Availability

In reliability engineering, the term availability has the following meanings:

The degree to which a system, subsystem or equipment is in a specified operable and committable state at the start of a mission, when the mission is called for at an unknown, i.e. a random, time.
The probability that an item will operate satisfactorily at a given point in time when used under stated conditions in an ideal support environment.

Normally high availability systems might be specified as 99.98%, 99.999% or 99.9996%. Representation The simplest representation of availability (A) is a ratio of the expected value of the uptime of a system to the aggregate of the expected values of up and down time (that results in the "total amount of time" C of the observation window) : A = \frac{E[\mathrm{uptime}]}{E[\mathrm{uptime}]+E[\mathrm{downtime}]} = \frac{E[\mathrm{uptime}]}{C} Another equation for availability (A) is a ratio of the Mean Time To Failure (MTTF) and Mean Time B

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Experimental Validation of the Suitability of Virtualization-Based Replication for Fault Tolerance in Real-Time Control of Electric Grids

Jean-Yves Le Boudec, Jalal Mostafa, Wajeb Saab, Seyed Alireza Sanaee Kohroudi

Real-time control systems (RTCSs) perform complex control and require low response times. They typically use third-party software libraries and are deployed on generic hardware, which suffer from delay faults that can cause serious damage. To improve availability and latency, the controllers in RTCSs are replicated on physical nodes. As physical replication is expensive, we study the alternative of exploiting virtualization technology to run multiple virtual replicas on the same physical node. As virtual replicas share the same resources, the delay faults they experience might be correlated, which would make such a replication method unsuitable. We conduct several experiments with an RTCS for electric grids, with multiple virtual replicas of its controller. We find that although the delay of a virtual machine is higher than of a physical machine, the correlation between high delays among the virtual replicas is insignificant, causing an overall improved availability.We conclude that virtual replication is indeed applicable to certain RTCSs, as it can improve reliability without added cost.

2018

Improving availability with recursive microreboots: a soft-state system case study

George Candea

Even after decades of software engineering research, complex computer systems still fail. This paper makes the case for increasing research emphasis on dependability and, specifically, on improving availability by reducing time-to-recover. All software fails at some point, so systems must be able to recover from failures. Recovery itself can fail too, so systems must know how to intelligently retry their recovery. We present here a recursive approach, in which a minimal subset of components is recovered first; if that does not work, progressively larger subsets are recovered. Our domain of interest is Internet services; these systems experience primarily transient or intermittent failures that can typically be resolved by rebooting. Conceding that failure-free software continues eluding us for years to come, we undertake a systematic investigation of fine grain component-level restarts, microreboots, as high availability medicine. Building and maintaining an accurate model of large Internet systems is nearly impossible, due to their scale and constantly evolving nature, so we take an application-generic approach, that relies on empirical observations to manage recovery. We apply recursive microreboots to Mercury, a commercial off-the-shelf (COTS)-based satellite ground station that is based on an Internet service platform. Mercury has been in successful operation for over 3 years. From our experience with Mercury, we draw design guidelines and lessons for the application of recursive microreboots to other software systems. We also present a set of guidelines for building systems amenable to recursive reboots, known as "crash-only software systems"

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Reducing recovery time in a small recursively restartable system

George Candea, Pranav Garg

We present ideas on how to structure software systems for high availability by considering MTTR/MTTF characteristics of components in addition to the traditional criteria, such as functionality or state sharing. Recursive restartability (RR), a recently proposed technique for achieving high availability, exploits partial restarts at various levels within complex software infrastructures to recover from transient failures and rejuvenate software components. Here we refine the original proposal and apply the RR philosophy to Mercury, a COTS-based satellite ground station that has been in operation for over 2 years. We develop three techniques for transforming component group boundaries such that time-to-recover is reduced, hence increasing system availability. We also further RR by defining the notions of an oracle, restart group and restart policy, while showing how to reason about system properties in terms of restart groups. From our experience with applying RR to Mercury, we draw design guidelines and lessons for the systematic application of recursive restartability to other software systems amenable to RR

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