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.
Digital transformation may be a bit of a catch all for adopting modern IT principles and technologies, from cloud platforms and services to mobility and big data to DevOps practices, but it is a real movement throughout the business realm.
The primary gist is to not only introduce new tech, but to also take a close look at the business processes and organizational units behind them to ensure that innovation can occur, and the bottom line is improved. In other words, technology for the sake of technology won’t solve any business problems. You must transform your entire organization with a combination of technology and process.
True digital transformation involves your entire organization and results in the integration of various systems and operations across the business. If that sounds like a major undertaking, it is.
It also comes with a slew of information security concerns that should not be overlooked in the rush to the cloud.
You would be a woefully uninformed and unprepared as an IT admin if you didn’t know that two major Microsoft products, the 2008 versions of SQL Server and Windows Server, are each about to reach their end of support. That means it’s time to upgrade or migrate lest you fall victim to inevitable security vulnerabilities.
One big question when facing a major software upgrade such as this is whether to remain in place, so to speak, and update to the latest version from your current deployment scenario on premise or in a hosted environment, or to move to a cloud-based server – namely Azure, since that offers you tight integration and lower costs with Microsoft products such as these.
SQL Server end of support is imminent, coming up on July 9, 2019. Windows Server has a few months to go, ending support on January 14, 2020.
As you research your options for enterprise productivity applications you likely will come across Microsoft 365 alongside the more commonly known Office 365.
In typical Microsoft fashion, there are an array of different plans and licensing levels for each option. Deciding which is the best option can therefore take some time.
What is Microsoft 365 and how is it different from Office 365? M365 includes enterprise-specific features that you would likely purchase separately, critically several Enterprise Mobility and Security components.
For businesses at the midsize and enterprise levels, M365 seems like the clear choice. But what exactly do you get at each level of M365? And how does it compare to O365?
DevOps — the marriage of the development and operations departments within a software organization — and Agile methodology have been mentioned alongside cloud computing for years now, and with good reason. Using Agile in the cloud is a classic pairing that goes together like peanut butter and jelly or macaroni and cheese…okay, let me go grab a snack before this simile gets me drooling.
But seriously, even if Agile and cloud technology aren’t as tasty as PB&J, they can still have you smacking your lips in satisfaction as you react to business problems with technology solutions in a much faster and more reliable manner.
Here’s why Agile software development practices work so well when you’re working with cloud infrastructure, even if you aren’t a software development company.