Founder of Windward Consulting Group. In addition to Windward, Sean was the Founder and CEO of RealOps, Inc., the pioneer in enterprise management Run Book Automation solutions which was acquired by BMC. Before starting Windward, Sean held senior positions with Predictive Systems and Booz Allen Hamilton.
Our Leadership
Meet our Calmbitious crew.
Leaders who balance an exceptional commitment to achieving success with a balanced state of tranquility and ease.
A get-it-done culture. We don’t speak it, we live it.
We look beyond mere certifications to simply focus on the right people for the job. Who are they? For starters, camaraderie is critical—because we understand that partnership without politics goes further. We hold ourselves to incredibly high standards—and prove our credibility time after time.
We call this exacting, no-drama attitude “calmbitious.” Get to know the team that leads and embodies our culture.
Mafa Amr
General Manager
Mafa is responsible for revenue generation and sales opportunities, as well as overall P&L for all business units. Prior to rejoining Windward, Mafa held a Management position at Nexius Solutions, Booz Allen Hamilton and Predictive Systems and previously spent a decade with Windward where he led the Commercial Sales Team.
Charles Semones
VP of Revenue Growth
Charles is responsible for managing all staff and resources within the Enterprise Services vertical, as well as program and project delivery, and business development. Prior to joining Windward, Charles spent 26 years at Xerox, responsible for the development of network and monitoring technologies and product development.
Bill Driscoll
VP of Customer Success
Bill is responsible for business development, project delivery, partner management and team leadership for his clients in Windward’s Commercial Services business unit. Bill rejoined the Windward team with 20-years’ experience leading professional services teams, notably with SevOne, Capgemini, US Air Force and Windward, focused on intelligent and automated IT service and operations management.
Nichole Kelly
VP of Marketing
Nichole is responsible for elevating Windward’s market position by demonstrating our value and competitive advantage to our addressable market. Nichole creates growth strategies that leverage our unique subject matter expertise to add measurable value to our prospects, customers and internal team members. Prior to joining Windward, Nichole has spent the last 22 years shaping the B2B marketing industry through her work with the Fortune 1000 companies as a market strategist, thought leader, motivational speaker and published author.
Cody Jelinek
Managing Director - Operations
Cody is responsible for all talent acquisition and resource management. Prior to joining Windward, Cody held various senior positions in executive search firms where he oversaw and led successful recruiting departments. Cody brings extensive experience and expertise in Technical Recruiting, Customer Relationship Management, and IT Service Management.
Pete Tony
Director of Finance
Pete is responsible for maximizing the return on financial assets by establishing financial controls, policies, procedures, and reporting systems. In addition, Pete monitors and confirms financial condition through both internal and external audits and achieves budget objectives by scheduling expenditures, analyzing variances, and initiating corrective actions. Prior to moving to the role as controller, Pete spent 15 years as the general accounting supervisor at Windward.
Michele Darwin
Director of Corporate Social Responsibility
Michele is responsible for Windward’s overall CSR strategy to identify, ideate and execute philanthropic, charitable and cause-related initiatives including the Windward Foundation. She maintains all donor and partner relations, fundraising and communications for the Windward Foundation and organizes the District Music Benefit, the foundation’s annual fundraiser. Previously, Michele spend 7 years leading marketing efforts for Windward Consulting Group.
How to Select the Best Government IT Consultancy
How to Select the Best Government IT Consultancy
Hiring the right partner can be a daunting task, especially in the government sector. You need to ensure you end up with a government IT consultancy firm you can not only trust, but who also fits the project requirements and budget. With so many different vendors, how exactly do you choose an IT firm to trust with your business who will directly contribute to your success?
Government IT Consultancy Checklist
- Check their experience and reputation. A good consultancy firm should have past experience in the same area of work that you are seeking, and at a similar scale. Their experience should include challenges faced as well as successes. You also want to ensure that you can trust an IT consultancy with your business reputation.
- Check Customer Satisfaction Score. A high CSAT score will instill confidence in the decision to choose a consultancy. Their CSAT score represents their success and achievements.
- Search their website and reviews. Their website can provide details about the type of work they do and if it is related to your needs, as well as important information about customers, culture, experience, etc. Also, always research the reviews of potential IT consultancies, because this provides insight about different peoples experiences.
- Verify the firm is included on the GSA Schedule. Any reputable IT consultancy will be on the GSA Schedule. Before considering any IT consultancy, make sure they are listed.
- Assess their communication skills. Successful communication is a must-have quality when hiring an IT consultancy. These are the people that will be responsible for the work on your project. You want to ensure updates are communicated clearly and professionally.
- Confirm their experience supporting classified work. When working in the government sector, you want to ensure you are choosing an IT consultancy that has been cleared and has cleared resources on their staff.
It’s always difficult to feel confident you are making the right choice when hiring an IT consultancy. Especially when there are not only so many different options, but also so many rules and regulations in the government sector. Following this checklist will help ensure you select the right government IT consultancy for your Agency, your project, and your stakeholders.
How to Select the Best Government IT Consultancy
IT Automation Toolbox: Workflows, Tools, Software, and Strategies to Uplevel
IT Automation Toolbox: Workflows, Tools, Software, and Strategies to Uplevel
Most IT operations managers and CIOs struggle with the daily challenge of getting more done with fewer resources. This requires more integration of technology, called automation, with an IT staff. Automation serves as a force multiplier, especially in cases where human error may cause outage or staffing is limited. IT automation is the toolbox that every IT operator needs because it does the following:
- Lowers cost
- Enhances productivity
- Provides greater availability
- Optimizes performance
- Improves reliability
But what does an IT automation toolbox include? First of all, it is a means to the goal of operational productivity, efficiency, and revenue generation. In this blog, discover the following items to add to an IT automation toolbox: workflows, tools, software, and strategies.
Workflows for IT Automation
IT workflow automation is defining a series of tasks to complete a process, and then removing all the manual steps. It is governed by setting rules in a delegated system or software to deliver dependency-based workflow tasks and functions that would otherwise be completed manually by the IT staff. Orchestration and IT automation enable organizations to integrate disparate tools and processes across their environment.
While it can be applied to all manner of systems from HR to marketing to sales teams, IT automation improves the workflow in IT departments in the following ways:
- Assign tickets and escalations to available team members
- Avoid duplicate support requests
- Confirm scheduled updates with stakeholders
- Get a handle on Shadow IT
- Manage assets and track usage trends
One of the major pluses of IT automation is that it takes menial tasks off the plates of IT staff. It is true that the IT department is meant to be a response team to critical systems issues in the enterprise, but mitigation should not be their constant priority.
IT automation as a strategy for improved workflows not only enhances the user experience but also optimizes the productivity of the IT department.This way, they can spend less time on a simple ticket that an automated system response could attend to and focus on contributing to larger ticket items that bring value to the company’s bottom line.
IT Automation Tools & Software
There are endless options in the IT automation software market. Some can be applied in any organization while others serve niche needs.
Instead of asking “which tool or software is the best”, look for the software that suits the needs of your department best. Overall, look for a workflow automation software that is fast, flexible and fulfills the needs of your team.
Add this checklist to your IT automation toolbox for when you go “shopping” for a software or system:
Simplicity
The whole idea behind automation is ease of use and access – look for a system or software that delivers a user-friendly interface, no-code solutions, and drag-and-drop designers.
Cloud operability
Cloud-based workflow automation tools are usually easier to maintain and run than on-premise versions. They also offer easy accessibility, reliable security, and data scalability.
Cross-system integration
Got a multitude of cloud apps to bring under one umbrella? Most cloud-based software come with interoperability with other cloud apps. Check the chosen workflow automation system for API compatibility and tools like ServiceNow.
Customizable features
No two businesses are alike and neither are their IT department processes; choose a system that is customizable for complex cases and allows conditional steps as well as multiple branches.
Reports and analytics
The strength of any IT automation system is a capability to review, analyze, and update – find a software tool that has built-in reporting to examine lags, monitor tasks, and make improvements in processes.
Mobile capabilities
Remote access is a necessity in today’s work environment. From notifications to approvals, ensure the software works for people on the go.
Sensible pricing
IT departments do not usually have an endless supply of budget. Find a vendor that offers reasonable pricing that is upfront and predictable.
