Observability is an indispensable concept in continuous delivery, but it can be a little bewildering. Luckily for us, there are a number of tools and techniques to make our job easier! One way to aid in improving observability in a continuous delivery environment is by monitoring and analyzing key metrics from builds and deploys. With tools such as Prometheus and their integrations into CI/CD pipelines, gathering and analysis of metrics is simple. Tracking these things early on is essential.

The client in consideration is one of the largest engineering, procurement, and construction (EPC) companies in India. With projects covering over 14 states in the country, its portfolio of services and offerings is widely diversified. It primarily engages in three forms of businesses – civil construction, road & highway development, and manufacturing.

Javascript is a pretty prolific programming language, used daily by people visiting any number of websites and web applications. NodeJS, it’s server-side version, is also used all over the place. You’ll find it deployed as full application stacks to functions in things like AWS Lambda, or even as IoT processes with things like Johnny Five. So when we think about Observability in the context of a nodejs stack, how do we set it up and get the information flowing?

Do you use an error tracking tool for your website? Have you ever tried to debug a problem that a user reported, and when you looked at your error tracking tool the reported error was simply: “Script Error”? Such errors are impossible to further debug because there is no additional information apart from that message.

As you most likely know, Grafana Labs is growing. Growing like crazy! As Goutham Veeramachaneni noted in his blog post, “~30 people in March 2018 and now, in August 2020 we’re 180+ people. That is 6x growth in 2.5 years.” And we have no intention of slowing that growth. Matter of fact, we’re hiring as quickly as we can — and on top of that keep hiring specialists just to scale out hiring even more.

You may be using your log data in a completely wrong way. Today, your business produces more data than ever before, and log data is at the center of all this because it contains the signals of what caused a problem. If your teams have to search for these signals in an ad-hoc manner, then they are wasting their precious time. Nearly every company in existence is dealing with this challenge because it may not have the tools to filter these signals from the noise.

AppSignal now supports the next API version of PagerDuty. 🎉 One of our devs was on support rotation the other day, and a customer asked whether we could add support for the next API version of PagerDuty. We won’t tell you who it was, but this developer typically answers questions by solving things as quickly as he can. So, two days later, boom! The improved integration for Pagerduty went live.

Look out for these Kubernetes monitoring best practices when evaluating a Kubernetes monitoring solution. It will be easier to make sense of them if your tools are Kubernetes native. Let’s face it. Running containers in Kubernetes brings a number of advantages in terms of automation, segmentation, and efficiency. However, the ability to monitor performance and availability in an ever-changing infrastructure like Kubernetes can be a challenge.

Today, we are excited to announce PagerTree has added 3 new chatbot services including Mattermost, Microsoft Teams and Google Hangouts Chat (this is in addition to our core Slack notification channel). Chatbots are available on all pricing tiers free of charge! :) If you don’t already have an account, sign up for a free-trial now. Our chatbots are will post alert details to a “channel” of your choice.

In today's world, the need for organisations to have comprehensive cybersecurity solutions in place has never been greater. New vulnerabilities are exposed on a daily basis, and data breaches pose not only monetary but reputational risk.