kai Wähner
Learn the differences between an event-driven streaming platform and middleware like MQ, ETL and ESBs – including best practices and anti-patterns, but also how these concepts and tools complement each other in an enterprise architecture.
Extract-Transform-Load (ETL) is still a widely-used pattern to move data between different systems via batch processing. Due to its challenges in today’s world where real time is the new standard, an Enterprise Service Bus (ESB) is used in many enterprises as integration backbone between any kind of microservice, legacy application or cloud service to move data via SOAP / REST Web Services or other technologies. Stream Processing is often added as its own component in the enterprise architecture for correlation of different events to implement contextual rules and stateful analytics. Using all these components introduces challenges and complexities in development and operations.
This session discusses how teams in different industries solve these challenges by building a native streaming platform from the ground up instead of using ETL and ESB tools in their architecture. This allows to build and deploy independent, mission-critical streaming real time application and microservices. The architecture leverages distributed processing and fault-tolerance with fast failover, no-downtime rolling deployments and the ability to reprocess events, so you can recalculate output when your code changes. Integration and Stream Processing are still key functionality but can be realized in real time natively instead of using additional ETL, ESB or Stream Processing tools.
ASE Performance and Tuning Parameters Beyond the cfg FileSAP Technology
The ASE configuration file contains a long list of changeable parameters, but many parameter still exists outside of the main configuration file. This session will be a discussion of hidden gems in other places that can make performance better for queries, networking, and system administration.
The document discusses best practices for using Neo4j drivers. It recommends connecting with neo4j+s:// for security and routing context. Drivers should verify connectivity before queries and reuse a single driver instance. Transactions should use explicit functions and parameters to avoid overloading servers. Bookmarks provide causal consistency by allowing queries to read their own writes.
ksqlDB: A Stream-Relational Database Systemconfluent
Speaker: Matthias J. Sax, Software Engineer, Confluent
ksqlDB is a distributed event streaming database system that allows users to express SQL queries over relational tables and event streams. The project was released by Confluent in 2017 and is hosted on Github and developed with an open-source spirit. ksqlDB is built on top of Apache Kafka®, a distributed event streaming platform. In this talk, we discuss ksqlDB’s architecture that is influenced by Apache Kafka and its stream processing library, Kafka Streams. We explain how ksqlDB executes continuous queries while achieving fault tolerance and high vailability. Furthermore, we explore ksqlDB’s streaming SQL dialect and the different types of supported queries.
Matthias J. Sax is a software engineer at Confluent working on ksqlDB. He mainly contributes to Kafka Streams, Apache Kafka's stream processing library, which serves as ksqlDB's execution engine. Furthermore, he helps evolve ksqlDB's "streaming SQL" language. In the past, Matthias also contributed to Apache Flink and Apache Storm and he is an Apache committer and PMC member. Matthias holds a Ph.D. from Humboldt University of Berlin, where he studied distributed data stream processing systems.
https://db.cs.cmu.edu/events/quarantine-db-talk-2020-confluent-ksqldb-a-stream-relational-database-system/
Applying DevOps to Databricks can be a daunting task. In this talk this will be broken down into bite size chunks. Common DevOps subject areas will be covered, including CI/CD (Continuous Integration/Continuous Deployment), IAC (Infrastructure as Code) and Build Agents.
We will explore how to apply DevOps to Databricks (in Azure), primarily using Azure DevOps tooling. As a lot of Spark/Databricks users are Python users, will will focus on the Databricks Rest API (using Python) to perform our tasks.
This document discusses using the Cloud Adoption Framework (CAF) Terraform modules to create Azure landing zones. It begins with an introduction to Azure landing zones and their purpose. It then discusses everything-as-code and using Terraform to deploy environments. The remainder of the document focuses on the benefits of using the CAF Terraform modules, including consistency, maintainability, reusability, and delivering value. It provides an overview of the core principles and fundamental building blocks of the CAF modules. Finally, it demonstrates how to get started with the CAF Terraform landing zones.