We see the big picture of your business – not just product application
Windward partners with leaders in technology with a vendor agnostic approach to ensure that we recommend the best products for your bottom line. Our consultants and engineers hold certifications on dozens of technologies, allowing them to keep their fingers on the pulse of the ever-changing IT industry.
Some of our partners and platforms include:
IT Automation Strategies
It is not enough to implement an automation system or program in the IT department. There has to be reasoning, thought and strategy put into the initiative to make it successful. CIOs and IT directors should take deep dives into the processes they hope to automate, understand how the work flows and where the workflow itself can be transformed.
Automation is a switch that goes with process transformation. CIOs should keep that in mind and consider the following IT automation strategies to achieve the optimal results as they leverage IT automation.
Create a vision of what is possible
Most organizations already have scripts automating some basic tasks, but now — as the ServiceNow report states — many are turning to artificial intelligence, machine learning and RPA to re-engineer sophisticated processes within their enterprises.
IT department managers and CIOs have to take the lead in their companies to help executives get on board with the change to automation tools and software. They can do this by championing changes in their own departments first; integrate automation technologies to clean up workflows; prove the value in complex tasks in IT; then move those technologies to other departments.
Understand the targeted process fully
Automation does not happen overnight; it takes strategic, measured planning. Start with one segment of a process – understand all the steps in the process, identify which steps are necessary, where bottlenecks occur, and what parts of the process can adjust and evolve with automation.
This is how a CIO can implement IT automation workflows into their department and eventually expand that process to the rest of the organization.
Show the value of automation
Most CIOs know that automation technologies are critical components to creating a competitive advantage. However, not all people agree; some see it as disruptive or displacing the status quo.
In order to get the IT team to understand the value of IT automation technologies, present the benefits and value: garner support by showing the deployment team how automation cuts back on long hours or late nights.
Rethink workflow, then automate
IT automation workflows should never stay static. CIOs should take their understanding of an existing process and find ways to improve it as they automate it; this initiates real transformation.
Aim for efficiency, not perfection
In an ideal world, IT automation is smooth, seamless, efficient and flawless. In truth IT automation integration takes time to implement and it is in constant evolution. Aiming for efficiency is a much better model than perfection. Engage in a continual, more agile approach, where you’re making changes, taking digital labor into account as you improve your process.
Implement a modern IT stack
Change is constant in the IT automation scene. Most IT departments have a system that updates and performs simple, manual tasks. Consider further implementations, like cloud-integrations, AIOps, sophisticated data analytics, and APIs to advance the IT infrastructure.
Manage change
Work environments do not usually respond well to changes in processes (“We’ve always done it this way!”). In these cases, CIOs should have a strong change-management strategy in place. This will help staff to adjust to the new workflow instead of rejecting change. When people understand their roles and responsibilities within a new framework and process, they are more likely to respond positively to advancing technologies. Enlist teams in training and stay communicative from the top-down always.
IT Automation Toolbox: Workflows, Tools, Software, and Strategies to Uplevel
AI for IT Operations: Everything You Need to Know to Get Ahead
AI for IT Operations: Everything You Need to Know to Get Ahead
“DefinITions” – Artificial Intelligence, IT Operations, AIOps
First, let’s dive into some terminology used in the IT space and make some clear distinctions on three common terms: artificial intelligence, IT operations, and artificial intelligence for IT operations (AIOps).
Related Reading: Learn more about the 5 Levels of AIOps Maturity
What is AI?
Artificial intelligence (AI), also known as machine learning (ML), is the simulation of human intelligence processes by machines, especially computer systems.
AI systems work by receiving data, analyzing it for correlations and patterns, and using those patterns to make predictions about future scenarios. For example, a chatbot that is fed examples of text chats can learn to produce “conversations” with people.
AI processes data and “gains knowledge” in three ways: learning, reasoning, and self-correction.
What’s more, AI has many benefits for enterprises because it can give insight into operations that may have been overlooked, and in some cases, can perform tasks better than humans, especially with tasks that are tedious, repetitive, or detail-oriented; such as analyzing large numbers of legal documents to ensure relevant fields are filled inappropriately.
Artificial intelligence tools can complete these tasks quickly and efficiently where a human eye can easily miss a checkbox.
What is IT Operations?
IT operations (ITOps) are the processes and services that are administered and managed by the IT department within an organization. The ITOps team usually functions as a distinct working group within the broader department; it includes a group of operators led by an operations manager.
The Disciplined Agile framework identifies six classifications for ITOps tasks, as well as the associated activities that correspond to each strategic objective:
- Manage infrastructure: Keeping infrastructure intact is a key function for IT Operations. It consists of computing and networking hardware, as well as the applications that run on them. This broadens to oversight of cloud environments, application deployment, network security management, facilities management and other hardware IT infrastructure components.
- Manage configurations: It is important to keep a record of hardware configurations and solution dependencies. This aids ITOps in implementing new configurations as well as maintaining existing ones for optimal performance of the infrastructure and services.
- Run solutions: The core of ITOps is to run solutions. Operators are responsible for implementing data back-ups, restoring systems after service outages or updates, configuring and tuning servers and other configurations. This ensures the IT infrastructure is not only optimized for performance, but also allocates resources where they are most needed.
- Evolve infrastructure: While their job is to maintain a functioning infrastructure, ITOps also act to innovate systems and implement changes as needed to benefit the business or organization. This includes: applying software patches, introducing new hardware and software applications, and identifying areas of change.
- Mitigate disasters: IT operations are always on standby for preventing disaster and implementing recovery plans for enterprises. ITOps teams plan, simulate and practice disaster recovery situations to avoid downtime and lost revenue if an unexpected service outage occurs.
- Govern ITOps: As a part of mitigating disaster, the ITOps team monitors and measures infrastructure performance, especially as it pertains to the organization’s security posture. It also develops operational metrics to evaluate the performance of key processes and services, manages software license compliance and conducts audits to verify that security and performance goals are met.
What is AI for IT Operations (AIOps)?
Artificial intelligence for IT operations (AIOps) is the application of artificial intelligence (AI) to improve or enhance IT operations. AIOps often uses big data, analytics, and machine learning to achieve the following:
- Collect and categorize huge volumes of data generated by ever-expanding IT infrastructure applications, components, and performance-monitoring tools.
- Differentiate “signals” out of the “noise” to identify events and patterns related to system performance and availability issues.
- Diagnose and report root causes to ITOps for immediate response and mitigation. In some cases, AIOps can and will resolve the issue without human intervention.
AIOps offers a strategic set of conglomerated tools to improve processes and response time for the IT operations team. It can replace multiple, separate, manual systems and manage them with a single, intelligent, automated ITOps platform.
As the IT operations landscape expands and diversifies, it becomes more difficult to fully monitor and respond with agility. AIOps bridges this gap and effectively optimizes IT operations management.
Why do we need AI for IT Operations?
Most organizations are moving from a traditional infrastructure of siloed, static physical systems to a dynamic mix of hybrid cloud and physical environments. The systems are running on virtualized or software-defined resources that scale and reconfigure constantly.
These systems generate a gargantuan amount of data that only continues to grow. According to a Gartner study, IT infrastructure generates two to three times more IT operations data every year. This increased exponentially during the COVID-19 pandemic with everyone working from home – and it is not “going back to normal” anytime soon. As lockdowns ease, 32% of companies plan to continue using AIOps for expanding remote work environments.
To that end, it begs for innovation in the way that IT operations teams work and respond. Traditional domain-based IT management solutions cannot keep stride with the volume; it’s difficult to sift through significant events out of the waves of surrounding data. Also, forget about trying to correlate data across different but interdependent environments.
Furthermore, legacy solutions cannot provide real-time updates and insights or predictive analysis for IT operations teams. This problem leads to an inundated system that lacks the capacity to respond to issues with agility and meet customer service level expectations.
This is where AI for IT operations comes into the picture. AIOps provides the visibility and agility that IT operations teams need to enable them to maintain exceptional service levels. AIOps analyzes performance data and dependencies across all environments extract significant events related to slow-downs or outages and alert IT, staff, to issues, root causes, and the recommended solutions. By and far, AIOps is an efficiency model.
