4 Steps to a People-First Strategy for Optimal DevOps
February 03, 2017

John Gentry
Virtual Instruments

IT teams are often tasked with managing the impossible: supporting the current needs of their organizations while continually developing applications and systems that reliably move business forward — oh, and let's not forget squeezing as much out of their budgets as they can, year after year with only nominal increases. Add to this the rapid pace of technology development and ever-increasing complexity caused by virtualization, hyperconvergence, BYOD and software-defined trends, and you get a perspective of the impossibilities that today's modern IT teams face.

This "new normal" can be thrilling, frightening or both, depending on your perspective. How enterprise IT manages compounding complexities, now and forever forward, affects overall business agility and innovation. With this inconvenient truth in mind, it's no wonder that DevOps and continuous delivery models are a primary focus. The performance and reliability of IT infrastructures delivering today's business-critical workloads is only as good as the accuracy and reliability of the systems monitoring and managing them.

While DevOps and continuous delivery models can (in theory) accelerate technology projects and help them run more smoothly and predictably, the required cultural realignment can prevent companies from reaping the full benefits. Developing and executing an effective strategy means shifting how teams collaborate and interoperate — and we all know how everyone loves change. Here are four steps that enterprise IT leaders are undertaking to facilitate the cultural adaptation and collaboration required to maintain IT and business agility:

1. Get buy-in, train, and enable data-informed collaboration

It seems so simple, but getting everyone on the same page must be the first, and sometimes the hardest, step. It is so important that it's worth repeating: Get. Everyone. On. The. Same. Page. The entire premise of DevOps and continuous delivery rests on the premise of bringing multiple teams together. Only then can you enable innovation, adaptation and transformation.

To make sure collaboration goes smoothly and delivers effective outcomes, focus on the basics. Start with development and operational functions, job descriptions, and similarities and differences. Determine the training and technologies needed to help with the cultural shift. Deploying analytics solutions that enable cross-domain collaboration is critical for aligning teams and helping them perform. These solutions help employees see DevOps transformation as an opportunity for growth, fueled by intelligence that they can consume, act upon and learn from.

2. Start simply, monitor comprehensively and decide confidently

There are several factors to consider when identifying which projects are good candidates to feed into the DevOps process, including overall scope, estimated costs and projected ROI. Start with projects that have a clearly defined and reasonable scope, as well as existing benchmarks. Determine success metrics for expected improvements, enable and monitor data-driven collaboration, and meet your targets.

This effort requires tight collaboration throughout development and operational organizations. Every team has relevant insights, which help form an accurate view of what it takes to deliver a successful project. It's crucial to have the right monitoring solution in place, one that provides a complete understanding of workload interdependencies, effects and how to optimize for overall performance.

3. Enable authoritative understanding and confident collaboration across silos

End users demand flawless experiences, and the ultimate charter for any DevOps team is to meet and exceed end-user demands. While DevOps teams must understand how new feature and functionality releases affect end users, they must also understand how these same releases affect the underlying IT infrastructures delivering them.

Effective DevOps models require close collaboration across multiple silos. To be effective, every collaborator must have an authoritative understanding of what's happening, and the confidence to act. End-to-end performance monitoring with algorithmically driven decision support provides teams with this accuracy and confidence.

4. Remember, DevOps has no "end state"

It's important to continually assess the training and cultural divides you are bridging. DevOps is a new way of life and it's just beginning. Everything is dynamic. Applications aren't static, and neither is the infrastructure that supports and delivers them. There must forever be a vigilant focus on understanding how organically evolving workloads affect the infrastructure. After new releases are put into production, everything must be constantly monitored and tuned for optimal performance.

Without an accurate, real-time understanding of end-to-end performance, every release cycle presents risks that can harm the DevOps process. It's critical to constantly gather and analyze performance data in order to determine how continually evolving workloads affect IT infrastructure performance. DevOps teams then need to use this data to proactively tune and manage infrastructures before emergent issues become actual performance problems.

John Gentry is CEO of Virtual Instruments.

Share this

Industry News

December 19, 2024

Check Point® Software Technologies Ltd. has been recognized as a Leader in the 2024 Gartner® Magic Quadrant™ for Email Security Platforms (ESP).

December 19, 2024

Progress announced its partnership with the American Institute of CPAs (AICPA), the world’s largest member association representing the CPA profession.

December 18, 2024

Kurrent announced $12 million in funding, its rebrand from Event Store and the official launch of Kurrent Enterprise Edition, now commercially available.

December 18, 2024

Blitzy announced the launch of the Blitzy Platform, a category-defining agentic platform that accelerates software development for enterprises by autonomously batch building up to 80% of software applications.

December 17, 2024

Sonata Software launched IntellQA, a Harmoni.AI powered testing automation and acceleration platform designed to transform software delivery for global enterprises.

December 17, 2024

Sonar signed a definitive agreement to acquire Tidelift, a provider of software supply chain security solutions that help organizations manage the risk of open source software.

December 17, 2024

Kindo formally launched its channel partner program.

December 16, 2024

Red Hat announced the latest release of Red Hat Enterprise Linux AI (RHEL AI), Red Hat’s foundation model platform for more seamlessly developing, testing and running generative artificial intelligence (gen AI) models for enterprise applications.

December 16, 2024

Fastly announced the general availability of Fastly AI Accelerator.

December 12, 2024

Amazon Web Services (AWS) announced the launch and general availability of Amazon Q Developer plugins for Datadog and Wiz in the AWS Management Console.

December 12, 2024

vFunction released new capabilities that solve a major microservices headache for development teams – keeping documentation current as systems evolve – and make it simpler to manage and remediate tech debt.

December 11, 2024

CyberArk announced the launch of FuzzyAI, an open-source framework that helps organizations identify and address AI model vulnerabilities, like guardrail bypassing and harmful output generation, in cloud-hosted and in-house AI models.

December 11, 2024

Grid Dynamics announced the launch of its developer portal.

December 10, 2024

LTIMindtree announced a strategic partnership with GitHub.