To help these teams monitor performance and manage incidents in these ever-complex IT infrastructures, vendors have introduced different types of point solutions:

• Monitoring: Monitoring solutions collect raw data indicating how well (or how poorly) a system or component is performing. Typically this is in the form of metrics, events, and logs.
• Observability: Observability tools help IT teams gain a more complete view across their systems and monitor the flow of data and requests through services.
• Incident management: Incident management software orchestrates the process for restoring a system to normal operation through notification, triage, escalation, resolution, and documentation.

How AIOps optimizes point solutions

Monitoring, observability and incident management point solutions bring particular expertise to their specific domain. In other words, they typically solve one problem in the incident lifecycle extremely well.

But there’s a problem: point solutions lack connectivity. They only provide siloed data that can leave significant gaps in understanding a system’s overall performance. Further, disparate solutions naturally create inefficiencies — multiplying the number of places an incident can live and failing to link issues that are often system-wide.

With operations and SREs under pressure to ensure the availability of complex IT ecosystems, teams need more sophisticated insights than narrowly-focused point solutions can provide. They need robust tools that enable continuous insights across an entire IT stack.

Enter artificial intelligence for IT Operations (AIOps). Domain-agnostic AIOps platforms are purpose-built to connect monitoring, observability and incident management tools and provide teams with a comprehensive solution to achieving availability.

By acting as the connective tissue between point solutions, AIOps technology analyzes and adds value to massive amounts of data across otherwise siloed tech stacks. By converging all systems and ingesting various types of data, AIOps tools give DevOps and SRE teams:

• One summary dashboard: Domain-agnostic AIOps solutions ingest all types of monitoring data and condense this information into a single, visual representation of system health.
• One place for incident lifecycle collaboration: An AIOps platform serves as the single location for teams to work together on resolving complex, multiservice incidents. The technology gives DevOps and SRE teams full visibility into the incident timeline from detection, notification and resolution.
• Apply system-wide intelligence: Connecting monitoring solutions with an AIOps solution allows teams to apply intelligence across their integrated tool stack. The technology adds key context to data, enabling DevOps and SRE teams to understand interdependencies and relationships. And its alert correlation helps make connections between data from multiple sources so teams can identify root causes faster.

In short, an advanced AIOps platform enables teams to see and understand everything necessary for them to ensure the top performance of their digital apps and services. And this holistic approach to monitoring and incident management produces significant results. With the full picture of system health and a streamlined incident workflow, DevOps and SRE teams can reduce mean time to resolution (MTTR) and build time back into their days to focus on more fulfilling, value-adding initiatives.

Why Moogsoft?

Of course, there’s a caveat. If an AIOps tool covers all domains, it will ingest a tremendous amount of data. Accordingly, it must be engineered to scale. The requirement for robust engineering is why most AIOps vendors do not actually provide insights across an entire IT stack.

But Moogsoft is not like most AIOps vendors. Moogsoft’s founders built their platform with convergence and scale in mind, allowing for true connectivity across all metrics data.

The post Why AIOps is the Connector Between Monitoring, Observability and Incident Management appeared first on Industry Leading AIOps and Observability Platform for IT Ops and DevOps.

The data we collected showed that teams are:

• Drowning in data thanks to monitoring tools proliferation
• Stuck in monitoring and incident management cycles
• Not even delivering on the availability promises they are making

It’s time for leaders to help their teams to unlock time to create optimal infrastructure for availability and escape the vicious cycles they are stuck in—where time is always spent fixing problems and rarely tackling the underlying causes to deliver improvements that have longevity. And for those teams who have autonomy over what work they do when—it’s time for them to adopt new practices and tooling that create an infrastructure that supports sustainable ways of working.

Here’s how to do it.

