Observability vs. Telemetry vs. Monitoring
Observability vs Telemetry vs Monitoring - What they are, differences and what lies in future.
The latest News and Information on DevOps, CI/CD, Automation and related technologies.
Observability vs Telemetry vs Monitoring - What they are, differences and what lies in future.
Explore the intricacies of scaling software delivery, from the nuances of continuous delivery to overcoming common challenges. Dive deep into how Cloudsmith can be the game-changer in your DevOps journey, ensuring agility, security, and efficiency in every release. Every business, from startups to established enterprises, feels the urgency to scale their software delivery. Why?
In case you missed it, HAProxy Technologies recently put out a press release about our stunning leadership position in G2’s Summer 2023 Grid® Reports for load balancing. We’re incredibly proud of these results, which are a direct result of the hard work and dedication of HAProxy’s community developers and our enterprise product and support teams. Looking at the Momentum Grid® Report for Load Balancing, the gap between HAProxy and the rest is impossible to ignore.
When we launched the Checkly CLI and Test Sessions last May, I wrote about the three pillars of monitoring as code. Code — write your monitoring checks as code and store them in version control. Test — test your checks against our global infrastructure and record test sessions. Deploy — deploy your checks from your local machine or CI to run them as monitors.
In Part 1 of this series, we introduced you to the key metrics you should be monitoring to ensure that you get optimal performance from CoreDNS running in your Kubernetes clusters. In Part 2, we showed you some tools you can use to monitor CoreDNS. In this post, we’ll show you how you can use Datadog to monitor metrics, logs, and traces from CoreDNS alongside telemetry from the rest of your cluster, including the infrastructure it runs on.
Recently in our Better Incidents Slack channel, there’s been some chatter around how people structure dedicated incident commanders at their company: distributed or centralized. The way I see it, there are two types of commanders: the temporary, distributed role — a hat that an on-call engineer or an engineering manager puts on during an incident. Then there’s the centralized, full-time role, where someone is the designated incident commander (or one of a few) for all incidents.