Performance monitoring is about understanding what's happening right now. It usually includes dealing with immediate performance problems or collecting data that will be used by the other performance tools (such as capacity planning) to plan for future peak loads.
In performance monitoring you need to know three things:
- The incoming workload
- The resulting resource consumption
- What is normal under this load
Without these three things you can only solve the most obvious performance problems and have to rely on tools outside the scientific realm (such as a Ouija Board, or a Magic 8 Ball) to predict the future.
You need to know the incoming workload (what the users are asking your system to do) because all computers run just fine under no load. Performance problems crop up as the load goes up. These performance problems come in two basic flavors: Expected and Unexpected.
Expected problems are when the users are simply asking the application for more things per second than it can do. You see this during an expected peak in demand like the biggest shopping day of the year. Expected problems are no fun, but they can be foreseen and, depending on the situation, your response might be to endure them, because money is tight or because the fix might introduce too much risk.
Unexpected problems are when the incoming workload should be well within the capabilities of the application, but something is wrong and either the end-user performance is bad or some performance meter makes no sense. Unexpected problems cause much unpleasantness and demand rapid diagnosis and repair.
Know What is Normal
The key to all performance work is to know what is normal. Let me illustrate that with a trip to the grocery store.
One day I was buying three potatoes and an onion for a soup I was making. The new kid behind the cash register looked at me and said: “That will be $22.50.” What surprised me was the total lack of internal error checking at this outrageous price (in 2012) for three potatoes and an onion. This could be a simple case of them not caring about doing a good job, but my more charitable assessment is that he had no idea what “normal” was, so everything the register told him had to be taken at face value. Don't be like that kid.
On any given day you, as the performance person, should be able to have a fairly good idea of how much work the users are asking the system to do and what the major performance meters are showing. If you have a good sense of what is normal for your situation, then any abnormality will jump right out at you in the same way you notice subtle changes in a loved one that a stranger would miss. This can save your bacon because if you spot the unexpected utilization before the peak occurs, then you have time to find and fix the problem before the system comes under a peak load.
There are some challenges in getting this data. For example:
- There is no workload data.
- The only workload data available (ex: per day transaction volume) is at too low a resolution to be any good for rapid performance changes.
- The workload is made of many different transaction types (buy, sell, etc.) It's not clear what to meter.
With rare exception I've found the lack of easily available workload information to be the single best predictor of how bad the overall situation is performance wise. Over the years as I visited company after company this led me to develop Bob's First Rule of Performance Work: “The less a company knows about the work their system did in the last five minutes, the more deeply screwed up they are.”
What meters should you collect? Meters fall into big categories. There are utilization meters that tell you how busy a resource is, there are count meters that count interesting events (some good, some bad), and there are duration meters that tell you how long something took. As the commemorative plate infomercial says: “Collect them all!” Please don't wait for perfection. Start somewhere, collect something and, as you explore and discover, add newly discovered meters to your collection.
When should you run the meters? Your meters should be running all the time (like bank security cameras) so that when weird things happen you have a multitude of clues to look at. You will want to search this data by time (What happened at 10:30?), so be sure to include timestamps.
The data you collect can also be used to predict the future with tools like: Capacity Planning, Load Testing, and Modeling.
ABOUT Bob Wescott
Bob Wescott is the author of The Every Computer Performance Book. Since 1987, Wescott has worked in the field of computer performance, doing professional services work and teaching how to do capacity planning, load testing, simulation modeling and web performance for Gomez/Compuware, HyPerformix/CA and Stratus Computer/Technologies. Now, Wescott is mostly retired, and his job is to give back what he has been given. His latest project is The Every Computer Performance Blog based on the book.
More than half (61%) of respondents reported that their teams are practicing observability, an 8% increase from 2020, signaling that overall adoption is on the rise, according to a 2021 survey from Honeycomb. However, the majority of respondents indicated their teams are at the earliest stages of observability maturity ...
Respondents to an OpsRamp survey are moving forward with digital transformation, but many are re-evaluating the number and type of tools they're using. There are three main takeaways from the survey ...
More and more mainframe decision makers are becoming aware that the traditional way of handling mainframe operations will soon fall by the wayside. The ever-growing demand for newer, faster digital services has placed increased pressure on data centers to keep up as new applications come online, the volume of data handled continually increases, and workloads become increasingly unpredictable. In a recent Forrester Consulting AIOps survey, commissioned by BMC, the majority of respondents cited that they spend too much time reacting to incidents and not enough time finding ways to prevent them ...
In the age of digital transformation, enterprises are migrating to open source software (OSS) in droves to streamline operations and improve customer and employee experiences. However, to unlock the deluge of OSS benefits, it's not enough for organizations to simply implement the software. They must take the necessary steps to build an intentional OSS strategy rooted in ongoing third-party support and training ...
In Part 1 of this series, we explored the top pain points associated with managing Internet-based WANs today. This second installment will focus on today's most prevalent SD-WAN deployment challenges specifically and what you can do to better manage modern WANs overall ...
Enterprise wide-area networks (WANs) have undergone an incredible transformation over the past several years. More often than not, they're hybrid, offering multiple connection paths between WANs. This provides many benefits but also makes them more challenging to manage than ever before. In Part 1 of this series, we'll explore the top pain points associated with Internet-based WANs ...
As we have seen during this digital transformation boom during the pandemic, technologists are managing more applications and data than ever before, which has led three quarters of technologists to be concerned with increased IT complexity. Even more significant, 89% admitted to feeling under immense pressure to keep up with the churn, according to the recent AppDynamics Agents of Transformation report. It's clear that the pandemic has pushed many technologists to their breaking point. To help tackle IT burnout, tech professionals need a "canary" to help them streamline and catch the anomalies before they cause any major performance issues ...
An hour-long outage this Tuesday ground the Internet to a halt after popular Content Delivery Network (CDN) provider, Fastly, experienced a glitch that downed Reddit, Spotify, HBO Max, Shopify, Stripe and the BBC, to name just a few of properties affected ...