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FreeBSD basics – 4 – Jails

Jails build on top of chroot (which is also known on Linux) but do not only limit access to the file system but also other resources such as network or processes.
The FreeBSD handbook provides a good overview of the advantages and disadvantages of the different types of Jails. In short, the types are: Thick – Highest level of isolation, Thin – Reduced isolation, Service – No file system isolation.
Before we can create Jails, we need to enable them with “sysrc”.
It doesn’t matter where on disk you put the Jails, but it is recommend to create separate file systems for them.
The template for the new Jails is actually a ZFS snapshot.
All that needs to be done to create a new Jail is to clone this snapshot.
While it is recommended to manage a Jail from the host system, you can also jump into the Jail.
Pretty easy to setup and really lightweight.
In the next post we’ll build on this to create a simple PostgreSQL as a service platform.
FreeBSD has no native support for containers, but instead offers Jails, which provide isolation from the host system by limiting access to resources such as network, processes, and file system.

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Siliconangle

135

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AWS introduces Amazon Aurora DSQL and DynamoDB enhancements for multi-region workloads

Amazon Web Services (AWS) announced new capabilities for Amazon Aurora and Amazon DynamoDB to support multi-region workloads.
The launch of Amazon Aurora DSQL offers a serverless, distributed SQL database with high availability, strong consistency, and PostgreSQL compatibility.
Aurora DSQL provides 99.999% multi-region availability, eliminates tradeoffs, and offers fast read and write performance.
Amazon DynamoDB now supports strong consistency for global tables, ensuring low-latency performance and scalability across multiple regions.

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Siliconangle

126

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AWS expands Amazon S3 with features to support Apache Iceberg and metadata management

Amazon announced at its re:Invent conference updates to its Amazon Simple Storage Service (S3) to make it the first cloud object store with fully managed support for Apache Iceberg.
Amazon S3 Tables deliver up to 3 times faster query performance with 10 times higher transactions per second and automated maintenance, ensuring S3 users manage and store tabular data on any scale.
S3 tables provide a purpose-built solution for managing Apache Iceberg tables in data lakes, providing faster query performance and higher TPS compared to general-purpose S3 buckets.
Amazon S3 Metadata is another new service that streamlines data discovery by automatically capturing queryable object metadata and custom metadata using object tags.
S3 Metadata captures system-defined details such as object size and source, integrating metadata into S3 Tables, ensuring an up-to-date view of data, accelerating analytics across data lakes.
Customers using S3 Tables can create dedicated table buckets that streamline the storage and querying of tabular data in fully managed Iceberg tables.
The service also offers advanced Iceberg features like row-level transactions, queryable snapshots via time travel and schema evolution.
S3 Metadata also enables customers to enrich their data by adding custom metadata with object tags and querying through SQL queries, which effective storage optimization and improved data preparation for analytics.
The release of Amazon S3 Tables seeks to address the issue of managing large-scale tabular data, which customers typically organize using Apache Parquet, a file format optimized for data queries and organizing billions of files.
Andy Warfield, VP of storage and distinguished engineer at AWS, says the system removes the overhead of data stores on top of objects to enable customers to shift their focus back to working with their data.

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Mysql

Galera Cluster for MySQL 8.0.40-26.21, and MySQL 8.4.3-26.21 released

Codership has released Galera Cluster for MySQL 8.0.40-26.21 and MySQL 8.4.3-26.21
The release includes Galera replication library 4.21 and introduces a synchronous option for MySQL High Availability solutions
Notable changes in the Galera replication library 4.21 include the removal of dependencies on openssl/engine.h and fixes for writeset serialization during Incremental State Transfers (ISTs)
Other improvements include fixes for race conditions during node syncing, changes in foreign key checks during IST, and enhancements in Galera MDL-conflict handling

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Insider

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Larry Ellison is investing up to $165 million to turn University of Oxford science research into products

Larry Ellison, the cofounder of Oracle, plans to invest up to $165 million into research at the University of Oxford.
The investment aims to transform research into products, focusing on key global challenges.
The Ellison Institute of Technology is opening a campus in Oxford in 2027.
The joint venture aims to reimagine how science and technology translate into solutions for humanity's problems.