1. Start with baselining your current availability state. You need to know what you’re dealing with to know what to change. And you need to be sure your destination aligns with your organization’s goals. In the context of availability, this means creating customer experiences that result in tangible feedback in the form of social sentiment, referrals and reviews, and product or service usage that ultimately result in increased income. You need to know what monitoring tools you have, how they are used, and what they are costing you. And you need to understand your current performance vis a vis the metrics you already have in place.
2. Then define a small set of KPIs to take forward—and make sure they are aligned to your business goals. As we noted in our previous blog in this series, fewer KPIs correlate with higher performance in terms of meeting SLAs so choose carefully. We recommend error budgets to ensure day-to-day adherence to promises and using MTTD and MTTR to aim to release time from unplanned work to make higher-level improvements. Tagging the type of work your team is doing—unplanned work, paying down technical debt, automating toil, platform improvements, new features—is also going to help you here.
3. Review your monitoring tools landscape and consolidate by prioritizing tools by value and usage. This will enable you to reduce your Total Cost of Ownership (TCO) and reduce noise.
4. Now it’s time to reduce the noise you’re getting from the monitoring tools that remain—use AIOps to do this and watch your MTTD drop along with the volume of unplanned work your team’s dealing with.
5. You can use that time that’s just been released to stabilize your system by paying down technical debt—thus also reducing unplanned work. Automating toil away releases even more time.
6. Now you have time to adopt the ways of working that leap you forwards—DevOps and cloud. And—instead of just maintaining customer experience, you can invest in innovating.

Getting control of your monitoring landscape, trimming it, and giving it AIOps superpowers is a virtuous circle that leads teams to a place where they can invest in their future—not just survive in the now. These technology teams are a direct line to the customer in a digital economy and their ability to guarantee customer experience and availability determines the success of an organization. Do not treat them like second-class citizens—enable them to be game-changers for your business.

The post How to Help Teams Create Optimal Infrastructure for Availability appeared first on Industry Leading AIOps and Observability Platform for IT Ops and DevOps.

In this blog post, we’ve interviewed a couple of past Quarter winners to hear their thoughts on their time at Moogsoft.

Jared & Valerie: What do you enjoy most about your job?

[V]: I would definitely say, the best thing about working at Moogsoft is just that the people are really great. During my interview process, I had the opportunity to meet a couple of people, which really impacted my decision to start working here and take this job. Being able to connect with other people from literally all over. It's been awesome, and everyone's so friendly, and the culture, I would say it's a very healthy culture to be in, which was important for me as well.

[J]: In my role specifically, I have the joy of getting to work with people and teams from all across the company rather than just a single team, and I found that I work really well that way and really come alive in the role. I get to connect and collaborate with people and other stakeholders just across the business, and I feel most fulfilled at work when getting to sort of lead an initiative, and get to pull people in from all these different parts of the business, and we get to see something come together in a really beautiful way. I found that people have so much value to add, and sometimes they might not even be aware of the value that they'll bring to the table for something, and just getting to set the table for others to brainstorm and throw out ideas, can really push something forward in a way that's only possible when they're there. And we're all collaborating together.

How would you describe Moogsoft's culture?

[V]: I would describe Moogsoft’s culture as just being one that really values the people over what they're doing. Although what we do is very fast paced and there's so many moving pieces, we're able to connect with the people on our teams laterally and unilaterally, just to be able to get to know people, and I would say it's a friendly culture. It's fun. It's light hearted. There are very serious moments, but there's also just time to just relax and to be friendly with one another.

[J]: I think calling a culture of work collaborative can be pretty overused, but I've truly never seen a collaborative spirit so alive in a company before. We don't work in silos on our teams. Cross functionality is really strong.and we definitely do our best work when we pull other people in from all these other teams to collaborate together. Um, just for the additional insight and the perspective to really round something out in a way that again can only happen when we are collaborating in a way that's cross- team.

And the other thing that I really enjoy, of course, is the work life balance that's promoted and encouraged, which in my experience is quite rare to find. As a dad and a husband, this is really important, because we're encouraged to take time for ourselves to be with their families, and to be present with the things that we value and enjoy outside of work

What is something you’ve really enjoyed at Moogsoft?

