A beginner’s guide to automation and AIOps

If you’re ready to expand—or even start—your automation and AIOps strategy, you’ve come to the right place. This blog post is ripe with practical next steps that you can use to better understand, help persuade and begin to implement AIOps within your organization. The case for infusing artificial intelligence (AI) into your IT operations is compelling, with tangible benefits and strategic use cases.

First, let’s start with a basic premise—as IT systems become more complex and intertwined, automation is the most essential tool you have at your disposal. We define automation as the application of technology, programs, robotics or processes that help you realize outcomes with minimal human input and at a scale that exceeds human abilities.

Now let’s look at how automation—when applied to IT—helps you achieve better business results in three key areas, along with what every beginner should know to get started.

AI-powered observability solutions deliver advanced monitoring to provide you with the context you need to resolve incidents faster. Traditional monitoring tools might give you metrics and data, but they often lack the ability to provide a complete picture of the system’s behavior. Observability, on the other hand, focuses on collecting real-time data, logs and traces to create a holistic view of your IT environment.

What beginners should know about observability:

• Observability is not an evolution of application performance monitoring (APM). APM delivers debugging of applications whereas observability delivers an understanding of applications. Watch the video: 

• Observability relies on advanced AI algorithms to analyze vast amounts of data quickly and identify patterns and anomalies.
• Observability tools discover conditions you might never know or think to look for, then track their relationship to specific performance issues for root cause analysis and speedier resolution. Read the Enterprise Guide.
• Using observability early in development is a good thing because it allows DevOps teams to identify and fix issues in new code before they impact the end user.
• You can scale automatically with observability. For example, you can specify instrumentation and data aggregation as part of a Kubernetes cluster configuration and start gathering telemetry from the moment it spins up until it spins down.
• Observability benefits systems of all sizes by proactively monitoring critical components and providing early detection of anomalies. Read about observability myths.

While modern applications and IT systems are growing more complex, many cloud users still fall back on a familiar habit of overprovisioning resources to mitigate any risk to performance. Yet almost a third of organizations estimate that they wasted their cloud spend. Automated operations powered by AIOps can help you break that expensive approach and optimize your IT infrastructure, resource allocation, and cloud usage. By analyzing historical data and real-time metrics, AIOps can help you make intelligent decisions on resource provisioning, ensuring that you scale up or down depending on demand needs. The result is that you can assure application performance at the lowest possible cost.

What beginners should know about automated operations:

• AIOps can help reduce unnecessary infrastructure costs by identifying underutilized resources and recommending their optimization or shutdown. Start by rethinking your cloud operations.
• By automating resource provisioning, you can avoid manual errors and optimize the overall performance of your IT systems.
• A cloud cost optimization platform allows you to continuously automate critical actions in real-time at a scale that can’t be matched by humans, no matter how skilled.
• FinOps (Finance + Operations) is an evolving financial management framework that can be included in automations operations to help deliver cost savings and faster innovation. Watch the video: 

• AI-powered solutions that help you automatically manage operations can also help you create more sustainable IT by reducing waste. Read the guide: Accelerating FinOps and Sustainable IT.

Incident management is a vital part of IT operations. The speed at which issues can be identified and fixed—the mean time to resolution or MTTR – is often the difference between IT fire drills or happy customers. AIOps uses AI algorithms and data analytics to automate the detection, analysis and resolution of incidents.

Implementing an AIOps platform is an excellent first step for any organization. For example, AIOps platforms can monitor server logs and network data in real-time, automatically identify patterns indicative of an incident and trigger an alert to the IT team. This proactive approach helps IT teams respond swiftly, minimizing disruptions and improving customer satisfaction.

What beginners should know about incident management and AIOps platforms:

• Traditional incident management, which relies on manual time and effort, is quickly being replaced by AI-powered AIOps platform. Read the AIThority article (link resides outside ibm.com) on incident management.
• This AI-powered approach turns incident management from reactive to proactive (and even preventative). Get the Gartner Market Guide.
• AIOps platforms can ingest and correlate data from various sources to provide a comprehensive view of the entire IT landscape.
• Users can share this comprehensive view on a single pane of glass, meaning operational silos and traditional (and time-consuming) war rooms are out and collaboration is in. Read the blog: “Smarter IT operations management with IBM AIOps Insights”
• AIOps platforms may either be self-hosted or implemented as a SaaS solution. That allows organizations of any size to find the solution that works best for them.
• Self-hosted AIOps platforms offer more control and customization options and are a good option for complex operations, while SaaS-based AIOps platforms provide ease of implementation and scalability, allowing organizations to focus on using the platform’s capabilities rather than managing the underlying infrastructure.

No matter where you are on your digital transformation journey, IBM is here to help. We offer solutions that help you move out of the old “break-fix” model into an AI-powered approach to help you deliver exceptional customer experiences, assure application performance, reduce costs and tackle the many challenges of a modern IT environment.