This document discusses reliability guarantees in Apache Kafka. It explains that Kafka provides reliability through replication of data across multiple brokers. It describes concepts like in-sync replicas, unclean leader election, and how to configure replication factor and minimum in-sync replicas. The document also covers best practices for producers like setting acks to all, and for consumers like committing offsets manually and handling rebalances. It emphasizes the importance of monitoring for errors, lag, and data reconciliation to ensure reliability.
The document provides an overview of Red Hat OpenShift Container Platform, including:
- OpenShift provides a fully automated Kubernetes container platform for any infrastructure.
- It offers integrated services like monitoring, logging, routing, and a container registry out of the box.
- The architecture runs everything in pods on worker nodes, with masters managing the control plane using Kubernetes APIs and OpenShift services.
- Key concepts include pods, services, routes, projects, configs and secrets that enable application deployment and management.
The document discusses Oracle Managed File Transfer (MFT), which provides a centralized solution for managing large file transfers and integrations. It saves organizations time and money by consolidating disparate partner solutions into a single platform. Oracle MFT integrates with other Oracle products to provide easy installation and deployment. Traditional file transfer systems are inefficient and insecure, while Oracle MFT allows for centralized management, monitoring, security and prevents disruptions to business operations.
A basic introductory slide set on Kubernetes: What does Kubernetes do, what does Kubernetes not do, which terms are used (Containers, Pods, Services, Replica Sets, Deployments, etc...) and how basic interaction with a Kubernetes cluster is done.
NOVA SQL User Group - Azure Synapse Analytics Overview - May 2020Timothy McAliley
Jim Boriotti presents an overview and demo of Azure Synapse Analytics, an integrated data platform for business intelligence, artificial intelligence, and continuous intelligence. Azure Synapse Analytics includes Synapse SQL for querying with T-SQL, Synapse Spark for notebooks in Python, Scala, and .NET, and Synapse Pipelines for data workflows. The demo shows how Azure Synapse Analytics provides a unified environment for all data tasks through the Synapse Studio interface.
This document compares and contrasts the cloud platforms AWS, Azure, and GCP. It provides information on each platform's pillars of cloud services, regions and availability zones, instance types, databases, serverless computing options, networking, analytics and machine learning services, development tools, security features, and pricing models. Speakers then provide more details on their experience with each platform, highlighting key products, differences between the platforms, and positives and negatives of each from their perspective.
This document provides an overview of Apache Kafka. It discusses Kafka's key capabilities including publishing and subscribing to streams of records, storing streams of records durably, and processing streams of records as they occur. It describes Kafka's core components like producers, consumers, brokers, and clustering. It also outlines why Kafka is useful for messaging, storing data, processing streams in real-time, and its high performance capabilities like supporting multiple producers/consumers and disk-based retention.
Databricks is a Software-as-a-Service-like experience (or Spark-as-a-service) that is a tool for curating and processing massive amounts of data and developing, training and deploying models on that data, and managing the whole workflow process throughout the project. It is for those who are comfortable with Apache Spark as it is 100% based on Spark and is extensible with support for Scala, Java, R, and Python alongside Spark SQL, GraphX, Streaming and Machine Learning Library (Mllib). It has built-in integration with many data sources, has a workflow scheduler, allows for real-time workspace collaboration, and has performance improvements over traditional Apache Spark.
The document discusses SPARC SuperCluster, a platform for database and middleware consolidation that provides maximum performance. It consists of SPARC T4 servers, Exadata storage servers, ZFS storage appliances, and other components engineered to work together. Implementing SPARC SuperCluster can significantly reduce costs through server consolidation compared to other solutions. It also offers built-in virtualization, Solaris operating system advantages for cloud computing, and lower TCO through better performance and simplified management.
Oracle super cluster for oracle e business suiteOTN Systems Hub
The document discusses Oracle SuperCluster, an engineered system optimized for Oracle E-Business Suite and Oracle Database. It provides examples of customers who implemented Oracle E-Business Suite on SuperCluster and saw significant performance improvements such as 5x faster transaction times, 2x faster patching, and a database migration completed in 12 weeks. The SuperCluster is described as Oracle's most powerful engineered system, with servers, storage, networking and software optimized to run Oracle software and applications extremely efficiently.