Listen Now: How AIOps Can Advance IT Operations
How does AIOps work?
Not all AIOps solutions are created equal. The easiest way to understand how AIOps works is to review the role that each component of technology — big data, machine learning, and IT automation–plays in the process.
In a nutshell, AIOps uses a big data platform to collect disparate ITOps data in one place, like:
- Historical performance and event data
- Streaming real-time operations events
- System logs and metrics
- Network data and packet data
- Incident-related data and ticketing
- Related document-based data
Then, AIOps applies targeted analytics and ML capabilities:
- Data Selection & Pattern Discovery: AIOps separates distinct events from the overall “noise”. Using analytics, AIOps creates rule application and pattern matching to explore IT operations data and to separate signals from all other data points.
- Inference: AIOps identifies root causes of issues and proposes solutions using industry-specific algorithms. Further, AIOps solutions correlate abnormal events with other event data across environments; then target the cause of an outage or performance problem and provide remedies.
- Automation & Collaboration: At a base level, AIOps can automate responses and route alerts along with recommended solutions to the relevant teams. It can also process results from ML to trigger automatic system responses that resolve critical events in real-time; even before users are aware anything occurred.
Continuous Learning: A true AI system learns and improves the handling of future problems. As the machine collects analytics, the AI changes algorithms or creates new ones to identify issues earlier and recommend other solutions. AI platforms aid the system in learning to adapt to environmental changes (i.e. new infrastructure provisioned or reconfigured DevOps teams).
What are the benefits of AIOps?
The most prominent benefit of AI for IT operations is that it strengthens and enhances the IT operations team. With AIOps, IT operations can identify, address and resolve latencies much faster than manually sifting through alerts and data points.
This results in many benefits across the board for an enterprise as a whole:
- Achieve faster mean time to resolution (MTTR): Slash the time it takes to respond to an event. AIOps pinpoints anomalies in the data pool and proposes solutions faster than humanly possible.
- Be proactive and predictive vs. reactive: Since AIOps never stops learning, it only gets better at identifying and alerting, or even resolving, urgent issues. It can provide predictive alerts that let IT teams address potential problems before they lead to slow-downs or outages.
- Evolve ITOps and ITOps teams: Once upon a time, ITOps responded to every alert from every environment, but that changed with AIOps. Instead, they receive alerts that meet specific service level thresholds or parameters – including the context required to make the best diagnosis and make the optimal corrective action. As AIOps learns and is able to take on the smaller, menial tasks, ITOps teams can evolve and focus on much greater strategic areas that bring value to a business.
Ready to evolve your ITOps team with AIOps?
AI for IT Operations: Everything You Need to Know to Get Ahead
AIOps – Riding the Tech Wave Towards Future IT Integrations
AIOps – Riding the Tech Wave Towards Future IT Integrations
Insights from AIOps Evolution Weekly | Episode 2
The latest AIOps Evolution Weekly Episode dives into where the term “AIOps” came from, what does it really means, and other philosophical tech ruminations like where AIOps is heading in the future.
Topics on AIOps integration included:
- How AIOps revolutionizes businesses for better productivity and ROI
- AIOps: Past, Present and Future AI Integrations
Let’s take a deeper dive into the article topics and the takeaways from Bill and Sean.
TL; DR?
Catch the full episode on YouTube
Topic 1: AIOps revolutionizes businesses for better productivity and ROI
Article: Survey: AIOps-driven network management can make your business run better
By: Shamus McGillicuddy, Research Director for the network management practice at Enterprise Management Associates
Enterprise Management Associates (EMA) published “Revolutionizing Network Management with AIOps”. The report found that 90% of the surveyed networking pros (309) believe applying AIOps to network management can lead to better business outcomes for an overall enterprise. In short, AIOps-driven network management can help a business run better. It translates into better employee productivity, improved customer experience, and revenue generation. But how exactly does AIOps enable this boost to the business?
Network management benefits
The EMA survey respondents identified the top benefits of AIOps-driven network management in the following order:
- Network optimization
- Operational efficiency
- Improved security/compliance
- Network resilience
- Cost reduction
Optimizing Existing Toolsets
According to the survey, about 91% of respondents are hoping that AIOps can address problems with their tools, including preventing conflicting or inaccurate data, prioritizing real-time insights, and eliminating tool fragmentation.
Gentle reminder: Don’t expect AIOps to fix all “tool problems”
Networking pros should not expect AIOps to be the “magic toolbox” that fixes all problems. Most respondents who had successful AIOps implementations reported that their AIOps interest was not driven by network management tool problems.
This suggests that successful users of AIOps are focused on transforming network engineering and operations, rather than addressing challenges with their network management tools.
Sean and Bill’s Take
- Sean and Bill both noted that the EMA study makes it sound like 90% of enterprises are using AIOps; it’s more like the vast majority (90%) of companies are only investigating AIOps as a potential solution, in their experience
- The reality is that roughly 10-15% of Windward clients are actively implementing AIOps
- The article touches on the “tech tale as old as time”: If a vendor had functionality where we could marry their solution with other tools and build AI around that, it would be useful. Vendors should look for ways to consolidate panes of glass with other tools, either through acquisition or ingesting and sharing data.
- Vendors have changed. The use cases have changed, but the argument is still the same. And you could make arguments on either side that, well, are these large vendors who have to go wide in order to continue to drive the massive amount of revenues that they have. Do they start to innovate through acquisition or do they actually continue to build and innovate internally on these technologies?
- CONCLUSION: In the next few years, the AIOps market may double or triple with more products and features touted from side companies, but those will most likely be absorbed into larger enterprises like ServiceNow or IBM.
Topic 2: AIOps – How we got here and where we’re heading with AI integrations
Article: Understanding AIOps: History, Uses, and Future
By: James Maguire, Editor-in-Chief at eWeek
The irony of our technological advancement as humans is that we have created systems that are so complex, especially in the IT domain, that we are overwhelmed. With cloud computing ever-expanding, data analytics superseded by real-time streaming data, hackers galore, and budget constraints, IT managers and department heads are crying out for help! The answer has come in the form of artificial intelligence (AI) for IT operations – or AIOps. But how did we get to AIOps, how do we use them and what is in store for us and AIOps in the future?
What is AIOps: Gartner Coins an (Awkward) Term
Although humans created IT systems that have overwhelmed us, we have also been advancing in creating a secondary system to help manage the original IT system. This secondary system has many names (AI for IT Operations, MLOps, etc), but the one that stuck, AIOps, was originally coined by Gartner in 2017.
The Uses of AIOps
The challenge of many IT systems is not having enough oversight or foresight to make predictive analyses and decisions on how to protect the current IT infrastructure.
AIOps fills in those gaps in knowledge; it provides predictive, problem-solving approaches to enable proactive reaction.
Top use cases among companies include the following:
- Predictive Alerting
- Root Cause Analysis
- Prioritizing Events
- Predictive Outages
- Service Desk Ticketing
The Future of AIOps – Two Shifts
Although AIOps is in a nascent stage of adoption, experts and analysts are predicting exponential growth in this market sector within the next 5-10 years.
- Exponential increase in AIOps
- AIOps will leverage more and more AI going forward, exponentially expanding the support it offers to IT systems
- Companies that don’t deploy AIOps may not be able to compete
- The AIOps market, hovering around $15 billion in 2021, is expected to hit $40 billion by 2026.
- The meaning of AIOps will change
- As it becomes more commonplace, the term AI will drop from the AIOps; it will simply be part of “operations”
- Companies will choose AIOps systems that will scale on multiple levels in the long-term
Sean and Bill’s Take
- One highlight of the article is some of the philosophy behind AIOps – Simple tasks done manually can really add up as systems become more complex. AIOps is the strategy that conglomerates all of that and simplifies these massive tasks and events.
- The use cases for AIOps are exactly the same as they have been for the last 20 years, but the infrastructure has gotten much more complex.
- While we focus on AI for IT Operations (AIOps), it will converge with other systems and departments in enterprises. AIOps / IT Operations personnel should be looking into this for the rest of the CIO organization.
- For AIOps to work well, we have got to really define and understand the problem. Then you can decide what’s the best use of technology to solve it.
