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Hot Topics from the Gartner Data Center Conference

Linh Ho

Last month I attended the Gartner Data Center Conference in Las Vegas. This show has grown quite a bit over the last few years. I believe over 2500 attendees this year roamed around the Caesars Palace — some camouflaged with the National Finals Rodeo fans.

This year, the hot topic was not only cloud computing but seems there were a lot of discussions around DevOps and analytics. Other topics of interest included Application Performance Monitoring (APM), End-user Experience (EUE), Business Transaction Management (BTM), Big Data and many more around IT operations.

Take a peek at the few bits and bites I picked up, I particularly found the polling questions interesting to share.

Poll: What is the biggest reason ITOps group isn’t doing more innovation?

41% too busy with day to day operations

27% politics

11% cultural

9% feel they are very innovative

7% not a priority

Not surprising. When IT is too busy with day to day operations like keeping the lights on, and expensive resources are stuck on a conference bridge figuring who is accountable to fix the problem; of course there is no time and resources put into innovation. Only when IT is proactive and preventive to issues that innovation has a spot on the agenda.

Though, 9% feel very innovative – It’d be interesting to hear from this 9% to understand what they are working on! Innovation clearly brings new ideas that drive change and create value that can only enable better business outcomes.

Poll: What is your top priority for availability and performance tool investment for the coming budget year?

26% APM

21% ECA

14% SLA

7% Virtualization

7% Server Monitoring

5% Network Monitoring

2% BSM

2% Cloud

Indeed APM is hot again, though this is referring to ‘new APM’ which is above and beyond the traditional deep-dive tools. One of the analyst cautioned about using last millennium’s tools to solve today’s problems! Deep-dive is only a slice of five dimensions of APM according to Gartner.

APM inquiries according to the analysts seem to have increased by over 50% compared to last year. Within APM, end-user experience and business transaction profiling are touted the two hottest topics.

Event Correlation Analysis (ECA) is second to APM, beyond ECA but somewhat related, we see customers looking to apply analytics for both IT and business operations. Approaches such as multi-dimensional OLAP (online analytical processing), CEP (complex event processing) and log analysis are commonly seen. Log parsing and analysis comes up for those looking to parse log files to assist with trouble-shooting primarily.

Bringing intelligence through the likes of CEP helps IT elevate its awareness of business impact, prioritization and prevent abnormal behaviors in both IT and business operations. Multi-dimensional OLAP helps bring different perspectives easily and quickly for problem isolation, impact assessment, resolution, optimization and more.

For example one can view service levels by business transactions, by users, by applications or flip it around to get resource consumption by applications, users, and transactions—think of a rubik’s cube for IT management.
These all borrow business intelligence concepts into the world of IT management – which is not a bad thing when the ultimate goal is aligning IT and the business.

I am surprised to see only 2% cloud for the next coming year, perhaps the audience just weren’t sure what Gartner meant by ‘cloud’ as it could be different extremes of initiatives. Or simply, the audience still isn’t quite ready.

Lastly, I can’t say I am surprised to see 2% BSM (Business Service Management); this term has been nebulous for quite some time and since the last pure-play BSM vendor was picked up by Novell --- we’re not hearing much from that corner.

DevOps surfaced quite a bit, here’s a couple of interesting polls.

Poll: Is your organization leveraging DevOps?

62% have not heard of DevOps before

11% aware of DevOps but not planning to use it

9% experimenting – not in production

8% using for both critical and non-critical apps

7% considering using DevOps in next 12-14 months

3% using it for non critical apps

This was a surprise – 62% have not heard of DevOps? I suppose to defend it, bridging that gap between dev and ops; we’re just not there yet. The reality I’d say, it is more OpsDev – how to help IT operation guys bring factual data to the Dev guys to fix issues that are causing pain in production. IT operation needs to be proactive at crossing over that wall. This can only improve productivity, communication and eliminate the traditional siloed approach. There is still some work to do here to break the great wall.

Poll: What process is most in need of being addressed via Devops?

36% Release management

35% Change management

12% performance management

12% capacity management

No surprises here. Change and release management are key processes to address via DevOps – how often do changes cause performance problems? Do you understand the change impact on your end-user experience, critical business transactions, application performance? Effective change and release processes can only be achieved with solid collaboration between dev and ops to minimize application rollbacks, improve quality releases and reduce risks of impacting performance.

Kudos to the Gartner analysts for the informative sessions, one-on-ones, dinners and drinks – they’ve gone the extra mile for attendees and vendors! Usually Gartner will have a write up on the Data Center poll results in the following spring; buckle up! it will be interesting to see what they make out of all this!

Linh C. Ho is VP of Corporate Marketing at OpTier.

