DevOps comprises automated and integrated processes between software development and operations teams. The blend of developers and IT operations working together throughout the product lifecycle creates a more seamless process. That said, there are still challenges and trends within DevOps that we should have our eye on.
This list of 10 DevOps predictions will help you stay on the ball in 2024 so you can make the best decisions for yourself and your organization.
1. Elastic Architecture
Horizontal and vertical cloud tech stack scaling, will be done dynamically. There won’t be the need to build for Christmas only for a system to be empty the rest of the year. Systems will be preconfigured to expand and contract based on consumption. – Sameer Rizv, Founder and CEO at Odesso
2. Generative AI Will Accelerate the Application Development Landscape
The landscape of application development is set for transformative shifts, particularly those propelled by generative AI, poised to significantly accelerate two critical areas. The first focuses on digital automation, aiming to minimize human intervention, enhance efficiency, and streamline processes. Simultaneously, software automation is set to undergo a paradigm shift as Generative AI not only generates code but also validates security, ensures performance, and automates test case creation and documentation.
Generative AI’s ability to comprehend and respond to natural language will play a pivotal role, accelerating various digital processes and paving the way for a new era of digital automation. There will be a fundamental rethinking of how data is generated, processed, and consumed with the integration of more contextual, conversational elements, directly triggering workflows from a conversation or an image. A lot of existing digital workflows are bound to be replaced by the AI solutions, setting pace to the digital transformation efforts.
AI-powered design tools will become widespread, aiding business teams in expressing their ideas effectively. Generative AI will emerge as a solution to collaboration challenges, bridging the gap between business and IT teams, enabling visualization, prototyping, and improved communication. However, developers using AI models for generating code, will struggle in refining the intent or prompt to get to the appropriate logic or code. These AI models will have to evolve more to support iterative development as it will become an indispensable assistant for professional developers.
More and more open source LLMs & AI models will emerge for specific use cases, large organizations will tend to create their own AI models from the foundational models to protect copyrights, secure and ethical use of AI. These custom AI models bring better visibility to the developers and their ecosystem on how these models are trained and developed, so as to gain more trust in how these AI solutions are put to use.
The enduring impact of the pandemic will continue to shape the way software is created and foster innovation. Despite a decade of existence, the adoption of applications developed by business teams aided by low code platforms, still faces challenges such as IT acceptance, security, scalability, and licensing models. Low-code platforms will embrace LLMs and other AI models in creating apps that are enterprise-deployable, specially crafted by professional developers, eliminating the risks associated with IT deployment.
The future of AI-powered application development holds the promise of heightened automation, seamless contextual integration, and transformative user experiences. – Deepak Anupalli, Co-Founder & CTO at WaveMaker, Inc.
3. Increased Adoption of GritOps
Another trend likely to gain momentum is the increased adoption of GitOps. This will enhance collaboration and streamline the deployment process, making it easier to manage infrastructure and applications through git repositories. – Anup Kayastha, Founder of Serpnest
4. We Will Start to Experience The Effects of Integrating Low-code Strategies With Generative AI Code-generation LLMs
Low-code is already a boon to developers and DevOps teams, streamlining key development processes while accelerating innovation timetables. But in 2024, the effects of integrating low-code strategies with generative AI code-generation LLMs will arrive (and continue to mature quickly). The impact on productivity will be transformative, with low-code code-generation tools achieving ever-greater code usefulness and functionality. The result will be unprecedented efficiency for developers and DevOps teams, and a market environment where organizations equipped with low-code-plus-genAI coding capabilities will absolutely lap competitors still relying on more traditional dev strategies. – Shomron Jacob, Head of Applied Machine Learning & Platform at Iterate.ai
5. Enhanced Focus on Monitoring and Performance Metrics
I think real-time monitoring and granular performance metrics will become more integrated into DevOps practices. With tough economic conditions still expected in 2024, companies will require fast and efficient systems to maximise their business profits. As such teams will increasingly rely on sophisticated tools that provide deeper insights into application performance, user experience, and system health, enabling quicker responses to issues and better decision-making. – Karl Threadgold, Managing Director at Threadgold Consulting
6. Expanded Use of Simulation and its “Left Shift”
With the ever-creeping need to make smarter decisions, simulations are more and more important to make better products. Related to generative design, we predict an expansion in the usage of simulation and “left shift” in when we use such tools in a product’s life cycle. Historically in the left-to-right product life cycle, 3D engineering saw simulation used predominantly in the engineering and manufacturing stages, towards the end of a product development. Once we had a finalized design, we simulated, got feedback, and iterated from there based on the requirements. This is changing.
In 2024, we expect to see simulation used comprehensively in areas it was previously used sparingly. We are seeing simulations in design stages, to more quickly react to feedback and constraints than before. The increase in simulation and testing doesn’t stop there. Simulation of the supply chain, born out of necessity during the height of the COVID-19 pandemic, is becoming more commonplace. We are seeing its benefits: savings of time, money, and better-built products that are more resilient to supply chain issues – Jonathan Girroir, Technology Evangelist at Tech Soft 3D
7. DevSecOps Will Start to Become Fundamental at the Start of Software Development
DevSecOps has been gaining significant momentum in the DevOps world, a trend I see continuing to grow rapidly. This approach, integrating security practices directly into the DevOps pipeline from the very beginning, is shifting from an emerging concept to a critical standard. As we prioritize security from the start of the software development lifecycle, it’s becoming a fundamental aspect, not just an optional add-on. The current rise in the adoption of DevSecOps marks a pivotal shift towards more secure and robust software development processes. – Maksym Lushpenko, Founder & CEO at Brokee
8. Cost Optimization and FinOps Practices Within DevOps Organizations
Efficiency is about doing more with less. In 2023 we finally reached the boundaries of the (not so) infinite computer known as the cloud. Similarly we reached the boundaries of VCs wallets. The resulting backlash has been for companies to take a fresh look at their IT departments and budgets and ask some hard questions about what is really necessary.
In 2024 we will see all DevOps organizations focus on cost optimization and FinOps practices. All new projects and architecture decisions must include a financial lens. Teams will need to be made aware of the financial impacts of their engineering decisions and actions. However, this should be an empowering rather than a limiting factor. It should encourage engineering teams to make decisions that are best for the business. – Ian Crosby, Field CTO at Aptum
9. DevOps Teams Will Leverage Cloud Infracture
DevOps teams must leverage cloud infrastructure for software development and implement robust security measures with SecOps teams every step of the way to safeguard applications and data against threats and vulnerabilities. Cloud providers offer features like identity and access management, encryption and threat detection to ensure data protection. Moreover, regular backups and disaster recovery options provided by the cloud infrastructure guarantee data availability and resilience. – Stav Sitnikov, CTO & co-founder, Stream.Security
10. SBOM Scanning Will Become Critical for Open-source Library Use
In software development supply chains, open-source libraries are a widely used component in software development – it’s so easy to grab a random open-source library, stick it in your code, and hope for the best. However, open-source libraries remain a weak underbelly and pose significant security risks as they are easily targetable by malicious actors aiming to compromise their integrity by inserting vulnerabilities or backdoors. Because of this, SBOM scanning will become critical to providing an accurate inventory of vulnerable open source libraries and containers. – Chad Loeven, Vice President of Business Development, OPSWAT
