As digital services become more complex and numerous, organizations need IT automation to address the challenges of maintaining those services.
So, what is IT automation? And what are the best strategies to reduce manual labor so your team can focus on more mission-critical issues?
IT automation is the practice of using coded instructions to carry out IT tasks without human intervention. IT admins can automate virtually any time-consuming task that requires regular application. Scripts and procedures usually focus on a particular task, such as deploying a new microservice to a Kubernetes cluster, implementing data retention policies on archived files in the cloud, or running a vulnerability scanner over code before it’s deployed. The range of use cases for automating IT is as broad as IT itself.
At its most basic, automating IT processes works by executing scripts or procedures either on a schedule or in response to particular events, such as checking a file into a code repository. Automating IT processes can encompass more capability when it’s built on an observability platform, or when employing AI and machine learning techniques for AIOps.
Monitoring and logging are fundamental building blocks of observability. Adding AIOps to automation processes makes the volume of data that applications and multicloud environments generate much less overwhelming. When monitoring tools release a stream of alerts, teams can easily identify which ones are false and assess whether an event requires human intervention. AIOps brings an additional level of analysis to observability, as well as the ability to respond to events that warrant it.
DevOps and DevSecOps methodologies are often associated with automating IT processes because they have standardized procedures that organizations should apply consistently across teams and organizations. Vulnerability management is one example of a DevSecOps workflow that teams should automate to ensure vulnerability scans run regularly.
Similarly, digital experience monitoring is another ongoing process that lends itself to IT automation. As organizations continue to adopt multicloud strategies, the complexity of these environments grows, increasing the need to automate cloud engineering operations to ensure organizations can enforce their policies and architecture principles.
Effectively automating IT processes is key to effectively addressing the challenges of complex multicloud environments. With ever-evolving infrastructure, services, and business objectives, IT teams can’t keep up with routine tasks that require human intervention. This results in outages, increased costs, and frustrated customers. Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises.
Automating IT practices offers enterprises faster data centers and cloud operations, as well as increased flexibility and accuracy. Automating routine IT tasks eliminates the human element—and the potential mistakes that come with it.
Automating IT practices without integrated AIOps presents several challenges.
- Developing automation takes time. In many cases, it can take longer to automate a series of steps than to execute that sequence of steps at a given time. In essence, solving an immediate problem manually can seem faster. But, over time, this turns into a more time-consuming, inefficient, and costly approach. The increased demand to get things done quickly often takes priority over taking the time to successfully automate IT operations.
- Testing automation can be painstaking. It’s also crucial to test frequently when automating IT operations so that you don’t automatically replicate mistakes. While automating IT practices can save administrators a lot of time, without AIOps, the system is only as intelligent as the humans who program it.
- Monitoring automation is ongoing. Similarly, it’s crucial to monitor automated IT processes to ensure automation scripts run as intended. Expect to spend time fine-tuning automation scripts as you find the right balance between automated and manual processing.
While automating IT processes without integrated AIOps can create challenges, the approach to artificial intelligence itself can also introduce potential issues. AI that is based on machine learning needs to be trained. This requires significant data engineering efforts, as well as work to build machine-learning models. Other forms of AI, however, such as deterministic fault-tree analysis, can determine root causes based on a topological map of dependencies, which eliminates guesswork and manual verification.
These challenges are not a reason to shy away from automating IT processes. Organizations can effectively and efficiently automate IT by building it on an AIOps-based observability platform. This kind of automation can support key IT operations, such as infrastructure, digital processes, business processes, and big-data automation.
There are several types of IT automation tools that are particularly useful for a broad range of IT use cases, including the following:
- Infrastructure and operations tools. These tools are critical for automatically creating virtual infrastructure and for updating operating systems as well as deploying containers.
- Digital process automation tools. These capabilities support business processes, spanning internal business systems and customer-facing applications.
- Batch process automation. This service can orchestrate executing batch jobs on regular schedules.
- Big data automation tools. These tools provide the means to collect, transfer, and process large volumes of data that are increasingly common in analytics applications.
A unified approach to automating IT processes using a tightly integrated automation platform is essential to avoid poorly integrated, siloed services. An IT automation strategy should start by breaking down the workflow, the types of operations they will perform, and how teams can best monitor and optimize them in production.
The goal of automation is to reduce IT complexity. Therefore, teams need a plan for change. Consider how your team can use various IT automation tools together in coordinated workflows to execute business processes. Workflow optimization is one method for keeping automation scripts relevant and robust. By tuning workflows, you can increase their efficiency and effectiveness.
Additionally, a sound IT automation strategy includes AIOps at its core. Using AIOps for automating IT helps organizations more immediately pinpoint the root cause of an issue and automatically respond. This enables IT admins to spend more time on innovation, rather than constantly fighting fires.
Leveraging an observability platform informs how an organization can optimize workflows. An AI-driven observability platform is a foundation for implementing a successful IT automation strategy.
The Dynatrace Software Intelligence Platform provides automatic and intelligent observability that overcomes the challenges of automating IT processes for cloud-native environments. With AIOps at its core, Dynatrace minimizes the initial cost to get started and provides the ability to test and tune IT automation.