Cloud Architecture Revolution

The introduction of cloud technologies is not a simple evolution of existing ones, but a real revolution.  Like all revolutions, it changes the points of views and redefines all the meanings. Nothing is as before.  This post wants to analyze some key words and concepts, usually used in traditional architectures, redefining them according the standpoint of the cloud.  Understanding the meaning of new words is crucial to grasp the essence of a pure cloud architecture.

<<There is no greater impediment to the advancement of knowledge than the ambiguity of words.>>

THOMAS REID, Essays on the Intellectual Powers of Man

Nowadays, it is required to challenge the limits of traditional architectures that go beyond the normal concepts of scalability and support millions of users (What's Up 500 Million) billions of transactions per day (Salesforce 1.3 billion), five 9s of availability (99.999 AOL).  I wish all of you the success of the examples cited above, but do not think that it is completely impossible to reach mind-boggling numbers. Using cloud technology, everyone can create a service with a little investment and immediately have a world stage.  If successful, the architecture must be able to scale appropriately.

Using the same design criteria or move the current configuration to the cloud simply does not work and it could reveal unpleasant surprises.

Infrastructure - commodity HW instead of high-end HW

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Ask HS: Design and Implementation of scalable services?

We have written agents deployed/distributed across the network. Agents sends data every 15 Secs may be even 5 secs. Working on a service/system to which all agent can post data/tuples with marginal payload. Upto 5% drop rate is acceptable. Ultimately the data will be segregated and stored into DBMS System (currently we are using MSQL).

Question(s) I am looking for answer

1. Client/Server Communication: Agent(s) can post data. Status of sending data is not that important. But there is a remote where Agent(s) to be notified if the server side system generates an event based on the data sent.

- Lot of advices from internet suggests using Message Bus (ActiveMQ) for async communication. Multicast and UDP are the alternatives.

2. Persistence: After some evaluation data to be stored in DBMS System.

- End of processing data is an aggregated record for which MySql looks scalable. But on the volume of data is exponential. Considering HBase as an option.

Looking if there are any alternatives for above two scenarios and get expert advice.

10 Things You Should Know About AWS

Authored by Chris Fregly:  Former Netflix Streaming Platform Engineer, AWS Certified Solution Architect and Purveyor of fluxcapacitor.com.

Ahead of the upcoming 2nd annual re:Invent conference, inspired by Simone Brunozzi’s recent presentation at an AWS Meetup in San Francisco, and collected from a few of my recent Fluxcapacitor.com consulting engagements, I’ve compiled a list of 10 useful time and clock-tick saving tips about AWS.

1) Query AWS resource metadata

 

Can’t remember the EBS-Optimized IO throughput of your c1.xlarge cluster?  How about the size limit of an S3 object on a single PUT?  awsnow.info is the answer to all of your AWS-resource metadata questions.  Interested in integrating awsnow.info with your application?  You’re in luck.  There’s now a REST API, as well!

Note:  These are default soft limits and will vary by account.

2) Tame your S3 buckets

 

Delete an entire S3 bucket with a single CLI command:  

aws s3 rb s3://<bucket-name> --force

Recursively copy a local directory to S3:

aws s3 cp <local-dir-name> s3://<bucket-name> --region <region-name> --recursive

3) Understand AWS cross-region dependencies

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