Presentation oracle super cluster t5-8 technical deep divesolarisyougood
This document provides an overview and agenda for a presentation on the Oracle SuperCluster T5-8. The document outlines key specifications of the Oracle SuperCluster T5-8 including its SPARC T5 compute nodes, Exadata storage servers, ZFS storage appliance, and InfiniBand networking. It also discusses configurations for the SuperCluster including database and application domains on the SPARC T5 nodes. Use cases and competitive advantages are highlighted such as performance, efficiency through data compression, and reliability.
The document discusses Oracle's new SPARC M7 server platform and its key features:
- The SPARC M7 processor features 32 cores running at 4.13GHz, software-based security and acceleration functions, and improved memory bandwidth and I/O performance over previous SPARC processors.
- New SPARC M7-based servers support the latest processor and memory technologies for higher performance and availability.
- The SPARC M7's "software in silicon" architecture provides hardware acceleration for encryption, database queries and decompression to improve security and analytics performance.
The document discusses Oracle VM virtualization software. It provides an overview of Oracle's virtualization strategy and portfolio, including Oracle VM VirtualBox for development, Oracle VM Server for production environments, and Oracle VM templates to accelerate application deployment. It highlights features such as centralized management, high performance, integration with Oracle technologies like Enterprise Manager, and lower TCO compared to VMware.
The document summarizes Oracle's SuperCluster engineered system. It provides consolidated application and database deployment with in-memory performance. Key features include Exadata intelligent storage, Oracle M6 and T5 servers, a high-speed InfiniBand network, and Oracle VM virtualization. The SuperCluster enables database as a service with automated provisioning and security for multi-tenant deployment across industries.
Oracle Solaris Simple, Flexible, Fast: Virtualization in 11.3OTN Systems Hub
Oracle Solaris
Simple, Flexible, Fast:
Virtualization in 11.3
Duncan Hardie – Principal Product Manager
Edward Pilatowicz – Senior Principal Software Engineer
Oracle Solaris
June 14, 2016
This document provides an overview of Oracle Solaris. It discusses security features like Silicon Secured Memory that protects against memory attacks. It describes how Oracle Solaris leverages across Oracle products and accelerates analytics and encryption workloads. Oracle Solaris also provides simple, secure deployment of applications in private or public clouds.
This email from [email protected] contains a link to a blog post on msdn.com about security notes for Microsoft Azure now being available as a PDF download. The blog post discusses a PDF with security best practices and configuration recommendations for Azure now being published to help customers securely deploy applications on the Azure platform.
Exadata and Database Machine Overview
The document provides an overview of Oracle's Exadata and Database Machine products. It discusses that Exadata delivers revolutionary performance that is 10-100x faster than traditional data warehouses. It then outlines the agenda and describes the Exadata architecture, features and performance capabilities. The Exadata storage servers work together in a grid configuration to deliver extreme performance for data warehousing, OLTP and consolidation workloads.
Oracle Solaris Application-Centric Lifecycle and DevOpsOTN Systems Hub
This document discusses application-centric lifecycles and DevOps. It describes how traditional waterfall development models with infrastructure silos have given way to agile development models and self-service infrastructure with DevOps. It then outlines Oracle's approach to providing a complete deployment pipeline for applications with tools for packaging, testing, deploying and updating applications and infrastructure in an automated and secure manner.
This document discusses security features of the SPARC M7 CPU. It introduces Silicon Secured Memory, which provides hardware-based memory protection to stop malicious programs from accessing other application memory without performance impact. This results in improved security, reliability, and availability of applications. Benchmark results are also provided showing the SPARC M7's performance advantages over other chips.
Webinář "Konsolidace Oracle DB na systémech s procesory M7, včetně migrace z konkurenčních serverových platforem"
Prezentuje Josef Šlahůnek, Oracle
9.3.2016
A2 a peep into the fastest servers for database middleware and enterprise j...Dr. Wilfred Lin (Ph.D.)
