amazon-timestream-tools
tagger
amazon-timestream-tools | tagger | |
---|---|---|
2 | 3 | |
230 | 17 | |
1.3% | - | |
8.5 | 5.5 | |
6 days ago | over 3 years ago | |
Java | Python | |
MIT No Attribution | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
amazon-timestream-tools
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Integrating Amazon Timestream in you Amazon Managed Workflows for Apache Airflow v2.x
This is a simple demo application called the flink_connector is used to take sample load data and then stream it into the Timestream database. This project uses Amazon Kinesis to stream that data, so we need to create a stream which we can do using the following command:
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AWS open source news and updates No. 38
Store and Access Time Series Data at Any Scale with Amazon Timestream – Now Generally Available great post from Danilo Poccia that introduces Amazon Timestream. Amazon Timestream is a time series database that makes it easy to collect, store, and process trillions of time series events per day up to 1,000 times faster and at as little as to 1/10th the cost of a relational database. Time series are a very common data format that describes how things change over time. Some of the most common sources are industrial machines and IoT devices, IT infrastructure stacks (such as hardware, software, and networking components), and applications that share their results over time. Time series information is often integrated with open source tools, and in the past I have used tools like Grafana or Kibana to dashboard this data in a way that you can begin to use to provide actionable insights. In this post, Danilo shows how you can integrate this with open source dashboard tools like Grafana, and provides a bunch of open source tools to get you going. GitHub repository here.
tagger
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Reflecting on 2020
For me personally, it was my first year working full time as a developer and I enjoyed it a lot. I had the opportunity to learn and use Java libraries like jOOQ and Vavr. (if you use Java and haven't tried them, give them a shot! ). Furthermore, I wrote my first Python tool (Tagger) and summarized my experience here. Aside from all the pandemic-related issues this year was pretty exciting for me and I'm curious to read about your accomplishments in the comments!
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AWS open source news and updates No. 38
tagger is an open source tool from Tobias Haindl that will help you to stay on top of your AWS resource tagging. Tobias has also written this great post that shows you how you can use this tool to report/audit on your current tagging coverage, and then use it to update/apply tags to your resources. I think this is going to be a very popular tool, as good tagging hygiene is foundational to good Cloud governance and management.
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Lessons learned from writing my first python package
A short summary of lessons I learned from writing my first python packages: taggercore and taggercli. More infos about them can be found here:
What are some alternatives?
projen - A new generation of project generators [Moved to: https://github.com/projen/projen]
aws-workflows-on-github - Workflows for automation of AWS services setup from Github CI/CD
mic-cloudformation-hub
dynamoquery - Python AWS DynamoDB ORM
django-taggit - Simple tagging for django
fargate-game-servers - This repository contains an example solution on how to scale a fleet of game servers on AWS Fargate on Elastic Container Service and route players to game sessions using a Serverless backend. Game Server data is stored in ElastiCache Redis. All resources are deployed with Infrastructure as Code using CloudFormation, Serverless Application Model, Docker and bash/powershell scripts. By leveraging AWS Fargate for your game servers you don't need to manage the underlying virtual machines.
amictl - Because you need to control your AMIs
flaker - Faker for Snowflake!
kms-issuer - KMS issuer is a cert-manager Certificate Request controller that uses AWS KMS to sign the certificate request.