From 30 November to 18 December, AWS re:Invent 2020 is running 100% online. Between the conferences, the leadership sessions and the workshops, there has been a plethora of announcements and new services presented. Did you miss them?!Here are the essentials!
TABLE OF CONTENTS
- Pre-re:Invent 2020
- Re:invent 2020 – Week 1 – 30 Nov. – 4 Dec.
- Re:invent 2020 – Week 2 – 7 to 11 Dec.
- Re:invent 2020 – Week 3 – 14 to 18 Dec.
Pre-re:Invent 2020
AWS Network Firewall, a new managed high-availability network firewall service for your Virtual Private Cloud (VPC)
It makes it easy to deploy and manage intrusion inspection, prevention and detection. It scales automatically with your traffic, guaranteeing high availability with no additional customer investment in security infrastructure.
With this service, you can implement custom rules to stop your VPCs reaching unauthorised domains, to block IP addresses or to identify malicious activity. AWS Network Firewall makes firewall activity visible in real time through CloudWatch metrics.
https://amzn.to/3pF0igJ
Amazon S3 Storage Lens, a storage analytics solution for the Cloud
It gives you visibility over object storage across your organisation.
This tool combines several data sets to help you spot anomalies, identify the cost savings to be made and apply data protection best practices.
Through its dashboards, you can easily see the actionable recommendations.
https://amzn.to/3ffw3Z5
AWS Backup, cross-account backup
With AWS Backup, you can back up across several AWS accounts on demand or automatically as part of a scheduled backup plan. Cross-account backup is valuable.
This documentation explains step by step how to do it with AWSBackup (how to create a backup vault, assign a customer master key…).
https://amzn.to/3kKUIpp
Network Load Balancer now supports Internet Protocol version 6 (IPv6)
With this new feature, you can support client IPv6 connections without changing your application. Your Network Load Balancer transparently converts IPv6 traffic into IPv4 traffic before routing it to the backend targets.
https://amzn.to/2Jfpyt8
Version 2 of the Amazon Athena query engine is now available
This new version brings several performance improvements and new features, such as:
- federated queries,
- support for schema evolution,
- the additional geospatial functions,
- support for reading nested schemas in order to reduce costs
- and the performance improvements for JOIN, ORDER BY and AGGREGATE operations.
https://amzn.to/3makJjp
You can now use a SQL-compatible query language to query, insert, update and delete table data in Amazon DynamoDB
PartiQL is a SQL-compatible query language. It makes it easier to interact with DynamoDB and to run queries in the AWS Management Console.
https://amzn.to/3m7cV1W
Modules for AWS CloudFormation
To simplify how you manage resources through AWS CloudFormation, you can now use modules.
Modules are reusable building blocks. They simplify the use of the specific resources you need while keeping resource configurations aligned with organisational best practices.
https://amzn.to/3m8B349
CodeSigning
With this service, you can now make sure that only approved and verified code is deployed in your AWSLambda functions.
Code signing is a technique used to confirm that code comes from a trusted publisher.
Code Signing helps administrators ensure that only signed code packages from trusted publishers run in their Lambda functions
and that the code has not been altered or tampered with since signing.
https://amzn.to/3lgP6DT
Re:invent 2020 – Week 1 – 30 Nov. – 4 Dec.
Amazon EC2 instance for macOS
We can now use Amazon EC2 Mac instances to build and test macOS, iOS, ipadOS, tvOS and watchOS applications
These instances have an 8th-generation 6-core Intel Core i7 (Coffee Lake) processor.
On the network side, they run in a Virtual Private Cloud (VPC).
https://amzn.to/3lq0Q72
AWS Lambda now supports up to 10 GB of memory
We can now allocate up to 10 GB of memory to a Lambda function.
That is an increase of more than 3 times over the previous limits.
Lambda allocates CPU and other resources linearly in proportion to the amount of memory configured. This means we can now have access to up to 6 virtual processors in each execution environment.
https://amzn.to/37vOuFc
AWS Lambda moves duration billing granularity from 100 ms to 1 ms
Good news for our wallets! AWS Lambda is reducing the billing granularity for Lambda function duration from 100 ms to 1 ms. This will lower the price of most Lambda functions, and even more so of short-duration functions.
Their compute duration will therefore be billed in 1 ms increments instead of being rounded up to the nearest 100 ms increment per invocation.
https://amzn.to/3mzCN6N
Preview of the next version of Amazon Aurora Serverless
This new version offers the ability to scale database workloads to hundreds of thousands of transactions in a fraction of a second.
https://amzn.to/33SGhKD
AWS Lambda now supports container images as a packaging format
With the Container Image Support service, we can now deploy AWS Lambda functions as container images with a maximum capacity of 10 GB.
https://amzn.to/3qvJNnV
Introducing Amazon QuickSight Q: ask questions about your data and get answers in seconds
Until now, QuickSight allowed companies to create and analyse visualisations of their customer data in minutes.
This service’s new “Amazon QuickSight Q” feature, based on machine learning, uses natural language processing to answer your company’s questions instantly. It is optimised to understand the business language you use day to day in your work.
Users can therefore simply type in questions such as “What is our year-on-year growth rate?” and get an instant answer in the form of a visualisation.
https://amzn.to/3lzm2HL
Amazon Monitron, a simple, cost-effective service for predictive maintenance
This new service offers an end-to-end machine #monitoring system to detect anomalies and abnormal behaviour.