[J]: There's been a lot. A recent project that was really fulfilling for me was getting to roll out a new piece of software internally for our teams to measure customer satisfaction. It was a joy to see those results come in from customers over the course of a few months, who just been absolutely raving about their interactions with us. And it was really rewarding to implement a tool not only to measure the external satisfaction with our customers, but it's also serving as a way to highlight the support team to our internal stakeholders. They're really proud of the processes that are in place on that team and the work that they're doing. And now there's a quantifiable and measurable way to show that.
[V]: Phil really does inspire me. The way that he's able to carry everything that he carries for our company is really astounding. His scheduling is so packed a lot of times, but he still makes time to connect with his employees and with people outside of business which is really awesome to me. He's also so knowledgeable about things that I have just been able to learn from him every time I have a conversation with him, and just being able to work directly underneath him allows me the opportunity to learn more and to be better, and inspires me to be excellent in everything that I do. It's been so great working here.

The post What’s It Like Working At Moogsoft? Our Employees of the Quarter Talk About Values, Culture and Collaboration appeared first on Industry Leading AIOps and Observability Platform for IT Ops and DevOps.

But, according to our recently released Moogsoft State of Availability Report, teams burn their time, money and energy on incident management. In fact, engineers overwhelmingly report that incident management takes up most of their time.

With so much investment in simply keeping their systems alive, teams lack the time to proactively optimize their infrastructures. And this becomes a vicious cycle — fragile systems generate more incidents and more incidents take up more time. As a result, engineers cannot prioritize increasing the infrastructure resilience that will free time for more innovation and value creation.

How to build tech stability

1. Take stock of your IT ecosystem’s current state.
   1. The first step in building tech stability is truly understanding your IT stack. This foundational work will set you up for the five remaining steps.
   2. Understand your organization’s business goals as they relate to availability.
   3. Determine which apps, services and infrastructure are essential to your organization.
   4. Analyze your availability targets like KPIs and service level agreements (SLAs).
   5. Review your monitoring tool stack, including each solution’s usage, maintenance requirement and licensing fee.
2. Reevaluate your KPIs.
   1. The truth will set you free — and help you create transparency and efficiencies. But, if you’re like most teams, your managers are in the dark about your team members’ everyday activities. And, your team does not measure meaningful data like mean time to detect (MTTD) and mean time to recovery (MTTR), meaning you do not know where you are losing time. (Spoiler alert: MTTD and MTTR are a significant 90 minutes of the average incident lifecycle.)
   2. Create transparency around your work distribution (especially between managers and team members) by tagging your ticketing tools for tasks like unplanned work, platform improvements and new features and tech debt.
   3. Track MTTD and MTTR and prioritize reducing these phases of the incident lifecycle.
   4. Measure the number of times customers flag an issue in addition to your other customer sentiment KPIs.*
      *Limit those KPIs — our research shows that fewer KPIs lead to higher performance and higher levels of availability.
3. Shrink your tool stack.
   1. With an average of 16 monitoring tools (and up to 40!), you likely have a lot of point solutions. Your disparate monitoring tools are not only expensive in licensing fees and maintenance and management time, but they also slow MTTD and MTTR by siloing information.
   2. Rank your monitoring tools by value.
   3. Get rid of less valuable tools and invest in the ones that help you meet availability goals.
   4. Reduce your time commitment to manage and maintain tools while saving money on licensing fees and decreasing noise and alert fatigue.
4. Prioritize noise reduction
   1. If you’re stuck in unfulfilling, time-consuming monitoring cycles, try artificial intelligence for IT Operations (AIOps). An AIOps solution converges all data from across your point solutions to detect incidents sooner, reduce noise, correlate alerts and facilitate collaboration across the incident workflow.
   2. Implement an AIOps solution that connects your monitoring tools and reduces alert noise.
   3. Align leadership and teams with an AIOps platform’s single view of monitoring data and insights.
   4. Use the AIOps technology to track data on unplanned work.
5. Pay down technical debt.
   1. As you start building system stability, you can dedicate time to further improving the IT ecosystem. Start with pre-production environments before moving on to the production environments.
   2. Use chaos engineering experiments to test the resilience of your digital apps and services.
   3. Leverage AIOps insights to determine where tech debt most affects your organization.
   4. Automate toil to release more time for your engineering team.
6. Invest in the future.
   1. Your now forward-looking organization must relentlessly innovate the customer experience. And it must continue investing in DevOps capabilities and your system’s capacity to withstand turbulent conditions.
   2. Compare how frequently your teams and tools catch incidents versus how frequently your customers flag these issues — and report on your improvement.
   3. Push a DevOps culture and adopt DevOps capabilities.
   4. Keep your focus on the customer experience.

