AIOps
Definition What is AIOps
Artificial Intelligence for IT Operations is a multilayered technology platform that automates and enhances IT operations through Artificial intelligence and machine learning. This is to help empower IT professionals with the information they need to make decisions and ultimately resolve service to an application faster.
AIOps Platforms leverage on big data, collecting a variety of data from various operation tools and devices in order to automatically sort and react to issues in real time. All this while ensuring they still provide traditional historical analytics.
*Is AIOps Equivalent to DevOps? *
DevOps refers to the continuous development and delivery of a project following the important steps of gathering information, development, testing, staging and deployment to production all this in a seamless manner.
AI in IT Operations on the other hand involves all the continuous integration and development processes and adds retraining into the process. This is where the data first ingested to the pipeline keeps upgrading through the training part as it learns more and more about the business through machine learning.
Therefore, AI Operations Differs from DevOps in that in DevOps during the continuous integration and development cycle, the data ingested in the first phase is still the same. This is however not the case as in AIOps as the AI Model keeps learning and hence the data evolves from time to time.
Why Do You Need AIOps?
To understand the great importance of AI in IT Operations let's have a case scenario of a company that helps its clients in their saving journey and luckily has thousands of clients.
The company focus is to ensure the application is up and that clients can either deposit or withdraw their savings consistently and on regular basis including performing of other tasks in the application too.
Can you imagine what will happen when you receive a call from your customer care representative that a client is trying to perform a transaction with no sucess since early morning because the application is probably down.
What do you do in that case scenario to get the application up and running in the shortest period of time to ensure seamless satisfaction of your clients?
And here is where Artificial Intelligence for IT Operations comes in, to identify, address and resolve slowdowns and outages of applications faster than the IT Professionals can be sifting manually through multiple IT Ops tools to solve the problem. This comes with a lot of specific benefits:
AIOps Strategy Achieve a faster mean time to resolution. By Cutting through the IT Operations noise and Correlation operating data from multiple IT Environments, AIOps is able to identify root causes and propose solutions faster and more accurately than humanly possible. This enables Organizations to set and achieve Previously unthinkable mean time to resolution goals. For example, a telecommunication provider in Brazil was able to use AIOps to reduce incident response times from 30 minutes to less than 5 minutes.
AI in IT Operations ensures the applications grows from Reactive to proactive to predictive management. Because it never stops learning AIOps Keeps getting better at identifying less urgent alerts or signals that could relate with more urgent situations. This means it can provide predictive alerts that let IT teams address potential problems before they even lead to slow down the application
AIOps helps you modernize your IT Operations and your IT Operations team. Instead of being bombarded with every alert from every environment. AIOps Operations team only receive alerts that need specific service level thresh hold or parameters, compared with all the context required to make the best possible diagnosis and take the best directive action. The more AIOps runs and automate the more it helps keep the “light on” with less human efforts. And the more your IT Operation team can focus on tasks with greater strategic value to the business.
How does AIOps Work ?
The easiest way to understand how Artificial Intelligence for IT operations works is to review and understand the role that each AIOps Component technology plays in the process. These include Big Data, Machine Learning and Automation
AIOps uses a Big Data Platform to aggregate siloed IT Operations data in one place. This Data can include historical performance data, streaming real time operations events, System logs and metrics, network data just to mention.
So, this is where then AIOps applies focused analytics and machine learning capabilities:
a) In separate significant event alerts from the noise. So, what AIOps really does is that it uses analytics like rule application and pattern matching to comb through your IT Operations Data and submit signals that is significant of normal event alerts from the noise.
b) You can also identify root causes and propose solutions, using industry specific or environment specific algorithms AIOps can corelate abnormal events and other events that are across environment to zero and on the cause of an outage or performance problem and eventually suggest remedies or solutions.
c) It can also be applied to automate responses, including Realtime proactive resolution. At a minimum AIOps can automatically route a lot and recommend the solutions to the appropriate IT Teams or eve create response teams based on the nature of the problem and the solution. In many cases it can process results from machine learning to trigger automatic system responses that address problems in real time before users are even aware of the occurrence.
d) Learning Continually to improve handling of future problems. Based on the results of the analytics, machine learning capabilities can change algorithms or create new ones to identify problems even earlier and recommend more effective solutions.
_AIOps Use Cases _
In Addition to optimizing IT Operations AIOps Visibility and Automation can support and help drive other important business and IT innovations. These include but not limited to:
- Anomaly or threat detection
AIOps is a valuable addition to a strong security management posture. In particular, when these threats are sophisticated multi-vector heuristics and algorithms can monitor traffic data for botnets, scripts, or other threats that can bring down a network, and Llyod machine learning can reveal trends that can jeopardize the availability of commercial services.
