Back in August Google Cloud announced the C3D instances powered by AMD EPYC 9004 "Genoa" processors while only last week was C3D promoted to general availability. Curious about the performance of C3D after being impressed by AMD EPYC Genoa bare-metal server performance at Phoronix as well as what I've seen with Genoa in the cloud at Microsoft Azure and Amazon EC2 / AWS, here are some benchmarks of the new C3D up against other GCE instances.

In Google's announcement last week they noted the general purpose C3D VMs can offer up to 45% performance increases over prior generation VMs. Given what I've seen out of Genoa and the great Zen 4 benefits like AVX-512 and transitioning to DDR5 system memory, these claims aren't all that surprising. Some of the specifics Google shared in their announcement was around 54% better NGINX performance, MySQL and PostgreSQL database servers up to 62%, and in-memory databases like Redis up to 60%.

Google Cloud offers C3D VMs up to 360 vCPUs (the C3D vCPUs are made up of a mix of physical cores and SMT sibling threads) and up to 2.8TB of DDR5 memory. For the purposes of this initial Google Cloud C3D benchmarking on Phoronix, I was focusing on the 60 vCPU C3D VM instance. For this article the following instance types were compared:

c3d-standard-60: The new C3D AMD EPYC Genoa instance with 60 vCPUs, powered by AMD EPYC 9B14.

c2d-standard-56: The prior generation AMD EPYC Milan instance with EPYC 7B13 processor. This instance was at 56 vCPUs with not having a 60 vCPU option.

n2d-standard-64: The AMD EPYC Rome based instance with EPYC 7B12 processors. Here the closest sized instance was 64 vCPUs.

c2-standard-60: The Intel Xeon Cascade Lake competition at 60 vCPUs for reference.

Unfortunately for Google's new C3 machine types that are powered by the latest-generation Sapphire Rapids processors, they are sized at 22 / 44 / 88 vCPUs (among other smaller and larger sizes). So unfortunately nothing in the 56~64 range as tested with the other machine types, which is why there wasn't any C3 instance tested for this article due to the starkly different sizing. In any case this article is mostly focused on the AMD EPYC generational performance in Google Cloud.

All of the tested instances were on Ubuntu 22.04 LTS. In addition to raw performance the performance-per-dollar based on the current hourly pricing was also tabulated.

Page 1 - IntroductionPage 2 - Google Cloud C3D HPC BenchmarksPage 3 - Google Cloud C3D BenchmarksPage 4 - Google Cloud C3D AI + TensorFlow / OpenVINO BenchmarksPage 5 - Google Cloud C3D Benchmarks

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Google Cloud C3D Shows Great Performance With AMD EPYC Genoa - Phoronix

The rush to embrace artificial intelligence, particularly generative AI, is going to drive hyperscale data-center providers like Google and Amazon to nearly triple their capacity over the next six years.

Thats the conclusion from Synergy Research Group, which follows the data center market. In a new report, Synergy notes that while there are many exaggerated claims around AI, there is no doubt that generative AI is having a tremendous impact on IT markets.

Synergys updated six-year forecast shows that the average capacity of new hyperscale data centers will soon be more than double that of current operational hyperscale data centers. And the total capacity of all operational hyperscale data centers will grow almost threefold between 2023 and 2028.

The research is based on an analysis of the data center footprint and operations of 19 of the worlds major cloud and internet service firms. By mid-2023, those companies had 926 major data centers in operation around the world. Synergy's projection for future data centers includes another 427 facilities in the coming years.

Synergy says the impact of generative AI advances has not so much fueled an increase in the number of data centers but rather led to a substantial increase in the amount of power required to run those data centers. As the number of GPUs in hyperscale data centers skyrockets, driven primarily by AI, the power density of associated racks and data center facilities also needs to increase substantially. This is causing hyperscale operators to rethink some of their data center architecture and deployment plans.

So if its a headache for AWS to manage this stuff, what will it be like for an average enterprise running five-year-old servers?

While corporations are rushing to embrace generative AI to improve their businesses, the cost of acquiring the hardware and operating it has given many pause. A DGX server from Nvidia, custom-built for generative AI and packed with hardware, can easily run in the six-figure range. For that kind of money, you can also buy about 10 regular servers. Which will enterprises prioritize?

