As a cloud project owner, you want your environment to run smoothly and efficiently. At Google Cloud, one of the ways we help you do that is through a family of tools we call Recommenders, which leverage analytics and machine learning to automatically detect issues and present you with optimizations that you can act on.
DevOps engineers always need to check processes, increase work efficiency, and optimize operations. The main part of the work is to improve the quality of the product and set up smooth workflows. That’s why you need to control systems and react to downtime as quickly as possible. One of the best ways to do so is to get timely notifications is Teams DevOps Applications. MS Teams is widely used in many companies, so you probably already have it.
When we graduated Loki into a GA release last year, there were more than 137 contributors who already made more than 1,000 contributions to the project. We also added hosted Loki to the lineup of Grafana Cloud offerings after it proved to be stable internally for our ops cluster, storing 40TB and half a trillion log lines each month. There was, however, one persistent problem that kept surfacing, especially for developers who were writing applications in Go: The regex package was slow.
Amazon Web Services Elastic Load Balancer (AWS ELB) enables websites and web services to serve more requests from users by adding more servers based on need. Unhealthy ELB can cause your website to go offline or slow down dramatically. Elastic Load Balancing automatically distributes incoming application traffic across multiple Amazon EC2 instances.
Netlify allows developers and businesses to publish modern web projects right from your git repos. There’s nothing to set up & no servers to maintain. This past month, Netlify launched Build Plugins, which allows Netlify users to automate and customize their build processes. We loved what the Netlify team was building and how they were automating tedious tasks for developers. So we built the Sentry Netlify Build Plugin!
The public cloud offers great scalability and flexibility for customers and is a model where service providers make many decisions on their behalf. For example, in cloud service providers like Google Cloud Platform (GCP), Amazon Web Service (AWS) or Microsoft Azure, a cloud load balancer is spun up on demand. The load balancer gets an IP address automatically and your application is ready to be served.
I’d like to share some of the best practices we’ve learned on our journey to battle performance issues with the Jaeger tracing tool. Some may say we are experts in logging. We log for a living, and have our log analytics service (which we based on open source ELK Stack) to prove it. We’ve mastered logging to the level where debugging and troubleshooting our system is a no-brainer.