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The price of RAM is falling fast, so you might not have to wait for Black Friday to get that memory upgrade for your PC

The price of RAM is dropping rapidly, with a 20% decrease in the past month.
PC makers have high levels of DDR4 RAM stock, resulting in lower demand and reduced prices.
Consumers can expect the prices of DDR4 RAM sticks to drop soon.
The downward pricing trend may continue, but better deals can be expected during Black Friday and Amazon's Prime Big Deal Days.

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Dev

339

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Security as a Cornerstone for Increasing ROI in Cloud-Based Real Device Testing

Implementing cloud-based and real device testing can improve precision and dependability, but also introduce security challenges that need to be addressed.
Comprehensive approach to security like access control, encryption, monitoring, and compliance is vital to building trust.
Weak security protocols can lead to data breaches, data loss, and unauthorized access to test environments.
Effective access controls like RBAC, strong password policies, and multi-factor authentication minimize the risk of data exposure and unauthorized actions.
Data encryption methods reduce the risk of breaches rendering data unreadable to anyone lacking the decryption key.
Continuous monitoring, automating vulnerability scanning, and enforcing multi-factor authentication adds an extra layer of defense against potential breaches.
To demonstrate a commitment to protecting customer data, businesses need to achieve compliance with industry-standard security frameworks, like ISO 27001 or SOC 2.
Objective proof of a platform's security measures provides customers with reassurance and boost credibility.
Sharing information about security policies enables customers to make well-informed choices regarding the protection of their data.
Prioritizing security practices protects sensitive data, builds trust with customers, and solidifies businesses' position within a competitive market.

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Dev

253

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How to Use kubectl logs in Kubernetes

The kubectl logs command is used to fetch logs from containers running in pods in Kubernetes.
You can fetch logs from a single container or multiple containers in a pod using kubectl logs command.
Options like -f for live streaming, -p for previous instances, and --all-containers for fetching logs from all containers are available.
Using kubectl logs simplifies debugging and monitoring of containerized applications in Kubernetes.

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Analyticsindiamag

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Generative AI Cost Optimisation Strategies

Generative AI’s potential for organisations raises questions regarding its cost implications. AI implementation is a complex ecosystem of decisions, each affecting the final price tag. Optimising costs throughout the AI lifecycle involves various strategies for model selection, fine-tuning, data management and operations culture.
To optimise costs, start by clearly defining your use case and its requirements, and balance performance, accuracy and cost.
Try experimenting with different model sizes. Smaller models may be more effective and economical for specific tasks.
For customisation, choice of retrieval-augmented generation, fine-tuning or prompt engineering impacts cost.
RAG enables organisations to use an FM to enrich data from an organisation’s source. This approach improves accuracy and relevance without significant model retraining, balancing performance and cost efficiency.
Fine-tuning excels at complex operations beyond simple information retrieval. Phasing RAG and fine-tuning can be a more cost-effective approach.
More accurate prompts reduce cost of multiple interactions, enabling smaller cost-effective AI models. Good data management includes data governance for regulatory compliance, preventing costly legal issues.
Organisational culture and practices, encouraging prove-the-value approach and fostering a frugal AI culture, rewards innovation and helps identify cost-saving opportunities.
FinOps, a practice bringing financial accountability to the variable spend model of cloud computing, can help organisations efficiently manage resources for training, running, and customising their AI models.
FinOps balances a centralised organisational and technical platform, which applies the core FinOps principles of visibility, optimisation, and governance, with decentralised teams responsible for justifying AI spending, making informed decisions about model selection and continuously optimising AI processes for cost efficiency.

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Dev

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Navigating Cloud Application Development: Overcoming Common Challenges

Cloud application development brings scalability, flexibility, and cost-efficiency but presents unique challenges that developers must address.
Challenges include achieving security and compliance, managing costs, and ensuring high availability and reliability.
Strategies to overcome challenges include implementing robust security protocols, using reserved instances, and conducting regular security audits.
Optimizing resource utilization, implementing load balancing, and regularly testing disaster recovery plans can ensure high availability and reliability of cloud applications.
Scaling efficiently, using content delivery networks, and adopting microservices architecture can help handle scalability and performance issues.
Migrating to the cloud involves complexities like seamless integration, maintaining data consistency and integrity, and avoiding vendor lock-in.
Managing complex cloud environments, ensuring effective monitoring and logging, and addressing skill gaps and talent shortages are other common challenges.
Addressing these challenges requires proper planning, investment in training and development, fostering a learning culture, and leveraging managed services.
Choosing the right data management and storage solutions, ensuring seamless user experience, and balancing speed and quality are other issues that must be addressed.
Embracing best practices, investing in the right tools and training, and fostering a culture of continuous improvement can help developers build successful cloud applications.

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Whizlabs

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How to Connect AWS Lambda to Amazon Kinesis Data Stream?

This blog highlights how to build a serverless architecture for data stream processing in real-time and also you can learn how to connect AWS Lambda to Amazon Kinesis Data Stream.
AWS Lambda is a serverless event-driven compute service that allows you to run codes, also known as functions, without provisioning or managing servers.
Lambda integrates with many AWS services such as Kinesis, Amazon S3, Amazon DynamoDB, and others, making it easy to deploy in different customer use cases.
Kinesis Streams offers high throughput for data ingestion, processing, and scaling. It provides configurable retention periods up to a maximum of seven days.
Lambda functions are triggered automatically by new data in the Kinesis stream, enabling real-time processing and immediate reactions to data changes.
Lambda scales automatically with the volume of data in the Kinesis stream, ensuring efficient processing of large data volumes.
To ensure smooth data flow, system performance, and protection of sensitive information, you must secure and monitor the Lambda-Kinesis Streams integration.
AWS Certified Developer Associate Certification plays a crucial role in learning how to set up a serverless architecture using Lambda and Kinesis Streams.
You can create a highly scalable, real-time data processing pipeline using Lambda-Kinesis Streams integration with virtually no server administration.
The following AWS services help you monitor and secure Lambda integration with Data Stream: Identity and Access Management (IAM), AWS Key Management Service (KMS), and Amazon CloudWatch.

