The Doppler Quarterly Special Edition 2019 | Page 73

By using cloud-based data services to fulfill persistent data storage needs for contain-
ers, the major drawbacks of “data in the container” (lack of independent scaling), Docker
volumes (tied to specific machines), or creating “data containers” (limited flexibility) are
avoided. By using a PaaS data store, the cloud provider manages the operational aspects
of data protection and scalability, and ensures containers can focus on application logic,
presentation and user service delivery. AWS’ Elastic File System, as an example, enables
a shared, mountable, automatically
scalable data environment well-
suited for persisting various types of
container data.
When used incor-
rectly, containers
can become another
bloated virtual
machine replace-
ment with little to
no value add.
Containers can be used as an effec-
tive way to package applications
for rapid deployment, upgrades
and lifecycle management. How-
ever, when used incorrectly, con-
tainers can become another
bloated virtual machine replace-
ment with little to no value-add. It
is important that as part of a con-
tainer implementation strategy, the
persistence of data and the movement of data is put in the proper functional areas to
facilitate scalability and operations. By leveraging PaaS services for communication and
data stores, containers can be focused on the execution of business logic while ensuring
robust persistent connections and interactions with the necessary data.
Written by Joey Jablonski, former CTO of Cloud Technology Partners (CTP)
and currently VP of Data Engineering & Analytics at iHeartMedia. and Neal Matthews,
Principal Architect, Cloud Technology Partners (CTP)
SPECIAL EDITION 2019 | THE DOPPLER | 71