A Blog of the ZHAW Zurich University of Applied Sciences
In part 3 of our article series “Dependability Modeling on OpenStack” we have discussed that we should run Chaos Monkey tests on an OpenStack HA installation and then collect data about the impact of the attack. While we did say that we want to collect data about the implemented OpenStack HA architecture, we were not […]
In this part of the Dependability Modeling article series we explain how a test framework on an OpenStack architecture can be established. The test procedure has 4 steps: in a first step, we implement the OpenStack environment following the planned system architecture. In the second step we calculate the probabilities of component outages during a given timeframe (e. g. 1 year). Then we start a Chaos Monkey script which “attacks” (randomly disables) the components of the system environment using the calculated probabilities as a base for the attack. As a last step we measure the impact of the Chaos Monkey attack according to the table of failure impact sizes we created in part 2. The impact of the attack should be stored as dataset in a database. Steps 1-4 form one test run. Multiple test runs can be performed on multiple architectures to create a empirical data which allows us to rate the different OpenStack architectures according to their availability.
In a former article we spoke about testing High Availability in OpenStack with the Chaos Monkey. While the Chaos Monkey is a great tool to test what happens if some system components fail, it does not reveal anything about the general strengths and weaknesses of different system architectures. In order to determine if an architecture with 2 redundant controller nodes and 2 compute nodes offers a higher availability level than an architecture with 3 compute nodes and only 1 controller node, a framework for testing different architectures is required. The “Dependability Modeling Framework” seems to be a great opportunity to evaluate different system architectures on their ability to achieve availability levels required by end users.
In his excellent article in Linux Technical Review #04 Jens-Christoph Brendel proposes a new way how to implement High Availability (HA) in current IT architectures. According to Bendel, modern IT architectures continually gain in complexity. This fact makes it difficult to guarantee availability on a certain level. Nevertheless High Availability is not merely a competitional advantage: for many companies keeping availability levels above 99,999 % per year is a matter of existence. Therefore a few systematic steps should help in planning and implementing high availability in your IT environment. This article shows a possible strategy on how to plan High Availability in the Mobile Cloud environment.