At a recent Lean project report out to stakeholders, a piece of analysis was presented which showed the quantity of metrics being captured, in various areas, at different organizational levels. IBM’s Watson had been used to generate the chart, and it told an interesting story. But that story needed some translating.

‘Look at all those metrics under ‘Managers”, said one Director, with enthusiasm. ‘Seems like they’re looking at a lot of different performance measures for their people’.
‘Yes,’ said the Lean Coach, ‘but is that a good thing in itself?’
Another Director chimed in, ‘Well, when I look at how few metrics are being captured on timeliness I wonder how anyone knows how they’re doing.’

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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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As an IBMer, and Six Sigma Blackbelt, I’m pre-disposed towards data. Information can be power. But with too much being reported, it can be hard to see the wood from the trees. Performance metrics are intended to allow teams and leaders to improve their performance. For many of those people, reading charts and interpreting data may not be a core skill and it certainly isn’t how the organization wants them to spend their time. So those teams generating masses of performance metrics may not be doing themselves, or their leadership, a service.

The key is to identify the critical few metrics. Ideally leading indicators of performance issues, rather than lagging ones. Leaving aside areas like SLA adherence and budget management to those responsible for governing them, these are the handful of metrics I would suggest a DevOps team needs to watch on a daily basis:

• Number of bug fixes for top 20 systems
• Number of critical issues, average time to close and longest time to close – looking just at the average may mask longer running issues
• WIP: number of projects in each phase of the SDLC
• Customer feedback for top 5 systems – preferably actual user feedback; failing that whatever you can infer from app usage. Top 5 systems may change over time as you launch new functionality or as usage changes according to the business calendar.
• Percentage of projects who deliver 100% of their agreed scope
• Core application availability – actual availability to users, not SLA adherence

What do you think? What do you measure?