Operations | Monitoring | ITSM | DevOps | Cloud

The past ten years marked a significant change in how software teams build and deploy applications. We moved away from bulky, slow, monolithic applications toward lightweight, scalable, distributed service-based applications. Meanwhile, tools like Docker, Kubernetes, and other container platforms helped accelerate this process. Despite this sudden growth, a fundamental question remains: what exactly is a service, and how does it fit into a microservice architecture?

When it comes to building reliable and scalable software, few organizations have as much authority and expertise as Google. Their Site Reliability Engineering Handbook, first published in 2016, details their practices to maintain reliability as Google scaled. But when you have over a million servers running thousands of services across more than twenty data centers, how do you monitor them in a consistent, logical, and relevant way?

With the right load balancing in place, the demand of increasing web traffic can become manageable, but how do you determine which load balancing algorithm is best suited for your applications? Does the ease of use of static load balancing better suit the services you provide, or would your system benefit from a more complex and dynamic set of algorithms to maximize efficiency? In this blog post, we discuss what to consider when deciding on the right load-balancing algorithm.

More than 20,000 companies around the world use Ansible as their Infrastructure as Code and configuration management tool. With the rising popularity towards managing infrastructure using IaC and config management tools, Ansible is one of the best open source tools to choose from. That is why we are excited to announce a new Grafana Ansible collection available to all Grafana Cloud users, including those in the generous free tier.

As of 2021, roughly 5.7 million mobile apps are available in app stores — 2.2 million for iOS and 3.48 million for Android users. Given the massive numbers, customers have a wide variety of choices. With such a high number of apps available, customer satisfaction is paramount, which means avoiding customer churn and retaining users.

We understand how critical a message archive can be to your organization. Empowering you with complete control over your data—including your message history—is a key tenet of our mission here at Mattermost! If you’re part of one of the many teams and communities that use Slack to collaborate – take note: After September 1st, 2022, you will no longer be able to access your Slack message history older than 90 days on your free workspaces.

Following on from the recent launch of our Anomaly Advisor feature, and in keeping with our approach to machine learning, here is a detailed Python notebook outlining exactly how the machine learning powering the Anomaly Advisor actually works under the hood. Or if you’d rather watch a video walkthrough of the notebook then check out below. Try it for yourself, get started by signing in to Netdata and connecting a node.

Developers commonly integrate the code and these frequent modifications in a central repository as part of the software development method is known as continuous integration (CI). Improved software quality, faster quality audit and bug fixes, and quick validation and release cycles are all major goals of continuous integration. Continuous Delivery (CD), which builds on top of Continuous Integration(CI), includes automating both builds and the complete software release process.