The COVID-19 pandemic has resulted in a surge in technology adoption by enterprises. Enterprises leverage technology for competitive differentiation and to gain new markets.

More and more enterprises transition from on-premises to the cloud and operate in hybrid environments. A multi-cloud framework integrates public and private clouds and legacy data centres. Such cloud-based assets offer elasticity and scalability. But the new landscape also throws up operational challenges and constraints. AIOps enable enterprises to understand the fast-changing landscape and overcome the challenges. This tech blog explains how enterprises leverage AIOPs for successful multi-cloud deployments.

1. Mastery over Cloud Transformation

Cloud transformation projects are complex and huge, often running into years. The change encompasses several areas and passes through several phases. Success depends on the flexibility to make adjustments when needed.

Data grows at an exponential pace in today’s age of Big Data. While the cloud offers a viable solution to host Big Data, enterprises need robust tools to make the data accessible and analyse it.

The success of cloud transformation depends on a unified Information Architecture for the data.

Modern applications that use containers, microservices and orchestration tools need standardised, automated processes. It also needs structures compatible with DevOps and Machine Learning Operations, with seamless portability and interoperability.

A crucial decision to make during the migration to the cloud is whether to embrace managed service available from big cloud providers or use workloads as a commodity between different providers

AIOps platforms become valuable assets during such cloud transformation. AIOps platforms provide independent observations. IT teams may make independent observations, without a tie-in to any service.

AIOps brings together data from various sources and makes it accessible irrespective of the location of the service. It enables tracking the data, understanding where the data comes from, and the parts of the system it has touched.

2. Managing the Complexity of Network Monitoring

Many enterprises graduate from monolithic applications to container-based microservices. While such services enable rapid deployment and other benefits, troubleshooting becomes difficult. The complex nature of container-based deployments makes the diagnosis of issues difficult. Tracing patterns that lead to failure also becomes hard.

Enter AIOps. AIOps based platforms:

• Analyse the entire data running in the system, to identify aberrations. The analysis covers operational, technical, commercial, and all other data. AIOps detects anomalies in real-time and enables prompt fixes.
• Tracks metrics, logs, and events. Machine learning algorithms analyse deviation from regular patterns.
• Automates network monitoring. It covers areas of the network landscape not covered by conventional network monitoring tools. Several features that operate under the hood. An ideal microservice does not last for more than a few minutes. Various services spin-off to different transactions. AIOps enables the IT team to view every transaction that goes through the services and ensures the fidelity of the system. Conventional network monitoring tools cannot catch all such transactions.

AIOps based platforms offer a unified way to understand the hybrid landscape. A single pane of view enables easy monitoring, provisioning, managing, and securing all clouds. Enterprises relying on such insights remain ahead of the curve and become proactive.

3. The Need for Informed Decision Making

Business success depends on the quality of decisions. Successful decision-making requires identifying the problem, understanding its magnitude, and finding a resolution.

AIOps complements decision making. The platform derives insights from many signals to augment information and makes such information accessible at the right time. The IT and operations team gains the ability to reflect on events. They may analyse the impact of changes on business operations and set better plans.

The improved visibility enables rich insights and a better understanding of the business. AiOps makes explicit how different parts of a business ecosystem interact. Rich visualizations make explicit the trends if things stay normal, or change.

Consider marketing. Most enterprises attribute marketing failures to the function itself. But the failure may have nothing to do with the marketing effort. Deep network monitoring, enabled by AIOps, may pinpoint operational problems that caused failures.

4. Enabling Agile Operations

IT and operations teams have traditionally been reactive, and often play catch up with the competition. They lose many opportunities by not being able to recognize signals that could lead to better outcomes. AIOps drives agility and resiliency, offers scale, and acts as a catalyst for innovation.

Consider the changes brought about by COVID-19. The pandemic has caused massive shifts in customer behaviour. Telecommuting, lockdowns, online shopping and digital transactions herald big changes. Only extremely agile businesses can keep pace with such changes. AIOps offers relevant insights to enable businesses to cope with change. For instance, many retailers found online sales and home delivery during the lockdowns, similar to Black Friday levels. AIOps offered such insights, enabling businesses to identify such trends and work accordingly.

5. Accelerated Digital Transformation

The biggest challenge facing enterprises today is keeping up with the pace and velocity of changes. The concept of the monthly release of updates is passé. New deployments now take place every day or even every hour.

AIOps visualise the landscape, allowing the IT and operations teams to keep up with the fast-paced changes. AIOps deploys Machine Learning on real-time data streams to make data analysis more potent and relevant.

AIOps drives innovation through the hybrid and multi-cloud environment. Speedy innovation speeds up digital transformation and reimagines business models.

An integrated multi-cloud and AIOps strategy deliver business agility to realise long-term value.

6. Improved Customer Satisfaction

Smart businesses place the customer first in everything they do. They orient their systems, including cloud deployments, in a way that serves customers well.

Things invariably go wrong in any business, especially when handling large volumes. The customer support or operations teams swamped with tickets is a disaster, at any time. The deep visibility offered by AIOps makes explicit the extent of deviance. It leads to instant mitigation measures. With the prompt interventions enabled by AIOps, ticket numbers reduce drastically. Employees spend less time on firefighting. They get more time to engage with customers better or undertake tasks that add value.

AIOps delivers intelligent insights that enable enterprise teams to proactively manage the complexity of their cloud-based deployments and derive business benefits. AIOps based platforms unlock silos and place the focus on business outcomes. It supports agility and change and pushes proactivity. AIOps enable enterprise teams an opportunity to reinvent their relationship with the business. It heralds a fresh, customer-centric proactive attitude towards work and digital transformation.