If teams want to move past just “keeping the lights on” to push higher organizational performance, they must reduce the time spent on monitoring and incident management. And the answer could lie in domain-agnostic AIOps. By connecting point solutions, AIOps gives teams insights from across the entire IT stack. And the technology’s informative and actionable data enables them to streamline the incident response and detect and remediate issues faster. All of this frees precious time, time that could be spent paying down technical debt, automating toil and further improving availability.

Interested in building your tech stability? Take Moogsoft’s AIOps solution for a spin.

The post Just Maintaining Availability? Try Building Stability appeared first on Industry Leading AIOps and Observability Platform for IT Ops and DevOps.

Moogsoft pioneered AIOps, essentially inventing the market 10 years ago. It is worthwhile revisiting why we did that to understand where we are going. My background is as the founder and inventor of Micromuse Netcool, and the RiverSoft’s OpenRiver technology. Those approaches were revolutionary in their day, but based upon the idea that infrastructure was fixed, applications may be less so. That radically changed with the advent of cloud computing and virtualization and we realized that AI was necessary to perform the advanced data analysis needed to quickly identify, diagnose and remediate the thousands of minor glitches that occur in a large business like Manulife. The rub being if they are left unresolved minor glitches can become major outages.

Looking forward, the arms race continues as we see increasing adoption of serverless, lambdas, SDN, DevOps, CI/CD and many other technologies. In fact the “doubling time” of change seems to be shortening. What this practically means is that we have to broaden the scope of our product from events to metrics, traces, logs, business data, environmental and social, and double down on the algorithmic sophistication we use to perform our critical task of moving our customers from 5 9’s to no nines. We today have a platform that can handle metrics, and we have active research in all areas of complex event analysis.

Tomorrow I envisage a single platform as the repository for all operational data, handling all availability management tasks from SecOps, DevOps, ITOps, SRE, Alerting, Problem Management and Service Desk. This will allow us to drive automation and liberate the time and attention of operations to run availability and risk as a business process not fire fighting!

Q: How does this take our ecosystem to the next level?

There are essentially two critical outcomes:

1. Availability: For example, one of our customers Manulife already does an excellent job of managing their error budget (total availability), targeting 5 9’s as the availability rate. Working together we can go after no-nines, ie 100% availability with business services being continuously available. We can see a time where major outages are exceedingly rare, if occurring at all and instead we manage a business operational risk metric. This essentially transforms platform services from a cost center to a P&L center as the consequence of opaque business operational risk is the need to hold higher reserves, reducing the return on equity. Not only can we target a better customer experience but better financial performance!
2. Operational Efficiency: Automation is the primary tool to reduce “toil” which is essentially the consumption of time in repetitive and mundane tasks by ops folks. These people are already overworked and overstressed (think air traffic control), and this really is about making sure they have more time for the fun side of the job, and a net reduction in the capital and opex spent by the firm in unproductive (but necessary) work.

So in short, better service levels, lower costs, more return on investment. That has to be good … right?

The post A Fireside Chat with Phil Tee, CEO of Moogsoft appeared first on Industry Leading AIOps and Observability Platform for IT Ops and DevOps.

For engineering teams tasked with managing the customer experience, KPIs often track availability. But which metrics do teams use to measure their availability? Do these KPIs actually help performance? And, critically, what do companies miss?

To demystify availability KPIs, the Moogsoft team launched its inaugural State of Availability Report. Here are some of the sometimes surprising findings about modern-day availability KPIs:

Teams spend a lot on availability — with little result

Teams spend most of their time on monitoring, and organizations invest in an average of 16 monitoring tools (and up to 40). Still, KPIs show that availability outcomes are not where they should be. In fact, 45% of customers notify teams about issues before their tools do. Why aren’t teams and tools stepping in faster to preserve the customer experience? Engineers are likely monitoring too many tools and piecing together insights from mountains of siloed data.

Solution: Companies should assess their monitoring tools to determine what exactly these tools are covering. IT leaders should make sure their monitoring tools provide a complete picture of system health, looking for overlaps, gaps and future optimizations. Additionally, leaders should measure how often customers catch incidents before tools do — and work to reduce that number.