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Insider

955

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Oracle stock is set for its best year since the dot-com boom after a 75% surge

Oracle shares have surged 75% this year, marking its best year since 1999 during the dot-com boom.
Strong demand for cloud and AI infrastructure has contributed to the stock's growth.
Larry Ellison's personal fortune has significantly increased due to the surge in Oracle's stock.
Oracle's market value has risen to over $500 billion and its net income jumped by 23% in the past year.

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Siliconangle

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Three insights you might have missed from Microsoft Ignite

Multicloud AI strategies are revolutionizing how organizations approach secure, scalable and integrated artificial intelligence solutions across complex technology landscapes.
Simplifying connectivity has become a critical focus due to the growing need for consistent access to data and applications in multicloud environments.
Multicloud AI strategies drive trust and resilience in hybrid cloud landscapes.
Strategic partnerships fuel hybrid cloud innovation to support AI workloads across diverse industries.
Innovative technologies and multicloud strategies are redefining scalability and efficiency for enterprise AI.
Dell Technologies Inc. has emphasized zero-trust security measures with its APEX Protection Services for Microsoft Azure, integrating data immutability, encryption and multi-factor authentication to safeguard customer data.
Aviatrix Systems Inc. contributes to multicloud AI strategies by enhancing security measures tailored for AI workflows, through integrations with Microsoft Security Copilot and Secure Service Edge.
Emerging technologies, such as quantum computing, artificial intelligence and next-generation networking, are transforming enterprise operations.
Partnerships between cloud providers and technology leaders are unlocking new possibilities for AI-driven hybrid cloud infrastructures.
Oracle Cloud Infrastructure addresses integration capabilities, 24/7 availability and comprehensive data governance, simplifying AI deployment and supporting multicloud AI strategies.

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Mysql

206

MySQL GTID tags and binlog events

MySQL 8.4 and newer have extended the Global Transaction ID (GTID) functionality with a new “tag” option.
A GTID is a unique ID that is assigned to a transaction. This is used if gtid_mode is set to ON.
The format of GTIDs is documented here. Before GTID was used replication worked based on a file and offset.
If you run SET gtid_next='AUTOMATIC:abc then the next transaction will have a GTID that includes the tag.
Why having a heartbeat tag matters is that losing the data of a heartbeat transaction is fine, while losing a transaction from an application isn’t.
Binlogs (short for binary logs) are logs of changes made to the database.
Adding tags impacts a few of the types of events that are sent in the binlog stream.
There is a new event called GTID_TAGGED_LOG_EVENT that has both new and old interal library
Replication between 8.4 (or 8.3?) and earlier versions of MySQL breaks when using tagged GTIDs.
Related bugs have been filed for incomplete internal documentation and behavior mismatch.

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Global Fintech Series

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New Updates in Oracle Life Sciences Empirica Streamline Safety Signal Management Compliance in the Cloud

Oracle has announced new updates to Oracle Life Sciences Empirica Signal and Topics.
The latest release extends out-of-the-box database choices for global safety monitoring and enhances the signal review process.
Multi-source signaling across proprietary and public safety databases enables sophisticated data mining and GVP-compliant signal tracking.
The updates aim to streamline safety signal management compliance in the cloud.

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Dev

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Day 3 of SQL Series || Basic Commands

In this blog, we discuss the basic commands of SQL, specifically the DML (Data Manipulation Language) commands.
The commonly used DML commands are INSERT, UPDATE, and DELETE.
The INSERT command is used to insert data into a table.
The UPDATE command is used to update existing data in a table.

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Dbi-Services

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Save Report to Power BI Report Server: Resolving the ‘Unexpected Error Encountered’

