The latest Cloud Forms from Redhat targets the easy use of AWS Cloud Formation and OpenStack Heat templates import, customization, creation, deployment.
It offers a service catalog of Cloud resources setups including load balancers, servers and more.
It also makes it easier to customize your Cloud templates by offering forms and variables per the templates you pick.
Then it triggers Ansible Tower for in depth deployment and configuration management of your instances.
The Cloud Management portal shows you your Cloud components, instances, operating systems and applications including general Linux and Windows as well.
Maybe it sounds like an enterprise vendor trying to grab it all..and maybe this time this vendor actually makes it..
I still would like to see TerraForm there as well..
Anyway there’s the video
If you feel overwhelmed by the breakdown of technologies Docker is built on, here is a cheat list to ease the pain 🙂
Amazon AWS Athena allows you run ANSI SQL directly against your S3 Buckets supporting a multitude of file formats and data formats
Here are my insights taken from a comprehensive YouTube session lead by Abhishek Sinha
- No ETL needed
- No Servers or instances
- No warmup required
- No data load before querying
- No need for DRP – it’s multi AZ
Uses Presto (in memory data distributed data query engine) and HIVE (DDL table creation to reference to your S3 data)
You pay for the amount of data scanned, so you can optimize the performance as well as cost, if you:
- Compress your data
- Store it in a columned format
- Partition it
- Convert it to Parquet / ORC format
Querying in Athena:
- You can query Athena via the AWS Console (dozens of queries can run in parallel) or using any JDBC enabled tool such as SQL Workbench
- You can stream Athena queries results into S3 or AWS Quick Sight (Spice)
- Creating a table for query in Athena is merely writing a schema that you later refer to
- Table Schema you create for queries are fully managed and Highly Available
- Queries will act as the route to the data so every time you execute the Query it re-evaluates everything in the relevant buckets
- To create a partition you specify a key value and then a bucket and a prefix that points to the data that correlates with this partition
Just note that Athena serves specific use cases (such as non urgent ad-hoc queries) where other Big Data tools are used to fulfill other needs – AWS Redshift is more aimed at quickest query times for large amounts of unstructured data, where AWS Kinesis Analytics is aimed at queries of rapidly streaming data.
Want to learn more on Big Data and AWS? Visit http://allcloud.io