How to make Digital Transformation work

The anytime, anywhere, any device access enabled by cloud applications calls for unified endpoint management along with security for desktops, laptops, tablets, and mobile phones. Shailesh Kumar Davey Vice President ManageEngine, talks about this and more.

In an era of rapid digital transformation, how is the IT management paradigm changing?

Digital automation is an overarching term that includes process automation and orchestration, document automation, mobility, and analytics enabled by technologies like Artificial Intelligence-Machine Learning (AI-ML), Natural Language Processing (NLP) and speech synthesis. This is made possible by a plethora of best of breed software applications hosted in public, private, or hybrid cloud environments. To maximize their benefits, these applications need to communicate with each other without residing in silos. Moreover, the data should be consolidated into a system of record accessible to employees who need it, as long as proper security constraints are in place. IT teams have to ensure that these applications have platform-like capabilities so that they can be extended, customised and integrated.

Companies need to react fast to market stimulus, develop and roll out software features without compromising quality. This calls for an automated approach in development and operations, wherein agile project management, continuous integration, automated testing, continuous delivery, and staged application rollout are common practices. Hybrid cloud management along with virtualization/container management will become more common in IT operations. Software defined storage will become crucial to store data in multiple formats to aid deep analysis of data and to keep storage costs in check. Application security and identity and access management will facilitate access from anywhere with any device, enabling calibrated access to data across trust zones. End point management to ensure that access devices are secure and protected will also become critical.

What is the role of AI in ITSM (IT Service Management)? What are the major applications of AI today?

Repetitive tasks in ITSM can be automated with AI if we have the right kind of data. AI can play a big role in trouble ticketing because most data in service desks is human generated. Powerful NLP techniques are being deployed in modern service desk solutions to enhance self service capabilities via chatbots, Kbase search, grouping similar tickets and auto tagging of tickets. Automated routing of tickets to agents with the requisite technical skills to ensure faster turnaround becomes possible with AI. Predictive analytics of KPIs like response time, agent work load, and open rates can help in appropriately staffing the service desk. Automated template answer selection and collaboration among agents can further improve their productivity.

Another major application of AI is in cloud management and cloud services. The enormous growth of cloud computing has resulted in a huge amount of data generated from cloud management systems. Utilising AI to analyse vast amounts of collected data helps the tech teams to gain a deep understanding of their systems. This means better alerting, proactive monitoring of availability and identification of the root cause of failure events—all of which ultimately enable organizations to provide the best possible customer experience and better manage cloud costs.AI can play a vital role in IT security and can lessen the burden of IT security analysts. Security analysis in the hybrid world calls for analysing large volumes of data and represents the search for the proverbial needle in hay stack. Data analytics and AI can augment the role of the analyst and help in automated anomaly detection, malware detection, security log analysis, privileged user monitoring, and drift in configuration.

With more and more organizations shifting to the cloud, how has that affected the processes and the methods they follow to manage their IT?

The ease of public cloud has raised the expectations of enterprise users, and they now want their organization IT to service their request similarly. This is classic case of consumerization of IT. Hence some of the relevant public cloud technologies have been made available in the private cloud by both commercial and open source vendors. We will see will more of such private cloud practices in the enterprise data centre. The anytime, anywhere, any device access enabled by cloud applications calls for unified endpoint management along with security for desktops, laptops, tablets, and mobile phones. Especially on tablets and phones, the variety of vendors and BYOD polices will challenge the IT team. Federated Identity and Access Management (IAM) has gained prominence. Federated IAM takes the Active Directory in the enterprise data centre and syncs it a cloud identity provider so that uniform IAM policies can be served to the users.

Data is the new oil. How are organizations handling the explosion of data and what are the security and regulatory concerns?

Technologies like AI, ML, NLP, and Optical Character Recognition (OCR) calls for large volume of data to be collected, stored, organized and processed. The data has to be safeguarded at all stages, whether it’s at rest, in motion, or at the point of usage. Privacy and security regulations are becoming stricter around the world. Data sovereignty requirements call for in-country data centres with data spread around in multiple data centres. Various techniques like encryption at rest and in motion, source tagging of data to record where it originated so that its access can be restricted accordingly, and data anonymization are becoming common place.
More than the technology, the organisational culture has to change. The IT team along with the legal/privacy/security team will have to sensitise the employees about the various regulations and also put practices in place to safeguard customers' data. The practices could start with the mundane—e.g., how to safely dispose of printed data—and escalate all the way up to having a data privacy officer.

How are DevOps and microservices changing IT management?

Cloud-based applications have redefined application development and software development life cycles. Monolithic applications have been broken down into microservices, which have been further broken down to serverless functions and Function-as-a-Service (FaaS). What used to be a 3-tier application now has lots of software pieces—referred to as separation of concerns—like the front end that serves end users, the back end that deals with databases, caches for faster recovery of data, Layer 3/Layer 7 software-based routing, and much more. All of these pieces are talking to each other via API endpoints and running on virtual/container environments with software defined storage and networking.

Each of these components may have independent cycles of development and deployment based on its usage, geographical spread of its users, and criticality of related issues. For example, financial or ERP software will be extremely critical during at the end of the month and hence cannot experience downtime during those periods.
The IT operations team has to manage the servers, the software application framework, the network connecting the various components, and the security of each component. Concurrently, they should maintain the agile nature of development and deployment. Configuration of servers, switches, applications, and databases is treated as code and is automated with the help of configuration management tools.

Network operation centre, security operation centre, and application and server performance teams all have to work together to troubleshoot performance problems. Automation, software control, rollback, and tractability are the key to a successful rollout and maintenance. DevOps has truly arrived.