User-oriented software monitoring is always important, no doubt about it. But with the relentless migration of software to the cloud, and the adoption of microservices and serverless architecture as functions as a service (Faas), monitoring is now critical business. These new ways to build modern software involve many moving parts and developers need to look through the complexity to quickly diagnose performance and functionality issues. Do it before notifying your users asking for the right tools.
Unfortunately, it is not if you can take on your legacy monitoring solution as an alternative. There are special challenges for cloud monitoring because of the fundamental differences compared to using physical servers, such as not always having access to hardware and applications and translations. Your case is running.
Before we go into the kind of tools you can use to monitor your software in the cloud, there is a question we need to answer: exactly, how is cloud monitoring different?
How is cloud monitoring different?
Software can easily be deployed to the cloud, but you need to think strategically about how you will monitor not only services and applications, but also the infrastructure and the platform that stores them. Remember, you will not have physical access to the servers running the software, so it is important to have the right tools to understand what your users are having.
The monitoring tools inherit the configuration request when new servers come and go, but that won’t cut it in the cloud. To ensure your cloud-based application is still accessible, not slow and running the way you expect, your monitoring tools must be able to handle one of the basic benefits of Cloud computing: easy expansion. These tools need to automatically adjust and continuously monitor cloud resources, even when they come and go.
Considering all of these requirements, we can divide effective cloud monitoring into three separate tools: site speed and usability tools, application performance and daily analysis. sign.
Page speed and availability
In a way, cloud applications are the victims of their own success. Because users can access software anytime, anywhere, power outages and availability problems cause customer service nightmares. Ensure that your website is always accessible that can mean the difference between a good product and a great product. For this reason, any cloud monitoring tool you choose should regularly check the availability of your websites.
On the positive side, whether your sites are available in binary answers – a group of users can access them or they cannot. A more subtle problem is extracting the visitor’s user experience, affected by every aspect of your site – from the page loading time to the broken login port. Capturing the issues here involves recording the steps your users take while going through your site and examining page factors to find out which elements are loading slowly or completely. is not.
Fortunately, there are tools that make this process easier. Pingdom is a cloud-based tool to monitor the availability of your web pages and notify you when your site crashes, when the page content changes or when the HTTP error status code is activated. . Using its control panel, you can see at a glance which applications are having problems. It is important to analyze page speed, the control panel also allows you to split page requests into individual steps so that you can identify delay bottlenecks that annoy your users.
Tracking the speed and availability of a site gives you a high level of understanding of how your site works. But to go deeper and see things at a more granular level, you need data directly from your web application and for many products, application performance monitoring is the only option to really understand. Health of the application. Instead of the external view that page speed provides, log performance analysis shows how the application’s inner workings are.
Traditionally, understanding your application’s performance involves tracking things like CPU usage, memory consumption and other hardware resources. These figures are still a valuable source of in-depth information about application behavior and many cloud platforms record resource performance data while your software is running atop. For example, AWS records CPUUtilization, showing the percentage of computing units currently used on an individual and can be an important part of the puzzle when pursuing performance bottlenecks.
But resource performance data can only tell you a lot about your application. If your service or application is running on a FaaS platform – such as Amazon AWS Lambda – you have no way to monitor those aspects, so you can’t know what computing resources are available. use.
In that case, you need to generate performance data from within your code. Integration with application performance tools is the key for your monitoring tool to easily digest the metrics you submit, whether they are custom generated metrics in your application or exported. play from runtime, like .NET or database tools like MongoDB.
An example of a server management and performance management tool that supports all of the features mentioned above is AppOptics. This tool allows you to monitor both your cloud infrastructure and applications and collect metrics to quickly identify performance and congestion issues. To handle a variety of deployed software, AppOptics includes more than 150 integrations and plugins for popular languages, frameworks and platforms.
Although applications, infrastructure and performance monitoring process data – values that describe efficiency or speed – log monitoring provides a richer way to understand the software’s behavior. friend. Typically, log messages are created in the application itself, because it is often the best place to detect abnormal conditions and create useful diagnostic messages. For example, contextual messages can be created in error handlers to assist in troubleshooting.
Because the cloud comes with the benefit of scaling automatically, it is more likely that you will run your code on multiple servers or as a collection of services if you are using microservice. That means you will have many log files to collect before you can analyze everything comprehensively, which you can do through diary aggregation – the process of collecting many log files into a location and merge logs together.
Summarizing your logs makes analysis much easier because you can see the entire picture of your software’s behavior at the same time, instead of viewing each log’s log file and having to merge total.
But once you have the logs aggregated, finding through that sea of data can be a challenge. Cloud monitoring tools also provide search and filtering capabilities to help you find the data you are looking for, even when the amount of data can overwhelm traditional tools.
One such tool is Papertrail – a log file analysis tool that provides a central location for summarizing records. Using a single view, you can diagnose problems no matter where they are in your infrastructure before they affect your users. Papertrail also offers advanced search and filtering features and direct tail features so you can pause, search and scroll through log messages in real time.
Adaptable to the cloud
Cloud-based software is now available everywhere and users will expect the ever-present nature of applications in the cloud. Choosing the right mix of page speed, application performance and log analysis tools is the key. Each must be designed to handle the basic principles of running your software in the cloud: automatically scaling, high availability and microservice architecture.
Finally, it is necessary to constantly monitor your services, applications, and infrastructure to provide a great user experience and give your users what they want – access to the section Your soft wherever you go.