Plus theres the expense of operating them. Nvidia GPUs are not known for being a low power draw. It's quite the opposite. They are the biggest power hogs in a data center. So for a budget-conscious enterprise, particularly a midsized one, deploying generative AI hardware might be too taxing.

In addition, the way AI operates is different from traditional line-of-business applications. There's the process-intensive task of training, which requires GPUs, and then theres inference, which runs off the models trained by the GPUs. Once a model is trained, theres a good chance you may not need to revise it for months. Then your very expensive hardware sits idle, unneeded, and depreciating.

Could enterprises do this themselves without using a hyperscale cloud provider? "Theoretically, yes, but costs might be prohibitive and access to the right sort of expertise could be severely limited, said John Dinsdale, chief analyst and research director at Synergy Research Group.

So the emerging trend in enterprise IT for generative AI is to farm out the training portion of its AI but do the inference, which is much less process intensive, in-house. Why invest hundreds of thousands of dollars in hardware that you only use sparingly when you can rent it out from Google or AWS?

This is known as AI as a service, an emerging offering from hyperscalars like AWS and Microsoft. We can expect more to come on that.

Link:
Hyperscale data-center capacity on pace to triple over next six years - Network World

Prague, Czech Republic, October 27, 2023 --(PR.com)--Devart, a recognized vendor of world-class data connectivity solutions for various data connection technologies and frameworks, announced new versions of ODBC Drivers with Server to Server authentication mode, support and compatibility improvements, and more.

The list of the improvements includes:- An update for Direct Mode, built on the SQLite engine, version 3.42.0;- Support for CREATE TABLE AS SELECT statement for xBase is now available;- Implemented Server to Server authentication for Salesforce Marketing Cloud (formerly ExactTarget);- Jira supports custom tables and custom fields now;- ListSurveys table and fields to the ListMembers table for SurveyMonkey are available now;- Compatibility with the Survey Rocket plugin for Sugar CRM;- Updated SQL engine for Sendinblue, along with multiple bug fixes and quality-of-life improvements.

To learn more about the recent release and download new products, visit:https://blog.devart.com/new-in-odbc-server-to-server-authentication-mode-support-and-compatibility-improvements-and-more.html

Devart ODBC Drivers are high-performance connectivity solutions with enterprise-level features for accessing the most popular database management systems and cloud services from ODBC-compliant reporting, analytics, BI, and ETL tools on 32-bit and 64-bit Windows, macOS, and Linux. Our ODBC drivers fully support standard ODBC API functions and data types to enable easy access to live data from anywhere.

About Devart

Devart is one of the leading developers of database tools and administration software, ALM solutions, data providers for various database servers, data integration, and backup solutions. The company also implements Web and Mobile development projects.

For additional information about Devart, visit https://www.devart.com/.

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Meet Updated ODBC with Server to Server Authentication Mode ... - PR.com

Google-parent Alphabet (GOOG, GOOGL) stock tumbled earlier this week after reporting slower-than-expected revenue growth for its cloud division. RBC Capital Markets Internet Analyst Brad Erickson sits down with Yahoo Finance anchor Rachelle Akuffo to talk about cloud technology's current influence on Big Tech earnings, particularly Meta (META).

"They have covered a lot more ground with money they have spent than people realized, they're not going to have to spend as much as people thought in 2024," Erickson says on Meta's building out of its facilities and AI infrastructure.

Click here to watch the full interview on the Yahoo Finance YouTube page or you can watch this full episode of Yahoo Finance Live here.

RACHELLE AKUFFO: --to see if it was unfairly punished, given how well the actual earnings report was about the focus on Cloud.

BRAD ERICKSON: Yeah, I got it. I would say so, the advertising business, we do a lot of channel checks in the ad space. We came in tactically constructive on the space where everybody hit numbers, or beat numbers, really, for Q3. Meta's guidance was fine for Q4, even including some impact they called out from the Middle East.

