Moving to a scalable, distributed microservice architecture poses a great deal of challenges for any organization. It gets harder to understand the system and pinpoint where errors originate. Logs get much messier, and stitching together a coherent picture of a particular request can be time-consuming or downright impossible. Distributed tracing can help with all of that.
Dear SCOM community, It's been 8 weeks since we launched the free Business Continuity edition (BCE) of our SCOM dashboarding product, and I’m glad to see that many community members have taken us up on the offer. The early feedback we received was encouraging and heartening, and we are happy to have helped ease the pressure on IT teams during these uncertain times, in however small a way.
Ruby may be over 25 years old, but it remains popular in the software community for its focus on programmer happiness. Building software with Ruby often involves leveraging one or more popular frameworks for the purpose of increasing productivity by relying on existing solutions to common problems. Ruby frameworks generally fall into two categories: web-facing frameworks and background job frameworks.
Imagine you are rolling out your application to multiple customers, they even might use it on premise. Of course you want to know if your application is running fine and the customer is not experiencing any kind of trouble or downtime - surely you would not want to ship this validation in your own system, as that might also be prone to any kind of error at some point. Which is why you decide to go for a third party uptime monitoring solution e.g. Uptime Monitoring.
I recently published an article on Citrix Performance Analytics (also called Citrix Analytics for Performance), part of the Citrix Analytics service in Citrix Cloud. In this article, i will analyze where Citrix Performance Analytics fits in relative to other Citrix performance monitoring and management tools in the market.
Today we will be talking to Noah Hilverling, or “N-o-X” on Github. He’s been with the Icinga team for almost 4 years now and is responsible for a whole lot of bug fixes and shiny features in Icinga 2.
One of the great things about Lumigo is that it records a lot of context about each Lambda invocation. This includes the invocation event and its return value, as well as the environment variables that were in use at the time. I find this super helpful because it gives me all the relevant information about an invocation in one place. I don’t have to jump between different screens to find the relevant information and then piece the clues together in my head.
When we discuss Splunk Phantom with customers here at Splunk, we end up talking about phishing pretty frequently. As discussed in a recent blog post, "Phishing Emails — Don’t Get Reeled In!," phishing is a super common issue that almost everyone deals with ad nauseum. It’s also a nuisance to investigate. The good news is that automation excels at dealing with repetitive, mind-numbing workflows like phishing investigations.
Data is the lifeblood of any organisation. It’s what drives customer engagement, boosts employee productivity, streamlines operations and, in some cases, even transforms age-old companies into digital powerhouses.
Every NOC engineer will tell you that the first thing they look for in an outage is “what changed?”. And they are right to look. While every organization is unique, Gartner reports that on average about 80% of IT incidents today are caused by changes in infrastructure and/or software.
