Operations | Monitoring | ITSM | DevOps | Cloud

Synthetic monitoring is one holistic technique within the wide world of IT monitoring and application performance monitoring (APM) and it’s focused on web performance. Synthetic monitoring emulates the transaction paths between a client and application server and monitors what happens. The goal of synthetic monitoring is to understand how a real user might experience an app or website. In this article, let’s go deep with this topic.

How do you come to grips with all of the code engineers are committing, pushing, merging, and deploying within your organization? Have you started even looking at that data? If not, you’re missing out on a crucial source of productivity, security, and Software Development Life Cycle (SDLC) data. But how can you get a handle on all of that code-related activity?

Managing logs is a significant part of an SRE's daily grind. Scattered within heaps of log data are invaluable insights - those small bits of information that can unveil underlying issues and patterns critical for system monitoring and troubleshooting. However, in an era where the volume of logs is astronomical, how do you discern the relevant from the irrelevant? Sumo Logic's array of log analytics features comes to the rescue, wielding the might of artificial intelligence.

OpenTelemetry is more than just becoming the open ingestion standard for observability. As one of the major Cloud Native Computing Foundation (CNCF) projects, with as many commits as Kubernetes, it is gaining support from major ISVs and cloud providers delivering support for the framework. Many global companies from finance, insurance, tech, and other industries are starting to standardize on OpenTelemetry.

Node.js logging is an important part of supporting the complete application life cycle. From creation to debugging to planning new features, logs support us all the way. By analyzing the data in the logs, we can glean insights, resolve bugs much quicker, and detect problems early and as they happen. In this post, we will talk about the who, what, when, where, how, and why of Node.js logging. Later in this post, the “how” section will give insights into using code.

Observability dashboards are powerful tools that enable teams to visualize and monitor the performance, health, and behavior of their applications and infrastructure. However, building observability dashboards is not a straightforward task, and many organizations make common mistakes hindering their ability to gain meaningful insights and respond to issues effectively.

The rapid software development process that exists today requires an expanding and complex infrastructure and application components, and the job of operations and development teams is ever growing and multifaceted. Observability, which helps manage and analyze telemetry data, is the key to ensuring the performance and reliability of your applications and infrastructure.

The advent of the data mesh has changed the way organizations manage and utilize data. It’s not expected to go away anytime soon. Data mesh, in short, is a popular approach to data management in the enterprise. Its primary goal is to empower teams, especially cross-functional ones. In this article, we'll delve into what data mesh is and explore its key principles. We'll also discuss some benefits of implementing this modern data mesh approach in your organization.

In recent years, microservices have emerged as a popular architectural pattern. Although these self-contained services offer greater flexibility, scalability, and maintainability compared to monolithic applications, they can be difficult to manage without dedicated tools. Kubernetes, a scalable platform for orchestrating containerized applications, can help navigate your microservices.