Based on machine learning, it can in particular predict when industrial equipment will need maintenance
https://amzn.to/39ALPNc
Amazon CodeGuru Reviewer announces security detectors to help improve code security
Amazon CodeGuru Reviewer helps us identify security risks by looking for critical issues and putting forward recommendations to fix them.
It is an additional feature of CodeGuru. As a reminder: AmazonCodeGuru is a machine learning based development tool that provides intelligent recommendations to improve code quality and identify the most expensive lines of code in #applications.
https://amzn.to/3lEwUE1
Amazon EKS now supports the creation and management of Amazon Elastic Compute Cloud (Amazon EC2) Spot Instances
This lets you take advantage of the considerable savings that Spot Instances offer for workloads running in your Kubernetes cluster.
https://amzn.to/3g2y5fv
Introducing new Amazon EBS general purpose volumes, GP3
Amazon Elastic Block Store (EBS) is a high-performance, easy-to-use storage service designed for use with Amazon EC2 instances.
On this service, we can now use a new EBS SSD volume type, gp3.
gp3 is ideal for applications that need high performance at low cost, such as MySQL, Cassandra, virtual desktops…
https://amzn.to/36z2lLI
AWS Amplify announces a new admin user interface
Discover its new features
https://amzn.to/3lBSh92
Re:invent 2020 – Week 2 – 7 to 11 Dec.
Introducing Amazon SageMaker Pipelines, the first CI / CD service purpose-built for machine learning
A word to developers and machinelearning scientists: AWS is adding another building block to Amazon SageMaker with Amazon SageMaker Pipelines. SageMaker Pipelines is the first CI/CD service purpose-built for machine learning. It makes it possible to automate and orchestrate #ML workflows.
It also offers (and this is no small thing!) DevOps best practices applied to machine learning, MLOps.
https://amzn.to/373uT09
Introducing Amazon HealthLake
With Amazon HealthLake, AWS takes one more step into the healthcare sector. Its aim: to help professionals make effective use of all the data to make the best care decisions.
Doctors, health insurance, pharmacies… collect quantities of information about patients (history, clinical observations, diagnoses, medication). Today, this data is spread across a multitude of systems (electronic medical records, laboratory systems, etc.) and exists in dozens of incompatible formats. Not simple, then.
HealthLake removes this heavy task of organising the data on each patient. It aggregates this information from different silos and formats into a centralised AWS data lake. It uses machine learning models to normalise this data and automatically extract meaningful medical information. Enough to diagnose better.
https://amzn.to/33YLkco
Amazon Kendra adds a #GoogleDrive connector
The machine learning based intelligent search service Amazon Kendra now adds a #GoogleDrive connector.
With AWS, there is no border. You can go and fetch your data anywhere! The aim: stay open!
https://amzn.to/2VZkDjh
Introducing Amazon SageMaker Data Wrangler
Most #ML models take a lot of time to aggregate data. Well, that time is now over thanks to a new service we discovered last week.
Amazon SageMaker Data Wrangler cuts this time from several weeks to a few minutes. It simplifies the data preparation and feature engineering process.
Using its selection tool, we can choose the data we want from various sources #AmazonS3, #Athena, #Redshift, #LakeFormation… and import it in a single click.
https://amzn.to/3m2lB91
A closer look at compliance with AWS Audit Manager
The new AWS Audit Manager service helps us continuously audit our use of #AWS to know whether our systems comply with regulations and standards: #gdpr, #security, #onlinepayment.
https://amzn.to/3gvB28J
AWS Security Hub integrates with AWS Audit Manager
Security Hub gives us a complete view of our security alerts. It brings together our security alerts or findings from several AWS services, such as #GuardDuty, #Inspector and #Macie…
https://amzn.to/33Xqc6a
Introducing Amazon Redshift ML
You can now create, train and deploy machine learning models in Amazon Redshift using SQL. This is possible with Amazon Redshift ML.
This new service has many advantages:
- It lets you create and train ML models with simple SQL commands without having to learn external tools.
- It offers the flexibility to use automatic algorithm selection.
- It lets #ML experts such as #datascientists select algorithms such as #XGBoost and specify #hyperparameters and #preprocessors.
https://amzn.to/2K4IoDT
3 new features for CodeGuru
Python support > You can now use CodeGuru to improve applications written in Python
Security detectors for CodeGuru Reviewer > To identify security vulnerabilities and check security best practices in your Java code
Memory profiling for CodeGuru Profiler > To optimise the way your application uses memory.
https://amzn.to/37Rz0vr
Re:invent 2020 – Week 3 – 14 to 18 Dec.
AWS CloudShell
AWS CloudShell gives command-line access to #AWS resources and tools directly from a browser.
With CloudShell, we can quickly run scripts with the AWS Command Line Interface (AWS CLI), experiment with AWS service APIs using the AWS SDKs…
https://amzn.to/2KdzfZZ
Amazon Managed Service for Grafana
This service makes it easy to create Grafana workspaces on demand, to visualise and analyse your data coming from multiple sources.
Grafana is one of the most popular open source technologies used to create observability dashboards for applications.
https://amzn.to/3ns4hvJ
For more on re:Invent, go to:
What is AWS Re:invent?
AWS re:Invent is an event organised by Amazon Web Services (AWS) for the global Cloud computing community. The event includes announcements, launches, sessions and more.
When is AWS re:Invent 2020 held?
AWS re:Invent 2020 runs over three weeks, from 30 November to 18 December 2020. See the agenda: https://reinvent.awsevents.com/agenda/