Falling in love with Kate Upton is easy but more easier is to be
swept off your feet by information lifecycle management (ILM) in the
Amazon Web Services (AWS). Simple, easily-configurable, fast, reliable,
cost effective and proven are the words which describe it.
Pythian has been involved with ILM for a long time. With various flavors of databases and systems, Pythian has been overseeing creation, alteration, and flow of data for a long time until it becomes obsolete. That is why AWS's ILM resonates perfectly well with Pythian's expertise.
Amazon S3 is an object store for short term storage, whereas Amazon Glacier is their cloud archiving offering or storage for long term. Rules can be defined on the information to specify and automate its lifecycle.
Following screenshot shows the rules being configured on objects from S3 bucket to Glacier and then permanent deletion. 90 days after creation if an object, it will be moved to Glacier, and then after 1 year, it will be permanently deleted. Look at the graphical representation of lifecycle as how intuitive it is.
Pythian has been involved with ILM for a long time. With various flavors of databases and systems, Pythian has been overseeing creation, alteration, and flow of data for a long time until it becomes obsolete. That is why AWS's ILM resonates perfectly well with Pythian's expertise.
Amazon S3 is an object store for short term storage, whereas Amazon Glacier is their cloud archiving offering or storage for long term. Rules can be defined on the information to specify and automate its lifecycle.
Following screenshot shows the rules being configured on objects from S3 bucket to Glacier and then permanent deletion. 90 days after creation if an object, it will be moved to Glacier, and then after 1 year, it will be permanently deleted. Look at the graphical representation of lifecycle as how intuitive it is.
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