Redhat Cloud Forms takes a bite into Cloud and Configuration Management

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.

Sounds perfect?

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

Redhat Insights – SecOps Automation running on Ansible Tower

Redhat remediation solution through Ansible Tower play books … dealing mostly with security risk assessment and mitigations (patches and more) https://www.redhat.com/en/about/press-releases/red-hat-delivers-analytics-driven-automation-latest-version-insights-ansible-integration

Dockerzing Docker

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If you feel overwhelmed by the breakdown of technologies Docker is built on, here is a cheat list to ease the pain 🙂

https://www.allcloud.io/blog/just-dockerize-it/

Serverless and AWS Lambda Tips and Tools

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Use services that allow integration of feature flags through out your application to dynamically test, activate or suspend features that (some) your users should be using. Here is one such service: https://github.com/launchdarkly/featureflags/blob/master/README.md
Track your external libraries through services that can alert of issues or vulnerabilities in those libraries – here is one such service called “Synk” – https://serverless.com/blog/4-ways-to-secure-prevent-vulnerabilities-in-serverless-applications/
Store all your external libraries as a local copy in your internal repositories so that your are not affected by mistakes or vulnerabilities that affect the public code repositories ( such as NPM public repository for java – see details here on how it badly affected many applications https://www.theregister.co.uk/AMP/2016/03/23/npm_left_pad_chaos/ )
Using a bigger memory tier could cause allocation of better CPU allocation which can bring your transaction processing speed from seconds to sub seconds
Monitor performance metrics of your application to determine when it changed and why
You must monitor for errors in your code. Don’t assume its working well
Using Lambda inside VPC requires attention to security groups same as for an EC2 instance
Make sure your Lambda function has the least privileges required in its IAM policy
AWS Toolkit for Eclipse: Support for Creating Maven Projects for AWS, Lambda, and Serverless Applications http://bit.ly/2muxucL

Ansible Tower 3.1 brings Workflows Log integration and Clustering

Ansible Tower 3.1 brings the new “Workflows” feature allowing you to hook Playbooks, set conditions in executing them and passing data from one Playbook to another.

Additionally Tower can now scale beyond a single instance allowing job processing through any one of the tower nodes in the cluster.

In Tower 3.1 you can easily direct all logs to a central log service such as ELK, Splunk, loggly or others.

More information here: https://www.ansible.com/blog/introducing-asible-tower-3-1

Pycharm seem to always more to it than you thought.. supporting Vagrant and Docker for remote debug is one of those thingies..
9 reasons you should be using PyCharm
What are your favorite add-ons for Pycharm?Ever used the paid version? Why?

AWS Athena says No so beautifully

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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