Blog Post Top IT Automation Trends in 2024: Hyperfocus on Agility and Efficiency
Few of our top nine IT automation trends are wholly new for 2024. Rather, most automation priorities are taking on a new urgency as enterprises demand faster, better, and more efficient digital products and services.
Editor’s Note: This blog post was originally published in January 2022, but is updated each year with our latest predictions. Here are the IT automation trends we see for 2024 and beyond.
IT automation trends have historically been dictated by the goals of IT operations (IT Ops). However, as the IT market continues to shift to the cloud, there’s a growing list of enterprise teams that have adopted automation as core to their role. The following list provides insight into how IT operations teams are partnering with their IT colleagues in DataOps, DevOps, and CloudOps to help their organizations deliver on crucial, top-level business strategies.
1. Demand for Cloud-Native Platforms Continues to Soar
As cloud adoption reaches saturation point, cloud-native platforms (CNPs) are no longer just a trend, but the very fabric of modern digital infrastructure.
However, the game has changed. Enterprises are moving beyond mere adoption to grapple with the complexities of managing workloads across hybrid and multi-cloud environments, pushing the boundaries of edge computing, and seeking to leverage artificial intelligence (AI) and machine learning (ML) models. Automation and orchestration are key to fully optimizing CNPs. This includes approaches like:
- Infrastructure as code (IaC): automating infrastructure provisioning and configuration in the cloud.
- Container orchestration: managing containerized applications across different environments.
- Continuous integration and continuous delivery (CI/CD): automating software development and deployment pipelines.
Those who embrace CNPs strategically and adapt to their ever-evolving capabilities will be the true digital pioneers of tomorrow.
2. Distributed Cloud and Hybrid IT: Beyond Multi-Cloud to Decentralized Agility
No longer a future vision, distributed cloud has become the infrastructure model of choice for modern businesses in 2024. This shift goes beyond simply using multiple cloud providers; it's about decentralizing resources across diverse environments, from cloud platforms to on-premises data centers and even user devices.
This decentralized future demands intelligent automation and orchestration platforms that can seamlessly manage and optimize processes across diverse environments. By embracing distributed cloud and its transformative potential, businesses can unlock unparalleled agility, resilience, and competitive advantage in the digital age.
3. Infrastructure Modernization Transforms the Mainframe Monolith
For decades, the mighty mainframe has served as the backbone of countless businesses, faithfully crunching data and churning out transactions. But the landscape is shifting. CNPs beckon, promising agility, elasticity, and scalability — qualities the monolithic mainframe struggles to match. Enter infrastructure modernization, a wave reshaping how organizations manage their IT infrastructure, with a particular focus on migrating mainframe workloads to the cloud.
But migrating these decades-old systems is no easy feat. Organizations need careful planning, skilled personnel, and robust migration tools to ensure a smooth transition. And in some cases, mission-critical applications still require the high availability and low latency offered by mainframes. A hybrid approach, leveraging both cloud and mainframe, may be optimal.
Whether fully embracing CNPs or taking a hybrid approach, automation is a critical consideration. You’ll need a modern platform that can simultaneously manage tasks on-prem and in the cloud.
4. Workload Automation Continues its Evolution to Service Orchestration and Automation
Anyone responsible for designing or executing their enterprise’s automation strategy, the growing prominence of the service orchestration and automation platform (SOAP) will be a big IT automation trend of focus in 2024. SOAPs offer many advantages over their workload automation (WLA) forerunners, starting with handling the needs of real-time, event-driven business models and the ability to automate just about anything in the cloud.
The larger goal of SOAPs is to drive business agility and digital innovation. These platforms achieve that by quickly integrating new technologies into larger workflows. SOAPs make it easy to connect to and control automated IT processes within any application, database, or platform that resides on-premises, in the cloud, and in containers. Once connected, enterprise end-users can centrally orchestrate automated workflows that span any connected tool within their entire IT ecosystem.
Looking back at our first three trends — cloud-native platforms, infrastructure modernization, and decentralized/hybrid environments — it’s easy to see why Gartner predicts that “By year-end 2025, 80% of organizations currently delivering workload automation will be using SOAPs to orchestrate workloads across IT and business domains.”
5. Automation for All: Democratizing Access to Automation Systems
IT Ops teams have long used WLA tools to automate IT tasks and jobs. As an increasing IT automation trend, enterprises are now empowering end-users throughout the business with self-service capabilities.
This trend is largely driven by a broader movement to decentralize IT services management. Traditionally, IT controlled all budgets and responsibility for anything related to technology. The cloud changed this by giving just about anyone access to technology. Supported by modern SOAPs, the rise of citizen automators — end-users who automate workflows in their most-used tools, like Teams and Slack — will continue, with more business users leveraging low-code/no-code tools to automate their own workflows.
