Application performance management (APM) and distributed tracing are practices that many teams have been using for years to help detect and mitigate performance issues within applications – while the first one was born in the era of big single-host monoliths, the latter is especially useful for distributed applications that use a microservices architecture, in which tracing is critical for pinpointing the source of performance issues.

The software industry has seen many evolutions. There is a new disruption in the market every five years or so. Software testing cannot remain isolated from all the latest trends and technologies. Testing strategies need to keep up with agile development, faster deployments and increasing customer demand for reliability and user-friendly interfacing. They need to be able to grow just as quickly and just as reliably as the business logic.

Observability has become one of the most important areas of your application and infrastructure landscape, and the market has an abundance of tools available that seem to do what you need. In reality, however, most products - especially leading open source tools - were created to solve a single problem extremely well, and have added additional supporting functionality to become a more robust solution; but the non-core functionality is rarely best of breed. Examples of these are Prometheus and Grafana.

OpenTelemetry has gained significant adoption in the past year. This blog is about the common Otel demo application, but you can refer to this primer about OTel in general. Although it has gained recognition in the industry, there are still many people who haven’t started using OpenTelemetry. If you are interested in exploring its capabilities but you’re unsure where to start, keep reading.

If you're reading this blog, you might ask yourself what container orchestration engines are, what problems they solve, and how the different engines distinguish themselves. Read on for a high-level overview of Kubernetes, Docker Swarm, and Apache Mesos, as well as a few of their notable similarities and differences.

Kubernetes is first and foremost an orchestration engine that has well-defined interfaces that allow for a wide variety of plugins and integrations to make it the industry-leading platform in the battle to run the world's workloads. From machine learning to running the applications a restaurant needs, you can see that just about everything now uses Kubernetes infrastructure. All these workloads, and the Kubernetes operator itself, produce output that is most often in the form of logs.

If you use Amazon Web Services, you have two load balancing options for your applications: Classic Elastic Load Balancer (CLB) and Application Load Balancer (ALB). And while choice is always good, the CLB vs. ALB debate can be intimidating. Which load balancer is right for your application? Is ALB better than CLB, or vice versa? This blog explores these questions.

Serverless computing is a modern cloud-based application architecture, where the application’s infrastructure and support services layer is completely abstracted from the software layer. Any computer program needs hardware to run on, so serverless applications are not “serverless” - they do run on servers - it’s just that the servers are not exposed as physical or virtual machines to the developer running the code.

A quarter has passed since we launched our Reliability Management capabilities that help developers focus on defining, monitoring and managing Service Level Objectives (SLOs) to drive great digital experiences. Reducing alert fatigue and balancing innovation with reliability are common outcomes that customers expect from Reliability Management. If you are new to SLOs, these insights from our customers capture common practices among peer developers.

In the past decade, we've seen explosive growth in the adoption of the cloud-based infrastructure model. IT organizations are increasingly choosing to reduce their up-front investments in IT infrastructure by deploying their applications into cloud environments. These environments offer on-demand availability of data storage and computing power that organizations need to handle high volumes of data and growing demand for application access and services.