The document provides an overview of Oracle's product direction, including its SPARC processor roadmap, Solaris operating system enhancements, and engineered systems. It outlines Oracle's focus on increasing application performance by 2x every two years through advances in SPARC processors and the embedding of Oracle-specific enhancements. Key systems like the M6-32 big memory machine and Exalytics are highlighted as providing extreme performance for in-memory computing and business analytics.
The document describes Oracle's MiniCluster S7-2 product. It is positioned as extending Oracle's SuperCluster family to smaller, mid-range workloads. Key points include that it provides 100% compatibility with SuperCluster applications and databases, but at a smaller scale and lower entry price point. It is designed to be easier to deploy, operate and manage than a full SuperCluster, with no need for specialized services. The MiniCluster features a virtual assistant for automated administration and security management to simplify operations.
The document introduces Oracle's Enterprise Cloud Infrastructure solution using SPARC T5 servers. It discusses Oracle's cloud strategy, challenges in building private clouds, and how Oracle addresses these challenges through optimized solutions like the Oracle Virtual Compute Appliance. It provides an overview of the Oracle Optimized Solution for Enterprise Cloud Infrastructure, including SPARC T5 servers, Oracle Solaris, Oracle VM Server for SPARC, and Sun ZFS Storage Appliance. Example configurations and best practices are also presented.
New Generation of SPARC Processors Boosting Oracle S/W Angelo RajaduraiOrgad Kimchi
This document discusses Oracle's SPARC T5 processor and SPARC T5 server systems. It provides an overview of the SPARC T5 processor's specifications and performance advantages. It then describes the new SPARC T5-8 and T5-4 server models, which offer up to 128 processor cores, 4TB of memory, and improved I/O and storage capabilities. Benchmark results are presented showing that the SPARC T5-8 significantly outperforms IBM Power systems on price/performance for database, middleware, and other workloads. A case study is also described where a financial services company found the SPARC T5-8 offered better streaming performance and lower costs than IBM Power solutions
The Oracle SPARC M7-8 server provides unique security and performance capabilities through the use of Software in Silicon technology. This technology allows for end-to-end encryption of data with no performance impact, detection and prevention of memory attacks, and extreme acceleration of Oracle Database In-Memory queries. The SPARC M7-8 server is ideal for enterprise workloads like databases, applications, Java, and middleware in cloud environments due to its high performance, security features, and lower costs compared to alternatives.
Oracle hardware includes a full-suite of scalable engineered systems, servers, and storage that enable enterprises to optimize application and database performance, protect crucial data, and lower costs.
With Oracle, customers have freedom from the complexity of having multiple databases, analytics tools, and machine learning environments. Oracle's data management platform makes it easier and faster for application developers to create microservices-based applications with multiple data types.
Building Efficient Edge Nodes for Content Delivery NetworksRebekah Rodriguez
Supermicro, Intel®, and Varnish are delivering an optimized CDN solution built with the Intel Xeon-D processor in a Supermicro Superserver running Varnish Enterprise. This solution delivers strong performance in a compact form factor with low idle power and excellent performance per watt.
Join Supermicro, Intel, and Varnish experts as they discuss their collaboration and how their respective technologies work together to improve the performance and lower the TCO of an edge caching server.
This document provides an overview and strategy for Oracle systems. It outlines challenges customers face with increasing costs, resource constraints, time to value, and outdated infrastructure. It then summarizes Oracle's engineered systems approach which provides extreme performance, low risk deployment, and breakthrough efficiency through fully integrated hardware and software solutions. The document reviews several Oracle engineered systems like Exadata, Exalogic, Exalytics, and Oracle servers that are designed to work together.
OpenWorld 2013 was a large conference with 60,000 attendees from 145 countries. Oracle announced several new products including an in-memory option for the Oracle Database that provides 100x faster queries and 2x faster transactions processing without requiring any application changes. They also announced a new Backup, Logging, Recovery Appliance designed specifically for databases. For systems, Oracle announced the M6-32 Big Memory Machine with up to 32TB of memory, updated Exalytics appliances, and new Exadata and ZS storage systems. For cloud services, Oracle announced expanded infrastructure, platform and application services available through its public cloud.