Related Links:

Linh Ho of OpTier Joins the Vendor Forum

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

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Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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Hot Topics from the Gartner Data Center Conference

Linh Ho

Last month I attended the Gartner Data Center Conference in Las Vegas. This show has grown quite a bit over the last few years. I believe over 2500 attendees this year roamed around the Caesars Palace — some camouflaged with the National Finals Rodeo fans.

This year, the hot topic was not only cloud computing but seems there were a lot of discussions around DevOps and analytics. Other topics of interest included Application Performance Monitoring (APM), End-user Experience (EUE), Business Transaction Management (BTM), Big Data and many more around IT operations.

Take a peek at the few bits and bites I picked up, I particularly found the polling questions interesting to share.

Poll: What is the biggest reason ITOps group isn’t doing more innovation?

41% too busy with day to day operations

27% politics

11% cultural

9% feel they are very innovative

7% not a priority

Not surprising. When IT is too busy with day to day operations like keeping the lights on, and expensive resources are stuck on a conference bridge figuring who is accountable to fix the problem; of course there is no time and resources put into innovation. Only when IT is proactive and preventive to issues that innovation has a spot on the agenda.

Though, 9% feel very innovative – It’d be interesting to hear from this 9% to understand what they are working on! Innovation clearly brings new ideas that drive change and create value that can only enable better business outcomes.

Poll: What is your top priority for availability and performance tool investment for the coming budget year?

26% APM

21% ECA

14% SLA

7% Virtualization

7% Server Monitoring

5% Network Monitoring

2% BSM

2% Cloud

Indeed APM is hot again, though this is referring to ‘new APM’ which is above and beyond the traditional deep-dive tools. One of the analyst cautioned about using last millennium’s tools to solve today’s problems! Deep-dive is only a slice of five dimensions of APM according to Gartner.

APM inquiries according to the analysts seem to have increased by over 50% compared to last year. Within APM, end-user experience and business transaction profiling are touted the two hottest topics.

Event Correlation Analysis (ECA) is second to APM, beyond ECA but somewhat related, we see customers looking to apply analytics for both IT and business operations. Approaches such as multi-dimensional OLAP (online analytical processing), CEP (complex event processing) and log analysis are commonly seen. Log parsing and analysis comes up for those looking to parse log files to assist with trouble-shooting primarily.

Bringing intelligence through the likes of CEP helps IT elevate its awareness of business impact, prioritization and prevent abnormal behaviors in both IT and business operations. Multi-dimensional OLAP helps bring different perspectives easily and quickly for problem isolation, impact assessment, resolution, optimization and more.

For example one can view service levels by business transactions, by users, by applications or flip it around to get resource consumption by applications, users, and transactions—think of a rubik’s cube for IT management.
These all borrow business intelligence concepts into the world of IT management – which is not a bad thing when the ultimate goal is aligning IT and the business.

I am surprised to see only 2% cloud for the next coming year, perhaps the audience just weren’t sure what Gartner meant by ‘cloud’ as it could be different extremes of initiatives. Or simply, the audience still isn’t quite ready.

Lastly, I can’t say I am surprised to see 2% BSM (Business Service Management); this term has been nebulous for quite some time and since the last pure-play BSM vendor was picked up by Novell --- we’re not hearing much from that corner.

DevOps surfaced quite a bit, here’s a couple of interesting polls.

Poll: Is your organization leveraging DevOps?

62% have not heard of DevOps before

11% aware of DevOps but not planning to use it

9% experimenting – not in production

8% using for both critical and non-critical apps

7% considering using DevOps in next 12-14 months

3% using it for non critical apps

This was a surprise – 62% have not heard of DevOps? I suppose to defend it, bridging that gap between dev and ops; we’re just not there yet. The reality I’d say, it is more OpsDev – how to help IT operation guys bring factual data to the Dev guys to fix issues that are causing pain in production. IT operation needs to be proactive at crossing over that wall. This can only improve productivity, communication and eliminate the traditional siloed approach. There is still some work to do here to break the great wall.

Poll: What process is most in need of being addressed via Devops?

36% Release management

35% Change management

12% performance management

12% capacity management

No surprises here. Change and release management are key processes to address via DevOps – how often do changes cause performance problems? Do you understand the change impact on your end-user experience, critical business transactions, application performance? Effective change and release processes can only be achieved with solid collaboration between dev and ops to minimize application rollbacks, improve quality releases and reduce risks of impacting performance.

Kudos to the Gartner analysts for the informative sessions, one-on-ones, dinners and drinks – they’ve gone the extra mile for attendees and vendors! Usually Gartner will have a write up on the Data Center poll results in the following spring; buckle up! it will be interesting to see what they make out of all this!

Linh C. Ho is VP of Corporate Marketing at OpTier.

Related Links:

Linh Ho of OpTier Joins the Vendor Forum

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...