(Note: This blog is an excerpt from Tom Petrocelli’s current report: Infrastructure as Code: Managing Hybrid Infrastructure at Scale) Key Stakeholders: CIO, Sysops, System Admins, Network Admins, Storage Admins, IT Operations Managers Why It Matters: New software architectures continue to add complexity to it infrastructure management. At the same time, organizations expect IT to deploy…
This approach offers advantages over the traditional approach of one language, one VM. For example, any program that is compiled for GraalVM can share libraries with other programs that is likewise compiled. Developers can write in different languages but still maintain interoperability and code reuse across them all. This also allows developers to continue to use code written in “older languages” while migrating to a new one. Similarly, it allows the continued used of majority language, such as Java, while leveraging languages that are built for specific purposes, such as R. Another advantage of GraalVM is ubiquity. One VM for multiple needs means fewer VMs to provision and update across IT servers and containers. That can be a serious time saver and makes maintaining large and complex systems a bit easier.
Blockchain looks to be one of those up and coming technologies that is constantly being talked about. Many of the largest IT companies – IBM, Microsoft, and Oracle to name few – plus a not-for-profit or two are heavily promoting blockchain. Clearly, there is intense interest, much of it fueled by exotic-sounding cryptocurrencies such as Bitcoin and Ethereum. The big question I get asked – and analysts are supposed to be able to answer the big questions – is “What can I use blockchain for?”
I have a new paper out called “Providing a Rapid Response to Meltdown and Spectre for Hybrid IT.” It’s sponsored by CloudPassage, and the paper is free from them.
This paper is designed to help key stakeholders mitigate the risk of Meltdown and Spectre, which will be especially difficult in hybrid or mixed systems.
There are billions of PCs and mobile devices affected by Meltdown and Spectre. That’s a big problem for OS vendors. For enterprise IT, there is also the need to deal with hundreds of millions of host servers and the virtual machines running on them. Meltdown and Spectre highlight just how difficult it is to update and patch hybrid systems with hosts, virtual machines, containers, and cloud servers in the mix. Don’t despair! There are solutions.
Take action by downloading my paper, underwritten by CloudPassage: “Providing a Rapid Response to Meltdown and Spectre for Hybrid IT.”
API management is a necessary but boring practice. As developers make use of a mix of public cloud, purchased or open source libraries, and homegrown services, the number of APIs used by developers quickly renders pouring through documentation impractical.
Microservices, usually accessed via RESTFul APIs, cause API calls to rapidly proliferate. Even modest-sized microservices-based systems experience API overload quickly. Agile development can exacerbate the problem of understanding and using APIs. The rapid pace of Agile, especially Scrum, leaves little time for proper documentation of APIs. Documentation often takes a back seat to continuous deployment.
As the year comes to a close, I have had the opportunity to reflect on what has transpired in 2017 and look ahead to 2018. Some of my recent thoughts on 2017 have been published in:
- InformationWeek: AWS Ignites Debate About the Death of IT Ops
- CMSWire: Will Microsoft Graph Deliver on the Promises of the Social Graph?
- DevOps.com: DevOps Gets More Exciting in 2018
These articles provide a peek ahead at emerging 2018 trends.
In the two areas I cover, collaboration and DevOps/Developer Trends, I plan to continue to look at:
• The continued transformation of the collaboration market. [Click to Tweet] I am expecting a “mass extinction event” of products in this space. That doesn’t mean the collaboration market will evaporate. Instead, I am looking for niche products that address specific collaboration segments to thrive while a handful of large collaboration players will consume the general market.
• The emergence of NoOps, for No Operations, in the mid-market. [Click to Tweet] The Amazon push to serverless products is a bellwether of the upcoming move toward cloud vendor operations supplanting company IT sysops.
• 2018 will be the year of the container.[Click to Tweet] Containers have been growing in popularity over the past several years but 2018 will be the year when they become truly mass market. The growth in the ecosystem, especially the widespread availability of cloud Kubernetes services, will make containers more palatable to a wider market.
• Integrated DevOps pipelines will make DevOps more efficient… if [Click to Tweet] we can get the politics out of IT.
• Machine learning will continue to be integrated into developer tools [Click to Tweet] which, in turn, will make more complex coding and deployment jobs easier.
As you know, I joined Amalgam Insights in September. Amalgam Insights, or AI, is a full-service market analyst firm. I’d welcome the opportunity to learn more about what 2018 holds for you. Perhaps we can schedule a quick call in the next couple of weeks. Let me know what works best for you. As always, if I can provide any additional information about AI, I’d be happy to do so!
Thanks, and have a happy holiday season.
For more predictions on IT management at scale, check out Todd Maddox’s 5 Predictions That Will Transform Corporate Training.
Note: A version of this post was published to Tom’s Tech Take II
As the fall season of tech conferences starts to wind down, something is quite clear – machine learning (ML) is going to be everywhere. Box is putting ML in content management, Microsoft in office and CRM, and Oracle is infusing it into, well, everything. While not a great leap forward on the order of the Internet, smartphones, or PCs, the inclusion of ML technology into so many applications will make a lot of mundane tasks easier. This trend promises to be a boon for developers. The strength of machining learning is finding and exploiting patterns and anomalies. What could be more useful to developers?
Here are some examples:
On the week of September 25th, 2017, Microsoft made a huge announcement at its annual Ignite and Envision conference. Microsoft has become one of a small number of companies that is demonstrating quantum computing. IBM is another company that is also pursuing this rather futuristic computing model. For those who are not up-to-date on quantum…
This past week (September 25 – 27, 2017) Microsoft held its Ignite and Envision Conferences. The co-conferences encompass both technology (Ignite) and the business of technology (Envision). Microsoft’s announcements reflected that duality with esoteric technology subjects such as mixed reality and quantum computing on equal footing with digital transformation, a mainstay of modern business transformation projects. There were two announcements that, in my opinion, will have the most impact in the short-term because they were more foundational.
The first announcement was that machine learning was being integrated into every Microsoft productivity and business product. Most large software companies are adding machine learning to their platforms but no company has Microsoft’s reach into modern businesses. Like IBM, SAP and Oracle, Microsoft can embed machine learning in business applications such as CRM. Microsoft can also integrate machine learning into productivity applications as can Google. IBM can do both but IBM’s office applications aren’t close to having the market penetration of Microsoft Office 365. Microsoft has the opportunity to embed machine learning everywhere in a business, a capability that none of their competitors have.