Most teams breach their SLAs

Despite a significant investment in availability, 25% of companies miss their service level agreements (SLAs). Interestingly, teams with higher SLAs — which tend to be teams at larger companies — meet them more often than teams with lower SLAs. This outcome could be due to the fact that bigger companies tend to employ dedicated IT Operations teams and use platforms and services purpose-built for incident management.

Solution: Because breached SLAs lead to negative customer experiences, poor organizational performance and unsatisfied employees, tech leaders must take immediate, proactive measures to help teams prevent incidents, fix them faster and meet their SLAs. Artificial intelligence for IT Operations (AIOps) solutions can catch incidents before they impact the end user and automate the incident lifecycle for rapid mitigation.

Error budgets are the most popular availability KPI

Error budgets, the time a system can fail without counting against the SLA, are the most tracked availability KPI among small- and medium-sized companies and those enterprises with more aggressive SLAs. While error budgets are somewhat helpful measurements in explaining that teams missing targets, they fail to explain the why teams missed their targets.

Solution: Tech leaders should focus availability KPIs on mean time to recover (MTTR) and mean time to discovery (MTTD), which explain the specifics behind missed targets. Then, leadership can set objectives for reducing both metrics.

Fewer KPIs and higher SLAs produce the best outcomes

Clearly, higher SLAs are tougher to meet. But teams with tougher standards meet them more regularly. It’s likely that teams with fewer, more meaningful metrics can focus their time on attaining clear goals and avoid decision fatigue caused by information overload. From a leadership perspective, more precise information can be more easily incorporated into decision-making.

Solution: Tech leaders should narrow the focus of their KPIs, raising overall standards and eliminating less significant metrics.

Teams do not measure 66% of incident downtime

While most teams focus their availability KPIs on MTTR, fewer than 15% measure MTTD. That’s a significant problem. On average, MTTD takes about an hour — twice the amount of time needed for incident resolution. In other words, most teams simply do not measure 66% of their incident downtime, providing inaccurate data about the average incident lifecycle. Additionally, inaccurate data can hinder necessary investments in teams and tools, slow long term availability improvements and hide unplanned work.

Solution: Tech leaders must reevaluate KPIs, measuring the end-to-end incident lifecycle from detection through resolution. Focusing on MTTD and MTTR will help IT teams get an accurate picture of the incident lifecycle so that they can ultimately improve their availability.

Based on the State of Availability Report, organizations and teams have room to optimize their KPIs to improve availability and, ultimately, the customer experience. After leaders evaluate their current KPIs, they must also evaluate their tools. Are teams’ existing tools helping teams meet their KPIs? An AIOps solution can address many of the issues identified, providing early incident detection, automating collaboration for quick incident response and remediation and preventing destructive patterns from becoming service-impacting incidents.

Interested in digging deeper into availability KPIs? Watch the recently released “Engineering KPIs: How to Align Executive Strategy with Team Flow” with DevOps industry experts who discuss the benefit of fewer metrics, what metrics matter most and how to align goals.

The post Demystifying Availability KPIs — and What Most Companies Miss appeared first on Industry Leading AIOps and Observability Platform for IT Ops and DevOps.

While IT leaders select and implement these tools to save teams time, our research finds they do quite the opposite. Engineers spend far and away more time on monitoring than they do on any other task  — innovative, value-creating tasks included.

Still, monitoring solutions are critical. Because the economy runs on technology, digital apps and services must be available around the clock. And that availability is dependent on monitoring tools that constantly comb through mountains of data to find performance-affecting incidents.

The problem is: traditional point monitoring solutions do not work for today’s IT environments. Engineering teams need much more efficient and effective monitoring solutions for better availability outcomes and less toil.

So, what’s the answer? IT teams must connect point solutions with artificial intelligence for IT Operations (AIOps).

The problem with point solutions

By themselves, point solutions only monitor one piece of the IT ecosystem: the IT infrastructure, application, network or digital experience. While this traditional approach hones in on specific aspects of system performance, it cannot keep up with modern availability demands. Here is why:

• Expense: Point solutions are unnecessarily expensive — both in the sheer amount of time teams spend managing and maintaining them and in the multiple licensing fees.
• Information silos: Keeping valuable data siloed in different tools slows information sharing, communication and, ultimately, incident detection and resolution.
• Downtime: By using disparate tools, engineers can miss significant insights into system-wide incidents, and incident timelines naturally lengthen.

