Evaluate the impact AIOps brings, Ask This:
- How well does your organization retain and engage people in teams that support the data lifecycle?
- How does your organization have real time holistic visibility of the application stack and Infrastructure map?
- How do techniques from the pre-analytics era differ from your new data science and business analytics approach, or have they just been re skinned to fit into the new terminology?
- Are you able to use your business intelligence tools to data mine the AIOps repository?
- How do your existing solutions integrate into event management, AIOps and Information Technology Service Management tools?
- When everything is known, how will you ensure data ethics in AI to not discriminate based on the data you have?
- How do you monitor all the components individually to make sure they are in their expected state, where is the relationship between components?
- How did your organization skilfully achieve digital transformation, and what tools did you need on path?
- What impact will AIOps have on functional collaboration across your organization?
- What telemetry data you monitor, at which stage and in what form?
- As the AIOps tool is the aggregator of data (trace, event, log), how much data in days/years will be kept in the repository based on the inventory listed?
- Does your organization use API based access to operational data storage so that almost any reporting needs can be met without requiring product changes?
- What proprietary and industry standard machine learning algorithms and data science techniques does the technology vendor incorporate?
- Do you know where employees have shared corporate data and under which accounts?
- How many outages can your organization afford to endure before the AIOps tool learns how to recognize them?
- Does your solution consolidate the real time monitoring data as well as historical data, with drill down capabilities to identify a problems root cause?
- Which business drivers will have a major impact on your business?
- Have there been any data center design trends that perhaps were not as prevalent a few years ago?
- What is the value AIOps brings to your organization relative to the cost?
- Does your products dashboard have the ability to integrate and display data from other products or publish data into other products?
- How did your organization achieve digital transformation, and what tools did you need on this path?
- Why is AIOps picking up pace suddenly in your organization when issues have been existing in the industry for the past many years?
- Who are the key leaders and at what stage of the data driven organization buy in process are they?
- How many times have you heard users voice concerns over allowing a machine take decision on its own, particularly if they are business impacting scenarios, and how do you manage this concern?
- What impact will AIOps have on team performance and morale?
- How do you pick the best data with which to train your systems, and how do you use your data to predict how well your systems will detect anomalies once you deploy them in a new data environment?
- What are your security restrictions for IT data to leave the corporate data center?
- Does your Center of Excellence have the right skills that combine business context and technical chops for defining solution architecture, managing change, and driving value creation?
- Can your solutions predict how a pending application release would affect the customer experience?
- Does your dashboard have the capability to understand the data and which datasets can be combined?
- What is the impact of change on operations and how does AIOps enable rapid change?
- Does the product you use provide data for service level performance, and availability monitoring dashboards?
- Can you have a virtual representation/image (generally 3D model) of a product, process or service being developed?
- Does your organization have a coherent vision in line with the most probable future market scenarios?
- What business objective(s) does your organization achieve by deploying artificial intelligence?
- Which applications are important to your organization and that you need an overview of?
- Does your organization use ML based methods to set conversion goals automatically for key steps, or is this be done manually?
- How many different monitoring tools does your organization currently use?
- What AIOps generated actionable insights from data generated by various IT assets and systems users do you have?
- Does your solution incorporate AIOps for advanced anomaly detection and correlation and visualizations that enable easy understanding of monitored environments?
- Does the Center of Excellence have strong executive support to prescribe and govern the AIOps implementation framework?
- Does your organization have a strategy to migrate legacy applications to a cloud based environment?
- Do you have a single view across your entire multi cloud ecosystem, from the performance of users and edge devices to your applications and cloud platforms, and all in context?
- Do you have any corporate firewalls or proxy servers that prevent HTTPS data communications to SaaS platforms?
- With the sheer volume of structured, unstructured, and IoT data available, how is your organization addressing the challenge that managing AIOps presents?
- As an IT operations leader, how do you pivot the way your organization works to adopt a true AIOps mindset that goes beyond mere aggregation?
- Which internal leaders are more likely to use data analytics and make data driven decisions?
- Which non IT related roles does your organization expect to support as an extension of its IT analytics?
- Does your product have the ability to identify problems when only a percentage of the same transaction types are failing or suffering performance degradation?