The document discusses Oracle's engineered systems and appliances portfolio. It provides sales highlights on Oracle Engineered Systems, noting over 5,000 systems shipped to date with over $1 billion in business. It then details a case study on migrating a customer's databases to Oracle solutions like Exadata, which delivered a 28% reduction in total cost of ownership over 5 years. Finally, it outlines new innovations in Oracle's products, including the Exadata X4, Exalogic X4-2, Oracle SuperCluster M6-32 and T5-8, Oracle Database Appliance, and Oracle Virtual Compute Appliance.
Oracle Key Vault Data Subsetting and MaskingDLT Solutions
The document provides an overview of Oracle Key Vault and Data Subsetting and Masking Pack. It discusses how Oracle Key Vault can be used to centrally manage encryption keys and securely share them across databases, middleware, and systems. It also summarizes the key capabilities of Oracle Data Subsetting and Masking Pack, which can be used to discover, mask, and subset sensitive data to limit its proliferation while sharing non-sensitive data with others. The document highlights use cases, challenges, methodology, transformation types, and deployment options for data masking and subsetting.
Secure Multi-tenancy on Private Cloud Environment (Oracle SuperCluster)Ramesh Nagappan
The document discusses implementing comprehensive security in a multitenant cloud environment using Oracle SuperCluster. It covers Oracle SuperCluster cybersecurity building blocks like secure isolation, access control, data protection and monitoring. It then discusses implementing secure service architectures on Oracle SuperCluster for single and multiple service workloads. Finally, it discusses approaches for securely consolidating multiple tenants on Oracle SuperCluster through physical and logical isolation techniques.
Fujitsu m10 server features and capabilitiessolarisyougood
This document provides an overview of the Fujitsu M10 server product line. It describes the hardware features and capabilities of the Fujitsu M10-1, M10-4, and M10-4S servers including their processors, memory, I/O, storage, and virtualization support. It also discusses the reliability, availability, and serviceability features, and performance advantages for running Oracle databases and SAP workloads on the Fujitsu M10 servers.
The document discusses new features in MySQL 5.7 including enhanced performance and scalability, next generation application support, and availability features. Key points include the MySQL 5.7 release candidate being available with 2x faster performance than 5.6, new JSON support, improved GIS capabilities using Boost.Geometry, multi-threaded replication for faster slaves, and new group replication for multi-master clusters.
- Oracle Database Cloud Service provides Oracle Database software in a cloud environment, including features like Real Application Clusters (RAC) and Data Guard.
- It offers different service levels from a free developer tier to a managed Exadata service. The Exadata service provides extreme database performance on cloud infrastructure.
- New offerings include the Oracle Database Exadata Cloud Service, which provides the full Exadata platform as a cloud service for large, mission-critical workloads.
This document discusses Oracle's SPARC systems and their ability to modernize legacy Unix applications and provide a path to the cloud. It describes how SPARC systems offer a modern, cloud-ready infrastructure that can leverage existing investments while improving security, capacity, and flexibility. It provides examples of SPARC solutions that delivered benefits like reduced costs, increased throughput, and scalability for customers in various industries.
The document discusses Oracle's ZS3 series enterprise storage systems. It provides an overview of Oracle's approach to driving storage system evolution from hardware-defined to software-defined. It then summarizes the key features and benefits of the ZS3 series, including extreme performance, integrated analytics, and optimization for Oracle software.
Technical deep dive on Java Micro Edition (ME) 8 (apologies for the partially messed up colors and slides - SlideShare is doing that during the conversion process)
➤ ►🌍📺📱👉 Click Here to Download Link 100% Working Link
https://click4pc.com/after-verification-click-go-to-download-page/
Wondershare Filmora is an very impressive video editing software. It allows you to edit and convert videos and share them on a variety of different hosting ...
