The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.
At BugSplat, we have a unique view of how uncaught crashes can impact individual teams (and entire companies) through our work building tools to find and fix bugs in live applications. We've seen firsthand the difference it can make when teams have a workflow for reporting every defect that makes it into production and when they don't.
Kubernetes is now the de-facto standard for container orchestration. With more and more organizations adopting Kubernetes, it is essential that we get our fundamental ops-infra in place before any migration. In this post, we will learn about leveraging Jenkins and Spinnaker to roll out new versions of your application across different Kubernetes clusters.
This is the third and final post (for now) in the series about developing email templates with MJML and deploying them to AWS. In the previous post, we developed a Gulp script to automatically build HTML from the MJML file and insert it in a template file for AWS. In this post, we will set up an automated build and deployment of the email template using Azure DevOps. A quick recap.
“Observability” seems to be the buzzword du jour in IT these days but what does it actually mean, and how is it any different from plain, old monitoring? In simple terms, observability is the ability to understand how a system is performing and how it is behaving from the data that system generates. It is not just about monitoring metrics or collecting logs, but also understanding the context of those metrics and logs, and how they relate to the overall health of the system.
With Cribl Stream, our customers are experiencing choice and control over their data that would have been a pipe dream (or maybe I should say a pipeline dream) before. The ability to get the right data to the right destination in the right format is extremely powerful. Stream can optimize the data being sent to expensive destinations; you can remove unnecessary or redundant fields, drop unnecessary events, or even pull valuable metrics from verbose logs. Optimizing your data has a few benefits.
We’re happy to announce that the Sentry SvelteKit SDK is now generally available and ready to help you monitor your SvelteKit application. Last year, we entered the Svelte ecosystem by creating an SDK for Svelte, which provides support for Svelte single page apps. We knew that SvelteKit was already quite far along back then and we kept a close eye on its development. We also received a lot of requests from the community to support SvelteKit.
Many organizations have faced the complex challenges that come with mainframe monitoring. MIPS-based cost models make native mainframe software expensive, and deploying individual agents to user desktops and devices is difficult to maintain and scale.
Migrating your on-prem applications to Azure can help you improve scalability, reliability, and security. It can also help reduce costs and free your engineering teams to focus on innovation and performance optimization. But it can be hard to understand Azure costs as they evolve during your migration and to see how they correlate with your resource utilization once you’re up and running in Azure.
Azure OpenAI is a service for deploying AI applications on Azure resources. With its easy-to-use REST APIs, you can leverage the service to access OpenAI’s powerful language models, such as ChatGPT, for your applications while taking advantage of the reliability and security of the Azure platform. Datadog already offers an out-of-the-box integration for OpenAI so you can monitor key performance trends, such as API usage patterns, token consumption, and more.