Catch the full details from AIOps Evolution Weekly
Episode Transcript
Transcribed from Temi without edits
Speaker 1 (00:01):
Welcome to the AI ops evolution weekly broadcast. This series features discourse on topics pertinent to the C level conversation revolving the integration of artificial intelligence into the ever evolving it operations landscape, discover trends, and actionable tips for digital transformation, as well as the latest news on how AI ops is transforming business and government operations to create flow in their organization. And don’t stay in the dark on the latest industry news. Join the AA ops evolution community to stay connected and subscribe to the show@aiopsevolution.com. Now let’s join our hosts, Sean McDermott and bill Driscoll. It thought leaders, visionaries, and the voices on the other end of the mic for the latest episode of AI ops evolution weekly.
Speaker 2 (00:53):
Welcome everybody to the AI ops evolution weekly broadcast. My name is Sean McDermott and my co-host bill. Bill. How you doing on this Friday? I’m good.
Speaker 3 (01:04):
Good. I’m looking forward to another week in a road going up to New York. So just visit
Speaker 2 (01:08):
Family. That sounds fun
Speaker 3 (01:12):
Out of town. Okay, go ahead. Cooler weather.
Speaker 2 (01:17):
Yeah. So do you want to, you want to talk a little AI ops stuff before the weekend? Nothing awesome. Okay. All right. So we got a couple of articles here, a couple of topic we want to talk about. So let’s start off today with so a network world article came out really referring to an EMA study that basically said that EMA study found networking pros who reported the most success with AI ops pointed to improve security compliance as a potential benefit. So this is a pretty interesting article. I think I say that every time, this is an interesting article, I guess we wouldn’t be talking about it if I didn’t find it interesting, but I think one of the things that was interesting to me about it is, and we’ll get into a little bit more, but just on the surface and report found that 90% of the surveyed networking pros believe applying AI ops to network management can lead to better business outcomes and overall for an overall enterprise. I found that interesting because that makes it sound like 90% of people are doing AI ops. And I don’t think that’s true. The I think the vast majority of companies right now are, at least in my experience are investigating AI ops as a potential solution for them. And so is this, is this a hope, you know like 90% of people hope that this is what’s going to turn out with AI ops?
Speaker 3 (02:45):
Yeah, I mean, I think so. I think, I think I do agree 90% are at least looking at AI ops, they’re evaluating it. We’re talking to customers every week just about doing an assessment or doing some experimental things. And so, yeah, I’d say I agree with that 90%, I think 90% are not, definitely not. In the middle of the implementation of any kind of AI ops that might be that might be in the mid, I don’t, we don’t have numbers, but you know, that could be 40, 50% I would say.
Speaker 2 (03:15):
Yeah. Yeah. I, I think that, you know, in our clients, you know, we’re looking at probably 10 or 15% are actually actively in implementation of AI ops solutions and mostly AI ops monitoring platforms. Do you agree with that?
Speaker 3 (03:33):
Yeah, I think you know, we’ll sort of see, I think we’re going to talk a little bit later about the vendor landscape, but you know, I think some companies that already have a vendor that’s, that’s invested in, you know innovating or, or investing in sort of AI ops capabilities. I think they’re definitely working with those vendors and maybe they’re doing it in a, in a POV status, or maybe they’re rolling it out to some extent, but, you know, I think the range of what we define as AI ops is pretty broad and, you know, I think it boils down to a handful of things. And I think some vendors are doing some point pieces of it and other vendors are sort of trying to go all in and really be nothing but an AI ops platform. And I think, I think it’s probably a low percent that are, that have invested in that, you know, pure play, you know, a hundred percent AI ops platform, it sort of bolts in and, and, and, and sort of fits with the rest of your ecosystem. I think it’s more individual features that are a, you know, machine learning, like, or even maybe some machine learning that, that I think a lot of customers are looking at implementing right now.
Speaker 2 (04:37):
Okay. Yeah. Another part of this article, and we can have a whole discussion on this and maybe we will in the future they quoted one person, one of the surveys, we have so many, so many tools and so many gooeys and every single tool is doing just one thing. If a vendor had functionality where we could marry their solution with other tools and build AI around that it would be useful. Vendors should look for ways to consolidate panes of glass with other tools, either through acquisition or ingesting and sharing data. Yeah. So I’ve been doing this a long time, right? I started our, my company twenty-five years ago and I was in operations before that this is like literally the age old as far as I’ve been, you know, almost last 30 years is best of breed versus platform place. Right. And we’ve seen this story before of, you know, do you go all in with CA do you go all in with BMC?
Speaker 2 (05:35):
Do you go all the way with HP back in the day to now it’s like, do I go all in, on service now? Do I go all in on Splunk? And so it’s like the vendors have changed. The use cases have changed, but the argument is still the same. And you could make arguments on either side that, well, are these large vendors who have to go wide in order to continue to drive the massive amount of revenues that they have do they start to innovate through acquisition and, and or do they actually continue to build and innovate internally on these technologies? In my experience over the last 20 years, a lot of these large vendors, they they innovate through acquisition, including a company that I sold to BMC and eventually you know, these tools start they’re written in different technologies, they’re architected differently. And they start kind of trying to glue them together into a platform, play this kind of best this best, or this full blown plat platform. But when you lift up the covers, it’s still somewhat of an architectural mess underneath. So what are your, what are your thoughts on that? And I guess, I think we should have a whole discussion on this in the coming weeks. Yeah, exactly. Yeah.
Speaker 3 (06:54):
I think, I think it’s sort of, that’s a great segue to the next topic, which is sort of the marketplace, but before I sort of go there yeah, there was one last point I thought was interesting, that was written on that, you know, that, that Seamus Magilla Katia network world pointed out which was a lot of, a lot of organizations are looking at the tools that they have. And like you said, all these disparate tools and looking at what are the gaps that we have in our tools, what’s the inaccurate data, or, you know, w what are we not getting in the tools? And, and kind of focus focusing from that point. I think a lot of vendors that will talk to that, that we’ll refer to are really looking at where’s the puck going. So in hockey, you skate to where the puck’s going.
Speaker 3 (07:36):
And I think what you’d really need to look at what he recommends is you got to look at your engineering, you gotta look at your operation, you’ve gotta look at the technology that’s coming and the infrastructure that’s part of that, your software defined network, function, virtualization, and containers, and the cloud, and say, what, what does that infrastructure going to look like? What are those services going to look like, and what are our needs, and then start to build towards those needs. Instead of just looking at your, you know, backwards, almost at the tools you have and what gaps you think you have, because fill in those gaps may not get you where you’re going. And so, you know, that that sort of leads to this, this where’s the marketplace going. And I think I’m not going to name any, any vendors because they’re, they’re really emerging, you know, coming out, but I’ve read articles just in the last couple of weeks from several that are really they’re really press releases, but they’re, they’re, they’re providing some insights that are really trying to find gaps that the large vendors have and figuring out how do we play, right?
Speaker 3 (08:34):
And, and all of their, all of their messaging is like, you don’t need to, you don’t need to replace anything. You just bring us in as an overlay, feed all this data. And then we’re going to give you the insights where you have patented, you know, unsupervised machine learning, or we have a, that you know, predictive algorithms or, or patented detections. And by bringing all of this data back into our system, we’re going to be able to kind of provide those insights, or we’re going to be able to provide that sort of real-time identification of where you really need to focus. And, you know, I, I think a lot of these vendors are going to be struggling with growth, you know, going into a large enterprise and the volume of the data, the disparity of the data, you know, I think some of them will find are probably one trick ponies or maybe three trick ponies. But you know, it’s going to shake out and they’re all sort of contributing to this growing market that really could double or triple in the next few years. And some of their innovations are going to die out and some of them are going to be acquired by the service now’s in the Splunks and the IBM’s and whatnot.
Speaker 2 (09:39):
Yeah. I think, you know, having, having gone through this, right. You, what you’re going to find is that a lot of these products that are emerging really aren’t products, they’re more features, and those features will ultimately be acquired. Those, those companies will be acquired for those particular features. And I think that’s a very common thing. The other thing I, I think that we need to keep in, in, in check here is, you know, the, the companies that are looking at AI ops, so companies that are always really on the bleeding edge of adoption are usually the largest enterprises that have the largest issues around scale. And w we’re seeing it right now with AI ops and, and these large, large enterprises that are just creating massive amounts of data and have to start employing AI technology to process it. And to, for all the use cases that I think we’re going to talk about in a little bit the but you know, a lot of these products, you know, when it come to market, I don’t know if they’re exact and in my experience geared, you know, ready for the enterprise.