Google had an unfortunate quarter with The cloud business, and it brought everything else down. And with the Meta result on Wednesday, I think the takeaway there was, unfortunately, people were looking for any reason to sell the stocks, I think that's probably a reflection on the broader macro, where we think the consumer is going, but looking for an excuse to sell the stock almost, and just made it a tough week until today with Amazon fortunately.

RACHELLE AKUFFO: And so speaking of Meta then, obviously 2023, the year of efficiency seemingly paying off at the moment. Obviously, the metaverse play, if we look over the past five years, still seeing some losses there. What are your expectations then for 2024, based on some of the cuts we've already seen Meta making this year?

Story continues

BRAD ERICKSON: I think it's going to be a combination of things. And you point to three factors that really drive the operating expense guidance they gave, which was modestly better than expectations. Number one, is just in general around headcount costs, facilities costs, I think there the message is, 2024 is going to continue to be another year of efficiency, that's number one.

Number two is just on their capital expenditures, these are around building data centers, and buying servers, and, certainly, graphics processors in the age of generative AI. I think there, what we learned on the call, which was positive, was that they've covered a lot more ground with money they've already spent, I think, than people realize, and so they're not going to have to spend quite as much as people thought in 2024.

And then the last one is Metaverse. And I think there, we don't love the losses, investors don't love the losses. Obviously, they're clearly continuing to spend, but I think the takeaway, again, nets out positively in that Mark Zuckerberg and his team are clearly acquiescing to investors desires to keep it more reasonable, meaning balancing the growth with that spend, and you're netting out to still an attractive consolidated P&L.

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2024 could be 'another year of effiiciency' for Meta: Analyst - Yahoo Finance

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Hybrid cloud security is a framework for protecting data and applications in a computing environment that includes both private and public clouds. It combines on-premises and cloud-based resources to satisfy an organizations diversified computing demands while ensuring strong security. This approach to cloud computing enables enterprises to benefit from the scalability and flexibility provided by public clouds while maintaining sensitive data within their own infrastructure.

As more businesses embrace hybrid cloud models to cater to their different computing demands, safeguarding the boundary between these environments has become critically important, making hybrid cloud security a top priority for ensuring protection, compliance, and resilience in an ever-changing digital ecosystem.

See our guides to public and private cloud security

Hybrid cloud security combines on-premises controls and practices with cloud-specific solutions, reinforcing data and application protection between environments. Hybrid cloud security starts with analyzing and categorizing data and progresses to customized security measures. Hybrid cloud security generally follows best practices for network security and cloud security:

These components work together to establish a complete hybrid cloud security strategy, but the specific components and their configuration will vary depending on the organizations security needs and the cloud services it employs.

A hybrid cloud architecture primarily involves integrating different types of cloud and on-premises technology to fulfill an organizations unique demands. Here are some examples of hybrid cloud security architectures.

An enterprise in this case combines its on-premises data center or infrastructure with a public cloud. Some workloads, apps, or data may be hosted on the organizations own servers, while others may be offloaded to a public cloud provider such as AWS, Azure, or Google Cloud.

Here, businesses can combine a public cloud with a private cloud, which may be housed in a dedicated data center. They use the public cloud for some processes and services, but keep a private cloud for more sensitive data or mission-critical applications.

Businesses may mix various public cloud providers, private clouds, and on-premises technology in more complex setups. This enables them to select the most appropriate environment for each workload, application, or data type.

Data synchronization is critical in hybrid cloud architectures to provide consistency across infrastructures. Connecting private clouds, legacy systems, and public clouds through the internet or private networks guarantees that data and applications flow seamlessly. A single management tool facilitates supervision because managing numerous cloud environments independently can be complicated due to differences in APIs, SLAs, and features from different providers. This provides a centralized interface for effective control and monitoring of hybrid cloud resources.

A hybrid cloud infrastructure gives enterprises a scalable, adaptable, and cost-effective solution that prioritizes data protection, privacy, and disaster recovery. This approach ensures business continuity and adaptation to changing demands by allowing for smooth resource allocation and cost control.

Hybrid clouds offer flexibility for enterprises with a wide range of demands and endpoints. They enable you to effortlessly move between on-premises and cloud servers based on your needs. You may manage your infrastructure at your own speed and respond quickly to changing demands.