A spectrophotometer is an essential analytical instrument widely used in various scientific disciplines, including chemistry, biology, physics, environmental science, clinical diagnostics, and materials science, for the quantitative analysis of substances based on their interaction with light. At its core, a spectrophotometer measures the amount of light that a chemical substance absorbs by determining the intensity of light as a beam of light passes through the sample solution. The fundamental principle behind the spectrophotometer is the Beer-Lambert law, which relates the absorption of light to the properties of the material through which the light is traveling. According to this law, the absorbance is directly proportional to the concentration of the absorbing species in the material and the path length that the light travels through the sample. By exploiting this principle, a spectrophotometer provides a powerful, non-destructive means of identifying and quantifying substances in both qualitative and quantitative studies.
The construction of a spectrophotometer involves several key components, each playing a vital role in the overall functioning of the instrument. The first critical component is the light source. The choice of the light source depends on the range of wavelengths needed for analysis. For ultraviolet (UV) light, typically a deuterium lamp is used, while tungsten filament lamps are commonly used for the visible light range. In some advanced spectrophotometers, xenon lamps or other broad-spectrum sources may be used to cover a wider range of wavelengths. The light emitted from the source is then directed toward a monochromator, which isolates the desired wavelength of light from the full spectrum emitted by the lamp. Monochromators generally consist of a prism or a diffraction grating, which disperses the light into its component wavelengths. By rotating the monochromator, the instrument can select and pass a narrow band of wavelengths to the sample, ensuring that only light of the desired wavelength reaches the sample compartment.
The sample is typically held in a cuvette, a small transparent container made of quartz, glass, or plastic, depending on the wavelength range of interest. Quartz cuvettes are used for UV measurements since they do not absorb UV light, while plastic or glass cuvettes are sufficient for visible light applications. The path length of the cuvette, usually 1 cm, is a critical parameter because it influences the absorbance readings according to the Beer-Lambert law. Once the monochromatic light passes through the sample, it emerges with reduced intensity due to absorption by the sample. The transmitted light is then collected by a photodetector, which converts the light signal into an electrical signal. This electrical signal is proportional to the intensity of the transmitted light and is processed by the instrument’s electronics to calculate absorbance or transmittance values. These values are then give
A common structure is to start with an introduction that grabs their attention, states your purpose, and outlines your agenda. Then, you move on to the body of your presentation, where you explain your robotics project, its objectives, methods, results, and implications.14 Mar 2024
The complete discuss in this topic
-- Computer Hardware --
Computer hardware refers to the physical components of a computer system that you can see and touch. These components work together to perform all computing tasks. ☝️☝️
Fonepaw Data Recovery Crack 2025 with key free Downloadmampisoren09
FonePaw Data Recovery is a software tool designed to help users recover lost, deleted, or formatted files from various storage devices. It works on Windows and macOS and supports recovery from hard drives, USB flash drives, memory cards, SD cards, and other removable storage.
⬇️⬇️COPY & PASTE IN BROWSER TO DOWNLOAD⬇️⬇️😁https://crackprokeygen.com/download-setup-available-free/
MiniTool Partition Wizard Professional Edition 10.2.1 Crackyousfhashmi786
➤ ►🌍📺📱👉 Click Here to Download Link 100% Working
Link https://click4pc.com/after-verification-click-go-to-download-page/
MiniTool Partition Wizard Pro Ultimate for Windows PC, is the best professional Partition Manager for Advanced Users! With this, you can Manage .
AnyDesk 5.2.1 Crack License Key Full Version 2019 {Latest}yousfhashmi786
➤ ►🌍📺📱👉 Click Here to Download Link 100% Working Link
https://click4pc.com/after-verification-click-go-to-download-page/
AnyDesk is a popular remote desktop software that allows you to access your computer from anywhere in the world.
Microsoft Office 365 Crack Latest Version 2025?yousfhashmi786
COPY PASTE LInK >>
https://click4pc.com/after-verification-click-go-to-download-page/
— Microsoft 365 (Office) is a powerful application designed to centralize all of your commonly used Office and Microsoft 365 applications in one ...