Operations | Monitoring | ITSM | DevOps | Cloud

AWS Lambda is the leading serverless computing solution and is one of AWS’ most successful products, to date. Its popularity is in large part because of the way it makes development easier and faster. Lambda completely abstracts away the maintenance of underlying infrastructure including compute, storage, memory, and networking. Developers simply upload their code in the form of Lambda functions and the service fully handles the execution of these functions.

Web applications like knockout.js help you to reach out to your audience and customers. And as your customer base increases, your web-application evolves so that you can cater to their varying needs. But the more features you introduce in your application, the more requests and responses need to be handled by your applications. That, coupled with design (CSS) can make your web applications pretty bulky. You must be thinking, “So what!

Subkeying is a way to group a set of crashes at some level other than the top level of the call stack. Subkeying is a way to group a set of crashes at some level other than the top level of the call stack. At BugSplat, crashes are grouped by a stack key and groups of crashes can be found on the Summary page. By Default, BugSplat groups crashes using the topmost level of a call stack. A subkey is created when crashes are grouped at a level other than the top level of a call stack.

If you're reading this, you're probably wondering how to get data from various Microsoft Azure services into Splunk. With the growing list of Azure services and various data access methods, it can be a little cloudy (pun intended) on what data is available and how to get all that data into Splunk. In this blog post, I'm going go over how Microsoft makes Azure data available, how to access the data, and out-of-the-box Splunk Add-Ons that can consume this data. So let's dive right in.

As more environments run on Kubernetes—including our own— Datadog has been making it easier to get visibility into clusters of any scale. To minimize load on the Kubernetes API server, the Datadog Agent runs in two different modes. The node-based Agent queries local containers or external endpoints for data, while the Cluster Agent fetches cluster-level metadata from the API server.

We all want lightning-fast websites and applications, but how do we prioritize our efforts in order to have the biggest impact on performance? We interviewed our own front-end team so we could share some best practices we use every day to improve and maintain the performance of Raygun.

Redis, which stands for Remote Dictionary Server, is an open source, in-memory data structure store that’s used as a database, memory cache, and message broker. It stores data entirely in memory in the form of key-value pairs. This gives it an edge over all other databases, as it eliminates the need to access data from the disk. It also makes Redis one of the fastest NoSQL databases, where data is accessed in microseconds because there are no seek time delays.

Many Grafana users export images of their dashboard panels. This feature powers the ability to receive alerts with a rendered image of the panel attached, which is valuable for quickly spotting if something is about to go sideways in production. Since Grafana v2.0, when support for server-side rendering of dashboard panels as images was introduced, PhantomJS has served as the built-in image renderer that enables this feature.

A few weeks ago, we announced that Sysdig is offering fully compatible Prometheus monitoring at scale for our customers, as well as a new website called PromCat.io hosting a curated repository of Prometheus exporters, dashboards and alerts. This got me thinking about how we were actually able to implement the changes necessary to offer this in our platform.