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The world today is focused on speed. We talk about time to market or value, companies advertise for employees capable of operating in fast-paced environments, and we idolize people that move fast and break things.
It's understandable that when we consider users now expect outstanding, digitally-enabled experiences as standard, it permeates all aspects of an organization. Business units expect technology solutions faster, applications are expected to be planned, developed, tested, and deployed in weeks — if not days — and wholescale digital transformation projects should happen quickly.
The problem is that when people want many things quickly, there's usually a bottleneck to be found somewhere. This throttles the speed of delivery while increasing the strain on wherever the blockage is — usually an under-resourced, overworked department such as quality assurance or testing.
When it comes to applications, many problems stem from how they've been developed. This is what DevOps was, in part, supposed to fix. Not with any miraculous tool but with a philosophy that brought developers and operations together. One that allows small teams to independently develop, test, and deploy code quickly, securely, and reliably to customers while simultaneously allowing these teams to fail fast and safely.
Running alongside DevOps is the agile methodology, a decades-old approach to software development that promotes incremental development, frequent releases, and automating processes where possible. Instead of overhauling applications, teams adjust what needs adjusting, get that released, followed by monitoring and review. They then rinse and repeat. It's an approach that fully aligns with a smart approach to digital transformation, emphasising constant iterations rather than a wholesale rip and replace.
Don't Just Automate Processes
The issue is that, in many cases, manual processes remain that require employees to trigger actions. If a team member hasn't completed a task, someone is off ill, or something else has held up their workflows, the whole DevOps pipeline can break down.
To tackle this, first, DevOps needs to automate those manual tasks. This has a wide-ranging impact, from improving consistency to increasing development quality and boosting employee satisfaction.
But automating tasks isn't the only step. DevOps functions also need to address environment inconsistencies. Infrastructure as Code (IaC) has attempted to address this, and it does work to a degree when used on correctly architected apps. However, it is not a silver bullet. As well as placing even more workload demands on development teams, IaC's variability allows different environments to be configured completely differently. As such, it is not a blind replacement for an attempt to make as many environments as production-like as possible.
Tackling Environment Inconsistencies in DevOps
For all the emphasis on automation within the DevOps community, the focus of automation has been on the migration of code. If you think about it, moving and managing the changes in source code is at the core of every continuous delivery pipeline. To address bottlenecks in automated pipelines, the push has been to include more things in the migrated code, such as infrastructure (IaC), testing, and more.
Simply turning more things into code means increasing the workload and responsibility of developers. This also lengthens the learning curve of newly hired employees. Everything as code isn't necessarily a game changer because, at the end of the day, we're still managing and migrating code forward from development environments to production. The biggest challenge in ensuring things in production work as in lower environments is the inconsistencies between these environments.
Removing Environment Inconsistencies
This isn't a new idea per se. After all, a core tenet of Continuous Delivery (CD) is to make all environments as production-like as possible. What is different is the idea that CD pipelines should include bidirectional communication of change information. An adjustment in production, such as an emergency update or hot fix, must be communicated upstream so the code written and tests performed in the next sprint reflect downstream changes.
Identifying Problems Rapidly
Environment synchronization doesn't mean that problems will be instantly eradicated, but what it does mean is that changes are propagated across the pipeline, so that each sprint begins with the most accurate information (and assumptions) as possible. Accuracy at the beginning of a sprint will result in fewer surprises during production or pre-production releases.
And that frees teams up to do more work. Rather than having to spend time remembering resolution steps from earlier environments or trying to resolve new problems outside of working hours, developers can reduce cognitive fatigue and apply these savings to higher production yields. Increased productivity, in turn, reduces backlogs and helps meet the need for speed all organizations now have.
Technology is advancing at an unprecedented rate as it strives to meet user expectations. For DevOps teams, tackling bottlenecks and avoiding unnecessary release troubleshooting is critical to ensure that pipelines remain clear and applications can be deployed rapidly. By streamlining and automating manual processes, development teams can unlock greater efficiency and throughput. And a key part of that is synchronizing environments to reduce inconsistencies. It holds immense potential for those teams creating the experiences propelling enterprise digital transformation journeys forward.