Operations | Monitoring | ITSM | DevOps | Cloud

Logs are valuable. Logs generated by a major backend resource that provides clients with access to crucial data are more than just valuable; knowing where they are and being able to manage and understand the information that they contain can mean the difference between smooth, secure operation and degraded performance or even catastrophic failure for your application. MySQL Server produces a handful of basic logs.

As we all know, the on-demand capacity mode of DynamoDB is great but can be cost-prohibitive in some cases (up to seven times more expensive than the Provisioned Capacity mode). The Provisioned mode, on the other hand, shifts to the development team the burden of predicting what level of capacity will be required by the application. And it’s not quite as straightforward to achieve the same level of scalability in the Provisioned mode as we enjoy in the On-demand one.

The Stack Infra team at Elastic uses many services to provide downloads for projects like Elasticsearch and Kibana to our users. One of these services is Fastly, which helps us optimize delivery to regions around the world. Keeping an eye on the performance and behavior of our CDN is important to ensure we're operating at the level we expect.

Today we’re announcing the general availability of Icinga Web v2.8.0. Besides the compatibility with IcingaDB, this release includes fixes for access controls, support for newer PHP and MySQL versions and additional search functionality. Icinga Web 2.8-RC1 was part of the RC1 release of IcingaDB.

Modern businesses rely on a complex ecosystem of digital networks, databases, applications, user devices, and more. The tools and platforms supporting this ecosystem undergo constant refinement and upgrades. However, the basic methods for monitoring infrastructure and application performance have remained unchanged, and logging is one such methods. Every computer, server, networking device, and application produces logs, a timestamped record of events within a system.

Modern businesses rely on a complex ecosystem of digital networks, databases, applications, user devices, and more. The tools and platforms supporting this ecosystem undergo constant refinement and upgrades. However, the basic methods for monitoring infrastructure and application performance have remained unchanged, and logging is one such methods. Every computer, server, networking device, and application produces logs, a timestamped record of events within a system.

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.

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!

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.

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.