Speaker 2 (10:50):
Right. And they’re kind of ready for mid-level enterprises. And then they go into these large enterprises and they kind of just get clobbered. So we’ll, we’ll see how that shakes out. I think you’re right. There’s this a lot of vendors coming out. I’ll do a little bit of a shameless plug right now, the AI ops evolution podcast, which we released season one it’s out, we’re actually in production right now of season two. And in season two, we’re actually focusing very much on the vendors and we’re bringing in every single vendor that we, you know, kind of the top 12 or 14 vendors, we’re still formulating the number and we’re interviewing each one of these vendors and giving them a chance to kind of talk about their vision, what they’re doing, what their product, what they see is where AI ops is going, where they’re meeting AI ops, what their differentiators are. So I think that’s going to be a really useful podcast for people that are thinking about AI ops and trying to sort through some of this, this vendor technology, but for this, for this broadcast, we don’t really want to kind of go too much vendors and give plugs and things like that. But any other final thoughts on that?
Speaker 3 (11:58):
Yeah. The one final thought is I think you brought up the point that these, a lot of these newer products are features. I think they’re contributing, they’re disrupting, right. But you know, they’ll name big time. You know, companies, we’ve all heard of fortune 100 companies that are their customers, but when you drill in, they really found a specific use case. They’re all trying to wedge themselves in and say for this new business unit, this new 5g or edge, or or containers or Docker, they’re, they’re really just laser focused on that, trying to get in and wedge themselves in and solve that use case. And they hope, you know, they’ll continue to innovate and grow. And I, and I do think from a company standpoint and enterprise standpoint, that is the place you want to start to innovate and experiment and try out some of these vendors that are bringing in some, some things that you’re not going to see from the big vendors for probably a few years out.
Speaker 2 (12:48):
Yeah. Yeah. It’s, I mean, the one thing I tell my clients right, is, you know, we say this all the time, AI ops is a strategy, right? It’s not a technology, it’s not a platform and you have to look at it over a multi-year. So you have to have a vision of what you’re trying to do. You have to have a starting point, you have to think about starting small and, and how you’re going to build momentum through AI ops use cases and kind of knocking them off one by one while people get involved, because there’s so much there’s a lot of, there’s a lot of myths around AI ops, too, right. That need to get dispelled through that process. And, and we’re just in the beginning, you know, I think that that’s there and that actually is a good lead in to our final topic.
Speaker 2 (13:31):
And Roy, the AI ops the history uses and future of AI ops. So article written by James McGuire of E week. So this, this, this one kind of caught my eye. It it’s an interesting article in that it goes a little bit into the history and a little bit into the future. And some of the current use cases right now, I actually wholeheartedly agree with pretty much everything in this article. And they talk a little bit about AI ops and where the term came from. It was actually coined from Gartner, which is interesting because we work with a number of analysts and they they’re all kind of trying to take their own spin on AI ops because they don’t want to call it AI ops to give, you know, a competitor like Gartner, you know, kudos. But in the end, AI ops is, was coined by Gartner.
Speaker 2 (14:19):
And that’s what everybody’s calling it. And it gets a little confusing when other analysts use other terms, you know, like, well, what does that mean? And they’re like, you mean, say I ops I’m like, oh, okay, great. Talk a little bit about some of the use cases. One of ’em the chief product officer from BMC talked about some of the use cases, the outlined five use cases. I think those were dead on, we’ll talk about those in a second. And then essentially, you know, what are the two shifts of AI ops coming into in the, in, in the future? So what are your thoughts on, I know you read this article, what are your thoughts on it? And I, you know, initially, and I think we talked ad nauseum about why AI ops is even a thing, right. And, you know, the processing of data, data streams, and massive amounts of data. I don’t think we need to get into that too much, but I think it’s interesting that, you know, kind of talking about the use cases that I’m the chief product officer for BMC brought up you know, what are your thoughts on that? Why don’t you outline these use cases and give me your thoughts on that.
Speaker 3 (15:25):
Okay. I’ll actually, you know what I didn’t take, I don’t have the article in front of me just to look at what those use cases are.
Speaker 2 (15:31):
All right then, and then I will take
Speaker 3 (15:33):
In front of you. Why don’t you do that? I
Speaker 2 (15:35):
Had some thoughts
Speaker 3 (15:36):
In front of me there. But I, I agree with you before you do that. I agree with you. It was a very well-written article. And I think you know, I like the combination of pragmatic pragmatism, you know, where things are going and kind of real use cases, but he also gets pretty philosophical about sort of, you know, the nature and where technology is going as a whole in complexity. You know, and, and really simple things that are getting solved. You know, they, they seem simple on the surface, but you compound them and it creates just massive amounts of complexity. So I’ll, I’ll leave it at that. Like I said, we’ve talked about kind of the why of AI ops, but I liked the way he explained some of that. But to some of the use cases you want to go through those.
Speaker 2 (16:17):
Yeah. Yeah. So these are use cases that you, you know, you work on on a daily basis. So you know, and, and again, you know, as we talk about the beginning of AI ops and why we were even talking about it, it’s about processing mass amounts of data. So when you get into the operations world, what are the areas that process massive amounts of data create law and it’s monitoring, right? Monitoring is really the, kind of the primary area that just creates tons of data, whether it’s monitoring infrastructure, monitoring, applications, monitoring containers, and microservices and things like that. So the five use cases you talked about were predictive alerting root cause analysis, prioritization of events, predictive outages, and service desk ticketing, which, you know, it’s kind of funny, right? Cause again, you know, we’ve been around the block for awhile and I’ve been doing this for 30 years and I can remember literally having conversations in the early two thousands, you know, with people and working with them on tools like micro muse, and an HP OpenView saying, Hey, you know, this is all about root cause analysis, right? And this is about prioritizing events and, and, and using this data from micro views to do predictive analysis. I mean, that was literally the story 20 years ago. Right. same exact use cases, use cases haven’t changed, but now we’re applying AI to it.
Speaker 3 (17:45):
Right? Yeah. I think it’s interesting, you know, I did HP OpenView back 20 years ago and then, and then IBM’s typology that came out of micro. And before that Riverside I’ve implemented those at some large telecoms banks medical pharmaceutical or medical facility. You know, and I think, you know, the big thing that HP did was downstream suppression, right? And it was like, we figured out downstream suppression suppression, when all those pings, you don’t have to, you know, paying failures, you don’t have to worry about, cause we figured out where it is, we’ve solved the root cause analysis. And it’s like, not really, there’s the, you know, networks are being configured at the layer more complex and then river soft and which was Mike Hermes. And then IBM came along and they figured out how to build a model that looked at connectivity and relationships and more the containers.
Speaker 3 (18:33):
It isn’t just a router, it’s a router of modules or it’s V lands and there’s a whole hierarchy in there. And they figured out how to get suppression that way and became all right, we’ve solved the root cause analysis. And now in today’s world, you’ve got multi cloud and containers and virtual machines that go up and down. And so, so the world of problems to solve is become so much bigger in today’s today’s you know, method is, let’s just enrich it with lots of information and we’ll look at the textual content of alerts and look for patterns there. And so, and I think this is just one step in that evolution, right? As far as all the different algorithms in machine learning that are going to start to be applied and kind of be brought to the forefront of, of how you solve these problems. But yeah, there’s five use cases you just mentioned. I didn’t note them down cause they’re really the same five use cases that we’ve been seeing for 20 years. Right. I don’t think that, I think that’s kind of a known, right.
