Weekly CloudNews: Why inadequate automation of onboarding and offboarding results in security risks and data loss

Welcome to this week’s edition of CloudBolt’s Weekly CloudNews!

Why inadequate automation of onboarding and offboarding results in security risks and data loss

Taryn Plumb, VentureBeat, November 16, 2022

“The pandemic accelerated hybrid work and cloud adoption — but it also ignited the Great Resignation. By the end of 2021, 69 million Americans ‘separated’ from their jobs. As more organizations are increasing their use of technology, they have fewer people to manage it. All of this has placed a strain on enterprise onboarding and offboarding capabilities. Still, businesses struggle to automate this process, resulting in critical loss of technology assets and unauthorized access, according to a new report from Oomnitza. A survey by McKinsey and Company, found that 53% of employers were experiencing greater voluntary turnover in 2021 than in previous years. The firm also reported that 51% of employers expect to cut jobs in 2022.

“At the same time, mid to large-sized companies have 187 SaaS applications on average, according to Okta’s Businesses at Work 2022 Report Increased IT demands and growing workforce turnover rates and the data privacy, security and financial risks that accompany them make automating secure offboarding processes a strategic business imperative, said Oomnitza cofounder, Ramin Ettehad. The 2022 State of Onboarding Process Automation Report, for which the research was conducted by YouGov, found that nearly half of IT leaders are doubtful about their organization’s ability to effectively automate the onboarding and offboarding of workers. Forty-nine percent of 213 senior-level IT professionals reported the loss of at least 5% of their technology assets due to workers leaving the company; while 27% lost more than 10%; and one fifth lost between 10% and 20%.” READ MORE

What observability means for cloud operations

David Linthicum, InfoWorld, November 11, 2022

“Observability seems to be mostly defined as the ability to determine key insights from a great deal of data. Observability as related to cloud operations normally uses data that’s being extracted from running systems. We use this data not only to determine if something is going wrong, but to figure out why and how to fix it. What’s the value of observability as a concept, and how is it of value to cloudops? Trends: What patterns occur over time and what do they mean for future behavior? Analyses: What does the data mean, and are there any insights we can draw from it? Observability provides the ability to analyze what the data means. Insights: What can we understand from the data, or what do we need to understand?

“Tracking: Can we monitor systems activity data in real time or near real time and leverage this data to find, diagnose, and fix issues ongoing? Learning: Learning systems look at massive amounts of data to find trends and insights and then use that data to learn about emerging patterns and what they mean. Alerting: What issues need to be dealt with in a timely manner? Actions: What happens because of an alert? Complex actions may involve dozens of actions taken by humans and thousands of automated actions to carry out immediate self-healing operations. Observability allows you to manage and monitor modern systems and applications built to run at faster velocities with more agile features. It is no longer good enough to deploy applications and then bolt on monitoring and management tools. The new tools must do so much more than simply monitor operations data.” READ MORE

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