Change is a constant in modern enterprises, to meet varying business needs as well as to optimize security, cost, and process efficiency. This means IT operations teams need to play dual roles: ensuring IT stability while enabling frequent change requests to software and hardware.
Each day IT teams manage many types of change requests. The most basic ones are part of the technology life cycle: commissioning new applications and devices, upgrading them, and decommissioning outdated ones. There may be scheduled changes like adding more disk space to accommodate updates, periodic changes like applying patches to applications for security and compliance reasons, one-time changes like migrating on-premise infrastructure to the cloud, or even emergency changes to deal with security attacks or system crashes.
Every change request has a direct or indirect effect on enterprise operations. While smooth change management results in smooth operations (most of the time!), a poorly executed change can create a domino effect of problems.
In recent years, the cadence of IT transformation has speeded up. This, predictably, is driving an increase in change requests. And that exposes the gaps in how they are managed.
The current state of change management
Tools for IT operations do offer capabilities to help make change easier, targeted towards certain aspects of change management.
Specifically, most IT service management (ITSM) tools have pre-built change management components. These make it easier for users to request changes (leveraging custom forms or change catalogs) as well help the change management process with customizable, often adaptive, workflows and change approvals roles and policies. Such ITSM tools can also provide visibility into other applications and platforms sharing the Configuration Item or CI that needs to change, highlight any conflicting change request, and help schedule changes and maintain a record of changes.
Sometimes, changes might cause negative impacts. That is, any change in the existing IT ecosystem may cause events or incidents, not only for the entity that was the target of the change, but also for entities sharing resources and on downstream processes. Best-in-class AIOps solutions like Digitate’s ignio™ AIOps platform can not only detect such incidents, but leverage built-in capabilities and knowledge of the enterprise IT context to understand the root cause, which in this case was a change request. This ensures mitigation of point issues (events, incidents, and downtimes) linked to any IT change.
However, even with these capabilities, IT teams often struggle to get end-to-end visibility and analytics on the changes happening across the IT ecosystem, which is needed for strategic planning activities. Also, often a change might have a prolonged or longer-term impact on the IT ecosystem, which makes it difficult to understand the cause and impact of any IT change.
In many organizations, IT operations teams do not have a precise, detailed approach to planning for changes, so they are often unaware of their potential impact. This results in unexpected delays and outages, as well as excessive time spent planning.
Leveraging AI to understand change impact
With our recent release of Eagle, the latest version of the ignio platform, Digitate now offers an AI-driven approach to assess the causes and impact of IT changes, making change planning more efficient. Using powerful new AI capabilities, the Eagle version of ignio not only analyzes change events but augments the analysis with behavioral changes in enterprise operations.
Now, ignio can analyze IT change tickets to capture all reported changes, such as patches, upgrades, application commissioning, or user onboarding. ignio then correlates this information with knowledge of the enterprise IT context, as well as analysis of historical and real-time metrics and events data to discover any behavioral changes in the enterprise (such as rising CPU utilization, increases in “service down” events, or outliers in URL response time).
Digitate takes an AI-based approach with the new change management function to assess behavioral changes that are linked to formal change requests. Analyzing the reported change requests and observed behavioral changes together can lead to very useful insights, such as:
- Why is a certain change requested?
- What is the effect of executing a change?
- Are there any unauthorized changes?
- Which entities/changes are high-risk?
Unlike other tool vendors, Digitate also draws on the power of analytics, to provide better insights into the changes, and helps de-risk the process of change management.
Key use cases where AI can improve change management processes
- Augment change planning and reduce change-induced risks
Most planned and periodic IT changes follow a change cycle, based on the type of entity and business need. For example, an operating system may require quarterly upgrades, a server system may require configuration changes every three weeks, and so on. The new AI-powered capacities in Digitate’s Eagle release provide an end-to-end view of changes across the enterprise, to help improve change planning.
- Identify entities at risk of missing changes
The Eagle release can highlight any process gaps leading to inconsistent execution of changes across the IT estate. For instance, if the servers in one location aren’t getting patch upgrades as often as servers in another location, it highlights the risk that the first servers may not be updated and policy-compliant.
- Assess the possibility of negative impacts
By correlating IT change request tickets with events and metrics data, the Eagle release can predict failures from change requests. For instance, for a particular server, it can correlate the reported change (a Windows patch upgrade) with reported issues (more reports of OS crashes). This helps predict and prevent similar issues from happening on other servers due to the same change request.
- Assess the causes and long-term effects of change
The Eagle release can mine long-term behavior and performance patterns before and after any change, to understand why a change was requested and what impact it has.
For instance, it can identify a trend of high-CPU utilizations of a server leading to frequent service outages as the cause for a patch update. It can also find the positive impact of the patch upgrade in terms of better CPU utilization and fewer service outages.
This is useful for both IT teams and application owners as it can help identify and mitigate similar issues using the same changes.
Also, by analyzing vital trends, IT managers can identify high-risk entities or changes and take appropriate actions.
As a leading provider of AI and automation solutions to transform digital operations, Digitate takes a unique approach to enable IT and business operations with intelligent capabilities that leverage our cutting-edge AI research. Change analytics is one of the many innovative new capabilities that are part of our latest Eagle release. Click here for more information on Eagle.
