The past decade has seen a drastic growth in the adoption of public cloud. One of the primary reasons for this is its cheaper infrastructure and ease of scale. With such rapid adoption of public cloud, the need for infrastructure automation also arises. This is because teams want to quickly provision infrastructure and automate tasks that previously took weeks in the case of traditional data centers, down to minutes in the public cloud.

Prometheus is a platform for real-time systems and event monitoring and alerting. The Prometheus project is free, open-source, and available on GitHub. Originally developed at SoundCloud, Prometheus became a project of the Cloud Native Computing Foundation in 2016, alongside other popular frameworks such as Kubernetes. The core of the project is the Prometheus server, which acts as the system’s “brain” by collecting various metrics and storing them in a time-series database.

Building and deploying highly scalable, distributed applications in the ever-changing landscape of software development is only half the journey. The other half is monitoring your application states and instances while recording accurate metrics. There are moments when you wish to check how many resources are being consumed, how many files are under access by the specialized process, etc. These metrics provide valuable insights into our tech stack execution and management.

Observability is a critical aspect of modern software development and infrastructure management. It involves the ability to gain insights into the internal workings of your systems, applications, and services through monitoring and collecting relevant data. With the increasing complexity of technology stacks and the need for real-time visibility, observability has become a fundamental requirement for businesses across various industries.

I used to think my job as a developer was done once I trained and deployed the machine learning model. Little did I know that deployment is only the first step! Making sure my tech baby is doing fine in the real world is equally important. Fortunately, this can be done with machine learning monitoring. In this article, we’ll discuss what can go wrong with our machine-learning model after deployment and how to keep it in check.

Heroku is a cloud-based platform that supports multiple programming languages. It functions as a Platform as a Service (PaaS), allowing developers to effortlessly create, deploy, and administer cloud-based applications. With its compatibility with languages like Java, Node.js, Scala, Clojure, Python, PHP, and Go, Heroku has become the preferred choice for developers who desire powerful and adaptable cloud capabilities.

Today we are going to touch up on the topic of why Graphite monitoring is essential. In today’s current climate of extreme competition, service reliability is crucial to the success of a business. Any downtime or degraded user experience is simply not an option as dissatisfied customers will jump ship in an instant. Operations teams must be able to monitor their systems organically, paying particular attention to Service Level Indicators (SLIs) pertaining to the availability of the system.

Graphite and Prometheus are both great tools for monitoring networks, servers, other infrastructure, and applications. Both Graphite and Prometheus are what we call time-series monitoring systems, meaning they both focus on monitoring metrics that record data points over time. At MetricFire we offer a hosted version of Graphite, so our users can try it out on our free trial and see which works better in their case.

Behind the trends of cloud-native architectures and microservices lies a technical complexity, a paradigm shift, and a rugged learning curve. This complexity manifests itself in the design, deployment, and security, as well as everything that concerns the monitoring and observability of applications running in distributed systems like Kubernetes. Fortunately, there are tools to help developers overcome these obstacles.

Prometheus and Grafana are the two most groundbreaking open-source monitoring and analysis tools in the past decade. Ever since developers started combining these two, there's been nothing else that they've needed. There are many different ways a Prometheus and Grafana stack can be set up.