If you are in IT Ops or DevOps, hardly a day goes by without someone mentioning AIOps. There are a few who think AIOps can replace IT Ops tools today. Others debate this, saying that AIOps is still a nascent field, and it will take a few more years until we see a full-fledged AIOps platform for IT operations management. But there’s always been a lot of confusion on how AIOps really works.
In our previous blog post, we discussed how we are approaching an important inflection point in the cloud migration timeline. Certain legacy applications will remain on owned infrastructure for the foreseeable future, but the scale and agility offered by cloud platforms offers competitive and operational advantages that most organizations cannot ignore. As cloud adoption became mainstream, many enterprises saw fewer objections to migrating their infrastructure to cloud. One Gartner report finds that many objections to cloud adoption are gradually becoming discredited and organizations are leaving behind the cloud experimentation stage and looking for strategic relationships with cloud technology providers.
A recent Gartner report states: “Organizations with a cross-discipline cloud strategy are more likely to find success in cloud initiatives and recognize the full benefits of cloud.”
Every organization looking at using network function virtualization (NFV) needs to consider monitoring. If you’re going to deploy a service, it’s really important that you know if it’s working — and what’s wrong if it’s not. That’s why monitoring — often called assurance — is a key part of every request for information, every request for proposal, every proof of concept, every NFV deal.
Here’s the challenge: the economics of on-premises monitoring are all wrong for the NFV business cycle.
In the article “Data Masking as Part of Your GDPR Compliant Security Posture” over on DEVOPSdigest, Zenoss talks about how to mitigate your application’s level of compliance by employing data masking or other pseudonymization techniques of personally identifiable information (PII) like names and email addresses. Zenoss suggests giving it a quick read to better understand how that strategy relates to GDPR.
IT organizations often find themselves monitoring effectively at small scale, but few have implemented solutions with the flexibility and capability to operate in elastically scaling environments.