Operations | Monitoring | ITSM | DevOps | Cloud

Debugging in production is always a necessary evil. No matter how well your code is written and reviewed, bugs are bound to appear, and their consequences are there for your users to see. While debugging any app has challenges, debugging legacy systems is a different ballgame. From unfamiliarity with the codebase to a lack of knowledge about the tech, your developers can find themselves aimlessly searching for solutions where solutions don’t exist.

This post was written by Siddhant Varma. Scroll down to read the author’s bio. Software development isn’t just about building and deploying software. There’s a wide range of operations and activities you need to tackle even after you’ve successfully deployed it. The two most common are observability and monitoring. While they’re similar in a lot of ways, it’s important to understand that they are not exactly the same, and each has its own purpose.

The customer success department at Honeycomb features a number of different roles dedicated to helping our customers succeed in every step of their observability journey. The work we do ranges from support engineers who provide timely assistance to customers, to customer architects who dive deep into the technical stuff, to product training who educate folks on features old and new.

As companies embrace containers, microservices, and complex architectural components, systems have grown more and more distributed and unpredictable, increasing the unknown unknowns. How can organizations remain efficient and effective in this type of intricate environment? With observability-driven development.

You may be thinking, “What on earth is an observability pipeline? And how does the Super Mario World fit in?” Hold on to your hat, my friend, because you’re about to find out!

Logz.io is excited to announce Service Overview, a fast and easy way to unify telemetry data and insights across your infrastructure and applications into a single interface. Our Beta users have reported simplified observability, faster time-to-insights, and observability consolidation.

Core Web Vitals (CWV) are Google's preferred metrics for measuring the quality of the user experience for browser web apps. Currently, Core Web Vitals measure loading performance, interactivity, and visual stability. These are the main indicators of what a user’s experience will be while using a web page.

As more companies rely on data insights to drive critical business decisions, data must be accurate, reliable, and of high quality. Gaining insights from data is essential, but so is the data’s integrity so that you can be sure that data isn’t missing, incorrectly added, or misused. This is where data observability comes in.

Elasticsearch® recently released time series data streams for metrics. This not only provides better metrics support in Elastic Observability, but it also helps reduce storage costs. We discussed this in a previous blog. In this blog, we dive into how to enable and use time series data streams by reviewing what a time series metrics document is and the mapping used for enabling time series. In particular, we will showcase this by using Elastic Observability’s Nginx integration.

I’m thrilled to announce that ServiceNow has been recognized as a Visionary in the 2023 Gartner® Magic Quadrant™ for Application Performance Monitoring (APM) and Observability. We believe this validates our strong vision and unique ability to help customers bring unified telemetry into their existing ServiceNow® Event Management and Service Operations solutions, reduce mean time to resolution (MTTR), and accelerate innovation.