Speaker 2 (19:32):
Yeah. Kind of a funny, funny story is that when so we founded, I founded a company called real ops back in 2004 and it was the first runbook automation platform on the market. And I remember when we were raising money and talking to investors and a lot of the investors one particular group who actually ended up who actually ended up investing in us basically said, Hey, I was doing this a long time ago. Like they haven’t solved this problem. Like that was literally like 17 years ago. So yeah, the use cases are exactly the same. It’s just that the infrastructure is getting so much more complex. Right. And w I kind of laugh about the use cases not changing, but in the end, that’s really what operations is all about. It’s it’s except that the infrastructure that we’re managing 15 years ago when you had, you know you know, switches connected to routers connected to, you know, in servers connected to a, a switch, it was more straightforward.
Speaker 2 (20:40):
Now you’ve got like you said, cloud services, you’ve got virtualization, you’ve got instances coming up and coming down. So your topology is almost changing instantaneously. And you’ve got all these new layers of, of, of software components that are all kicking off information. It’s just harder and harder. So last thing before we kind of head out for the weekend the last part of the article, which I thought was really about the future, right? Two shifts and in AI ops, one about AI will exponentially increase, which we kind of mentioned before. We’re just in the beginning throes of this. And and I think that, you know, three years from now, we’re going to see very different things going on AI ops. And the other thing is AI ops meaning is going to change. I think where I stand on this, this thing is I think that the concept of AI ops, if you’re, if you’re thinking about it as a monitoring platform, yes.
Speaker 2 (21:40):
AI ops is going to change. The meaning is going to change. When you think about AI ops as a strategy as we do, then I don’t know if the meaning changes. You just accept the fact that AI is going to start embedding into all kinds of different parts of your infrastructure and your, and your, your management systems, whether it be virtual chat bots, like service now is working on now, or, and we talked about last week, embedded AI into salt, into hardware platforms, into the bedded, into the bedded, right into the right into chips of, of, of, of the servers and things like that. I think that’s going to, that’s going to change, which basically goes back to shift one that it’s going to accelerate, you know, very, very fast.
Speaker 3 (22:32):
Right. All right. Yeah. I’ll make a couple comments on what he said about the future is a quote on me. He said he sort of used AI for it, operations, which is what IOP stands for now to just becoming more broadly AI operations and becoming, and I’ll quote a single all encompassing AI system that doesn’t just help monitor it operations, but also forecast business spending employee retention rates analyze the success of marketing campaign. So he really makes a pretty bold step and says this AI, that we’re kind of focusing on it operations, as well as the AI and all these other problem areas are all gonna converge. And I think we, we kind of touched on that last week and that I had said, you know, that the AI I ops or it operations people should be looking into the rest of the CIO organization.
Speaker 3 (23:19):
The other thing he mentioned is just the convergence of AI ops and robotic process automation. You know, and I think my big takeaway there was really, I think people have to get really good and our customers and we as well at defining problems very well. And I think as you define the pro those problems, you’re trying to solve very well. I think then you start to educate yourself on machine learning and AI, and what are the what’s the level or what’s algorithm, or what’s the approach to solve the problems? Because I think it isn’t, you don’t just apply AI, AI, or robotic process automation in a blind way to the problems. You really got to understand the problem that you’re facing and what’s the best use of technology to solve it.
Speaker 2 (24:02):
Well, I think that, I think that wraps up this week and I appreciate your time. I hope you have a great weekend. I hope everybody watching has a great weekend and get some time off. And we appreciate you guys listening in. I want to thank our sponsor Winward consultant group. The number one global leader in AI ops for sponsoring this, this broadcast. And we will see you next week. Thanks bill. Have a great weekend. All right.
Speaker 3 (24:30):
See you, Sean. See you next week. Bye.
Speaker 1 (24:33):
Thank you for joining us in this conversation about AI ops and the future of it. Operations interested in a deeper dive on these topics. Check out our resources available@aaopsevolution.com and remember to subscribe, to get the latest episode.
AIOps – Riding the Tech Wave Towards Future IT Integrations
Enterprise IT Consulting: Strategy Planning in a Post-COVID World
Enterprise IT Consulting: Strategy Planning in a Post-COVID World
Enterprise IT consulting firms have seen the pace of digital transformation initiatives dramatically accelerated since the beginning of the COVID-19 pandemic. These changes have major implications for planning IT strategies moving into 2022 and beyond. Here are some challenges we’ve observed, and the strategic shifts IT leaders are making to adjust.
Processes and policies have changed rapidly, including how internal operations work, how employees communicate with one another remotely, how supply chains move goods from enterprise to end-customer, and how customers interact with the enterprise.
The rapid adoption of a broader net of digital technologies also means more digital vulnerabilities across an enterprise.
With all these challenges in mind, IT leaders now bear more responsibility for a larger digital asset footprint. That means strategic budget shifts and resource reallocation, so new tools and technologies can be effectively managed.
Tech investments surged during the pandemic while other departments tightened their belts – but with that bigger investment comes greater responsibility for IT teams. This trend is not slowing either. According to a McKinsey Report, 67 percent of top economic performers are planning to double down on tech as a differentiator.
This increased responsibility has given tech leaders a seat at the executive table for IT strategy planning across the enterprise. It has also left them in a position to make critical infrastructure decisions on their own; which can be stressful, time-consuming, and costly. With teams and resources stretched thin, IT leaders often turn to enterprise IT consulting vis-à-vis managed service providers (MSPs). They offer strategic guidance and expertise on their accelerated journey towards digital transformation.
Read Now: Why IT is Essential to Enterprise Analytics
Tech Leaders: Steering the Ship in Uncertain Waters
Tech innovation is now more closely correlated with business strategy than ever. Most successful companies – according to the same McKinsey report, over half of the top 10 percent of high performers – are looking to their top tech leaders to play a central role in shaping the overall business strategy.
As tech leaders take on this higher-level enterprise strategic planning, they need a long-term vision with measurable milestones. It’s difficult to forecast given the current level of uncertainty about the future. Adding to the challenge is that digital transformation does not happen overnight.
It’s an intrinsically complex effort requiring long-range planning. It takes systematic changes not only in physical hardware and software but also in attitudes and behaviors across the enterprise. This is easier said than done, especially with a limited budget and resources for companies recovering from recent events.
Read Now: “16 Quality-Assurance Steps to Take Before Rolling Out New Tech”
Enterprise IT Consulting: A Trusted Guidepost for IT Strategy
The first step in attaining digital transformation is assessing current systems for what works, what doesn’t, and where gaps exist. This provides the starting point and foundation for IT strategy.
Once tech leaders answer these questions, the next step is finding the right solutions to fill gaps, developing a plan to sunset or migrate away from technologies and systems which aren’t working, and seeking efficiencies that could free up the budget to acquire and resource replacements.
This process can be complicated and overwhelming for many IT teams, especially in the midst of keeping everything running in the here and now.
With hundreds of vendors advertising themselves as the “best solution” or “best tool” for the job, it can be a headache at minimum sifting through each one to find the “right one.” For this reason, enterprises often seek outside expertise and advice from enterprise IT consulting agencies.
Consultants bring niche expertise and an objective outside perspective. This allows businesses to save time and money, as well as increase competitiveness and professionalism.
Saving time and money have always been part of a company strategy, but COVID-19 made it even more necessary to utilize people, processes, and resources efficiently. As leaders make critical decisions for strategizing a budget for technological developments across an enterprise, savvy IT consultants and MSPs are resources they can trust.
Read now: Enterprise Monitoring: Are We Running in Place?
Enterprise IT Consulting Benefits
The best IT consultants are a more valuable resource for Fortune 500 companies as Information Technology transforms business operations. Keeping up with current trends and an evolving landscape can be a full-time job. An enterprise IT consulting agency provides specialized expertise; suggests more efficient models and processes, and help increase return on investment (ROI).
Other benefits include the following:
- Consultants are invested in your goals: Your ROI, your goals and your bottom line matter most to consultants. They are working to help achieve customer goals and milestones with actionable advice and guidance.
- IT Consultants have an array of partnerships and are not pushing a product: Most of the time, vendors focus on selling a product. But working with the right IT consultant will get to the true solution an organization seeks. They are not invested in providing a product, but in providing strategic value to the organization.
- They are aware of today’s changing digital standards and regulations: The strength of enterprise IT consulting is providing niche expertise. An experienced IT consultant likely has completed several previous projects similar to those of their customers. This gives tech leaders peace of mind and increases the likelihood of success.