How to make your point solutions talk

Engineering teams need to connect otherwise siloed monitoring tools to streamline processes and speed incident detection and resolution. This is where AIOps comes in.

Domain-agnostic AIOps solutions are purpose-built to ingest all types of monitoring data collected from various point solutions. Instead of managing a slew of monitoring tools, engineers can use their AIOps solution to get a single line of sight across the entire IT infrastructure. And the benefits are numerous:

• One platform: AIOps provides a single, streamlined point of interaction for the entire incident lifecycle — from detection and notification through resolution.
• Single dashboard view: Instead of switching from tool to tool and analyzing disparate charts, AIOps platforms summarize the health of all systems and put that summary in one easy-to-see, easy-to-understand dashboard.
• Apply overall intelligence: By reducing alert noise through deduplication and correlation and connecting the tissue between all monitoring alerts, AIOps tools can quickly identify the incident’s root cause and keep engineering teams focused on the most significant, business-impacting issues.

Why Moogsoft isn’t just another tool in the toolbox

Unlike most AIOps vendors, Moogsoft was built to converge data from the entire incident lifecycle and provide companies with a holistic monitoring solution. So, we have domain expertise and (a long list of patents to back that up). We enable true connectivity across monitoring data, allowing for earlier detection, more uptime and less human toil.

We can still hear IT leaders now: I need another tool?!

Yes, but…

1. Moogsoft AIOps can identify redundant tools and help teams consolidate their tech stacks.
2. Moogsoft AIOps delivers far more value than adding point solutions to fill monitoring gaps.

IT teams already know the importance of availability and, thus, monitoring — that is demonstrated in their immense investment in monitoring tools. But IT leaders struggling to meet modern availability demands despite this investment should resist reaching for yet another resource-intensive monitoring tool. Instead, they should allow a sophisticated AIOps tool to seamlessly connect monitoring data for expedited incident detection and resolution and significantly improved availability outcomes.

The post Managing a Slew of Monitoring Tools? Here’s How to Make Them Talk. appeared first on Industry Leading AIOps and Observability Platform for IT Ops and DevOps.

While pieces of this spooky tradition persist, just a few other things have changed in the past 2,000 years. For starters, we are a digital society. We increasingly rely on an array of digital apps and services that enable our work and play. In fact, we depend on these technologies so heavily that the mere thought of their failure occupies the nightmares of countless IT teams and business execs.

What is causing these nightmares?

Incidents: the modern-day ghouls and goblins

Business leaders tend to fear the fallout of downtime — decreased sales, tarnished brands and disappointed customers. In the meantime, DevOps and site reliability engineers (SREs), those responsible for keeping digital apps and services working, focus on the ghouls and goblins behind this downtime: incidents.

And talk about scary. Depending on their severity, incidents in your applications, cloud services, networks and IT infrastructures can result in costly performance issues or system downtime, the spookiest things of all.

Luckily, today’s digital tools can detect your ghouls and goblins or, at least, turn them into benign pumpkins, fairy princesses and kitty cats. Here’s how.

AIOps: modern-day ghouls and goblins don’t stand a chance

Keeping your systems ghoul- and goblin-free requires monitoring solutions — but not just any monitoring solution. Most companies already have point solutions that detect specific disruptions at specific stages.

While point solutions efficiently monitor pieces of your system, their siloed approach to monitoring does not tell the full story of your technology’s performance and creates costly inefficiencies. Managing and maintaining your various tools take time and money. So, instead of armoring your systems against trouble, you spend time monitoring and maintaining your tool stack. And there’s another problem.

Let’s say an incident was causing performance issues. Instead of looking at one holistic analysis of your entire ecosystem to quickly detect the problem, you’d have to piece together information from disparate tools. While the clock is ticking, these ghoulish incidents could be wreaking havoc on your system.

What is the preferred method to stop ghoulish incidents in their tracks?

