Cloud is now the destination of choice for several SMEs and large enterprises, thanks to lower costs and improved performance versus on-prem infrastructure. This has sparked many new technological advancements, including artificial intelligence (AI) and machine learning (ML) cloud IT operations management (ITOM) tools.

Trianz experts were at the forefront of the cloud revolution, and now our experts help our clients leverage emerging cloud AI and ML technologies to automate their cloud operations workflows. Automation can significantly reduce the administrative burden on your IT department, while simultaneously reducing the risk of human error—both of which contribute to business agility and resilience. Microsoft Azure, released in 2010, offers both.

Leverage the Benefits of AI and ML on Microsoft Azure

AI and ML, though efficient, are still emerging technologies and are not suited for all use cases. For that reason, we recommend leveraging AI and ML for low-level administrative workloads initially.

By implementing AI and ML on Microsoft Azure, your enterprise will experience benefits like:

  • Efficient AIOps and MLOps – AI and ML workloads are incredibly resource-hungry, making the Azure cloud an excellent choice for Artificial Intelligence Operations (AIOps) and Machine Learning Operations (MLOps). Microsoft Azure offers elastic resource scaling and lower overall resource acquisition costs compared to on-prem, driving down the cost of AIOps and MLOps in the cloud.

  • Edge processing for AIOps and MLOps – AI and ML workloads are highly sensitive to fluctuations in read/write latencies, as well as web packet latency, meaning the closer you are to the data center, the better. Edge computing is a new computing paradigm that aims to bring data center resources closer to the user or data source, reducing latency and improving performance. This will improve the efficiency of AIOps and MLOps on Azure, reducing costs and increasing processing capacity.

  • Pre-trained ML models – On Azure, many enterprises believe that custom models will be needed to leverage ML. While a custom model will offer more tailored processing for niche workloads, many ML workloads can be performed using pre-trained models on Azure. These models are available through MicrosoftML for R for statistical workloads and MicrosoftML for Python.

Azure AI and ML Services with Trianz

Trianz is an industry-leading AIOps and MLOps consulting firm, which has helped hundreds of our Fortune 500 clients leverage the benefits of AI and ML on Microsoft Azure. We have been at the forefront of new technological developments since our founding and have developed unrivaled knowledge and expertise across the cloud computing industry.

We offer a range of AI and ML assessment and implementation services, including:

  • Candidacy assessment – Owing to the niche circumstances in which you can use AI and ML, it would be wise to understand your business candidacy for these technologies. While these technologies have many benefits, you need to be able to leverage them to experience the benefits.

    Trianz experts can perform a full candidacy assessment of your existing Azure infrastructure to determine your suitability for AIOps and MLOps. We can also determine candidacy for enterprises looking to migrate from on-premises to Azure. If we deem you suitable, we can help you start leveraging the extensive functionality present on the Azure AI and Azure Machine Learning platforms.

  • AIOps and MLOps – ITOM in the cloud can be an arduous task, due to the new skills and competencies that are required to build optimized and secure cloud solutions. Due to IT operations mismanagement, this can lead to inefficiencies and security holes in your network, driving up costs and putting your data at risk.

    With AIOps and MLOps on Azure, these technologies take the guesswork out of ITOM. Our experts can point an AI at your pre-existing Azure data analytics platform, so it can analyze and monitor your network. Then, we add ML into the mix to automate the remediation of low-level service requests on Azure, reducing the ITOM burden for your IT department.

  • Fuel your AI and ML with data lakes – AI and ML platforms require a gargantuan amount of data to maximize their potential. This is because AI and ML uncover hidden correlations in your data, meaning more data results in more correlations and insights.

    Our experts can implement a solution based on the Azure Data Lake platform to centralize your data and optimize it for AIOps and MLOps workloads. Specifically, Azure Data Lake Analytics taps into the Azure AI and Azure Machine Learning platforms for a unified data storage and analysis solution on Azure.

Leverage AI and ML on Azure with Trianz

Back in 2004, the introduction of the cloud revolutionized enterprise computing. Now, AI and ML represent an even larger paradigm shift. Trianz will work with you to simplify your digital evolution and help you leverage these bleeding-edge technologies in a risk-averse manner.

The future is automated. Join thousands of businesses that are already leveraging AI and ML on Azure with Trianz.

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