Operations | Monitoring | ITSM | DevOps | Cloud

In Part 1 of this series, we looked at EFS metrics from several different categories—storage, latency, I/O, throughput, and client connections. In this post, we’ll show you how you can collect those metrics—as well as EFS logs—using built-in and external tools.

Amazon Elastic File System (EFS) provides shared, persistent, and elastic storage in the AWS cloud. Like Amazon S3, EFS is a highly available managed service that scales with your storage needs, and it also enables you to mount a file system to an EC2 instance, similar to Amazon Elastic Block Store (EBS).

Containers are lightweight, portable, easily scalable, and enable you to run multiple workloads on the same host efficiently, particularly when using an orchestration platform like Kubernetes or Amazon ECS. But containers also introduce monitoring challenges. Containerized environments may comprise vast webs of distributed endpoints and dependencies that rely on complex network communication.

GitHub Actions are a powerful way to add automation to any source code repository. When you take that power and connect it with InfluxDB, you get an amazing combination that allows you to automate data generation, manage GitOps workflows, and a whole lot more. This post will highlight some of the interesting ways to use InfluxDB and GitHub Actions.

As a startup, we always want to focus on the most important thing — to deliver value to our customers. For that reason, we are a huge fan of the serverless options provided by AWS (Lambda) and GCP (Cloud Function) as these allow us to maintain and quickly deploy bite-size business logic to production, without having to worry too much about maintaining the underlying servers and computing resources.

Your feedback is what makes Honeycomb better. We ship changes often (you can see updates in real time on our changelog), so it can be easy to miss some of the new improvements that can help you get the most out of Honeycomb. Whether it’s a big new product feature or an enhancement of existing features, you may not always be up on the latest goodness waiting for you in Honeycomb.

In the internet-driven economy, businesses rely on applications for different functions in the customer, partner, and employee spheres. Over the years, such applications have become more functional, faster, and user-friendly. However, end users still encounter slow loading pages, transaction failures, and esoteric error messages. These errors cause inconvenience to the users and lead to significant financial and reputational losses.

Every database administrator (DBA) is—first and foremost—human. And everyone makes mistakes. It’s not the absence of mistakes but rather how you prepare for those mistakes that makes you a great DBA. Luckily, there are many ways to prepare for those mishaps, whether the errors are made by you or someone else on your team. One commonly made mistake is to drop an object in a database or accidentally delete data.

In the ScienceLogic webinar, “Clearing the Path for Automated Operations,” we look at how one global technology organization got their IT house in order through the application of AIOps and a strategic approach to implementation, based on ScienceLogic’s AIOps Maturity. ITOps teams are overloaded with manual, repetitive work that creates management bottlenecks and takes time away from new projects.