CIOs and DevOps Leaders Must Consider Model Driven Operations to Remain Competitive
by Stefan Johansson, Global Software Alliances Director, Canonical
The emergence of “big software” – a complex assembly of many software components sourced from different vendors, running on multiple distributed machines, providing to its user the impression of a single system – has raised the importance of operations in a software, and in particular, a hybrid cloud world.
Integration and operations now consume a significant share of technology budgets, and for IT organizations and there is no sign of slowing down.
To help alleviate the burden of integrating software components many IT organizations are adopting open source software and model driven operations to reduce complexity and integration costs while improving time to market.
The cloud and microservices (independent services that interact with a network) are making software implementation more challenging and distributed.
The costs and intricacies of Big Software are keeping many CIOs and DevOps leaders awake at night. Where do these technology leaders turn for answers? In-house solutions are expensive to deploy and integrate, probably not.
Costly systems integrators that only focus on solving one technology challenge and have a long learning curve, not optimal. Or organizations can continue to invest in siloed solutions only to achieve incremental gains, too expensive and time consuming.
Forward-thinking IT & DevOps executives are adopting:
“Buy what you can, build what you have to, and integrate for competitive advantage.”
These hurdles are why model driven operations are changing how software is deployed and operated today.
For CIOs and DevOps, model driven operations improves how software is not just deployed, but scaled across the enterprise or among various cloud services, providers, or bare-metal servers.
One of the main values for model driven operations is the ability to share and reuse open source code that has common components and functionality so development organizations can spend their time and resources deploying solutions unique to their business.
This allows internal teams and systems integrators to leverage model driven operations to focus on what they do best while delivering business value, improve lead time and be more efficient.
For example, when a new server needs to be deployed, modelling can automate most, if not all, of the provisioning process. Automation makes deploying solutions much quicker and more efficient because it allows tedious tasks to be performed faster and more accurately without human intervention.
Even with proper and thorough documentation, manually deploying a web server or Hadoop deployment, for example, could take hours compared to a few minutes with service modelling. This is why CIOs and DevOps chiefs are adopting service modelling as a way to make the most effective use of their team’s precious resources and time.
Further, model-driven operations gives development organizations more choice in how services are consumed (public, private, or hybrid cloud) and options that make it easier to replicate environments with the same software and configurations.
As these systems evolve, organizations can deploy pre-configured services, private infrastructure solutions including OpenStack, and even the organization’s own code to any public or private cloud. This allows enterprises to deploy solutions that are consistent, integrated, and relevant to their business needs.
Companies like Google, Amazon, AT&T, and many others have all moved to model-driven operations to provision and deploy software and cloud services across multiple domains and environments faster and more efficiently.
Canonical’s approach to service modelling
Companies are integrating the tools and technologies that will help drive business outcomes faster, more reliably, and efficiently. Software modelling solutions like Canonical’s Juju helps customers to build and deploy proofs of concepts faster, integrate solutions more seamlessly while expanding their organization’s capabilities more broadly.
Juju is a universal modelling solution that speaks to executives, developers, and operations. Imagine using a solution that enables the deployment of revenue-generating cloud services with only dragging and dropping a few commands.
Juju Charms, which are sets of scripts for deploying and managing services within Juju, allow organizations to connect, integrate, and deploy new services automatically without the need for consultants, integrators, or additional costs or resources. Companies can choose from hundreds of microservices that enable everything from cloud communications via WebRTC, IoT enablement, big data, web services, mobile applications, security, and data management tools.
Further, with the rise of open source, enterprises, and programmers can leverage the power of a vast library and a community of developers to design, develop, and deploy their solutions much faster.
Additionally, network administrators and developers can free up their time to focus on bringing to market revenue-generating solutions and services, rather than architecting complicated network stacks and deploying additional resources.
What matters to the developer is what services are involved, not the details of how many machines they need, which cloud they are on, whether they are big machines or small machines, or whether all the services installed are on the same machine.
There has been a shift from software and infrastructure orchestration to model driven operations that makes the task of deploying distributed systems – or Big Software – more efficient and faster. It’s about choice and options.
It’s time to let software do the work
The world of software deployment is becoming more and more complex. Software deployments were once simple and spread across a few machines, now they have evolved to become distributed across many machines, operating systems, regions, and environments.
This shift has created both a competitive threat and simultaneously, a massive opportunity. Many CIOs and DevOps executives are exploiting these opportunities, while others risk being relegated to the dustbin of oblivion.
Model driven operations helps organizations to reduce complexity, improve efficiency, and deploy revenue-generating services and solutions faster.