Once again it’s time for another Barney Style “Break Down!”. Translating complex IT (InformationTechnology) terms into simple and relatable terms. Today we are going to dive deeper into an AWS resource that makes DevOps (DevSecOps) agile and flexible. If you are not familiar with the Barney Style breakdown on DevOps follow this link tbs DevSecOps . This article is going to breakdown the features of a software product that Amazon offers.
Get real time, as well as advanced, metrics on the health of your cloud.
ML (Machine Learning) makes it possible to accomplish business goals by manipulating information collected from a server. SageMaker Neo is an Amazon Web Services machine learning(ML) resource that makes it easier to use artificial intelligence to super power your business production through smarter predictions. You’ll save time and still be accurate when using your ML training models. Neo is automatically optimized to give you double the operating power for use on any ML framework and target hardware platform. The open source documentation gives developers the ability to open the hood of Neo and customize their ML environment. Neo offers numerous benefits that can be used on any server.
The Graph API V3.3 The premier method of reading and writing to the Facebook social graph for apps is the Graph API. If you want to know how to interact with all of Facebook’s SDKs and products, or use other APIs which are extensions of the Graph API, then you have understand the Graph API.
Amazon’s AWS SageMaker makes it possible to build, train and deploy machine learning models quickly. It is fully managed and covers the entire ML (machine learning) workflow. A lot of large companies use SageMaker resource. With SageMaker you can; collect and prepare training data, choose and optimize your ML algorithms, setup and manage training environments, and tune your model for optimization. Models can be deployed and managed in production. Use reinforcement learning to build smart outcomes. SageMaker is open and flexible and AWS will provide detailed instructions on how to use the SageMaker resource.
Do you know how your network works? Which servers are running? What data centers are they in? Are they set up for high availability and fault tolerance? What is your disaster recovery plan? If you don’t have the answers to these questions, then it will behoove you to give us call before it is too