According to the 2016 State of DevOps Report by Puppet and DORA, the mean time to recover when a service incident occurs ranges from less than one hour for high IT performers to less than one day for medium and low IT performers. Put that in a real-world scenario: your OpenStack application and the data associated with it that spans multiple virtual machines failed (for one reason or another). Now you need to rebuild something you’ve already spent time developing. Are you—and your boss—OK with that rework taking hours to days? Or do you think you’d be wishing you fell in the range of high IT performers, and you could quickly recreate what you lost in less than one hour?

Now, take it a step further. What could you be doing with that time you now need to dedicate to rebuilding something? What will that rework take you away from? The next phase of your development? Lunch? Happy hour? Sleep? What price would you put on the personal cost to you?

Step 1 of 7

14%

Which of the following best describes how you currently monitor and manage systems across your hybrid cloud environment?(Required)

Multiple separate tools for different environments

Multiple separate tools for different monitoring and management functions

Single consolidated dashboard

Custom built monitoring and management solution

No full monitoring and management solution

Don’t know

How valuable would it be for your monitoring and management solution to incorporate predictive analytics to help you identify and address system issues that are critical and not waste time or effort working through all the data and “noise” that is not critical?(Required)

Extremely valuable

Moderately valuable

Somewhat valuable

Slightly valuable

Not valuable

How do you most typically address potential system issues BEFORE they impact your operations?(Required)

Automated workflows and playbooks to remediate potential issues as soon as they are detected

An orchestrated response process that leverages automation, AI, and human expertise to rapidly respond to potential issues

Advanced monitoring tools such as predictive analytics and anomaly detection to proactively identify and address potential issues

Respond to issues as they arise, using manual processes and troubleshooting techniques

A combination of automated remediation, orchestrated response, and/or proactive monitoring to address potential system issues

Don’t know

Other

What methods does your organization use to control and monitor cloud/IT spending?(Required)

Centralized procurement processes

Pre-approved budget thresholds

Automated cost monitoring tools

Department-level spending controls

Regular cost audits and reviews

Cloud cost optimization platform

Approval workflows for resource provisioning

Native financial operations tools provided by the cloud provider

No formal controls in place

Don’t know

Other

Please specify:

Which methods do you rely on most to detect security vulnerabilities in your systems?(Required)

Automated scanning tools

Manual assessments

Vendor notifications

Threat modeling (for early detection)

None of these

Don’t know

Other

Please specify:

What are the TWO most common ways you prioritize vulnerabilities to address within your environment?(Required)

Based on potential impact

Based on exploitability

Regulatory compliance requirements

Based on CVSS scores

Risk-based analysis of multiple factors

First-in-first-out approach

No formal prioritization process

Don’t know

How do you typically handle system updates and security patches?(Required)

Automated updates and patches

Manually review and apply updates and patches on a regular schedule

A combination of automation and manual review

Apply updates and patches on an as-needed basis.

Outsourced update and patch management

No defined process

Don’t know

Other

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The 2016 State of DevOps Report authors wanted to calculate the cost of excess rework per year for organizations. They created a formula to calculate the number:

Cost of excess rework = Technical staff size x average salary x benefits multiplier x percentage of technical staff time spent on excess rework

Here’s what they found:

• High performers have 11 percent excess rework
• Medium performers have 22 percent excess rework
• Low performers have 17 percent excess rework

At first glance, those numbers seem odd. Why would the low performers have less excess rework than the medium performers? The report clarified that by explaining “low performers spend less time on rework … because they report spending a greater proportion of time on new work. We believe this greater amount of new work could be occurring at the expense of rework, thus racking up technical debt.”

It’s clear all organizations have some amount of rework as a result of a failure of some kind. The question is, What is the cost of that rework? Let’s take a look at the results of the study.

For the most part, the simple answer is that rework will likely cost your organization millions (unless it’s costing you billions). It’s just a matter of how many millions.

We often get asked why it’s necessary for OpenStack environments to have a data protection strategy and a backup solution. The conventional (but wrong) thinking is that virtualization can take the place of data recovery. Frankly, the answer to why is contained within those numbers above. If you don’t have a backup and recovery solution for your OpenStack development efforts, are you willing to spend money and resources on reworking the lost data? And if you are, how many millions are you willing to spend on it? Let me remind you that you are trying to recover to a point in -time … persistent data included. If you say, “If you built your cloud appropriately, this shouldn’t be an issue ….” Madame or Sir, if your virtualized cloud has that kind of resiliency, then I would like to work for you.