The Future of Optimizing DevOps with Agile Deployment Solutions
August 22, 2023

Scott Willson
xtype

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.

Overcoming Bottlenecks

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.

Scott Willson is Head of Product Marketing at xtype
Share this

Industry News

May 13, 2025

Pegasystems unveiled Pega Predictable AI™ Agents that give enterprises extraordinary control and visibility as they design and deploy AI-optimized processes.

May 13, 2025

Kong announced the introduction of the Kong Event Gateway as a part of their unified API platform.

May 13, 2025

Azul and Moderne announced a technical partnership to help Java development teams identify, remove and refactor unused and dead code to improve productivity and dramatically accelerate modernization initiatives.

May 13, 2025

Parasoft has added Agentic AI capabilities to SOAtest, featuring API test planning and creation.

May 13, 2025

Zerve unveiled a multi-agent system engineered specifically for enterprise-grade data and AI development.

May 12, 2025

LambdaTest, a unified agentic AI and cloud engineering platform, has announced its partnership with MacStadium(link is external), the industry-leading private Mac cloud provider enabling enterprise macOS workloads, to accelerate its AI-native software testing by leveraging Apple Silicon.

May 12, 2025

Tricentis announced a new capability that injects Tricentis’ AI-driven testing intelligence into SAP’s integrated toolchain, part of RISE with SAP methodology.

May 12, 2025

Zencoder announced the launch of Zen Agents, delivering two innovations that transform AI-assisted development: a platform enabling teams to create and share custom agents organization-wide, and an open-source marketplace for community-contributed agents.

May 08, 2025

AWS announced the preview of the Amazon Q Developer integration in GitHub.

May 08, 2025

The OpenSearch Software Foundation, the vendor-neutral home for the OpenSearch Project, announced the general availability of OpenSearch 3.0.

May 08, 2025

Jozu raised $4 million in seed funding.

May 07, 2025

Wix.com announced the launch of the Wix Model Context Protocol (MCP) Server.

May 07, 2025

Pulumi announced Pulumi IDP, a new internal developer platform that accelerates cloud infrastructure delivery for organizations at any scale.

May 07, 2025

Qt Group announced plans for significant expansion of the Qt platform and ecosystem.

May 07, 2025

Testsigma introduced autonomous testing capabilities to its automation suite — powered by AI coworkers that collaborate with QA teams to simplify testing, speed up releases, and elevate software quality.