We’ll also see demand from line-of-business teams who want access to automation as a service. With this model, IT Ops centrally controls the automation platform and provides it as a service to developers, data and cloud teams, and more.
6. The Rise of Holistic Observability
The first five trends in this list form an intricate IT landscape of interwoven workflows, distributed systems, and a wide user base that present a new challenge: maintaining visibility and control.
While traditional monitoring focuses on predefined metrics, observability empowers IT teams to understand the "why" behind their automated systems. It leverages diverse data sources, including logs, traces, and metrics, to paint a holistic picture of what's happening within the automation engine. This newfound transparency unlocks several key benefits:
- Proactive troubleshooting: identify and address potential issues before they escalate, preventing downtime and ensuring smooth operations.
- Root-cause analysis: precisely pinpoint the source of errors, even in complex workflows, eliminating guesswork and speeding up resolution times.
- Performance optimization: gain insights into resource utilization and bottlenecks, enabling fine-tuning of automated processes for optimal efficiency.
- Security monitoring: uncover anomalous behavior and potential security threats in real-time, strengthening overall system resilience.
The future of IT automation is all about gaining deep, contextual understanding of how systems behave. A SOAP like Stonebranch Universal Automation Center (UAC) helps pave the way for streamlined observability, offering a centralized stream of telemetry data from all corners of the hybrid IT ecosystem.
7. The Emergence of Machine Learning Automation
Much as data pipeline orchestration emerged onto the scene a few years ago, the newest frontier lies in orchestrating the entire machine learning (ML) pipeline. This involves seamlessly integrating, automating, and optimizing every step of the ML lifecycle, from data acquisition and pre-processing to model training, deployment, and monitoring. This intersection of the ML lifecycle and automation is called MLOps.
SOAPs are emerging as a leading conductor of the MLOps symphony. They provide the tools and infrastructure to:
- Automate repetitive tasks: free data scientists and engineers from manual ML tasks, allowing them to focus on higher-level strategic work.
- Enhance collaboration: effortlessly link the work of data scientists and operations teams.
- Streamline workflows: connect different ML tools and processes seamlessly, eliminating bottlenecks and optimizing the entire pipeline.
- Ensure governance and compliance: enforce data privacy and security regulations throughout the ML lifecycle, mitigating risks and building trust.
8. The Evolution of Data Pipeline Meta-Orchestration
Data analytics continues to be one of the fastest-growing segments of automation. After all, data doesn’t provide much value on its own. It needs to transform into actionable insights that help businesses succeed.
Modern data teams use DataOps methodologies to design, implement, and manage end-to-end data flows. This approach brings together data, development, and IT Ops experts to manage the dev/test/prod lifecycle of collecting, ingesting, standardizing, integrating, storing, and delivering data.
To architect, engineer, and manage complex data pipelines in 2024, IT professionals will increasingly turn to service orchestration and automation platforms as a meta-orchestrator of the entire data pipeline toolchain. However, they won’t use SOAPs to replace the pipeline’s highly specialized toolset. Instead, they’ll use SOAPs to centrally manage and orchestrate all automated processes across their pipelines from a single command center-like platform.
9. Generative AI: the Race is On
When discussing technology trends for 2024, it's impossible not to mention the rapid growth of generative AI (genAI). In the coming year and beyond, automation vendors will prioritize meeting enterprise demand for this evolving category of tools.
However, there's still a lot of work to be done. From incorporating genAI into the automation software itself to automating users' ML models and MLOps pipelines, automation can complement genAI initiatives in many ways:
- Proactively identify areas for process improvement: predictive analytics to forecast and resolve potential issues before they happen, suggest better utilization of development resources, and monitor and alert on possible SLA violations.
- Feed AI/ML models: automation of data and ML pipelines from source data to ingestion to deployment.
- Rapid development of integrations: reduce manual effort by automatically generating test-case scenario code and data for APIs.
- Generate automated tasks and workflows: combine genAI and jobs-as-code to create and deploy complex, domain-specific workflows, thus reducing effort while ensuring best practices.
- Self-service AI chat: support natural-language queries to learn about a tool instead of reading and searching documentation. This allows business users to build and execute automated workflows independently.
Leveraging automation software alongside genAI has the power to create a powerful synergy that fosters creativity, optimizes product development, and empowers end-users.
Final Thoughts About IT Automation Trends
As the IT professionals Stonebranch works with are well aware, task automation, job scheduling, and workload automation have long been on the automation agenda for many organizations. Of course, with the urgency driven by business users and additional IT functions, the requirement to centrally orchestrate an exceedingly complex list of disparate automation tools — both within and outside of IT Ops — has become a paramount objective in 2024 and beyond.
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