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Intel’s new Core Ultra 9 285K may struggle against its predecessor

Intel's latest flagship, the Core Ultra 9 285K, faces stiff competition not just from AMD, but also Intel's last-gen Raptor Lake refresh core i9-14900K
Both cores were launched at the same starting price of $590 with a difference of one-year release date
The Core Ultra 9 285K stacks well on the efficiency side than the big jump in performance gains it promised
Intel Arrow Lake-S specializes in efficiency with a lower power draw, offering the same performance as the Core i9-14900K, but this remains untested
The Core Ultra 9 285K has fewer cores and lacks Hyper-Threading, but it has its own neural processing unit
The Core Ultra 9 285K has a higher base clock frequency than its predecessor, but has a lower turbo frequency
Intel moved from LGA1700 to LGA1851 socket with the Arrow Lake processors, resulting in memory support that abandons DDR4 RAM but supports only up to 192GB of DDR5-6400
Intel pins its efficiency advantage with the Core Ultra 9 285K on single-core productivity-based tests
Content creation yields promising results for Intel's Arrow Lake-S flagship against Ryzen 9 7950X3D in some tests, but uncertain against 9950X and i9-14900K
Intel Arrow Lake-S flagship CPU may struggle to convince buyers, as cost-efficient Core i9-14900K is now $150 cheaper

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Dev

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Executive and Employee Leadership Framework Applied in my Cloud Team

During a leadership training exercise, the concept of the Executive and Employee leadership framework was introduced.
Leaders were organized into groups and took turns acting as executives or employees.
As the executive, they had to listen to scripted concerns and offer solutions within a 5-minute timeframe.
This exercise emphasized the challenges faced by executives and the importance of considering different viewpoints.

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Dbi-Services

384

Mastering Custom Integration Runtimes in Azure Data Factory: An Introduction to Our Upcoming Series

This post is an introduction to a six-part series focused on the Integration Runtime (IR) within Azure Data Factory (ADF).
Azure Data Factory (ADF) is a cloud-based data integration service that enables the creation and scheduling of data-driven workflows.
Integration Runtime (IR) is the compute infrastructure used by ADF to provide data integration capabilities across various network environments.
The series will cover topics such as security prerequisites, accessing on-premises file systems and SQL Servers, implementing shared IR, setting up P2S VPN, and using SSIS IR in ADF.

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Dev

138

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AWS Network Load Balancer, cross-zone enabled now supports zonal shift and zonal auto-shift

AWS Network Load Balancer now supports zonal shift and zonal auto-shift features.
Zonal shift allows customers to quickly shift traffic away from an impaired Availability Zone.
Zonal auto-shift automatically shifts traffic away from an at-risk Availability Zone.
Customers can configure zonal shift or enable zonal auto-shift through the NLB console or API.

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Digitaltrends

120

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I’m worried Intel is making a mistake with Arrow Lake

Intel's Arrow Lake CPUs is another major shift where it kills long-standing Hyper-Threading feature and debuts Core Ultra branding on desktop.
While the company has shown that the architecture is very efficient for laptop market, it's a completely different market and may fall flat on face for desktop market.
Intel's main focus isn't to deliver improvement in gaming performance, however, lower power draw and lower temperatures.
Gaming performance leads most CPU reviews and still represents an important use case for enthusiast/desktop CPUs. Even if Intel is able to maintain gaming performance, it doesn't encourage spending $400 to $600 on a new CPU and motherboard.
Intel faces a big problem with AMD's 3D V-Cache. Intel's flagship Core Ultra 9 285K may underperform Ryzen 7 7800X3D by about 5%.
Efficiency is important but not more important than performance. The Ryzen 7 7800X3D wasn't a success because it was efficient. It was successful because it was super fast.
If the upcoming Ryzen 7 9800X3D is anything like Ryzen 7 7800X3D, Intel has a tough time to win back gamers with Arrow Lake CPUs.
Though Intel wants to make more-efficient CPUs, it needs to deliver an efficient part while still lifting up gaming performance.
The first batch of Arrow Lake chips are unlocked for overclocking which might make all the difference for performance, given that you're an enthusiast.
While efficient CPUs sound great, the prediction is that Arrow Lake CPUs will not hit as Intel wants it to.

