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<blockquote>The cloud is about how you do computing, not where you do computing.<br />&nbsp;<br />- Paul Maritz, former CEO of VMware</blockquote>
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This quote from Paul Maritz has been floating around for some time, but how relevant is it today? The first chapter of this guide examined what [[cloud computing]] actually is and how it has changed since the mid-2000s. We've gone from talking about how to implement web services at the turn of the century to advanced cloud services that are going "hybrid" or "serverless." Despite the massive shift in thinking, however, one aspect has always remained the same: you have to have internet access to use services provided on the web. In that sense, the "where" of the performed computing is important. In another sense, "where" matters, as we discovered in the second chapter on cloud standards, regulations, and security. Where the data is created and where it resides are important considerations for regulatory purposes, as are the methods used to secure the cloud, and who holds responsibility for them. "Where" is also a consideration when asking about your data in the cloud. Its location is relevant to not only risk assessments and [[risk management]] practices—as described in the third chapter—but also to where you do your work: the laboratory. In the fourth chapter we discussed how a laboratory and its unique [[workflow]]s, industries services, and affecting regulations shape decisions on cloud projects, while also addressing the benefits and drawbacks. In the fifth, we explained the concept of managed security services, which further abstracted the “how” and “where” of computing via the third party, who manages the security of your cloud and on-premises solutions remotely! And in the sixth chapter, we distilled much of the previous chapters down into how a [[laboratory]] chooses and implements one or more cloud solutions. Even there, "where" comes into play, as you ask the cloud service provider where their servers are located and where your data will be stored, while you ask yourself "where" you envision your lab with cloud computing solutions in the future.
==''Introduction to Quality and Quality Management Systems''==
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The goal of this short volume is to act as an introduction to the quality management system. It collects several articles related to quality, quality management, and associated systems.


When considering all this, however, Maritz was only partially off. There are many "wheres" to choosing and implementing a cloud-based service for your laboratory, including where you do your computing from, and even where your security is managed from. But cloud computing is certainly more about “how” you do computing in your laboratory. Cloud computing has proven to be at least a partially disruptive force over the years, changing organizations' IT departments, security planning, budgeting, and many other aspects, often for the better, though with its own complications. Laboratories can now host [[laboratory information management system]]s (LIMS) and [[electronic laboratory notebook]]s (ELNs) in the cloud and use [[infrastructure as a service]] (IaaS) to host serverless code that triggers when a cloud-connected instrument takes a reading and uploads the data. Laboratory users can now pull up information about not only automated lab procedures but also the security status of the equipment managing those procedures using a tablet while parked in the grocery store parking lot. Environmental sensors in Alaska can send data to a [[software as a service]] (SaaS) application hosted in Europe for processing, and then be accessed by an authorized user in Australia. Yes, the where of it all is related, but ultimately how the laboratory computes has now been changed with cloud computing.
;1. What is quality?
:''Key terms''
:[[Quality (business)|Quality]]
:[[Quality assurance]]
:[[Quality control]]
:''The rest''
:[[Data quality]]
:[[Information quality]]
:[[Nonconformity (quality)|Nonconformity]]
:[[Service quality]]
;2. Processes and improvement
:[[Business process]]
:[[Process capability]]
:[[Risk management]]
:[[Workflow]]
;3. Mechanisms for quality
:[[Acceptance testing]]
:[[Conformance testing]]
:[[Clinical quality management system]]
:[[Continual improvement process]]
:[[Corrective and preventive action]]
:[[Good manufacturing practice]]
:[[Malcolm Baldrige National Quality Improvement Act of 1987]]
:[[Quality management]]
:[[Quality management system]]
:[[Total quality management]]
;4. Quality standards
:[[ISO 9000]]
:[[ISO 13485]]
:[[ISO 14000|ISO 14001]]
:[[ISO 15189]]
:[[ISO/IEC 17025]]
:[[ISO/TS 16949]]
;5. Quality in software
:[[Software quality]]
:[[Software quality assurance]]
:[[Software quality management]]


That doesn't mean there are fewer considerations and complications with a shift to the cloud. The laboratory should approach any migration to or addition of cloud services with assertive yet balanced project planning that takes into account organizational goals, management buy-in, necessary stakeholders, scope and responsibility, existing IT and data structures, risk management and regulatory considerations, budgeting and IT requirements, provider vetting, training, maintenance, and security monitoring. Vetting providers and their services can be particularly time-consuming, but it remains a critical component of any cloud-based move in your lab. Given all these complications, laboratories shouldn't be afraid to seek additional help from knowledgeable consultants and managed security service providers with experience implementing and securing cloud in laboratories, particularly when in-house expertise is lacking.
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Hopefully this guide has been a boon to understanding cloud computing and all the considerations that come with it. Laboratories have much to consider when moving to or adding to their position in the cloud. The fact that you've made it through this document is a strong testament to your desire to ensure the success of a cloud project for your lab going forward. Good fortunes to you and your organization going forward.

Latest revision as of 19:46, 9 February 2022

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Introduction to Quality and Quality Management Systems

The goal of this short volume is to act as an introduction to the quality management system. It collects several articles related to quality, quality management, and associated systems.

1. What is quality?
Key terms
Quality
Quality assurance
Quality control
The rest
Data quality
Information quality
Nonconformity
Service quality
2. Processes and improvement
Business process
Process capability
Risk management
Workflow
3. Mechanisms for quality
Acceptance testing
Conformance testing
Clinical quality management system
Continual improvement process
Corrective and preventive action
Good manufacturing practice
Malcolm Baldrige National Quality Improvement Act of 1987
Quality management
Quality management system
Total quality management
4. Quality standards
ISO 9000
ISO 13485
ISO 14001
ISO 15189
ISO/IEC 17025
ISO/TS 16949
5. Quality in software
Software quality
Software quality assurance
Software quality management