_- Event Correlation _
Infrastructure teams are faced with floods of alerts and yet, there is only a handful that really matters. AIOps can mine those alerts use inference models to group them together and identify upstream root cause issue that are at the call of the problem. This transforms the overloaded inbox with alert emails into one or two notifications that really matter.
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- Intelligent Alerting and Escalation_
After Root cause alerts and issues are identified, IT Operations teams can make use of artificial intelligence to automatically notify subject matter experts or teams of the incident's location for faster remediation. Artificial intelligence can act as a routing system immediately setting the remediation workflow in motion before human beings ever get involved.
Please Park technologies is one such example that is leveraging the power of AI OPS to its advantage the platform monitors your hardware and continuously basically it uses machine learning to predict a fault based on a previous and real time data of the system before it even occurs. A ticket is created automatically if and when a fault is detected so this ticket includes all the necessary details required to resolve the issue.
- Incident auto-remediation
AI OPS is also being used as an end-to-end bridge between IT Service Management and IT Operations Management tools. Traditionally IT Service management teams sift through infrastructure data to identify and remediate issues at the root cause AI OPS extracts root cause influences from infrastructure a lot and then eventually sends them to the ITSM team or tools through API integration pathways.
- Capacity Optimization
Capacity optimization can also include predictive capacity planning and refers to the use of statistical analysis or AI based analytics to optimize application availability and workloads across infrastructure.
So, what this analysis can do is they can proactively monitor raw utilization bandwidth CPU memory and much more to help increase overall application uptime.
How to GET Started with AIOps?
Starting out in the AIOps side of technology shouldn't and isn't as tough as one might think. Below are top three actions a business can take to ensure seamless implementation of AIOps in their IT Operations.
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- Put together a Business Scenario and Target_
We all wouldn't want to start implementation of an idea without a well laid out business project Rubic on what exactly we want to solve thorough this specific implementation.
Set out the key Goals of your AIOps plan, which part of the business exactly would you like to consume most of that implementation? What are some of the Key performance indicators that will be used to gauge the sucess of the implementation or even be considered consider during implementation.
It is also good to look how your business has been previously affected by what you currently want to prevent. How has outages impacted your business before both from the financial perspective and the social trust to your business products?
Check your revenues before and use this to set a solid plan on what you really want to achieve, taking even the simplest details onto consideration.
This a key and fundamental step that shouldn't be overlooked and helps ensure high sucess rates in the implementation of AIOps in one's business.
2. Small but Specific, with Clear Objectives.
Don't be in a hurry to start implementing, massive project sprints through AIOps. Start small and build from there, with specific target goals in mind.
Kick off with the little available data, ingest it into the business create meaningful insights and start solving your most pressing business problems.
This will ensure that one understands the basic building blocks of the business success and build from there, ensuring simplicity in problem solving that even future business leads will be able to comprehend. Ensuring understanding of the business goal from the head start while still incorporating critical business concepts to the implementation.
_3. Decide on your AIOps Solution For the business _
As the say, using the right tools do the right job, one also need to do the same for their business. Choose the right AIOps solution to solve your business problem. Be intentional, specific and not forgetting that when all you have is a hammer everything looks like a nail.
There are dozens of AIOps solutions on the market be sure to understand the different types that already exist and why you need to select any of them.
Below are simple criteria features one should consider in choosing an AIOps Platform:
a) What Type of AIOps solutions do you need exactly is it Domain-Agnostic or Domain-Specific?
Is it going to meet your needs?
b) What is your preferred effort and time of implementation, this should align with the needs and nature of your business. A payment application used in a hospital will need faster implementation time compared to a grocery selling app used by rural farmers to Connect them to wholesale buyers.
c) How easy to use and maintain is the platform you want to choose. Is the maintenance cost matching the business budget? Do you have the required personnel and resources to handle and maintain the system.
d) The final but most important consideration is how much money has the business set aside for the implementation of AIOps in its budget.
We all don't want t to go ahead and spend even more from what is allocate by the budget. Choose an AIOps plan that is best fit to solve your business problem and also falls in your budget ranges. This is to be highly considered as it cuts across most of the points earlier stated.
One Key important thing to note is sure to book a demo and have atrial with your selected AIOps Provider of choice. This gives you a chance to ask the provider about customer references. You get to know more on their client support guidelines.
Also be sure to also ask about their legal guidelines. If it's a foreign company, are they licensed to provide solutions in your country.
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