- Does your organization have in house structure to implement the policy / policies?
- Do you deliver your own IT operations management capabilities or augment what you have with expert outside support?
- Does the product present risks for users?
- AIOps correlates data about applications and underlying infrastructure using Artificial Intelligence techniques and makes predictive analysis and efficient root cause analysis possible, how do you present that data in your organization?
- What security measures are in place in your organization to prevent introduction of malicious code, and what is your process that you would follow if an event occurs?
- How much access to your network does the provider need in order to implement and support its solution?
- How does the vendor support and enhance current incident management workflows and support critical use cases?
- Is your organization aware of future service disruption and can it act before business transactions break down?
- Have you defined your ethical standards, and are you building your AI in a way that will align with them?
- How do you make sure your organization is always ahead of developments in the AIOps space?
- Does the solution have customizable role based access to the functionality and the management information?
- Do you have a clear strategy for where to use cloud and how to ensure connectivity across your landscape?
- What budget level does your team expect to spend on AIOps projects in the next 3 years?
- How does your anomaly detection solution that leverages machine learning impact your business operations?
- Is looking at Transaction Trace sufficient, or does your organization look at outbound and inbound dependencies at each hop as well?
- How does your organization ensure that privacy and confidentiality are protected when applying AI/ML/AIOps technologies to personal information holdings when the solution is not run in house?
- What area will you be most focused on for using AIOps to drive insights over the next 3 years?
- What is the ideal kind of preparation that is required for the data before AIOps analysis?
- In which emerging technologies will your organization invest/is your organization investing in as part of your most recent digital transformation?
- Does the solution support graphic user interface (GUI) for developing processes, and sequences following like Business Process Model & Notation (BPMN)?
- Can users train and re train the AIOps models, or does this require additional customization, support or permissions?
- Do you have the right event context to quickly troubleshoot and restore enterprise services before there is any business impact?
- What capabilities do you have for tracing infrastructure, application, and/or business performance to changes made to infrastructures and applications?
- How are you visualizing ITSM, event management, AIOps and log data on the dashboard?
- How many applications do require monitoring of logs and will additional licences be required for log monitoring?
- How ready is your organization for full automation to manage network performance and network security?
- How do you make sure you can keep working on your digital transformation and become a data driven organization?
- How does AIOps directly impact Mttr, service level, and the cost to achieve service levels?
- Does the solution go beyond basic Machine Learning algorithms?
- How does the business context (business application name) get applied to the mapping?
- Is the solution able to handle multiple data feeds from multiple sources for example, APIs, mainframes, text box descriptors, screen scrapping?
- What languages and applications do people use in each stage of the data lifecycle?
- What level of accountability for AI driven mistakes does your orgnization want to accept?
- Is your context as granular as where in the code are the bugs you need to fix to which users who were affected by those errors and was there a significant business impact?
- How does the correlation of your monitoring tools remove the IT noise and provide insight into the decision making process?
- Are teams specialized, or do they have multiple specializations working together?
- How would you previously detect production issues that impact user experience and service performance?
- With what transaction processing monitoring tools does your product integrate?
- Is there a place for ML driven automation in the future or will simpler analytics be enough?
- How do you view the future of ITSM in your organization over the next three years?
- Are performance feeds and configuration data available from all underlying network components?
- Does the solution have a unique selling proposition and clear market differentiators?
- Are there complementary software or hardware dependencies that need to be in place for an AIOps model to function correctly?
- Is the solution able to deal with structured data across a large variety of heterogeneous platforms?
- What level of capacity and involvement is required to develop a solution or to support the use of COTS (including customization and configuration) for dashboard solutions?
- Which types of data/alerts does your advanced analytics solution collect through fully supported third party integrations?
- How much do you have to pay for the investment in order to get the benefits of that investment?
- What type of support will you need from the vendor in the event assistance is required?
- How does your solution discover and map the relationships between infrastructure components?
- How do you ensure that the purpose of your AIOps solution is to understand what is disrupting the customer experience?
- What impact has AIOps had on the relationship between IT and other parts of the business?
Bachelor of Commerce - BCom from Nizam College at Hyderabad Public School
2y👍👍