Two major enterprise computing platforms are reaching their end of life this week. Tomorrow (January 14th), in fact. While this may seem like a last-minute blog entry, we know there are plenty of you out there still running Windows 7 on corporate desktops and Windows Server 2008 or 2008 R2 in your data centers.
Microsoft itself estimated that 60% of its Windows Server install base was still running 2008 back in August. Some of those instances may have been upgraded or migrated to cloud VMs, but we’re betting many of them remain. Unofficial estimates peg the number of Windows 7 machines worldwide at around 200 million.
Change can be hard, especially when your systems seem to be working properly and upgrading appears to be a complex and time-consuming endeavor. But operating systems that have reached End of Support open the door for vulnerabilities, bugs, and incompatibility with newer infrastructure. They also make it more difficult to deploy and support newer software that can improve employee efficiency and empower the business to drive revenue in new areas and to compete with others in the industry. With Windows 7 and Windows Server 2008 End of Support upon us, what are your options?
It’s been over a month since I attended the Gartner IT Symposium/Xpo in Orlando and I’ve spent that time really chewing on some of the great sessions and thought leadership presented at the show. Modern IT practices remain a moving target so plugging into the analyst machine every once in a while helps me get a bigger picture beyond even our day to day at Green House Data (which can be pretty diverse itself, with big pushes on DevOps and digital transformation while we balance our existing data center, cloud, and managed services pillars).
It was interesting hearing Gartner start to shift their message from “cloud is the only option” to “cloud is an option.” As cloud adoption strategies have matured we have seen this attitude shift as well, with more organizations looking multi-cloud while maintaining some on-prem systems. One presentation on public cloud costs compared to on-prem data centers really helped drive this home. The bottom line is that the cloud is not automatically cheaper or even necessarily more efficient depending on the application or purpose of the deployment.
Other major topics included how to find digital talent, as the management of human capital and IT teams continues to evolve alongside the industry, as well as one of my favorite presentations, “Are You Maximizing Your Security Operations Center,” which had a ton of great information around security.
With the symposium still fresh in mind, here is my list of where enterprise IT operations are heading in 2020 and beyond.
Green House Data was onsite last week at Microsoft Ignite. We had some incredible conversations at our booth about Azure, PowerApps, application modernization, DevOps, Windows Server end of support, and more. Of course, while we were working the floor, Microsoft made a bevy of product announcements around core products and services that are sure to shake up your IT world! I’m super excited about these new developments, so here are my top takeaways from the show.
It happens to everyone at some point. Your budget gets slashed; the economy tanks; you’re suddenly in the red thanks to cloud sprawl. Whatever the cause, you’ll likely face a mandatory cost cutting initiative at some point in your IT career.
While cost cutting is a reality, it is fundamentally different from ongoing cost optimization. You should be practicing cost optimization as part of your regular duties, reviewing spend and ensuring the technology, hardware, software, and services in use across your organization are serving their business need and appropriately configured in scope and performance.
By formulating and practicing a cost optimization protocol, you’ll be prepared should the day for cost cutting ever come, while also gathering evidence for the impact IT has on the overall bottom line.
It might feel like DevOps is eating the world, but there’s still room for other innovations within and adjacent to IT operations. One such example is the DataOps movement. The general inspiration behind DataOps is similar to DevOps in that is strives to provide higher quality deliverables from shorter cycles by leveraging technology and specific methodologies around it.
DataOps does not boil down to DevOps principles applied to data analytics, however. While both approaches may embrace automation, continuous improvement, and strong communication between departments, DataOps is less of an infinite cycle and more of an injection of agility into a one-way data pipeline.
Let’s explore the roles, strategies, and technologies at play in a DataOps approach to analytics.
Last week I introduced key agile concepts including the history of and essential roles required for Scrum practices. I described a real-world example of how DevOps could have saved my organization major headaches and expenses.
In Part Two of this post on using agile Scrum methodology within DevOps ecosystems, we'll examine the Four Values of Agile and learn how to change your organizational mindset to accommodate this new paradigm.
In early 2001 I was involved in a software development project on integrating bolt-on application to a JD Edwards ERP software platform. The team completed the initial requirements collection and developed a comprehensive Business Requirement Document (BRD), investing roughly two to three months. The team had multiple review sessions to identify gaps in the requirements process and after a few cycles received approvals to proceed to the development phase.
While development was in progress, some of the EDI-based vendor data sources changed the mapping. This situation created chaos in the project. The management team decided to hold off the development phase. The project had to go through the requirements cycle again to identify the gaps. This situation impacted the schedule and budget, creating massive frustration in the organization. The first six months of the project investment was on hold. The sequential software development process we followed did not allow the flexibility to deliver any incremental value to the organization since the beginning of the project.
If we had followed an agile approach, this challenging outcome might have resolved in a different manner. The short intervals of development would have produced incremental value to the organization. Therefore we would have minimized the organizational concerns of not providing any value for six long months.
Here's how agile practices, Scrum, and DevOps all work together. Learn how to overcome adoption obstacles and several keys to Scrum success in this two-part blog series.
With some organizations looking to move cloud workloads back on-premises to mitigate costs and regain control over their hardware and audit trails, you might be questioning cloud-first and cloud-only initiatives for infrastructure procurement.
After all, for years marketing pushed lower overall costs after migrating to the cloud. So what gives? Why are many cloud workloads ending up more expensive than their on-prem counterparts?
You've probably heard the old joke before that the cloud is “just someone else's data center.” That may have been true a decade ago, but no longer.
Forcing a cloud migration is not the key to savings. You must understand the business value, catalog and think deeply about the existing and desired state of your infrastructure, rearchitect your workloads, and adjust your workflow to this new paradigm. Here are the five key areas you need to plan things out.
As you continue to adopt cloud technologies and pursue digital transformation, you’ll overhaul databases, migrate data to the cloud, and continue to connect more and more information gathering tools to your digital environment.
With unstructured data pooling rapidly in cloud object storage and structured data overwhelming your databases, you’ll wisely implement data management protocols that include long term archiving, encryption and security measures for sensitive data, and strategic use of various cloud and on premises storage methods to minimize costs.
But are you taking advantage of that data beyond how it used in the applications that gather and handle it? There are business insights to be gleaned and platforms like Power BI can help you make sense of it. If you don’t have time to learn a new platform or budget to hire a full time data analytics staff, you can instead find an Insights as a Service provider to help.
Serverless functions (often referred to as Functions as a Service or FaaS) will no doubt continue to grow in popularity and remain a cornerstone of IT services for many years to come. However, they are simply another way of building, maintaining, and delivering IT systems. With that in mind, they naturally have disadvantages or situations in which they may not be the preferred technology to use. These are due both to the nature of serverless and how it is currently implemented by cloud service providers.