Every business is a software business. And by software, we don’t mean code—we mean running software serving customers in production. Those customers may be internal to the company, they may pay you money, or they may represent attention that increases ad revenue—either way, making them happy is your business. And your fast, reliable software makes them happy. Application performance monitoring, also known as APM, represents the difference between code and running software.

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Choosing the right APM tool is critical. How do you know which is the right one for you? Here are the top 13 open source application performance monitoring(APM) tools which can solve your monitoring needs. Open source APM tools have added benefits over their SaaS counterparts. Open source tools are more transparent as you can verify its source code, and you can use it without going through the pains of taking approvals usually required for using a third-party vendor tool.

Both DataDog and New Relic are popular monitoring tools that provide a wide range of products covering different aspects of application and infrastructure monitoring. In this post, I have compared Datadog and New Relic on important features like APM, log management, infrastructure monitoring, OpenTelemetry support, etc. info 💡 I instrumented a sample Spring Boot Application and sent data to Datadog and New Relic to evaluate my experience.

One area where communication breakdowns commonly occur is between helpdesk / IT teams / SREs and database administrators (DBAs), especially when troubleshooting application problems associated with databases. Smooth communication between different teams is key to resolving application performance issues efficiently and speedily. However, it is usually inappropriate for helpdesk staff to have access to the database monitoring privileges and tools used by DB administrators.

One of the major trends in software development in the last decade has been “shifting left” responsibilities that have traditionally been under operation’s domain to earlier in the software development life cycle (SDLC). It first came in the form of DevOps where a lot of the software engineering best practices were introduced to the deploy, operate, monitor phases. Such examples include continuous integration and continuous deployment (CI/CD) and Infrastructure as Code (IaC).

In microservices architecture, observability tools enable you to create central dashboards to gauge the health of your distributed systems. New age observability tools have shifted to providing quick workflows to debug application issues. In this post we will explore top 11 observability tools that you can consider to use for your software systems. In today's digital economy, distributed architectures have become the norm.

For any software company, a log monitoring tool is a must for collecting, storing, and providing a centralized view of all logs from different applications and hosts for faster anomaly detection, incident resolution, and troubleshooting. They can also help detect security threats and provide audit trails. They are effective in capacity planning, decision-making, and ensuring optimized performance.

In this article, we will use OpenTelemetry to instrument a sample Flask app for traces. Flask is one of the most popular web application frameworks of Python. It consists of Werkzeug WSGI toolkit and Jinja2 template engine. Instrumentation is the biggest challenge engineering teams face when starting out with monitoring their application performance. OpenTelemetry is the leading open-source standard that is solving the problem of instrumentation.

Falcon is a minimalist Python web API framework for building robust applications and microservices. It also compliments many other Python frameworks by providing extra reliability, flexibility, and performance. Using OpenTelemetry, you can monitor your Falcon applications for performance by collecting telemetry signals like traces. Instrumentation is the biggest challenge engineering teams face when starting out with monitoring their application performance.