Artificial intelligence for IT Operations (AIOps). AIOps uncovers insights often trapped by siloed point solutions, enabling you to gain valuable insight into the performance of all of your digital apps and services. Are there ghouls and goblins hiding behind the fairy costumes and pirate get-ups? If there are, the AIOps solution seamlessly hands off the incident — with its valuable context — to engineering teams to fix.

AIOps also connects the dots between siloed monitoring solutions, filling data gaps where those ghouls and goblins can otherwise go undetected.

Go even further with modern AIOps

Now, not all AIOps technology can effectively increase your uptime, so choose your tools wisely. Legacy tools will not let you know about incidents until after they have occurred and after they have likely given your users a downright ghoulish experience.

To avoid outage nightmares, you need to select an advanced AIOps tool. Solutions, like Moogsoft’s, ingest various types of data from across an IT infrastructure, notifying you of a lurking data anomaly early in the incident lifecycle. With this early detection plus the solution’s automated collaboration, IT teams can fix incidents before they impact your user.

With an AIOps solution, you can sit back this Halloween, knowing that you’ll be alerted to any trouble brewing in your system!

The post Ghouls and Goblins Beware: You Do Not Stand a Chance Against AIOps appeared first on Industry Leading AIOps and Observability Platform for IT Ops and DevOps.

Of course, your weekdays and weekends could include a slew of other digital apps and services — project management, music streaming, accounting, gaming and the list can go on.

The bottom line is: we live in a highly digital economy where apps and services touch just about every aspect of our lives. We not only want these technologies, we depend on them. So, every modern business must guarantee the performance and availability of their apps and services. But it’s not an easy task.

How do companies guarantee their business-critical uptime?

They invest in monitoring solutions — either point solution monitoring or domain-agnostic artificial intelligence for IT Operations (AIOps). Both tools gather data indicating how an IT environment is performing. And both have the ultimate goal of preventing outages, maintaining uptime and attaining continuous service assurance. But each solution takes a slightly different approach to monitoring.

We will walk you through the pros and cons of each approach to identify which is best for modern IT environments.

Point Solution Monitoring: Pros and Cons

Point solution monitoring looks at a single piece of a company’s technology stack – the digital experience, IT infrastructure, application or network.

Pro(s):

• Point solutions are the historical solution to monitoring — and many have perfected their area of focus.
• Point solutions solve problems at every stage: monitoring, observability and incident management.
• Point solutions typically bring particular expertise to one piece of the availability puzzle.

Con(s):

• Point solution monitoring produces siloed data that leaves gaps when trying to figure out the full picture of system performance.
• Because human teams must piece together siloed data to figure out an issue, teams can miss vital context to an incident or outage. And missed context can slow mean time to recovery (MTTR).
• Single domain monitoring tools proliferate in the tools stack, and teams spend too much time monitoring these tools for incidents and managing and maintaining them.

Domain-agnostic AIOps: pros and cons

AIOps ingests various kinds of data from various sources to give engineering teams a real-time understanding of issues affecting their technology’s availability and performance.

Pro(s):

• Domain-agnostic AIOps connects the tissue between all tools’ alerts, so teams can get insights across an IT stack and identify root cause faster.
• AIOps solutions enrich monitoring data, extracting insights to make data informative and actionable.
• AIOps tools ingest various types of data, allowing teams to consolidate their copious monitoring tools, decreasing noise and alert fatigue.
• AIOps automates the incident workflow in one platform to streamline incident response and decrease MTTR.

Con(s):

• Domain-agnostic AIOps is a new way for many companies to think about incident management and can require significant change management.

…and the winner is!

Because our digital society is intolerant of downtime, companies must adopt monitoring tools that detect incidents before they impact business operations and consumers. Modern monitoring tools must identify anomalies early in the incident lifecycle and then expediently route the contextualized information to human teams so they can resolve incidents quickly. And they must act as the connective tissue across existing siloed monitoring tools, giving teams one place to go to manage the entire incident lifecycle.

Only AIOps can do this.

Perhaps Pankaj Prasad, Sr Principal Analyst at Gartner described AIOps best when he said the technology “connect[s] the dots to convey a story.” While point solutions give engineers all of the dots in a disorganized pile, domain-agnostic AIOps solutions deliver engineering teams with the comprehensive picture. This allows teams to identify the source of the problem earlier, respond more rapidly, improve availability outcomes — and, ultimately, compete in our digital economy.