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Dev

161

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94% of Workloads Will Be in Cloud by 2021: Expert Insights to Avoid Costly Mistakes

A whopping 94% of workloads and compute instances will be processed in cloud data centers by 2021, according to Cisco's statistical projections.
Before making the move to the cloud, it's essential to devise a detailed strategy that fully considers the cloud environment, security, and computing services.
Each business has unique requirements, so it's crucial to assess different cloud computing models in detail and determine which one best suits your business needs.
Streamlining your business operations and processes doesn't necessitate any hardware installation, which is why many companies opt to undertake the procedure in-house.
Introducing new technology inevitably brings inherent risks, and it's your duty to mitigate these factors and ensure adherence to industry regulations.
Migrating your business operations to the cloud environment is a significant step; however, you need to pay attention to every minute detail.
Whether you're moving your entire business operations to the cloud or only a part of it, security should always be the top priority.
It's a common mistake for companies to attempt to migrate their entire application portfolio to the cloud simultaneously.
Establishing a robust governance infrastructure is often overlooked by many organizations, yet its absence can have far-reaching consequences.
By adhering to the guidelines outlined here, companies can mitigate disruption, ensure regulatory adherence, and optimize costs.

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Dev

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Avoid Costly Loops in AWS Step Functions

AWS StepFunctions is a powerful orchestration tool, but it can lead to costly loops.
Endless loops in StepFunctions can generate costs, although they are eventually stopped by AWS after exceeding 25,000 events.
To avoid costs and endless loops, implement a callback pattern with an SQS Queue.
The callback pattern provides a retry mechanism and accounts for failures in processing.

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Msandbu

116

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How can Generative AI help us in terms of IT Security?

Generative AI models can aid IT security by using natural language queries to collect information and find necessary data to improve and integrate workflows.
Generative AIis evolving rapidly, can handle various media types like music, images, or even application code.
Generative AI now adds new functionalities called 'functions' which allow models to generate specific outputs that can trigger scripts or API calls.
Generative AI is quite useful for code analysis because security professionals don’t need to install a sandbox virtual machine to understand the code. Instead, LLMs can help understand the code's functionality quickly.
Generative AI can also be used in automating code reviews and security scans, making for a more efficient and secure software development process.
Generative AI can help attackers create malware, ransomware, or exploits that bypass security measures by automating vulnerability discovery and obfuscating the code.
However, Generative AI can also be used for sophisticated phishing or deepfake attacks unlike anything seen before. The dual nature of AI presents new cybersecurity challenges for organizations.
Overall, Generative AI can have significant benefits for IT security, but it is crucial to consider the potential threats and to always be cautious.

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Msandbu

434

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Setting up VM Insights using Terraform

VM Insights provides a couple of things: Process Map, Connection List, Performance Monitoring, and logs for Network Connections between virtual machines.
To configure VM Insights using Terraform, you can manually configure a VMInsight Data Collection Rule (DCR) to get the required configuration parameters.
The Terraform code provided showcases how to deploy VMInsights as part of your Terraform configuration, including specifying the destinations, data flow, and data sources.
By following this approach, you can easily set up VM Insights using Terraform for monitoring and managing virtual machines.

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Msandbu

210

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Azure Monitor Agent Syslog forwarding to Sentinel Troubleshooting and Disk usage

This article covers how to configure Syslog to forward logs to Azure Monitor Agent and ultimately send them to Microsoft Sentinel. The author discusses common troubleshooting steps and how to manage disk space if Syslog logs start filling up your disk. The article provides a one-liner from Microsoft that is useful to configure Azure Monitor agent on the machine and do the correct configuration on it to forward it.
The article shares a list of recommended log sources from which the log categories should be collected from the Syslog server. If you are collecting information from services such as VMware, then you should add user logs.
The author discusses the steps to check for available space and clean up excessive logs if your disk is filling up due to Syslog data. These steps include checking Disk Space, checking Azure Monitor Agent error logs and cleaning up unnecessary logs.
To free up disk space, we can remove large or unnecessary logs that are stored locally, since our goal is to forward them to Sentinel. The article describes how to delete unnecessary logs.
If you encounter other issues and if the disk usage is not the culprit, you can run a built-in troubleshooter to diagnose and resolve issues. The article discusses how to run the troubleshooter and disable and re-enable the Azure Monitor Agent when needed.
To configure Syslog to stop logging locally and forward logs directly to Azure Monitor Agent (which will forward it to Sentinel), the article instructs to edit the Syslog configuration and disable local log storage. After editing the configuration, the Syslog service needs to be restarted to apply the changes.

