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How value-stream mapping delivers a better DevOps toolchain

While the DevOps movement was built on concepts such as cross-discipline collaboration and communication—bringing together developers and their goals, priorities and efforts with those of operations and other stakeholders—many of today’s tools have only begun to bring these concepts to life. While DevOps, in theory, should unite segmented disciplines and work groups, enterprise products that are supposed to facilitate that process only provide limited automation, integration and visibility.

Adding more DevOps tools to the mixture has helped in some areas, but hurt in others, as the software development lifecycle has become increasingly bulky. Organizational leaders are overwhelmed with managing these complex toolchains. Many of the enterprise DevOps managers I talk to say they struggle to get control and gain a holistic view of all the DevOps tools in the lifecycle.

Enterprises use DevOps tools to help drive continuous build, test, delivery and other functions across the lifecycle. But many IT professionals say that to implement continuous improvement and feedback holistically, they need to be able to measure across the entire lifecycle, from planning to operations.

Value mapping can help with that.

Many organizations are looking to fix problems or improve processes that have very siloed DevOps tools, with different data sources that aren't integrated. This inhibits those involved in leading software development or DevOps initiatives from getting the most value out of their DevOps tools, and enabling "smart DevOps” in their organizations. They don’t have a way to measure and improve processes across the entire software development lifecycle.

Here's how value mapping that abstracts from the DevOps toolchain can benefit your organization's software development and lifecycle management.

DevOps mindset more important than formality

Integration is key

With the rise of best-of-breed tool chains, integration is a vital first step to getting the needed big-picture view of the software development lifecycle tools and processes. Existing investments and legacy assets shouldn’t impede the full utilization of newer DevOps tools, but the sheer number of tools available to help organizations succeed in DevOps can become a hindrance if those tools are not properly integrated, and if data consistency and integrity are not assured.  

Ensure visibility and traceability

Despite the advances we’ve made as an industry in improving the process for software development and deployment, managers still struggle to see everything that is happening across the board, and to connect teams, processes and tools appropriately. Tracing events and data and their associations across tools is another existing gap in what DevOps point tools have yet to offer. Correlated end-to-end visibility shortens the time-to-value of the development and delivery lifecycle greatly. Redundant processes are eliminated, successful strategies can be expanded across distributed teams, and feedback is integrated at a more rapid pace. 

Better visibility usually means better traceability, which is essential for the pipeline’s health and performance. When managers can follow each error to origin, they correct issues faster, and ensure better work quality due to the accountability required of team members. A quicker and more accurate continuous feedback loop is possible when stakeholders from a number of business units—InfoSec, operations and legal—have visibility into the entire process.

Don’t underestimate data’s importance

We’ve seen explosive buzz in the tech industry over the last few years around data—analytics, storage, processing, etc. Data plays a vital role in DevOps as well. In this arena, the challenge is leveraging the data that DevOps tools generate. A reality of the heterogeneous environments of today’s enterprise is that each tool within the DevOps chain generates its own unique events and data. Each tool likely generates reporting and tracking information as well, but without intelligent event integration and correlation, how can an enterprise make the most out of the vast amounts of data produced? 

The need for correlation of data between existing tools—so that companies can turn that data into actionable information—is great. DevOps stakeholders are asking for a single-pane-of-glass view of correlated data that provides insight across all stages of the software delivery lifecycle, from planning and application development to testing, deployment, and production monitoring.

This enables all teams adopting DevOps to accelerate from concept to production to improve the velocity and quality of application delivery to the business.  For example, a release manager may see that, although the last release came out on time, it increased service desk incident tickets by 20 percent. Traceability of chains of events and data helps with the implementation of corrective actions and processes.

Why value-stream mapping matters

At the rate things are changing in software development, this should be obvious: As DevOps initiatives and processes evolve, organizations change their toolchains. As you do so,  focus on process improvement and creating a value-stream map of your software development lifecycle across application portfolios, from planning to operations. Establish a baseline and develop KPIs for measurement and continuous improvement and feedback.

Value mapping that abstracts from the specific DevOps toolchains allows organizations to evolve toolchains and still capture the data that drives critical KPIs across the software development and delivery lifecycle. Managers can use these metrics to accelerate collaborative, continuous improvement and feedback processes, and initiatives like control points, quality gates, audit-readiness, and fast-fix and rapid-response abilities.

The industry has come a long way in bringing together developers with other organizational stakeholders to improve the speed and quality of software development. But as DevOps tools meet the siloed needs across the software development lifecycle, organizations  must have a better understanding of their DevOps value stream across that lifecycle.

By having end-to-end correlated visibility across every DevOps toolchain component, organizations can leverage objective metrics and KPIs to ensure that delivery is operational and meets quality SLAs for the business. By prioritizing these considerations, you a will better leverage existing investments and set up your organization for future success in an industry and movement that is ever-changing. 

DevOps mindset more important than formality
Topics: DevOps