The post Point Solution Monitoring vs. Domain-Agnostic AIOps. Which is Right for You? appeared first on Industry Leading AIOps and Observability Platform for IT Ops and DevOps.

The problem with having too many KPIs is that they cause information overload and noise. That means the teams accountable for fixing problems and incidents are overwhelmed with data and then suffer from decision fatigue. As Kai Wang, Divisional CIO, Silicon Valley Bank puts it:

“It's not the tools that help drive culture, it’s the data. Data don’t lie. But if you’re not careful, you can be drowning in data and won’t be able to see the needle in the haystack.”

Decision fatigue can result in poor choices as individuals make mental shortcuts in their decision analysis.

The right metrics are the ones that show teams how they are performing and where they can reduce unplanned work. The purpose of focusing on lowering unplanned work is to increase the capacity to invest in the platforms—making them more stable, sustainable, and scalable. And to release more time for teams to invest in creating more value outcomes for their customers and improving customer experience.

SLAs are a given—and Service Level Objectives and Service Level Indicators along with error budgets help manage teams' performance within the parameters agreed with partners and customers. And teams with the highest levels of SLAs (five nines) have the fewest KPIs—and are most likely to be meeting their SLAs. These teams also rely on error budgets much more than teams working with lower SLAs.

SLA’s have been well-established since the beginning on information technology, but the popularity today of SLOs and SLIs is associated with the market adoption of Site Reliability Engineering (SRE), a set of practices initially developed by Google. These four KPIs work together in this way in the context of availability where typically a certain amount of downtime is permitted across a defined period and can typically show up as the sum of several problems or incidents:

• SLA: A formal agreement that describes how much downtime the customer will tolerate before there are—usually financial—repercussions
• SLO: A lower number the team choose to create a buffer so they don’t breach the SLA
• SLI: A continually tracked metric that indicates where the SLO might be broken
• Error budget: Suppose a payment service has an SLA of 98%, then the SLO must be higher. Considering an SLO of 99% availability, the error budget would be 1%. That 1% in a 28-day window is 3.65 days of downtime. If, after 15 days, the SLI is 99.5%, then you’re meeting your SLO and within your EB. If the SLI dips below 99%, then you’ve used up all of your EB and are no longer meeting the SLO.

So error budgets are undoubtedly useful for ensuring that services are up and running as people expect and prioritizing problems/incidents around other work, so they tell us something about a team’s performance—but they tell us very little about where improvements can be made.

When there is a problem or an incident, activity falls into broadly one of two types:

1. Discovering the incident and its cause
2. Resolving the issue and repairing and recovering the system

Enter the MTTXs—a slew of metrics relating to the Mean Time to do something that’ll get the service back up and running. You can check out the full report for a more detailed analysis here, but our research has shown that there are two mean-time metrics that really matter:

1. Mean Time to Detect (MTTD)
2. Mean Time to Recovery (MTTR)

We found that very few teams are measuring MTTD today and yet this relates to 66% of their MTTR. And it’s also one that can be quite easily reduced using AIOps that takes all the data streaming from the monitoring tools and reduces the noise using correlations and patterning techniques to quickly pinpoint the root causes of the issue.

This is a significant chunk of time that teams can claim back from unplanned work. That’s time that can be used to pay down technical debt, automate toil, and experiment with chaos engineering—things that directly improve the underlying stability of the system and improve future performance so availability doesn’t exist on such a knife-edge. It’s time that teams can invest in innovative platform improvements or new features that enhance customer experience. Available systems with rich customer experience—with the right business models—lead to high-performing organizations. So, when you’re choosing your availability metrics:

• Only pick a few—and make sure they include error budgets (to keep you on track) and MTTD (to help you claim time back)
• Make sure your teams aren’t drowning in data—and we also found teams have too many monitoring tools and spend too much time monitoring—use AIOps to reduce their burden on their cognitive load limits
• Measure work distribution—not just unplanned work but also what’s invested in paying down technical debt and automating toil and what the consequences of this investment are

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