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When Is It Too Early to Think About Monitoring?

David Hickman

When is it too early to think about monitoring?

In a word, “NEVER.”

I’ve heard people say that they are super busy with production deployments and fast-moving projects. They haven’t had much time to think about a performance monitoring strategy for their new applications.

But waiting until your applications are already in production is a mistake. However, it’s one that you can avoid.

Develop, test and deploy your applications with monitoring already in place and save yourself a lot of headaches. Let me count the ways:

1. Using the same monitoring tools for both pre- and post-production

Obviously, you will be doing performance testing during development and QA. But if you use different tools before and after, you might get inconsistent results. And you’ll have to retrain the people that did the original testing on the new performance monitoring tools. After they’ve moved on to other projects.

Having a monitoring strategy in place ensures that people are using the same tools throughout the lifecycle. .So that you can expect consistent measurements and more efficient troubleshooting and response if necessary.

2. Monitoring – independent from administration – eases access and alleviates concerns

Many developers need access to performance metrics during testing and often that means providing administrative access to middleware platforms to get those metrics.

When you’ve implemented an independent monitoring solution then developers can self-service their performance monitoring needs without worrying about providing administrative access.

3. Monitoring best practices implemented at design-time means less effort at run-time

Correlation of metrics between related technologies is what allows you to see things in context. For instance, show me all the servers that support a particular application. That's significantly easier than wading through 1000’s of servers trying to figure out which ones support my “banking” application. This is especially helpful when time is of the essence. But how does your monitoring system know which instances are related?

Well, you could map it manually, often using naming conventions for your services and engines. The better you stick to well-defined naming conventions, the easier it is. This is another reason why including monitoring requirements in your application building process will pay dividends down the road. Because “automatically” is so much easier than “manually”.

4. Capacity Planning is easier if you’ve been collecting performance data all along

If your business is successful, your apps will get busier and you’ll need to ask yourself if you have enough capacity for future growth? Of course, it’s hard to answer that question if you have no baseline data.

However, capturing performance data from the start enables you to see the resource usage trends over time. Correlate that to expected traffic growth for your application and you'll be on stable ground as you analyze your resource requirements for the next 6-12 months.

5. You don’t have to worry about running out of steam

For a lot of companies, once an application is written, people celebrate and move on. Things that you promise you’ll get to later – never seem to be a priority anymore. Unless, of course, you are hit with a severity one outage and then all heck breaks loose. Then people start panicking because there is no visibility into what is breaking down and where.

Building monitoring requirements into the application development cycle ensure that these things are not forgotten in the hustle and bustle of the next project. In fact, some of our customers will not sign off on a project unless monitoring is ready to go BEFORE moving into production. They make it a priority from the start so that they don’t have to struggle for resources AFTER everybody thinks they are done and move on to something else.

So, the next time somebody asks you about your monitoring strategy for your new apps, instead of saying “I’m too busy to think about it right now,” you should say, “I’m way ahead of you”.

David Hickman is in Product Marketing at SL Corporation.

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When Is It Too Early to Think About Monitoring?

David Hickman

When is it too early to think about monitoring?

In a word, “NEVER.”

I’ve heard people say that they are super busy with production deployments and fast-moving projects. They haven’t had much time to think about a performance monitoring strategy for their new applications.

But waiting until your applications are already in production is a mistake. However, it’s one that you can avoid.

Develop, test and deploy your applications with monitoring already in place and save yourself a lot of headaches. Let me count the ways:

1. Using the same monitoring tools for both pre- and post-production

Obviously, you will be doing performance testing during development and QA. But if you use different tools before and after, you might get inconsistent results. And you’ll have to retrain the people that did the original testing on the new performance monitoring tools. After they’ve moved on to other projects.

Having a monitoring strategy in place ensures that people are using the same tools throughout the lifecycle. .So that you can expect consistent measurements and more efficient troubleshooting and response if necessary.

2. Monitoring – independent from administration – eases access and alleviates concerns

Many developers need access to performance metrics during testing and often that means providing administrative access to middleware platforms to get those metrics.

When you’ve implemented an independent monitoring solution then developers can self-service their performance monitoring needs without worrying about providing administrative access.

3. Monitoring best practices implemented at design-time means less effort at run-time

Correlation of metrics between related technologies is what allows you to see things in context. For instance, show me all the servers that support a particular application. That's significantly easier than wading through 1000’s of servers trying to figure out which ones support my “banking” application. This is especially helpful when time is of the essence. But how does your monitoring system know which instances are related?

Well, you could map it manually, often using naming conventions for your services and engines. The better you stick to well-defined naming conventions, the easier it is. This is another reason why including monitoring requirements in your application building process will pay dividends down the road. Because “automatically” is so much easier than “manually”.

4. Capacity Planning is easier if you’ve been collecting performance data all along

If your business is successful, your apps will get busier and you’ll need to ask yourself if you have enough capacity for future growth? Of course, it’s hard to answer that question if you have no baseline data.

However, capturing performance data from the start enables you to see the resource usage trends over time. Correlate that to expected traffic growth for your application and you'll be on stable ground as you analyze your resource requirements for the next 6-12 months.

5. You don’t have to worry about running out of steam

For a lot of companies, once an application is written, people celebrate and move on. Things that you promise you’ll get to later – never seem to be a priority anymore. Unless, of course, you are hit with a severity one outage and then all heck breaks loose. Then people start panicking because there is no visibility into what is breaking down and where.

Building monitoring requirements into the application development cycle ensure that these things are not forgotten in the hustle and bustle of the next project. In fact, some of our customers will not sign off on a project unless monitoring is ready to go BEFORE moving into production. They make it a priority from the start so that they don’t have to struggle for resources AFTER everybody thinks they are done and move on to something else.

So, the next time somebody asks you about your monitoring strategy for your new apps, instead of saying “I’m too busy to think about it right now,” you should say, “I’m way ahead of you”.

David Hickman is in Product Marketing at SL Corporation.

Hot Topics

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 ...