Category: Python

As the Python Software Foundation’s new security sponsor, AWS is providing funding to the PSF to hire a full-time safety and security engineer dedicated to improving the security posture of the Python Package Index (PyPI).

Learn how to use AWS services and open source tools to automate the deployment of a Python Flask application to the AWS Cloud using CodePipeline.

What is Redis? Redis is an incredibly popular open source (BSD licensed) in-memory data store, generally used as a database, cache, or message broker. Redis is regularly touted by developers as the most loved database and you’ve used Redis when on Twitter, GitHub, Instagram, Airbnb, and many other products. Redis Clusters enable you to scale […]

In this blog post, we explain how to create a multi-stage Dockerfile that uses eksctl, kubectl, and aws-auth. This will allow you to call Kubernetes APIs to create and manage resources through a unified control plane. You will interact with the Kubernetes API using Python, and the config map is created using a Jinja2 template. […]

Data has become the language of business. Organizations leverage data to better understand and deliver value to their customers. As a result, there is a growing need in many organizations for flexible patterns that can be leveraged to develop new applications and functionality to interact with their data. APIs, or application program interfaces, are a […]

In this post, AWS intern engineers Azfaar Qureshi and Shovnik Bhattacharya talk about their experience building the OpenTelemetry Prometheus Remote Write Exporter for Python. They share their experiences in tackling challenges they faced while building this tool, which is used for sending metrics to Prometheus protocol-based service endpoints. As software deployments become increasingly more complex, […]

Data science is hard. Customers face business challenges today at a scale larger and more complex than ever before, and data scientists bring unique skills to the table to help solve some of those problems. The concept is simple: Data scientists use large amounts of data to break a problem down into pieces that machines […]

Web applications interacting with AWS in a number of ways may need to represent and display sets of information in the form of charts, diagrams, or graphs. Common examples of that information includes small amounts of data coming from AWS Costs & Usage Reports or Amazon Elastic Compute Cloud (Amazon EC2), either historical or real-time. […]

Modern applications are increasingly relying on compute platforms based on containers and serverless technologies to provide scalability, cost efficiency, and agility. Although this shift toward more distributed architectures has unlocked many benefits, it has also introduced new complexity in how the applications are operated. In times past, debugging was as straightforward as logging into the […]

Customers on AWS deploy trained machine learning (ML) and deep learning (DL) models in production using Amazon SageMaker, and using other services such as AWS Lambda, AWS Fargate, AWS Elastic Beanstalk, and Amazon Elastic Compute Cloud (Amazon EC2) to name a few. Amazon SageMaker provides SDKs and a console-only workflow to deploy trained models, and […]