It can be expensive to set up and manage on-premises data centers. By transferring resource-intensive activities to the cloud, a hybrid cloud approach can allow for cost-effective solutions. Cloud companies charge depending on consumption, which can lower infrastructure and maintenance costs, particularly for companies trying to meet fluctuating demand. Real-time monitoring and clear payment alternatives help with expenditure control.

Hybrid architecture is extremely scalable, allowing for company expansion by adding or deleting cloud servers as required. Employees may connect to the office system using a variety of devices without the need for extra hardware. Depending on demand, operations can be scaled up or down to optimize expenses.

Large amounts of data may be stored and analyzed in the cloud. To guard against cyber attacks, cloud systems include powerful security features such as encryption, firewalls, authentication, and data backups. Data security is improved by privacy features like number masking and dynamic caller IDs. Hybrid solutions enable you to preserve sensitive data on private clouds while keeping general data on public servers.

Cloud bursting allows workloads to be expanded to a public cloud during demand surges and then scaled down to the original server. This rented resource solution saves money and time while adjusting to changing workloads.

If security, privacy and regional compliance demands are met, storing or backing up critical data on cloud servers improves disaster recovery capability. Multiple backups provide data management even in the face of unforeseen occurrences like natural catastrophes. Because cloud-based operations can be expanded and controlled from anywhere, they provide business continuity in crisis scenarios.

When compared to typical security methods, securing a hybrid cloud environment brings unique challenges, particularly for enterprises with stringent regulatory requirements and established procedures. Some areas of concern include:

It is important to understand the shared responsibility of your company and cloud service providers. Cloud providers protect the infrastructure, but clients must protect their data and applications.

How to address this challenge: To protect data and applications, ensure that providers can satisfy regulatory requirements and incorporate business continuity and disaster recovery strategies in service level agreements (SLAs). And keep tight controls on access and other frequent cloud security mistakes.

When issues develop within the infrastructure of a cloud service provider, teamwork is required to resolve them. Issues such as data commingling in multicloud systems, data privacy influencing log analysis, and disparities in defining what constitutes an event can all provide difficulties.

How to address this challenge: To reduce downtime and data exposure, enterprises should define explicit incident response plans, including communication methods, and verify they comply with the cloud providers policies.

Cloud applications are vulnerable to a variety of security risks, and a range of products address certain areas of this issue, such as software development life cycle security, authentication, compliance, monitoring, and risk management. Managing them separately can be difficult logistically, so look for solutions that incorporate various security roles.

How to address this challenge: Organizations should take a DevSecOps approach to security, including it in the application development lifecycle. Using automated security testing tools and doing frequent code reviews helps to protect the integrity of apps.

Because sensitive data is dispersed across several environments in hybrid cloud security, consistent security procedures and monitoring are required to prevent exposure and breaches.

How to address this challenge: Using a data-centric security approach, such as data encryption, data classification, access restrictions, and data loss prevention solutions, may help protect sensitive information no matter where it is stored.

Because of the requirement to follow varying standards across numerous cloud environments, compliance and auditing pose issues in hybrid cloud security, demanding complicated monitoring, reporting, and adherence processes.

How to address this challenge: To ease the compliance process, organizations should establish a centralized compliance and auditing system that uses automated technologies to monitor and report on the compliance status of their hybrid cloud environment.

While specific configurations may differ, adopting these best practices assists businesses in mitigating risks and successfully responding to security challenges.

Encrypting data in transit and then examining it guarantees that sensitive information is kept private during transmission while also allowing for the discovery of any possible security risks or breaches. This way, security is ensured on both ends.

Continuous configuration monitoring and auditing aid in detecting deviations from defined security standards and policies, ensuring that the hybrid cloud system stays compliant and safe. Monitor and audit settings across all of your clouds and data centers on a regular basis. Misconfigurations, which are frequently the consequence of human mistakes, are a major source of vulnerabilities. Automation is a useful technique for ensuring secure setups.

Vulnerability scans uncover possible flaws in the system, allowing for quick correction to strengthen security against hostile actors. Conduct vulnerability checks on a regular basis to uncover weak places in your infrastructure. Make use of automated solutions that prioritize vulnerabilities based on risk profiles to ensure efficient and successful remediation.

