Private registry authentication support for Amazon Elastic Container Service (Amazon ECS) is now available with the AWS Fargate launch type! Now, in addition to Amazon Elastic Container Registry (Amazon ECR), you can use any private registry or repository of your choice for both EC2 and Fargate launch types.
For ECS to pull from a private repository, it needs a secret in AWS Secrets Manager with your registry credentials, an ECS task execution IAM role in AWS Identity Access Management (IAM) with a policy granting access to the secret, and a task with the secret and task execution IAM role ARNs in the task definition.
Whether you are new to the the cloud and AWS or an experienced cloud developer, this guide is designed to help you get started with Docker containers on AWS ECS and AWS Fargate quickly and easily.
If you are brand new to the cloud or containers you should first read the introduction to cloud and container concepts.
If you already feel familiar with Docker containers, and just want to deploy your containerized application quickly and reliably head to the architecture patterns section to find a collection of infrastructure as code examples for popular application architectures. You can either deploy the templates onto your own AWS account in a few clicks, or download them to customize or use as a reference for developing your own application template.
This post discusses how maps are implemented in Go. It is based on a presentation I gave at the GoCon Spring 2018 conference in Tokyo, Japan.
What is a map function?
To understand how a map works, let’s first talk about the idea of the map function. A map function maps one value to another. Given one value, called a key, it will return a second, the value.
map(key) → value
Now, a map isn’t going to be very useful unless we can put some data in the map. We’ll need a function that adds data to the map
insert(map, key, value)
and a function that removes data from the map
There are other interesting properties of map implementations like querying if a key is present in the map, but they’re outside the scope of what we’re going to discuss today. Instead we’re just going to focus on these properties of a map; insertion, deletion and mapping keys to values.
As more and more developers and companies adopt serverless architecture, the likelihood of hackers exploiting these applications increases dramatically. The shared security model of cloud providers extends much further with serverless offerings, but application security is still the developer’s responsibility. There has been a lot of hype about #NoOPS with serverless environments 🤥, which is simply not true 😡. Many traditional applications are frontended with WAFs (web application firewalls), RASPs (runtime application self-protection), EPPs (endpoint protection platforms) and WSGs (web security gateways) that inspect incoming and outgoing traffic. These extra layers of protection can save developers from themselves when making common programming mistakes that would otherwise leave their applications vulnerable. With serverless, these all go away. 😳
Serverless makes it easy to deploy a function to the cloud and not think about the infrastructure it’s running on. While certainly convenient, this leaves many developers with a false sense of security. By relying too heavily on the cloud provider, and not coding defensively, developers can significantly reduce their overall security posture. As with any type of software, there are a myriad of attacks possible against serverless infrastructures. However, unlike traditional web applications, serverless architectures are “event-driven”. This means they can be triggered by a number of different sources with multiple formats and encodings, rendering WAFs useless and opening up a completely new attack vector…
What is the maximum network throughput of your EC2 instance? The answer to this question is key to choosing the type of an instance or defining monitoring alerts on network throughput. Unfortunately, you will only find very vague information about the networking capabilities of EC2 instances within AWS’s service description and documentation. That is why I run a network performance benchmark for almost all EC2 instance types within the last few days. The results are compiled into the following cheat sheet.
You may have heard of Amazon Aurora, a custom built MySQL and PostgreSQL compatible database born and built in the cloud. You may have also heard of serverless, which allows you to build and run applications and services without thinking about instances. These are two pieces of the growing AWS technology story that we’re really excited to be working on. Last year, at AWS re:Invent we announced a preview of a new capability for Aurora called Aurora Serverless. Today, I’m pleased to announce that Aurora Serverless for Aurora MySQL is generally available. Aurora Serverless is on-demand, auto-scaling, serverless Aurora. You don’t have to think about instances or scaling and you pay only for what you use.
This paradigm is great for applications with unpredictable load or infrequent demand. In production, you can save on costs by adjusting to scale based on actual load, in extremely granular increments – matching your demand curve almost perfectly. In development, you can save on costs by automatically pausing the cluster (scale to zero!) when it’s not in use. I’m excited to show you how this all works so let’s look at how we launch a Serverless Aurora cluster.