2018 saw how digital transformation disrupted business by changing the way businesses gleaned customer insights, leveraged technological capabilities and experimented to drive growth and boost revenue, and become market leaders. Over one trillion US dollars were spent by businesses on public cloud platforms, edge computing, microservices, AI and ML, VR and other cutting-edge digital technologies to enhance customer experiences, improve business agility, and increase employee engagement.
Experts predict that in 2019, digitalization will further speed up innovations, and push for adoption of these new technologies to gain competitive advantage without losing sustainability. Likely, these will be the 7 major trends that will transform the way enterprises look at digital ops management this year.
It is important for organizations to stay updated with the latest trends in digital and IT operations management in order to stay ahead of competition. Some of the digital and IT operations management predictions are listed here -
In the third quarter of 2018, 65% of the market share of public cloud platforms and infrastructure was with tech giants Amazon, Google, and Microsoft. Businesses are today looking for multiple cloud providers so that they can take advantage of innovative products, avoid lock-ins, gain a global presence and benefit from flexible pricing strategies.
According to Gartner, by 2022, enterprises will allocate 28% of their spending to public cloud platforms and infrastructure. Providers of public cloud services are aggressively offering private cloud solutions to garner a greater share of the data center market. Enterprise services who want data sovereignty, compliance or latency without giving up the cloud's agility and flexibility will rely heavily on managed private cloud offerings. The big three cloud platforms made some interesting announcements -
CIOs were happy with the ‘lift and shift' strategies when they had to move complicated, outmoded legacy software to public cloud services in the initial stages of moving to the cloud. However, we may see legacy portfolios being rebuilt in 2019; only then will enterprises be able to truly leverage the security, flexibility, and utility pricing advantages of the cloud. It is more viable in the long run if you want to reduce technical debt and unlock enterprise agility.
Logs, metrics, traces and other data sources will be utilized by DevOps teams for recognizing, authenticating, and debugging cloud-native systems. Modern observability demands the ability to combine and glean pertinent insights from the observability pipelines, with the help of tools like Prometheus to monitor, Fluentd for logging, and Jaeger for distributed tracing.
IT professionals will require new techniques for managing independent cloud-native services; however, it is vital to understand the relationships between the entire system and individual elements so that troubleshooting microservices in production will be much more efficient.
The standard deployment method in the recent past for enterprise services that have agility, scalability, reliability, and high availability has been to use software containers. Moving from managing virtual machines to orchestrating containers; from monolithic development architecture to agile microservices; these will forever change the way cloud-based apps are built, deployed and optimized by enterprises. Managing the health and performance of services that are containerized will give rise to the necessity of IT Ops teams learning new skill sets and developing new competencies. Gone are the days of depending on manual scripts for managing massively distributed systems; they will need to adopt ‘infrastructure as code' principle for provisioning, deploying, monitoring alerting, and automatically scaling services that are cloud-native.
AIOps or artificial intelligence for IT operations is something modern IT infrastructure professionals need to stay abreast of the range, momentum and magnitude of IT data, both event and operational. Teams will be able to stop service outage proactively, take stock of incidents in real time based on contextual knowledge, and resolve problems with AIOps tools. Enterprises will be able to execute and optimize mission-critical systems with AIOps in the following ways -
It is possible to boost key metrics to manage incidents: these include mean times to detection, response, restoration, and incident volume resolved in a particular service window. Integrating machine learning and techniques of data science in AIOps delivers quicker incident coordination and response, while at the same time, reducing human effort, and time spent on every alert with advanced analytics, probability, and root cause analysis etc.
With AIOps you will be able to combine event and incident insights from multiple IT management systems, whether on public cloud or on-premises. Shared AIOps platforms offer central visibility, speedier impact analysis, and enhanced coordination for a wide range of stakeholders like business sponsors, app owners, and infrastructure teams.
For a business to compete effectively, IT teams should move from just managing hybrid IT infrastructure to the prioritization and support of services that are critical to the business. Ops management that is focused on service is a combination of knowledge about customers, business insights and pertinent metrics, and focuses on improving digital performance, enhancing engagements with customers and supporting business goals. IT professionals must concentrate on the business value of the IR services, and also deliver comprehensive infrastructure visibility and control in business processes.
Companies that want to emerge as winners in 2019 will need to have rock-solid strategies and be very focused on executing them effectively. The way in which businesses adopt and/or react to these vital trends in IT will pave the way for further innovation, operational change, and business value.
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