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Dev

125

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Maximizing Cost Efficiency on ECS Fargate: ARM Architecture and Fargate Spot Strategies

This article highlights some cost-saving measures that can be implemented to minimize the expense of running Elastic Container Service (ECS) on Fargate by AWS.
The author suggests minimising resource allocation for development environments, which can lead to significant cost savings. They set the minimum configuration of 256 (.25 vCPU), 512 MiB for their development environment.
Fargate Spot instances are up to 70% cheaper than standard Fargate instances; thus, by using Fargate Spot for development environments, costs can be reduced.
Stopping tasks during non-working hours in development environments can significantly reduce Fargate costs, and this can be done using EventBridge and Lambda to schedule task stop and start times.
Migrating from x86_64 architecture to Arm architecture can reduce; up to 20% Fargate pricing while maintaining high performance.
In the CI/CD workflow, docker buildx enables efficient multi-architecture image builds, making the infrastructure more flexible.
The article suggests utilizing Compute Savings Plans, as this allows committing to a consistent amount of compute usage (measured in USD/hour) over a 1- or 3-year period, offering significant discounts across EC2, Lambda, and Fargate.
By implementing these cost optimization strategies, significant reductions in ECS on Fargate costs can be achieved while maintaining system stability.

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Medium

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AWS Lambda Function Techniques (particularly with SNS & SQS)

The author shares their learnings from shipping production workloads with AWS Lambda Functions.
They emphasize the importance of avoiding mistakes and implementing Lambda Functions properly.
The techniques they've adopted primarily involve working with AWS SNS, SQS & EventBridge.
These techniques can be applied to other services and help make Lambda Functions consistent, reliable, and efficient.

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Digitaltrends

1.9k

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TikTok lays off hundreds for AI moderators while Instagram blames humans for its own issues

TikTok has laid off hundreds of human content moderators as it transitions to an AI-first moderation scheme.
The company currently employs a mix of human and AI content moderators, with machines handling 80% of the work.
Instagram admitted that recent issues with locking accounts and marking posts as spam were caused by mistakes made by human moderators.
The age verification issue on Instagram is still being investigated.

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Dev

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CI/CD in Azure DevOps for .NET Microservices Product Order Services

Automating the deployment process in microservices architecture using Azure DevOps.
Guide to setting up a CI/CD pipeline for .NET microservices, Product and Order services.
Steps to configure Azure Repos and create a CI/CD pipeline using YAML.
Explanation of pipeline stages including build, test, Docker image build and push, and deployment.

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Dev

179

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Building a crashproof cloud backend in Python using REST and PostgreSQL

This guide shows how to build and deploy a crashproof Python backend for an online store using DBOS and FastAPI.
The guide covers a single service, several REST APIs, and a PostgreSQL database.
The checkout workflow is created and backed out if it fails, returning reserved inventory and marking the order as cancelled.
The guide also shows how to write the HTTP endpoints for payment and checkout and retrieve product information.
The guide concludes with creating a workflow to dispatch orders that have been paid for.
The source code for this example is available on GitHub and also provides additional information on deploying to the cloud and running the app locally.
DBOS serves as a backend to make the application scalable and resilient.
DBOS provides durable execution to write crashproof workflows, uses queues to manage API rate limits gracefully, and scheduled workflows to run functions at recurring intervals.
Other example applications created using DBOS can also be explored.
Overall the guide provides a useful showcase of how to build a crashproof cloud backend in Python using REST and PostgreSQL.

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