The one complaint that an IT administrator dreads to receive is one where an end user says, “My application is slow!”. The application in question can be a web application, an enterprise application like SAP, Microsoft SharePoint, or a SaaS application like Salesforce or Office 365. Since the application is accessed over a network, it’s natural that the network team is pulled up first under the suspicion that it’s a network issue.
If you’re trying to evaluate and understand the ROI of building an observability practice and carve out a budget for it, you’re not alone. You’ve probably got some monitoring and metrics capability already, but that’s proving to not be enough–how can you empower your teams as your environment becomes too complex for the basics? And how much will that cost?
Software as a Service (SaaS) is a mainstream way of bringing enterprise applications to hundreds of thousands of application users at a stable cost. Rather than loading client software on a desktop PC, we lease software from the cloud, and monitor how the SaaS application is delivered. That makes it available to everyone in the enterprise.
Data drives every decision we make at Datadog. That includes decisions about when to leave the office to catch the train! A few years ago, Datadog engineers created MTAServiceChecker.com to provide ourselves and our fellow New Yorkers with detailed insight into New York’s subway system, the MTA. For a recent Datadog hackathon, Chuck Hagenbuch and I, part of our growing engineering team here in Boston, created a version of the service checker for our local system, the MBTA.
Squared Up 4.1 just landed. And what better way to start this announcement than the promise of more feature releases?! It’s been seven months since Squared Up 4.0, but the hard work put in by the development team since then has set us up for a bright, feature-rich future. All those juicy performance improvements and platform changes mean, moving forward, you can expect a new feature release from us every two to three months.
Today is a very special day for Squared Up and, we hope, for the broader SCOM community. We are incredibly excited to announce the launch of Cookdown, a new brand dedicated to optimising SCOM with platform extensions and integrations.
Amazon Elastic Load Balancing ( ELB ) allows you to create load balancers for your application without having to actually manage the servers that do the load balancing. However, since it’s a managed service, you have less visibility with traditional monitoring tools. As such, it becomes even more important to take advantage of the available monitoring tools in AWS. In this post, we’ll explain how to use CloudWatch to monitor Elastic Load Balancing and what is important to watch.
Sentry recently experienced two minor outages related to database lock-contention: a situation where a process stops executing as it waits on another to release a shared resource they each depend on. It’s kind of like [insert comical metaphor intended to inspire a light-hearted chuckle here].
The StatsD stack is one of the most popular monitoring solutions to instrument your code using custom metrics. In this post we will describe the StatsD metrics architecture, metrics types and formats, proving code examples for the Golang, NodeJS/Javascript and Python programming languages.
