APMdigest asked experts from across the IT industry for their opinions on what IT departments should be monitoring to ensure digital performance. Part 3 covers the development side.
Code-level issues are a common cause of application slowness and have fueled the need for distributed transaction tracing, which can help isolate the exact line of code with errors. This type of monitoring can also be effectively applied in both pre- and post-production environments, enabling us to prevent performance issues before they impact end users as well as help isolate them when they do occur.
When this type of application monitoring is done in context of infrastructure dependencies, it helps distinguish if there are other issues affecting application code processing, such as a bottleneck in the application server, long-running database queries, slow third-party calls, or other issues that may be associated with the application ecosystem. Applications are the heart of IT workloads, and application performance monitoring is critical to effectively ensure the performance of digital services.
Director, Product Marketing, eG Innovations
Digital performance is complex and can be measured in many ways, but one critical consideration is how well does the application do what it is supposed to do? Is it meeting a functional performance metric for customer expectations? To ensure this, organizations need to look at the "fingerprint" of each error in code to discern its importance as well as look at the number of critical errors per release. This dictates the overall functional reliability of the code. It also requires you to be code-aware, monitoring from inside the application at runtime, not surrounding it or listening to the exhaust.
CTO and Co-Founder, OverOps
Most people already know to monitor the obvious things, like total latency to response. But my favorite monitor comes from Anatoly Mikhaylov's talk at DASH this year. He spoke about finding massive infrastructure costs hidden in error codes. Adding APM monitoring to the errors in your endpoints can show costs you wouldn't otherwise see.
APM Developer Advocate, Datadog
When automating you application release, it's important to remember what you need to monitor. This will allow you to go as fast as possible, but also make sure you are doing it efficiently. Monitor your lead time, success vs failure rate and mean time to recovery will ensure you focus on value rather than on effort.
Co-Founder and CTO, DBmaestro
One key area to make sure you monitor: API calls. There aren't many applications I come across these days that do not include some 3rd-party API, be it for authentication, analytics, storage, or customer relationship management. Such API calls can so greatly impact digital performance that not monitoring them to identify things such as performance slowdowns and dependencies is a prescription for pain.
Senior Consultant and Founder of RootPerformance
Cloud, containers and microservices are creating increasingly ephemeral, modular and volatile IT environments. In these dynamic environments, traditional monitoring approaches fail. A modern monitoring approach is required to provide complete visibility into the applications, containers, host and underlying supporting infrastructure. This includes having visibility into the performance of and data returning from APIs which have become a key component to any microservices architecture. A modern monitoring approach includes the analytics and intelligence to understand how changes might impact the overall user experience and flexible monitoring techniques that don't overload the containerized application environment.
Director, Product Marketing, CA Technologies
Finding a tool that fits seamlessly into your workflows, setting performance benchmarks, validating payloads, and getting visibility into the performance of API transactions is critical to help teams get rapidly identify and fix issues in production so that the delivered digital experience matches the vision for end-users.
VP of Product, AlertSite UXM, SmartBear
APIs are the fundamental building block of modern software. While engineering teams have built extensive monitoring systems to check the health of code execution paths, they have little visibility into what's going on with APIs. An API failure can bring down systems and without proper monitoring in place, it can be very hard to debug what's going on.
The nature of development means systems are going to spring into existence and then back out again often, and that this rapid change is OK, which means your monitoring needs to be OK with it. The ability to monitor containers, ephemeral services, and the like, is a must.
Head Geek, SolarWinds
Let's go to the extreme and say you could only monitor one thing — that one thing would be microservice response time. In this brave new world, it's actually quite difficult to understand how well your revenue-critical application is performing. While traditional metrics still matter (CPU, memory, disk, etc), your response time on a microservice-by-microservice basis is the thing that matters the most. This single metric will tell you more about the customer experience than anything else. It will indicate downtime or more subtle performance problems in your application. While this metric alone will not tell you "why" something is going on, it will tell you "what" is happening and allow you to quickly isolate a problem to a handful of services or some set of underlying infrastructure.
As you evolve and enhance your company's hybrid data center infrastructure to keep pace with your industry, understanding your unique workload I/O DNA is paramount to success. Real-time monitoring of the I/O path – from the virtual server to the storage array – is essential to ensuring digital performance. For mission-critical applications, understanding the performance of each and every transaction is the cornerstone of customer satisfaction and revenue assurance.
CMO, Virtual Instruments
Read Len Rosenthal's new blog on APMdigest: Infrastructure Monitoring for Digital Performance Assurance.
Read What You Should Be Monitoring to Ensure Digital Performance - Part 4, covering the infrastructure, including the cloud and the network.
As the data generated by organizations grows, APM tools are now required to do a lot more than basic monitoring of metrics. Modern data is often raw and unstructured and requires more advanced methods of analysis. The tools must help dig deep into this data for both forensic analysis and predictive analysis. To extract more accurate and cheaper insights, modern APM tools use Big Data techniques to store, access, and analyze the multi-dimensional data ...
Modern enterprises are generating data at an unprecedented rate but aren't taking advantage of all the data available to them in order to drive real-time, actionable insights. According to a recent study commissioned by Actian, more than half of enterprises today are unable to efficiently manage nor effectively use data to drive decision-making ...
According to a study by Forrester Research, an enhanced UX design can increase the conversion rate by 400%. If UX has become the ultimate arbiter in determining the success or failure of a product or service, let us first understand what UX is all about ...
The requirements of an APM tool are now much more complex than they've ever been. Not only do they need to trace a user transaction across numerous microservices on the same system, but they also need to happen pretty fast ...
Performance monitoring is an old problem. As technology has advanced, we've had to evolve how we monitor applications. Initially, performance monitoring largely involved sending ICMP messages to start troubleshooting a down or slow application. Applications have gotten much more complex, so this is no longer enough. Now we need to know not just whether an application is broken, but why it broke. So APM has had to evolve over the years for us to get there. But how did this evolution take place, and what happens next? Let's find out ...
There are some IT organizations that are using DevOps methodology but are wary of getting bogged down in ITSM procedures. But without at least some ITSM controls in place, organizations lose their focus on systematic customer engagement, making it harder for them to scale ...
If you have deployed a Java application in production, you've probably encountered a situation where the application suddenly starts to take up a large amount of CPU. When this happens, application response becomes sluggish and users begin to complain about slow response. Often the solution to this problem is to restart the application and, lo and behold, the problem goes away — only to reappear a few days later. A key question then is: how to troubleshoot high CPU usage of a Java application? ...
Operations are no longer tethered tightly to a main office, as the headquarters-centric model has been retired in favor of a more decentralized enterprise structure. Rather than focus the business around a single location, enterprises are now comprised of a web of remote offices and individuals, where network connectivity has broken down the geographic barriers that in the past limited the availability of talent and resources. Key to the success of the decentralized enterprise model is a new generation of collaboration and communication tools ...
To better understand the AI maturity of businesses, Dotscience conducted a survey of 500 industry professionals. Research findings indicate that although enterprises are dedicating significant time and resources towards their AI deployments, many data science and ML teams don't have the adequate tools needed to properly collaborate on, build and deploy AI models efficiently ...