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Currently, information on the general availability of C8g and M8g scenarios is being shared.
Cloud C8g environments provide a perfect setting for compute-intensive workloads, offering unparalleled efficiency for High-Performance Computing (HPC), batch processing, gaming, video encoding, scientific modeling, distributed analytics, CPU-based Machine Learning (ML) inference, and real-time ad serving applications.
Innovative applications leveraging Graviton4 technology demonstrate remarkable value in efficiently handling mainstream workloads, particularly in M8g scenarios. M8g scenarios are ideal for functions aligning with software servers, microservices, gaming servers, medium-sized data repositories, and caching clusters.
Several significant advancements are now accessible in each of these scenarios. The C8g and M8g configurations offer significantly larger occasion sizes, featuring up to three times more vCPUs (up to 48xl) than equivalent 7g configurations, alongside increased memory resources: up to 384GB for C8g and up to 768GB for M8g. Additionally, these scenarios provide 75% greater memory bandwidth and two-fold increases in L2 cache over comparable 7g situations. By leveraging this capability, you can process larger volumes of information, efficiently manage increased workloads, accelerate time-to-outcomes, and ultimately reduce your total cost of ownership. These scenarios offer up to 50 Gbps of network bandwidth, a significant increase from the up to 30 Gbps community bandwidth and up to 20 Gbps Amazon EBS bandwidth available on Graviton3-based environments. In a manner analogous to R8g scenarios, C8g and M8g situations offer two uncoated steel dimensions (metal 24 XL and metal 48 XL), respectively. You’ll be able to properly dimension your scenarios and deploy workloads that benefit from direct access to physical infrastructure.
Specifications for the C8G Situation:
1 | 2 | As much as 12.5 | As much as 10 | |
2 | 4 | As much as 12.5 | As much as 10 | |
4 | 8 | As much as 12.5 | As much as 10 | |
8 | 16 | As much as 15 | As much as 10 | |
16 | 32 | As much as 15 | As much as 10 | |
32 | 64 | 15 | 10 | |
48 | 96 | 22.5 | 15 | |
64 | 128 | 30 | 20 | |
96 | 192 | 40 | 30 | |
192 | 384 | 50 | 40 | |
96 | 192 | 40 | 30 | |
192 | 384 | 50 | 40 |
The specifications for the M8G situations are as outlined below:
1 | 4 | As much as 12.5 | As much as 10 | |
2 | 8 | As much as 12.5 | As much as 10 | |
4 | 16 | As much as 12.5 | As much as 10 | |
8 | 32 | As much as 15 | As much as 10 | |
16 | 64 | As much as 15 | As much as 10 | |
32 | 128 | 15 | 10 | |
48 | 192 | 22.5 | 15 | |
64 | 256 | 30 | 20 | |
96 | 384 | 40 | 30 | |
192 | 768 | 50 | 40 | |
96 | 384 | 40 | 30 | |
192 | 768 | 50 | 40 |
- AWS Graviton4 processors deliver bolstered security through perpetual memory encryption, dedicated caches for every virtual CPU, and support for pointer authentication, further safeguarding customer workloads.
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These scenarios are built upon a rich array of building blocks, which offloads numerous conventional virtualization features to dedicated hardware and software. Delivering unparalleled efficiency, unparalleled availability, and unparalleled safety, this solution significantly minimizes virtualization overhead.
- Linux-based workloads, including those utilizing containerized and microservices-based architectures, thrive alongside the C8g and M8g situations when paired with applications written in standard programming languages such as C/C++, Rust, Go, Java, Python, .NET Core, Node.js, Ruby, and PHP.
C8g and M8g situations are currently present in the US East region, primarily occurring north of a certain point. US-based customers have access to four main AWS Areas: Virginia, Ohio, Oregon, and Frankfurt, which is a key location in Europe. With Amazon EC2, you only pay for what you use. For extra data, see . Gather information that will aid in initiating the process of transitioning your functions to Graviton event types. Visit the website to begin your Graviton adoption process today?
To request additional training, visit our website and submit feedback. Alternatively, send suggestions to [insert email address] or contact your typical AWS Help associates.
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