Applying security updates on a regular basis keeps software and systems up to date, addressing known vulnerabilities and improving the hybrid cloud infrastructures security posture. By shortening the period between patch release and implementation, the window of opportunity for possible cyber attacks is reduced.

To reduce the danger of unauthorized access or lateral movement by attackers, zero trust security necessitates strong authentication and access rules that regard all users and devices as untrusted entities. Implement security principles based on zero trust, which prioritize least-privilege access and strong authentication.

Create an effective response strategy in the event of a security compromise. In the case of a security breach or disaster, a recovery plan specifies how to restore services and data while minimizing downtime and data loss and guaranteeing business continuity. Keeping backup storage separate from the original data source reduces the chance of a single point of failure and speeds up remediation operations.

Endpoint security solutions, such as EDR and multi-factor authentication, prevent illegal access and data breaches by securing endpoints such as devices and user access points. While cloud computing has revolutionized company security, endpoints could still remain a weak link. It is critical to protect data going through and between these devices.

The hybrid cloud security landscape is continuously expanding, and several major companies now offer comprehensive solutions to protect your data and apps in hybrid environments. Here are three of the top hybrid cloud security solutions to consider.

Acronis Cyber Protect Cloud specializes in providing comprehensive services to safeguard data across various environments, particularly in hybrid cloud setups, making it a good option for organizations seeking to secure and manage their data in complex, multi-cloud, and on-premises environments.

Key Features: Acronis includes AI-based antivirus, anti-malware, and anti-ransomware technologies for proactive threat prevention, as well as fail-safe patching, forensic backup, and continuous data protection.

Services: Data backup and recovery, cybersecurity tools against malware, ransomware, and other threats, and services for data storage and management.

Unique Offering: AI-Based Protection, blockchain technology, and integrated data protection.

Skyhighs Cloud Native Application Protection Platform offers an all-in-one solution for securing cloud-native applications, encompassing a risk-based perspective on application and data context.

Key Features: Skyhighs CNAPP examines workloads, data, and infrastructure in real time, detecting misconfigurations, software vulnerabilities, and sensitive data. For comprehensive security, it defends against configuration deviations, automates assessments, and supports short-lived workloads with application allow-listing, workload reinforcement, integrity monitoring, and On-Premises Data Loss Prevention (DLP) Scanning.

Services: Offers a unified set of controls based on an integrated platform, customer assistance, and expert guidance.

Unique Offering: Skyhigh (formerly McAfee MVISION) is a pioneering platform that integrates application and data context, combining Cloud Security Posture Management (CSPM) for public cloud infrastructure and Cloud Workload Protection Platform (CWPP) for application protection across virtual machines, compute instances, and containers.

Trend Micro Cloud One platform has broad support across public cloud providers (AWS, Google Cloud, Azure), VMware-based private clouds, and on-premises storage.

Key Features: Trend Micro offers AI and ML-powered vulnerability analysis, a bug bounty program for zero-day attack readiness, contributions from 15 global research centers, managed detection and response services, protection for cloud-native applications, and versatile integrations via native APIs. Advanced automation enhances vulnerability detection and compliance monitoring.

Services: Managed detection and response, threat analysis, and professional assistance are all available through the platform.

Unique Offering: Provides full coverage, including open source assets, filling a critical cybersecurity gap. Trend Micros relationship with Snyk offers specific coverage for open source assets, making it a good option for businesses that already rely on open source.

Businesses should explore hybrid clouds if they have dynamic workloads, seasonal swings, need gradual cloud adoption, or want flexibility in the face of an uncertain future. Hybrid clouds allow businesses to adapt at their own speed, giving financial relief and a safety net for those hesitant to embrace full-scale changes. Hybrid cloud security, which combines traditional on-premises security practices with cloud-specific measures, ensures a comprehensive defense strategy, allowing organizations to benefit from cloud computing while effectively safeguarding their data and applications from evolving cyber threats and regulatory compliance issues.

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What Is Hybrid Cloud Security? How it Works & Best Practices - eSecurity Planet