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To integrate Slack and PagerDuty with your monitoring system, please reach out to MetricFire. Book a demo with the MetricFire team to discuss integrating Slack and PagerDuty and how that can support your monitoring system.
Slack is a popular channel-based messaging platform that improves business communication and collaboration. This cloud-based solution offers enterprise-grade security and scalability, along with many innovative features that make it easier to have quality work conversations.
The core functionality of Slack revolves around chat rooms where users send messages and files. You can organize these rooms by topics, teams, projects, office locations, and other categories to keep the discussions highly relevant to that work. Users can also directly message each other. In addition to text messages, voice, screen sharing, and video chats are also supported.
You have a lot of flexibility in working with Slack. Your channels can be open to everyone in the organization, available for users outside of your organization, or made private for a subset of employees. A robust search function simplifies the process of looking up information, so it’s readily available. There is also an option of free-to-use and paid plans.
Slack workspaces create a central repository for work-related information, whether that’s being shared in messages, file attachments, links, or other formats. Slack performance monitoring allows you to see how your organization is utilizing this platform, whether it’s having issues, and ways to optimize it for your specific use cases.
One of Slack’s strengths is its integration support with many software types, allowing you to perform your work without leaving the workspace. For example, when you connect MetricFire and Slack, you can send immediate notifications to a specific channel so the right staff members see it. Since the alerts show up in a centralized communications tool being used for other daily work activities, they get noticed and acted on faster.
PagerDuty is an incident management platform used to help teams quickly detect and fix infrastructure problems. It manages automatic notifications when a problem occurs, escalates the issue where necessary, and schedules on-call resources.
With its SaaS platform, PagerDuty provides businesses, developers, and administrators a range of powerful tools to help them quickly manage client-impacting issues. By arming your business with the insight to proactively manage events that may affect customers across your IT infrastructure, PagerDuty helps you to maintain customer experience and satisfaction. It also allows you to sustain your brand reputation and revenue streams.
PagerDuty comes with hundreds of native integration points to ensure that the right data gets in the hands of the right people in real-time. By taking advantage of machine-learning, PagerDuty automatically handles resource scheduling and issue escalations. You can customize PagerDuty notifications to use a combination of phone calls, SMS, push notifications, and emails depending on the issue severity, time of day, or defined support hours.
These features are why PagerDuty can be such a useful companion to your MetricFire applications such as Hosted Graphite. For example, you might use Hosted Graphite to receive alerts about system performance, code bugs, or other issues. If you use PagerDuty as well, you would find it of immense use when you wanted automatic delegating to the people in your organization. One way would be to use PagerDuty to create alerts that it automatically assigns to specific people on your team.
You can create a PagerDuty service on MetricFire's Hosted Graphite that triggers once an alert criterion reaches a specified threshold. Once triggered, the service delegates tasks to specific individuals, leaving you free to focus on other important job functions.
To integrate Slack and PagerDuty with your monitoring system, sign up for a free trial with MetricFire. Talk with the MetricFire team about how to integrate Slack and PagerDuty and get Slack and PagerDuty interacting with your MetricFire dashboards directly.
MetricFire is a full-scale platform that provides infrastructure, system, and application monitoring using a suite of open-source monitoring tools. We enable you to use Hosted Graphite and aesthetic custom dashboards to visualize your metrics so you can understand what is happening.
MetricFire offers users a complete ecosystem of end-to-end infrastructure monitoring, comprised of popular open-source monitoring software services: Graphite and popular dashboards. Plugins for many other open-source projects are preconfigured, such as StatsD, collectd, and Kubernetes. You get all these within a hosted environment as a single product. Not only does MetricFire fit well into the infrastructure monitoring use-case, such as network monitoring and server monitoring, but we also do application monitoring and business intelligence.
Through this hosted environment, MetricFire boosts the unique features of open-source projects to give you more functionality than the original products. Below are some of the MetricFire features at a glance:
The key thing to remember is that Hosted Graphite by MetricFire is more than just Graphite. Our Hosted Graphite product actually adds data dimensionality and better data storage.
The benefits of MetricFire are:
“We now have over ten times the amount of metrics we started with, and on different accounts. One of the great things about MetricFire is that scaling to support this increase has been hassle-free, requiring no additional work on our side.”
“Building and managing an on-premise installation at this scale would require a lot of engineer time, especially in the first year...we use this engineering time to work on initiatives closer to our core business”
“There’s complete transparency with everything MetricFire do which means we can accurately predict what we’ll be spending and comfortably keep within our budget.”
"Every time I have a question, I get an answer from support after just a couple of hours. Their technical knowledge is excellent.”
In this article, we’ll discuss what can go wrong with our machine-learning model after... Continue Reading
