According to a report by Gartner, by 2023, 90% of organizations will be using cloud services and DevOps practices, highlighting the growing importance of staying current with these trends for businesses to remain digitally competitive.

As businesses increasingly rely on digital solutions, staying up-to-date with cloud and DevOps trends is a must for future-ready businesses.

Evolution of cloud services

Cloud services have come a long way since their inception, and in 2024, the emphasis is shifting from revolutionary changes to evolutionary refinement. Instead of introducing groundbreaking concepts, the focus is on enhancing and expanding existing services.

One key aspect of this evolution is the maturity of cloud offerings. Cloud providers are now focusing on fine-tuning their services, and improving performance, security, and compliance. This refinement benefits businesses by providing more stable and reliable platforms for their applications.

The cloud ecosystem is trending towards greater interoperability. In the past, vendor lock-in was a concern for many organizations, but now, efforts are being made to ensure that cloud services are more compatible with each other. This means businesses can choose the best services for their needs without worrying about integration challenges.

The current state of DevOps

DevOps, often seen as the synergy of software development and IT operations, remains a primary strategy in 2024. Despite some predictions about its decline, DevOps has only seen an increase in its adoption, particularly among organizations that were initially slow to integrate it into their practices.

A principal factor in the sustained relevance of DevOps is its flexibility in adapting to the changing demands of businesses. With the acceleration of market demands, DevOps practices such as continuous integration and continuous delivery (CI/CD) stand out for their ability to expedite software and update delivery, aligning closely with customer expectations.

DevOps is not static; it evolves with technological advancements and industry shifts, continually refining its methodologies to align with new operational demands and opportunities for innovation.

The integration of DevOps into business operations transcends traditional boundaries, fostering collaboration, enhancing efficiency, and facilitating a culture of continuous improvement that drives organizations forward in a competitive environment.

Challenges in implementation

Implementing DevOps, especially in large, established enterprises, presents its own set of challenges. Cultural resistance to change stands out as a formidable obstacle. Employees and management accustomed to traditional workflows may find the shift to a DevOps culture unsettling or challenging. Addressing this resistance requires more than mere mandate; it necessitates fostering an environment where the benefits of change are clear and embraced at all levels.

While DevOps continues to emphasize team autonomy and the efficient creation of value, its practical applications are constantly adapting. No longer confined to a rigid set of practices, DevOps now molds itself to the unique contours of each organization’s needs.

Additionally, complex legacy systems in established enterprises pose a significant hurdle. Integrating modern DevOps practices into systems that were not designed with such agility in mind requires thoughtful planning and often substantial modification.

Impact of AI and machine learning

Artificial Intelligence (AI) and Machine Learning (ML) are playing an increasingly important role in the world of DevOps and cloud services. These technologies hold the promise of improving the daily work of developers, operators, and architects.

One area where AI and ML are making a difference is in predictive analytics. By analyzing historical data, these technologies can anticipate issues before they occur. This proactive approach minimizes downtime and reduces the need for reactive troubleshooting.

AI-driven automation is streamlining repetitive tasks, freeing up valuable time for teams to focus on more creative and strategic aspects of their work. For example, AI-powered chatbots can handle routine customer inquiries, while ML algorithms can optimize resource allocation in cloud environments.

AI in code generation and data governance

Integration of AI goes further than operational efficiency. It extends into code generation and data governance. AI-driven code generation tools can help developers write code faster and with fewer errors. AI and ML models are aiding in data governance by ensuring data quality, security, and compliance.

No-code and low-code development platforms are also benefiting from AI enhancements. These platforms, which enable non-developers to create applications, are becoming more accessible and powerful with the integration of AI-driven features – empowering business users to participate more actively in the application development process.

Rise of platform engineering

The shift towards platform-centric thinking is leading to the formation of new teams and the adoption of innovative techniques and tools.

Platform engineering is a concept that’s gaining traction, involving creating and maintaining robust, scalable platforms on which applications and services can be built.

Platform engineering teams are responsible for designing and managing the infrastructure, middleware, and shared services that enable developers to build and deploy applications seamlessly. These teams collaborate closely with development and operations teams to ensure a smooth development and deployment process.

Influence of “team topologies”

The book “Team Topologies” by Matthew Skelton and Manuel Pais has had a profound impact on how organizations structure their teams to support cloud-based platforms – introducing the idea of team types, such as platform teams, enabling teams, and stream-aligned teams.

Platform teams, in particular, play a central role in platform engineering – focusing on creating the foundational components and services that other teams can leverage to build their applications. This is an approach that promotes a clear division of responsibilities and fosters a culture of collaboration and innovation.

Adoption of FinOps – Increased focus on cloud costs

As organizations continue to migrate their workloads to the cloud, there is a growing emphasis on managing and optimizing cloud-based costs. The discipline of Financial Operations, or FinOps, is gaining prominence as a means to achieve visibility, ownership, and control over cloud spending.

FinOps practices involve tracking and analyzing cloud usage, setting budgets, and implementing cost-saving measures. This not only helps organizations manage their expenses but also ensures that resources are allocated efficiently.

One of the challenges in cloud cost management is the complexity of pricing models offered by cloud providers. FinOps teams work to decipher these models, identify cost optimization opportunities, and implement strategies to reduce unnecessary spending.

FinOps’ adoption reflects the increasing importance of cost management in the cloud-native era, with organizations striving to optimize their cloud spending.

Cloud-native frameworks are seeing broader adoption in diverse systems

Cloud-native frameworks and tools are experiencing widespread adoption in 2024. These frameworks enable the development and deployment of applications designed specifically for cloud environments. Some noteworthy trends include:

WebAssembly (Wasm)

As a binary instruction format designed for web applications, WebAssembly distinguishes itself by enabling code to execute with high performance on various platforms. Developers leverage WebAssembly to create applications that excel in efficiency, security, and independence from specific platforms.

The architecture of WebAssembly facilitates a closer-to-native execution speed, enhancing the user experience by reducing the latency often associated with web applications.

Its design focuses on safety and sandboxing, which are paramount in mitigating the risks associated with running code from the web, thereby bolstering application security.

eBPF (Extended Berkeley Packet Filter)

eBPF offers capabilities for real-time monitoring and tailored processing of network and system events. Its utility in providing granular visibility into system and application behaviors marks a substantial advancement in observability and security domains.

Developers and operators use eBPF to craft sophisticated monitoring and debugging tools that were previously difficult or impossible to implement, enabling them to respond swiftly to emerging issues and optimize system performance.


OpenTelemetry is a comprehensive toolkit comprising APIs, libraries, agents, and instrumentation that collectively furnish extensive observability into software systems. By enabling organizations to gather, process, and scrutinize telemetry data, OpenTelemetry facilitates enhanced monitoring and debugging of applications.

The framework aids in identifying performance bottlenecks, understanding dependencies, and troubleshooting issues, thereby contributing to the stability and efficiency of software systems.

Sustainability and green computing

Sustainability and green computing are also gaining traction within the cloud-native community – with the rising awareness of environmental concerns, organizations are seeking ways to reduce their carbon footprint in the digital space.

Cloud vendors are stepping up to the challenge by offering tools and services that enable businesses to monitor and control their carbon emissions, including:

  • Tracking the energy consumption of data centers
  • Optimizing resource utilization
  • Using renewable energy sources

As cloud-native practices are further adopted, such as containerization and serverless computing, it leads to more efficient resource utilization, reducing both energy consumption and carbon emissions.

Tim Boesen

January 25, 2024

7 Min