1. Monitoring and AIOps delivers the ultimate DevOps platform.
This piece in DevOps Zone details how investing in innovative monitoring and alerting tools and procedures is key to fully embracing AIOps.
When it comes to delivering software through a DevOps model, the primacy of the platform is increasingly evident. DevOps platforms are multi-tenant, self-service oriented, developer-centric, and are an essential component of a multi-cloud strategy. They provide guide rails and standardized tools and technologies for developers to build, test, and iterate with ease. A core component that must not be neglected when operating a DevOps model, however, is resilience.
The ultimate goal for DevOps engineers when architecting a DevOps platform is to create an environment that feels as though it was made for the developer, by the developer. Reducing the time developers spend implementing various capabilities, such as security, testing, and monitoring features, allows them to focus on improving the delivery of their services, creating the optimal experience for both the developer and the customer.
Bringing automation into the remediation process through an AIOps platform furthers this enhancement as the chances for potential breaks in production are vastly reduced. This is the model that all service providers aim for with their DevOps strategy.
2. Africa is looking to emerging technologies like AIOps to fuel its economic recovery in 2022.
This article in Soko Directory explains how 80 percent of African companies are planning to move towards AIOps in the next year.
Economic recovery and growth are top of mind for countries in Africa, and many are now realizing that accelerated digital transformation is at the heart of achieving this.
Forward-thinking leaders, policymakers, and organizations are turning to AI – which is helping organizations experience the equivalent of 10 years of growth in less than one year in areas such as e-commerce.
By leveraging emerging technologies like AI, countries can surely drive greater efficiencies, create jobs, enhance competitiveness and productivity.
The increased use of AI isn’t limited to organizations and businesses. AI is playing a key role in crucial industries such as agriculture. It can help to deliver data analytics and predictive insights to help farmers make better-informed decisions. This will lead to improved agricultural outputs for smallholder farmers and big agribusiness players – promoting sustainable development and boosting food security.
3. Here’s the real reason AIOps will change IT.
An article in Intellyx the uptick in the adoption of AIOps and why it is the future of IT.
According to recent data and anecdotal conversations, AIOps seems to finally be picking up some serious adoption steam. Many industry observers attribute this growth to just the normal adoption cycle running its course. Others point out that increased complexity and criticality levels are leaving AIOps as the only recourse for resource-strapped IT organizations.
As AIOps goes mainstream, there will be those that leverage it to gain some incremental value. And then there will be those that allow it to transform almost everything about how IT functions. And the difference will play a huge role in determining who wins and loses in the experience economy.
Organizations will only realize the full value from their AIOps investments when they view it as a transformational tool that helps them build the political, cultural, and procedural supports to reorient the IT function around delivering digital experiences that win in the market — and create a space where no one ever again wonders what that server is running.
4. AIOps is the riddle wrapped in the mystery inside the enigma.
The term AIOps leaves some feeling confused about what it really means. This article in Forrester tries to begin to explain AIOps by starting with some common questions.
- Is AIOps a technology, a platform, a solution, a capability, or a combination of each?
- Does one size fit all?
- Is the end state the same for everyone?
- Will every effort look identical in how it achieves its end state?
- Are there commonalities across industries and organizations? (tools, skills, approaches, objectives)
We need to come to some agreement on these questions to move forward. Ultimately, we need to arrive at a common understanding that clears up some of the confusion around the term AIOps and agree on some fundamental principles about the concept of AIOps.
Just getting started with AIOps and want to learn more? Read the eBook “Your Guide to Getting Started with AIOps»
