Although Machine Learning is not new but recently it is quickly going forward thanks to public cloud providers such as AWS. By introducing SageMaker AWS is making Machine Learning more accessible and even more affordable to developers and data scientists. When combined with other AWS services such as Glue which facilitates data engineering, AWS becomes a perfect place for practicing and deploying machine learning applications.
This Re:Invent, Amazon Web Services introduced a number of very powerful new features to Lambda. These include layers, custom runtimes and the ability to execute Lambdas through an ALB. Now what could be a better way to demonstrate these functions then by deploying a custom Omgrofl runtime?
API Gateway is a service that allows you to manage access to all sorts of backend systems. Since its release in 2015, many new features and variants have been added. In this post we’ll explore the differences, use cases and performance of the Edge Optimized, Regional and Private API Gateway.
This is the first post of three where we are going to showcase how to build and configure a Data Continuity Service (DCS) for Amazon DynamoDB by using Amazon DynamoDB Streams, AWS Lambda, and the Amazon S3 services.
Many of our customers use VPNs to set up secure connections to their AWS environments. A few common use cases for VPNs are hybrid clouds, remote backups, and federated user management. This article will describe how to test VPN connections without requiring access to the remote end.
When managing your own cluster in ECS, there are 2 metrics you can use to scale your instances. Namely, these are the CPU and Memory reservation. For reference, I would like to mention here the simple mechanics behind them. Each of these metrics represent the percentage of CPU and respectively Memory units that are reserved by running tasks in the cluster.
In Sentia MPC, we’re trying to use as much AWS services as possible - also for tooling. With this approach, lately we’ve decided to use AWS CodePipeline, together with other tools (CodeBuild, CodeCommit) for deployment process.
In the cloud, containers provide a containerised environment enabling your code to be built, shipped and run anywhere. This can be simply done by just running your code without setting up your operating system.
Currently, CloudFormation doesn’t have support for the Parameter Store Secure Strings, which is unfortunate. This is just a matter of time though, as AWS will probably announce support at some point in the future, rendering this post obsolete.
As you might know, AWS CodeBuild is a service by AWS which can run your integration test or builds for you. It can be triggered by CodePipeline to deliver artifacts, and you can use CodeDeploy to deploy those artifacts to your servers.
At SENTIA we have developed our own object model for CloudFormation templates.
For the generation of the CloudFormation Resource object in this object model,
we parse the CloudFormation Resource Types Reference.
Before you can use Locksmith, you must create an IAM user and configure
Locksmith with its credentials. Locksmith can be both used stand-alone and
managed by a service. Here we show how to use Locksmith as a stand-alone tool.
Recently a client requested a feature which involved screenshots of random urls. Now, there are several services out there which will do this for you.
Most of these services have interesting rest api’s and pricing models. I really wanted to develop something with Serverless, and took this as an opportunity to check things out. This will run on the Amazon services (eg: Lambda).