- They work with your team side-by-side from implementation to integration: Top IT consultants work as an extension of the business. They will start a project and see it through to maturity. This includes deployment, migration, integration, implementation, employee training, guidance, troubleshooting, and follow-up.
One of the great challenges ahead for tech leaders and C-level executives is not only adapting to post-COVID uncertainties but leveraging post-COVID possibilities. Successful leaders will see this as an opportunity to restructure and grow business initiatives. The technological transformation that started with COVID is not slowing down.
IT innovators looking for a way to give their enterprise a leg up in the competitive landscape should consider enterprise IT consulting. These companies bring unique outside perspectives to the table and focus on how to help tech leaders win at realizing their strategic plan and vision.
We understand the enterprise needs to quickly adjust to the new world of COVID-19 and beyond.
See how we can help.
Enterprise IT Consulting: Strategy Planning in a Post-COVID World
How AIOps Benefits the Entire Organization – Not Just IT
How AIOps Benefits the Entire Organization – Not Just IT
The AIOps Market was valued at USD 13.51 billion in 2020 and is projected to be worth USD 40.91 billion by 2026. As this industry continues to expand, IT leaders have to communicate AIOps benefits for the business to leadership.
Yet, this is easier said than done oftentimes. According to a Gartner report, in 2021 about 75% of AI projects will remain at the prototype level as experts and organizational functions cannot engage in a productive dialogue with leadership teams.
In response, here are five ways that AIOps benefits and provides value to an entire organization – not just the IT department. And, yes, revenue accumulation is one of them.
1. AIOps tools benefit collaboration across the enterprise
Data silos are a common problem for many organizations and a source of inefficiency. A data silo collects and houses information for one group, and is not shared across the enterprise.
When only certain groups within the organization have access to data, it slows processes down. Additionally, it doesn’t provide a full picture of an issue to all. This creates bottle-necking and could lead to misdiagnosed errors on a system.
In contrast, AIOp tools boost collaboration, workflows, and bandwidth within IT groups. In breaking down data silos, AIOps makes data available for all teams to analyze and monitor. This, in turn, leads to faster identification and resolution for any errors while increasing productivity.
Furthermore, it also extends into the rest of the organization. With customized reports and dashboards, teams across departments can understand their tasks and requirements quickly. Not only that, AIOps tools down data silos and bolsters inter-departmental conversations that drive better business metrics.
2. Propels digital transformation
Companies seeking to enact digital technologies across the enterprise should start with AIOps. The IT department often leads change management in digital transformation and adoption. As with any strategy, companies that start implementation in a small sector of their organization will be more successful with a tiered approach to AIOps maturity.
This adds business value by saving time and effort so staff can focus on innovation. Additionally, it provides end-to-end visibility into infrastructure and applications. This includes a security overview and analysis, which we expand on more in the next section.
3. AIOps, a first-line of defense
Due to its capabilities to organize and isolate events in massive datasets, AIOps has long had the potential for reaching into cybersecurity. As a bridge between IT operations and security operations, AIOps boosts system uptime and reliability. Here’s how:
One scenario is detecting application performance issues. AIOps sifts through thousands of data points and constantly learns how to resolve and respond to various events inside of a given dataset. With visibility into security data, AIOps can detect foreign data causing issues that could be linked to a cyber attack against the underlying server.
That point of recognition would immediately trigger a defense process. In contrast, traditional tools would play these anomalies out as performance issues, not security threats.
This is only one example of how AIOps can be the first line of defense for cybersecurity. Going even further, AIOps could shut down a server that’s under attack or shut off access to a storage system that is compromised.
4. Improves service delivery and performance monitoring
From the standpoint of the IT department, AIOps provides constant monitoring and performance analysis as well as forecasting and resolution of issues (sometimes before they even arise).
While this benefits the IT operations team by releasing them from constant monitoring, it also benefits the end-user experience.
It enables IT personnel to respond to larger ticket items that require more human interaction or they can resolve issues quicker, for instance. This in turn produces a better end-user experience as customers and internal teams will either 1) not know about the issues because AIOps resolved them) get an immediate response from the IT support desk.
Ensuring a seamless customer experience with predictive analytics is an important business objective.
5. AIOps reduces costs and improves ROI
Yes, AIOps saves organizations time and resources! Businesses realize improvements by decreasing mean time to repair (MTTR).
Automation removes repetitive manual tasks from the plates of the IT team and puts the team in a better position to serve higher-level enterprise needs. In this way, organizations optimize the overall capacity of their teams with both increased output and cost savings.
Don’t take our word for it though. Check out the case study below to find out real facts and figures on the benefits of AIOps in cost reduction.
Case study: The economic impact of AIOps
A large financial service institution cut its MTTR by 40% in the first six months after implementing AIOps, leading to greater availability of customer-facing services and greater revenue for the business.
At the level of cost, the company reduced its tool sprawl by 50%, from over twenty tools to fewer than ten. This decrease in tools led to millions of dollars saved in the following ways:
- Reduced license fees
- Lowered cost of maintenance and operations of the tools
- Reduced complexity in the tool ecosystem.
Implementing AIOps as an evolution
Businesses can no longer survive without technological advancement – that much is clear. So, IT leaders need to make it very clear to leadership teams that AIOps is a way forward towards digital transformation and staying relevant.
The enterprise-wide benefits of AIOps are clear: It provides better communications, breaks down silos, equips your IT teams to better respond to customers and end-users, and provides an avenue for tech innovations. This is an important strategic stance that elevates a business by improving performance, visibility, and availability.
Start conversations with your leadership team about everything AI for IT operations.
How AIOps Benefits the Entire Organization – Not Just IT
IT Process Automation: An Answer to the Talent Crunch?
IT Process Automation: An Answer to the Talent Crunch?
COVID-19 caused major upheaval in more ways than just global health. It exacerbated an already existing tech talent skills gap. Prior to the pandemic, over half of the CEOs were nervous about the skills gap, and by 2019, 70 percent expressed concerns. The labor shortage has tech and enterprise leaders mobilizing different tactics to fill the skills gap. While some may turn to the global freelance market or upskilling current employees, there are those who present artificial intelligence (AI) for IT process automation (ITPA) as a viable, cost-saving answer to the talent crunch. |
IT Process Automation Streamlines Functions
AI for IT Operations (AIOps) represents a symbiosis between man and machine. Much of the conversation revolving around AI often spirals into a fear of the rise of something akin to “I, Robot.”
This isn’t helpful when we are talking about threats on a massive scale and trillions of data points beyond the human capacity to manage. AI is about helping people find essential roles alongside the automated tools used by many modern IT teams.
While AI can pull, push, lift, and calculate, it takes people to invent, contextualize, and make decisions based on ethics and morals. Research has shown that businesses have the greatest success when employees and technologies cohesively operate. Another point to remember is that AI will never replace humans, and it is not an excuse to avoid upskilling ourselves. Indeed, with AI humans will only create better technologies and processes.
Related Reading: How AIOps Benefits the Entire Organization – Not Just IT
IT Process Automation Tools Scale Operations Efficiently
ITPA tools can handle a wide range of IT operations automatically and accelerate IT processes with fewer errors. Here are some of the use cases for IT process automation tools:
- Managing service requests automatically
- Automating routine IT tasks
- Streamlining asset management
- Automating IT-related onboarding and off-boarding tasks
- Managing IT security and compliance
- Digitizing process and supporting digital transformation
Feel free to read our IT process automation use case to learn more about designing an AIOps approach and discover more applications.
Six IT Process Automation Benefits
1) Cost savings
Besides the cost of wages and labor (estimated at $2 trillion in the United States annually), there’s the cost of lost profit. On average, enterprises lose 20 to 30 percent of revenue due to inefficient processes.
ITPA minimizes the amount of labor and time it takes to complete manual tasks in an enterprise. Reports show that automation technology saves departments between 10 to 50 percent on costs associated with manual tasks.
2) Increased productivity
An IT team that is focused on menial tasks or trying to keep up with every, single anomaly in the network is going to get burned out and lose momentum. Automating processes has a two-fold productivity benefit:
- It speeds up the amount of time it takes to resolve multiple issues simultaneously
- It frees up the IT team to focus on higher-level business initiatives that are geared towards producing revenue.
