AIOps is an umbrella term for using complex infrastructure management and cloud solution monitoring tools to automate the data analysis and routine DevOps operations. The main flaw of system monitoring tools built 10 or even 5 years ago is that they were not built to meet the demands of the . They cannot either deal with the sheer of the incoming data, be able to process all the of the data types or stay on par with the of the data input. As a rule of thumb, such have to split the data into chunks, separate what is seemingly important and cut off what is seemingly unneeded, operating with focus groups and statistical samples, instead of dealing with the whole integrity of data. 3 V’s of Big Data volume variety velocity cloud monitoring solutions The most important result is that some important patterns might be left unseen and totally excluded from the picture on the phase of data analysis. This renders the whole process utterly useless, as if Big Data analysis cannot produce actionable business insights, it cannot deliver the 4’th and most important V of Big Data — . data visualization Value AIOps enters the scene Processing all the incoming machine-generated data on time is not humanly possible, of course. However, this is exactly the sort of tasks algorithms like excel at. The only remaining question is the following: how to put these tools to good work in the daily life of DevOps engineers? Artificial Intelligence (AI) deep learning models Machine Learning (ML) Here is how AIOps can help your IT department: . An ML model can be trained to process all types of data generated by your systems — and it will do so in the future. If a new type of data must be added — a model can be relatively easily adjusted and retrained, keeping the performance all-time high. This will ensure data integrity and fidelity, resulting in a comprehensive analysis and tangible results. Process ALL the data rapidly . When all the data is analyzed, the hidden patterns emerge and actionable insights present themselves. The DevOps engineers can then distinguish the need for infrastructure adjustments in order to avoid the performance bottlenecks and can have a seat at the C-suite table with specific data-based suggestions for infrastructure optimization and operations improvement. In-depth data analysis . When the event patterns are identified, automated triggers can be set. Thus said, when the statistics show that certain events always lead to a particular (negative) result and certain actions must be performed to rectify the issue, DevOps engineers can create the triggers and automate the responses to such events. Automation of routine tasks Thus said, if a monitoring solution reports the increased CPU usage due to an increased number of connections, etc., Kubernetes can spin up the additional app instances and use the load balancing to distribute the visitor flow and reduce the load. This is the simplest scenario, real-world use cases are much more complex and allow to automate literally any routine DevOps task, enabling the ML model to launch it under certain conditions and deal with the issues preemptively, not after a downtime occurs. Business benefits of using AIOps Deploying AIOps solutions allows achieving the following positive outcomes: , leading to a positive end-user experience Uninterrupted product availability , instead of permanent firefighting Preemptive problem solving , due to the analysis of all the data your business generates instead of working with stripped down samples Removal of data silos and root-cause remediation , allowing your IT department to concentrate on improving the infrastructure and processes, instead of dealing with repetitive and time-consuming tasks Automation of routine tasks , as the in-depth analysis of the logs helps show the impact of managerial decisions and evaluate the efficiency of adopted business strategies Better collaboration Final thoughts on what is AIOps and why it is important As you can see, opting for AIOps tools and solutions can be greatly beneficial for your business. This might seem to be a marketing gimmick of AIOps solution vendors…but there are none as of yet. The late majority of businesses is yet struggling with their and perform their . transition to DevOps culture digital transformation At the same time, the truly innovative companies are already applying their efforts to combining AI algorithms, ML models, and DevOps systems to deliver the cutting-edge cloud monitoring and infrastructure automation solutions of tomorrow. Applying these practices results in tremendously better customer experience, shorter time to market for the products, more effective infrastructure usage and better collaboration within the team. However, even these innovators do not have an out-of-the-box solution available for their needs and have to build such systems themselves using like Splunk, Sumologic, Datadog, Prometheus+Grafana, Kubernetes and Terraform, etc. What is more important, while the idea itself is of great importance, the level of infrastructure management skills needed to implement it by far exceeds the abilities of common companies. popular DevOps tools This is where like IT Svit come into action. We have ample experience in the fields like: Managed Services Providers Cloud infrastructure design and implementation, Performance optimization Cloud monitoring, logging and alerting AI deployment and ML training Building complex distributed systems for Big Data analytics Combining all these skills allows us to deliver complex yet efficient systems that enable our customers to drive much more value to their product users. Data integrity underpins efficient strategy analysis, better resource allocation and improved interactions within the team and with end users. The unaltered quality of our work resulted in popular international business rating agency Clutch listing IT Svit among the in 2017–2018. leaders of IT outsourcing market in Ukraine Should you want your idea to become our next successful project — , we are always ready to help! contact us Originally published at itsvit.com on August 29, 2018.

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