Green House Data can transform your IT operations for modern practices and the latest technology. Enterprise Advisory Consulting, DevOps processes, PaaS migration and implementation, and ongoing Professional Services are here to help you take that next step.
IT modernization is top of mind for many CTOs and CIOs. Whether your base platform is an on-premise data center, hosted in the cloud, or colocated, Green House data can help you migrate to modern platforms and gain efficiency and reliability.
Hybrid, multi-cloud, hyperscale, and on-premise infrastructure can be tough to orchestrate and administrate. Green House Data has the dedicated support and technical staff to help you manage complex IT environments.
Automated IT infrastructure isn't here to take your job. Instead it helps you focus on what really matters — enabling your users (rather than patching 100 desktops). Automate apps, scaling, cloud migration, and routine maintenance with software and consulting from Green House Data.
Getting Started with Azure – Basics, Tips, and Tricks
Learn the basics you need to know to get started with Azure cloud including virtual machine creation, introduction to Azure concepts, and more. This pre-recorded webcast is from Microsoft MVP and Green House Data Principal Consultant Aman Sharma.
Green House Data has passed a rigorous independent audit to certify our staff capabilities and corporate processes around Microsoft Azure technologies. Trust your hyperscale cloud project to an MSP who can pivot and scale based on your desired business outcomes, regardless of the workload, application, or offer at hand.
Green House Data’s SpotLITE Discovery Process showed us how we could right-size our data center needs and cut out 30% of the cost by eliminating redundancies. What we thought we needed wasn’t the case and Green House Data gained our trust when they pointed this out instead of turning a blind eye and letting us over build and over spend.
Avid has a lot of specific requirements around individual apps. Green House Data learned the “snowflakes” that make the business work and delivered the deployment on time and on budget.
They are very knowledgeable and anticipate our needs in a way I didn’t think was possible from a vendor.
Mountain West Farm Bureau Insurance
Every time I talk to one of our cloud team members at Green House Data, I feel like I learn something new about Azure.
If your organization is large enough to have an information security manager or an entire security team, then it’s likely that any security issue or task will be pushed in their direction. That’s why you hired them, isn’t it?
Security is a specialized area of IT and it requires specific skills for a holistic approach. It is also a moving target with many components and attack vectors across your technology stack. A dedicated security team or individual, whether in-house or contracted, can therefore be valuable. But security must be a shared responsibility among every user, no matter their role.
There’s an inherent problem here and its name is Diffusion of Responsibility. When everyone has a stake in security and there are dedicated managers to boot, users could be more likely to engage in risky behavior. After all, it’s taken care of! That’s why we hired that security guy.
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.
A fundamental building block for your successful adoption of cloud services is the organizational hierarchy, a mode of organizing your cloud services, resources, and virtual machines in such a way that you ensure cloud governance and can better resolve billing within your organization.
Cloud governance is the answer to common questions like:
“How do I keep my data compliant with industry regulations?”
“How can I implement chargeback within my organization so I know which departments are consuming cloud services and account for that usage?”
“How can I mandate security and access measures across our cloud environment?”
By implementing a flexible set of controls and overall organizational hierarchy within Azure, you can enable adoption of the cloud services your business units require and avoid shadow cloud use. A well-designed enterprise cloud environment can accommodate modern agile practices alongside traditional workloads.
Here’s how to structure your organizational hierarchy within Azure so you can set governance requirements and encourage speed of delivery for your individual departments and business units.