3) Reduced errors
To err is unfortunately human and it happens in the IT department, too. Things get past people or fall to the wayside for a myriad of reasons. Reducing the chances of errors occurring with automation improves processes, interactions, and redundancies in operations.
4) Faster response to system problems
Since IT process automation utilizes data analysis and ML to “learn” about the IT environment, it can make data-driven decisions that do not require human intervention. Automating systems is like engaging a checks-and-balance system to mitigate errors before they escalate. This, in turn, enables IT, teams, to be more proactive and resolution-oriented.
5) Improved, simplified user experience
People like simplicity, convenience, and fast access to service. This is what most customers are looking for when comparing different providers. Automating IT processes ensures faster, more accurate, better quality services for clients as well as employees.
Instead of shuffling through a paper trail, teams can retrieve information instantaneously and assist customers. Happy customers mean meeting the bar of a promised standard of operational excellence. This builds trust, loyalty, and ultimately ROI.
6) Compliance benefits
As we become more technologically engaged, new rules and regulations continue to emerge to address these advancements. That being said, automation is traceable and under control. In this way, it helps enterprises to do the following:
- Meet security measures
- Protect confidential or sensitive information
- Provide retention methods for personal data
Leveling up IT digital transformation initiatives
Once again, it can’t be stressed enough that AI is not meant to eliminate human IT engineers, but to work as an extension of them. It helps them to level up IT initiatives and their own skill sets.
AI-powered tools promise to free up IT pros to focus on other parts of their job that are higher-level or more business-oriented. Equipped with automation platforms, teams can take a deeper dive on creating more robust and elaborate digital transformation initiatives.
As mentioned, it eases the sheer volume of alerts that IT teams have to deal with on a daily basis. One way to optimize processes is to aggregate data collection in a centralized platform.
In this case study, a government agency was able to establish a single platform for managing IT configurations, assets and business processes on the classified network with ServiceNow. The implementation allowed for IT process automation, saving time and effort across departments. The operation as a whole saw dramatic improvements to efficiency and visibility.
There is no doubt that AIOps is important to the future of the IT industry. However, it is less about filling skills gaps and more about enabling IT teams to provide real-time solutions. Humans will always be vital to the IT management process because they bring moral consideration, judgment, critical thinking, and experience to an IT automation process.
While statistics and anecdotal evidence continue to emerge about the talent crunch in the IT workforce, there is general optimism that the situation will correct itself.
ITPA will be part of this shift as well as improving education programs, upskilling, and retaining existing workers. If you’d like to learn more about how Windward has helped organizations navigate this transition successfully, we’d love to hear from you.
IT Process Automation: An Answer to the Talent Crunch?
AIOps Platforms: ServiceNow vs Moogsoft
AIOps Platforms: ServiceNow vs Moogsoft
AIOps isn’t a software, it’s a strategy – but investing in the right AIOps platforms can help set you up for success. Two big SaaS players offering AIOps solutions for enterprise clients are Moogsoft and ServiceNow. As a platform-agnostic IT consultant, Windward is well-placed to give an objective overview of these two software leaders and what they have to offer.
Let’s take a look at these two software platforms to see how they might fit into your organization’s AIOps implementation plans.
What is an AIOps platform?
As every business wants to grow more, IT infrastructure will demand an absolute change in scale. The conventional approaches for monitoring, managing and fixing IT operations are no longer efficient as the digital landscape requires handling trillions of data sets.
In the current era, there is a sharp increase in the volume of data generated inside and outside the organization from IT infrastructure and applications. This puts CIOs in a challenging position as they struggle to identify actionable insights from the cluster of data sets. CIOs are looking for AI strategies to obtain better visibility and enhance the performance of their IT environments.
AIOps (Artificial Intelligence for IT Operations) is a multidimensional technology approach that deploys big data analytics, machine learning, and automation to ensure the IT operations are smarter, more predictive, and more productive. AIOps platforms will play a crucial role in transforming IT operations from reactive to proactive and ultimately predictive.
ServiceNow and their AIOps Tools
ServiceNow AIOps is a solution that runs proactive and secure digital operations by predicting and preventing issues and automating resolutions. It helps move IT operations from a reactive team to one that works intelligently for your business.
It has been designed for users to gain visibility across IT infrastructure and apps, maintain service health, and optimize cloud delivery and spend.
Key Business Benefits of ServiceNow AIOps Tools
- Identify the root cause of incidents and provides actionable insights across teams
- Reduce outages by taking action based on guided recommendations
- Collect, predict and analyze telemetry/log data for enhancing visibility and reducing noise
- Simplify repetitive tasks with pre-built playbooks and knowledge base resources
- Extend Configuration Management Database (CMDB) and create a strong data foundation with service graph
Key Capabilities & Functionality of ServiceNow AIOps Platform
- IT Operations Visibility: Gain visibility across the IT infrastructure, application, and services.
- Discovery: Get a holistic view of the IT operations footprints across on-premises data centers and the cloud.
- Service Mapping: Map the relationship between IT components and business services in a dynamic environment.
- Certified Management: Discover, itemize and proactively manage the TLS (Transport Layer Security) Certificates.
- Firewall Audit and Reporting: Track firewall policies, monitor ownership, and perform proactive audits
- Service Graph Connectors: Accurately import and standardize external data into the CMDB (Configuration Management Database)
- Predictive AIOps: Predict and prevent issues with a single system to gain insights and automate resolution
- Event Management: Reduce event floods from monitoring tools and gain insight into business service health.
- Health Log Analytics: Proactively analyze real-time log data and detect anomalies.
- Site Reliability Operations: Register services, track changes and respond to incidents.
- ITOM Optimization: Optimize strategy, operations, and spend across a multi-cloud environment.
- Cloud Management: Minimize business risk and manage costs with self-service delivery of cloud services.
All You Need To Know: Integrations & Pricing of ServiceNow AIOps Software
ServiceNow integrates with existing software and third-party applications and data sources. The most common integrations of ServiceNow are with CMDB, Incident Management, Problem Management, Change Management, User Administration, and Single Sign-on.
The size of the company (No.of employees/users) being the first step in ServiceNow’s custom quote calculation, the number of licenses also weighs in to influence the total price.
Moogsoft and their AIOps Tools
Moogsoft is an AIOps platform that uses artificial intelligence to ensure uninterrupted service delivery and improve the efficiency of IT operations. It assists businesses to analyze data, detect anomalies, diagnose the root cause of a problem, and strategize the business plans. By using machine learning algorithms, it supports DevOps and ITOps teams to deliver faster, smarter, and more efficient applications with reduced downtime.
Key Business Benefits of Moogsoft AIOps Tools
- Remove noise and distractions
- Correlate information across multiple data sources
- Facilitate frictionless, cross-team collaboration between different IT specialists
- Capture information in the background using machine learning
- Identify the root cause of the problems
Key Capabilities & Functionality of Moogsoft AIOps Platform & Tools
- Collaboration: Make sure the collaboration across IT teams is a quick way to resolve complex multi-service incidents
- Enrichment: Add context to ingested alerts from various data sources to provide actionable insights
- Correlation: Make logical connections between data from anywhere in technology stacks
- Noise Reduction: Large volumes of data hinder detecting and fixing an outage
- Anomaly Detection: Identify anomalies that are outside normal operating behavior and impede the customer experience
- Custom Integration: Build customized integrations to any data source for full observability and collaboration
All You Need To Know: Integrations and Pricing of Moogsoft AIOps Platform
Moogsoft AIOps platform enables the integration of any database from any existing tool. It empowers the IT systems to monitor, measure, analyze and report for ensuring the business apps and services work productively. And also, the inbound metrics API serves as an endpoint where the employees can send time-series metrics from the monitoring services for correlation by Moogsoft. The price for the subscription starts from $833/month and may vary based on the purpose and size of the company.
Why you might need both ServiceNow & Moogsoft Together With Winward
AIOps is a strategy, not software. It accelerates the IT operations in terms of increasing performance, predicting outages, automating tedious tasks, making reporting actionable, and improving risk management while coupling with AIOps platforms like Moogsoft, ServiceNow, and Splunk.
The right solution is highly dependent on your existing IT ecosystem.
Book a meeting with one of our experts to discuss.