Recently, we began using IP geolocation within StatusGator to learn where are users are located. We are happy to say that it’s working out well. We hoped to use these insights to tune our marketing. To that end, we added the Ahoy gem to help collect information related to how our advertising campaigns are going. The Ahoy gem also uses the geolocation gem to lookup IP addresses. This significantly increased the number of IP geolocation lookups.

In many projects, the product development workflow has three main concerns: building, testing, and deployment. Each change to the code means something could accidentally go wrong, so in order to prevent this from happening developers adopt many strategies to diminish incidents and bugs. Jenkins, and other continuous integration tools (CI) are used together with a source version software (such as GIT) to test and quickly evaluate the updated code.

The world of DevOps is a pretty confusing place for folks just starting out. Even figuring out what “DevOps” means can be hard. Is it CI/CD with Kubernetes and Serverless to drive Agile product iterations? Or is it SSH-ing into a box and restarting Apache? You guessed it. All of the above and most things in between.

Cron job failures create chaos for your users and your team. After analyzing over a million failure reports these 4 problems emerged as the most likely causes of preventable job failures.

Lately, IT teams are looking for Docker monitoring tools as legacy products like cAdvisor and Sysdig cloud do not offer greater insights. Docker monitoring needs a crucial change in the way your agents, plug-ins, and monitoring works to support containers. Many enterprises have started deploying significant production workloads on Docker, it seems there is a substantial shift towards adopting Docker.

Since a book series called “… for Dummies” was launched, people have finally come to realize how much they don’t know about the particular area they thought they previously knew about. We’ve all started from somewhere. Self-learning, learning at school or even in the office at our jobs. A breakthrough was achieved when we realized that something absolutely strange to us, became quite familiar.

Building a serverless application means you usually trade in old issues for new ones. This is an attempt to create a decision framework and break down arguments for and against using serverless vs. other computing models.

As we’ve discussed in part one and part two of this series, Service Level Objectives (SLOs) are essential performance indicators for organizations that want a real understanding of how their systems are performing. However, these indicators are driven by vast amounts of raw data and information. That being said, how do we make sense of it all and quantify our SLOs? Let’s take a look.

Handling large images has always been a pain in my side since I started writing code. Lately, it has started to have a huge impact on page speed and SEO ranking. If your website has poorly optimized images it won’t score well on Google Lighthouse. If it doesn’t score well, it won’t be on the first page of Google. That sucks.

More groups are progressing from just talking about Event-Driven Automation to actually doing it in practice. StackStorm helps make this easy. When organizations start offloading business-critical tasks and automating for real it becomes essential to ensure that the Automation engine itself is not a single point of failure when it is responsible for recovering a fleet of servers, managing datacenters, and automating remediations.