aws-graviton-getting-started
serverless-application-model
aws-graviton-getting-started | serverless-application-model | |
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62 | 98 | |
828 | 9,259 | |
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Python | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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aws-graviton-getting-started
- AWS Graviton Technical Guide
- Cómo comenzar a trabajar con AWS Graviton: La pregunta del Millón
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What infra did you deploy for Iceberg/Hudi/Delta?
EMR serverless + Athena + Glue works for us. We are evaluating Graviton instance to further optimize stuff. AWS link if you are interested
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Slash CAPEX, OPEX, and Carbon Emissions with T408
Now we turn our attention to carbon emissions which are presented in Table 8. In the table, the AMD – CPU only and AMD – T408 server watts/hour are actual measurements on the test system during operation. To estimate the AWS server watts/hour, we reduced the CPU-only AMD number by 60%, which is the savings that Amazon claims that Graviton3 CPUs provide over other CPUs. In all three cases, we multiplied this by the number of servers, then hours, days, and years, to compute the three-year power consumption total.
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Framework ARM
https://aws.amazon.com/ec2/graviton/ https://cloud.google.com/compute/docs/instances/arm-on-compute
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Google Has Developed Its Own Data Center Server Chips
From the relevant product page [0]:
"AWS Graviton3 processors feature always-on memory encryption, dedicated caches for every vCPU, and support for pointer authentication."
Further reading on pointer authentication [1].
[0] https://aws.amazon.com/ec2/graviton/
[1] https://www.qualcomm.com/content/dam/qcomm-martech/dm-assets...
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can i repurpose a server and make it a computer
Amazon makes their own Arm CPUs, like the Graviton3: https://aws.amazon.com/ec2/graviton/
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Cost Cutting AWS strategies
Read More about Graviton Processors
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Blackberry Partnership Panning Out!
According to BlackBerry, both QNX and IVY can run on EC2 instances powered by AWS’ Graviton2 processor. Graviton2 is an internally-developed processor that AWS debuted at re:Invent last year. It promises to provide up to 40% better price performance than comparable chips. "
- AWS Graviton
serverless-application-model
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Simple and Cost-Effective Testing Using Functions
The complete solution with SAM is available here.
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Deploying a Serverless Dash App with AWS SAM and Lambda
There are many options to deploy Serverless Applications in AWS and one of them is SAM, the Serverless Application Model. I chose to use it here, because it doesn't add too many layers of abstraction between what's being deployed and the code we write and our infrastructure is quite simple.
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Serverless Apache Zeppelin on AWS
The solution uses AWS SAM with the global configuration for Lambda functions and the public API you can use to access Apache Zeppelin. The stack deployment provides the URL as an output value.
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Using design patterns in AWS Lambda
When you combine this with the AWS Serverless Application Model you can also very easily include your dependencies. Or use a compiled language like golang for your Lambda functions. You simply run sam build before you run the aws cloudformation package and aws cloudformation deploy commands. SAM will build the binary and update the template to point to the newly built binary. Package will then upload it to S3 and replace the local reference to the S3 location. Deploy can then create or update the stack or you can use the CloudFormation integration in CodePipeline.
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Serverless Site Health Check Notification System
I'm a big fan of using an Infrastructure as Code (IaC) approach for any project. My go to tools for this are the Servlerless Application Model (SAM) and it's associated CLI (SAM CLI). For more official use cases and for cross platform apps I typically use Terraform.
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Starting My AWS Certification Journey as a Certified Cloud Practitioner
AWS SAM
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API Gateway, Lambda, DynamoDB and Rust
Kicking off the tour and not starting a war, but I'm going to be using the Serverless Application Model.
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Consuming an SQS Event with Lambda and Rust
The diagram here is super simple. I'm going to write something a little later that shows how this code could fit into a bigger workflow, but for now, I'm keeping it basic. And yes, that's the SAM Squirrel in there.
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AWS Data Engineer Associate Certification - Coming Soon
Interestingly, AWS CDK and SAM are both explicitly mentioned. While CDK broadly addresses Infrastructure as Code, SAM is highlighted for its role in developing serverless data pipelines - a hugely underrated concept.
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A Beginner's Guide to the Serverless Application Model (SAM)
Naturally, there are several options available to declare your cloud resources. The options with the most popularity are the CDK, AWS CloudFormation, SST, Serverless framework, Terraform, and AWS SAM. There are others, but when talking about Infrastructure as Code (IaC), these are the ones you hear about most often.
What are some alternatives?
drupal-pi - Drupal on Docker on a Raspberry Pi. Pi Dramble's little brother.
aws-elastic-beanstalk-cli - The EB CLI is a command line interface for Elastic Beanstalk that provides interactive commands that simplify creating, updating and monitoring environments from a local repository.
KasmVNC - Modern VNC Server and client, web based and secure
LocalStack - 💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline
buildx - Docker CLI plugin for extended build capabilities with BuildKit
Moto - A library that allows you to easily mock out tests based on AWS infrastructure.
examples - TensorFlow examples
sst-start-demo - A simple SST app to demo the new `sst start` command
sysbench - Scriptable database and system performance benchmark
openvscode-server - Run upstream VS Code on a remote machine with access through a modern web browser from any device, anywhere.
examples - A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
aws-sam-cli - CLI tool to build, test, debug, and deploy Serverless applications using AWS SAM