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ChatOps

How ChatOps Helps IT Teams Work More Effectively

From setting up new hires with everything they need to get to work to troubleshooting technical difficulties, IT teams often field the same kinds of requests over and over. And while each request might feel like a small task, collectively they can add up to a huge time sink in the long run.

Get Started with ChatOps with "7 Steps to ChatOps for Enterprise Teams"

The right tools enable your team to ship amazing code quickly. But between building, deploying, testing, monitoring, and maintaining software, all those great tools can create a lot of stuff to keep track of. Luckily, there’s a solution to this problem: ChatOps. ChatOps is a collective approach to running DevOps workflows and building a collaborative team culture.

ChatOps and Mobile Adoption: The Power of Teams Working Where They Are

The way we socialize, learn, shop, and receive care has changed drastically over the last 18 months. For many of us, perhaps one of the most drastic changes was the way we work. While work from home (WFH) was an option before the pandemic, NCCI states, “only 6% of the employed worked primarily from home and about three-quarters of workers had never worked from home.” Fast forward to 2021, and according to NorthOne, here’s how much things have changed.

Why ChatOps & Incident Management are the Perfect Pair

ChatOps has become an integral part of software development and IT operations, as teams rely on automated notifications to take the place of manual alerts. In the past, if there was an alert, someone would need to manually find that notification. Then, they would have contact team members to notify them one by one so they could start working on a resolution. In this complex network of communications, it was easy to lose information, duplicate work, and simply waste time coordinating the team.

What's New: Introducing Next-Gen ChatOps With PagerDuty and Slack

In this new world of digital everything, new application versions usually mean that you’re going to get bigger and better features, more capabilities, and an uplifted user experience, right? When I talk to customers, many can’t wait to upgrade the PagerDuty integrations that they depend on to test new features. If you’re a PagerDuty for Slack user, the next-generation version of our Slack integration will certainly be an exciting development.

5 workflow automations for Mattermost that we love at n8n

n8n is a fair-code licensed tool that helps you automate tasks, sync data between various sources, and react to events — all via a visual workflow editor. Our team has been using Mattermost for internal communication since the very beginning, and in time we have developed a ChatOps practice by integrating Mattermost with our workflows. In this article, we present five of our favorite use cases of n8n with Mattermost, for both work productivity and team engagement.

What is ChatOps?

The term ‘ChatOps’ was first coined by Github to describe how their internal teams used a bot called Hubot to handle DevOps. Since then, ChatOps has been practically (and successfully) adopted by numerous organizations as an additional enabler to the DevOps framework. ChatOps is a conceptualized collaboration model that embeds DevOps processes and tools within an organization’s communication channels to aid transparency and workflow automation.

How ChatOps and Runbooks Coexist

ChatOps was established by GitHub as a way to automate operations-driven tasks through a chatbot by using it to run essential scripts and commands, allowing the automation of many simple tasks. It has since evolved to include integration of operations and improvement tools, and functions as a collaborative platform allowing teams to easily communicate and manage their workflow. Using a ChatOps solution also allows you to document an easily accessible timeline of your team’s verbal exchanges.

Kubernetes Health Alerts

When a pod is unhealthy in a Kubernetes cluster, does anyone notice? Have you ever deployed a new version of an app to Kubernetes, tried to test the new feature you added or bug you fixed and found the same behavior as before? Have you ever then double-checked your code, rerun your tests, checked a few more things, only then to realize that while the deployment got updated, the new pods never replaced the old because of some misconfiguration or other mistake?