To simulate a production-like environment, a demo was prepared for Power BI Report Server where report deployment phase revealed an unexpected authentication error that required a deeper understanding of Windows authentication mechanisms and network name resolution.
Power BI Desktop for Power BI Report Server (September 2024 version) was used for development, AdventureWorksDW2022 database backup was used as the data source and the report was developed using the AdventureWorksDW2022 sample database.
Report deployment started which appeared straightforward on the surface, but an error of “Unexpected error encountered” occurred due to an authentication issue.
Root cause analysis revealed two critical issues as name resolution failure on the domain controller and Active Directory Replication Latency issues.
Since WIN-LAB3 is not part of any domain, system failed to resolve WIN-LAB3’s name and authenticate using valid credentials which ultimately caused the error.
Solution suggested was to ensure proper DNS resolution between development and server machines and to configure appropriate credential mapping in Windows Credential Manager.
Steps such as retrieving IP Address of WIN-LAB3, updating the Laptop’s Hosts File and Configuring Network Credentials were implemented to resolve the issue.
This implementation demonstrates how to bridge the authentication gap between domain-joined and standalone systems in a Power BI Report Server deployment.
To ensure seamless communication between two separate machines, the development machine (where Power BI Desktop is installed) must be able to resolve the Power BI Report Server name.
A Power BI Report Server valid account defined in the Development machine via the Credential Manager allows seamless communication between the two machines.

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Analyticsindiamag

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Oracle Quietly Becomes Every Cloud’s Best Friend

Oracle has entered the multi-cloud era with partnerships with Microsoft Azure, Google Cloud, and AWS.
Oracle's strategy is based on its control over data and being more open than its counterparts.
Major companies like Vodafone and Voya Financial are using Oracle's multi-cloud services.
Oracle's cloud services revenue grew in Q1 2025, but it still lags behind competitors AWS, Microsoft Azure, and Google Cloud.

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Mclaughlinsoftware

342

Using Python’s getopt

The getopt library in Python is used to parse command line arguments passed to Python in the script invocation.
Python’s argparse allows a program to accept arguments/options in any order.
The getopt function is the preferred option because it is more intuitive than the getopt2 function.
You can use the getopt module as follows: python run.py -s Hello -n Goodbye.
The getopt function parses command line arguments with output messages on error or invalid input.
Python’s getopt library is the cleanest, easiest way to implement switch and parameter handling.
The author suggests using Python’s getopt library as the approach adopted by the general Python community.
Using getopt in Python would be simpler and cleaner despite the additional imports.
In comparison, using Python’s argparse allows a program to accept arguments/options in any order.
You simply enumerate through the list of command line arguments with a simple "for i in range(argc)" loop.

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Dev

347

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Part 8: SQL Injection Series - Advanced Prevention Techniques and Real-World Applications

In the 8th part of the SQL Injection series, advanced prevention techniques and real-world applications are discussed.
Advanced prevention techniques include input encoding, whitelisting and input validation, privilege minimization, web application firewalls, and advanced database security.
Real-world applications of secure coding practices include securing login pages, e-commerce platforms, and protecting REST APIs.
Emerging trends in SQL Injection defense include AI-based threat detection, secure development frameworks, and zero trust architectures.

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Dbi-Services

184

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Offloading PostgreSQL Backups to Azure Blob Storage Using PGBackRest, Managed Identity, and SAS Tokens

This article discusses how to offload PostgreSQL backups to Azure cloud's blob storage securely to reduce infrastructure costs and provide cloud-based disaster recovery capabilities.
The setup involves creating an Azure-managed identity and a SAS (shared access signature) token, which gives a time-limited, secure connection to the offsite backup location.
Next, the article covers setting up the PostgreSQL application and configuring local and remote backup repositories to accomplish the backup plan.
PGBackRest script is adapted to renew the SAS token periodically and update the pgBackRest configuration file in the PostgreSQL server.
The SAS token, which is used to access the blob storage, and the managed identity can be audited and monitored in Azure's cloud app hosting environment for added security and compliance.
The article provides examples of how to automate the renewals of the SAS token and how to test the solution to ensure it works as expected.
The SNMP protocol enables a manager to monitor the operations of remote software on its network for greater efficiency in network management and reduced downtime. SNMP has its own challenges and benefits. This article provides an overview of SNMP's functionality, how it works, its benefits, and the challenges it presents.
This article explores how to use AWS EC2 instances for GPU-accelerated computing, which offers several benefits like high-performance computing, better task parallelization, and lower infrastructure costs.
The article discusses the process of creating an EC2 instance, launching the instance, and installing the necessary tools and libraries on it for GPU-accelerated computing.
Lastly, the article provides multiple examples of how to get started with specific tools, libraries, and code examples that can help in running the model more efficiently on EC2 instances.
In conclusion, this article provides a step-by-step guide to implementing GPU-accelerated computing on Amazon's AWS platform and helps readers to get started with specific tools, libraries, and code examples.

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