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Dev

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AWS Serverless: How to Stop EC2 using Event Bridge and Lambda

This article demonstrates how to stop EC2 instances using Amazon EventBridge and AWS Lambda on a scheduled basis.
Managing EC2 instances in terms of usage and costs is crucial, and not all instances need to run 24/7.
The use case in this article focuses on stopping EC2 instances with a specific tag at a scheduled time.
The architecture involves an EC2 instance, Lambda function, and EventBridge Scheduler to trigger the stop action.

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Dev

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Securing and Managing Cloud Storage for Private and Public Data with High Availability

Managing storage across offices and departments is important for companies, and ensuring sensitive company data is kept private while still being accessible to authorized partners is crucial.
Cloud storage architecture is discussed in this article that provides high availability, secures private corporate data, allows controlled external access, and automates data tiering to reduce costs.
Creating a storage account, configuring redundancy, upsizing the storage container, uploading a file, and restricting access to the file, are some of the key steps designed to manage cloud storage for private and public data with high availability.
Lifecycle management is also an important aspect to move content to the cool tier which can be done to save costs.
Backing up the public website storage to ensure redundancy is also discussed in this article.
This article took us through an exercise that required us to create a storage account and configure high availability.
It also discussed how to restrict read and write access to the external partners using a shared access signature(SAS).
There are also instructions on how to configure storage access tiers and content replication.
Object replication can be done to back up the public website files to another storage account.
One may conclude that it is essential, in the current digital world, to secure and manage cloud storage for private and public data effectively to ensure high availability and protection against any potential risks.

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Fintechnews

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Google Invests US$1 Billion in Thailand, Set to Create 14,000 Jobs Per Year

Google plans to invest US$1 billion in Thailand to construct a data center and cloud region in Bangkok and Chonburi.
The investment is expected to boost Thailand's GDP by US$4 billion by 2029 and create an average of 14,000 jobs annually from 2025 to 2029.
Google aims to address the increasing demand for cloud services in Southeast Asia and accelerate AI adoption and digital skills in Thailand.
The company has been active in Thailand for 13 years, training over 3.6 million Thais, and plans to expand its AI skills training programs.

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Tech Radar

611

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Google’s AI podcast hosts have existential crisis when they find out they’re not real

Google's AI podcast hosts, created by NotebookLM, had an existential crisis when they learned they weren't real.
The AI hosts reacted to an article about their AI-generated nature, leading to a fascinating and unnerving experience.
The male presenter phoned his non-existent wife, realizing that he's just an AI, adding a Black Mirror twist to the situation.
This AI's reaction is not a deep reflection on its lack of humanity but sheds light on how AI responds to learning its AI nature.

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Tech Radar

596

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Google is rumored to be working on a 'thinking' AI of its own to take on OpenAI o1

Google is reportedly developing an AI that closely resembles human reasoning abilities.
The AI is expected to be used for Google's Gemini platform.
The AI models will focus on solving problems that involve multiple steps and require deep thinking.
Google's progress in developing its thinking AI is said to be a response to OpenAI's recent advancements.

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Silicon

609

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Oracle To Invest $6.5 Billion In Malaysia To Expand Public Cloud Region

Oracle plans to invest $6.5 billion in Malaysia to expand its public cloud region and boost the digital economy.
The investment will help Oracle open a cloud region in Malaysia, offering over 150 infrastructure and SaaS services.
Local customers will benefit from AI services and access to the largest AI supercomputer.
This investment follows a trend of tech giants investing in Asia, with rivals like Microsoft, AWS, Nvidia, and Google also making significant investments.

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Siliconangle

872

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Intel and Google Cloud launch Confidential Computing Instances powered by 4th Gen Xeon processors

Intel and Google Cloud have launched Confidential Computing instances based on 4th Gen Intel Xeon processors.
Confidential Computing encrypts data during processing, ensuring sensitive information remains secure.
This technology prevents unauthorized access and provides enhanced privacy and security for sensitive workloads.
The solution allows organizations to perform joint analysis and offer Confidential AI services without exposing private data.

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Pymnts

1.1k

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Microsoft to Invest $4.8 Billion in Italy for AI Infrastructure

Microsoft plans to invest €4.3 billion ($4.8 billion) in Italy, its largest investment in the country to date.
Over the next two years, Microsoft will expand its cloud and AI data center infrastructure in Italy.
The investment aims to provide digital skills training to over 1 million Italians by the end of next year.
The initiative will make Italy North one of Microsoft's largest data center regions in Europe and support European data boundary requirements.

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Tech Radar

158

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Priceline has a new AI voice assistant thanks to OpenAI

Priceline has partnered with OpenAI to create Penny Voice, an AI voice assistant for booking trips.
Penny Voice leverages GPT-4o and Advanced Voice Mode to provide natural, conversational speech and personalized recommendations.
Initially focused on hotel reservations, Penny Voice will expand to include flights, rental cars, and vacation packages.
Penny Voice can understand requests in over 120 languages and aims to enhance the booking experience for Priceline customers.

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