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To integrate Amazon Firehose and webhooks with your monitoring system, please reach out to MetricFire. Book a demo with the MetricFire team to discuss integrating Amazon Firehose and webhooks and how that can support your monitoring system.
With the ever-increasing popularity of streaming content, the need to enable users to collect, store, capture, and process large amounts of data from their distributed streams is crucial. By using Amazon Kinesis Data Firehose, you can capture massive amounts of live video data from millions of sources, and then make them available to consumers in a data-efficient and cost-effective format.
Amazon Kinesis Data Firehose lets you quickly load streaming data into data stores, data lakes, and analytics services. You can use it to capture, transform, and deliver streaming data to a range of Amazon services, including Amazon Redshift, Amazon S3, Amazon Elasticsearch Service. You can also use Kinesis to connect to generic HTTP endpoints and service providers such as New Relic, MongoDB, Datadog, and Splunk.
Firehose is a fully managed service that automatically scales to match your data throughput. You can also use it to compress, transform, and encrypt your data streams. This feature minimizes the amount of storage required for your streaming data and increases security.
Amazon Kinesis Data Firehose integrates with Amazon CloudWatch metrics so you can collect and analyze your data streaming metrics. For example, you could monitor the IncomingBytes and IncomingRecords metrics to track data ingested into Kinesis Data Firehose from your data producers. You can use Kinesis Analytics to analyze and process your data streams using standard SQL. It also comes with pre-built stream processing templates to help you manage your data analytics.
By integrating Amazon CloudWatch with the MetricFire platform, you can display your streaming metrics on aesthetically pleasing dashboards. MetricFire's advanced filtering lets you choose only the data views you want to see and discard the rest. You can also set up simple rules to discard data you no longer need, plus receive alerts via email or Slack when your data streaming is doing something it shouldn't.
Webhooks are user-defined HTTP callbacks triggered by an event, such as pushing code to a repository or posting a comment to a blog. They allow you to send data from one application to another whenever a specific event occurs. When an event is triggered, the source site makes an HTTP request to the URL configured for the webhook.
Webhooks are one of only a few methods available to allow web applications to exchange information with each other. At first, webhooks might seem like an API, but they are slightly different. Webhooks don't need to give a request to get a response, while APIs need to send a request to get a response. Webhooks let you receive, while APIs require you to retrieve. Think of it like API calls and polling need to knock on the door (requesting) to give that information to someone. Webhooks just simply throw that information at the door as there is no need to request permission.
There are many reasons to use webhooks. You could use a webhook to connect a payment gateway with your email marketing software to notify a customer by email if a payment bounces. You might use a webhook to send event data to external databases or data warehouses like Amazon's Redshift for further analysis. Or you could use webhooks to sync customer data between applications, such as when a user changes their email address. By using a webhook, you can ensure that the change is reflected in your CRM as well.
With MetricFire, you can use WebHooks in two different ways. First, they are useful for integrating metric data from various platforms and services, including CircleCi, Pingdom, Sentry, and more. Second, you can create WebHooks from within MetricFire to send notifications to applications and services that accept WebHooks.
To integrate Amazon Firehose and webhooks with your monitoring system, sign up for a free trial with MetricFire. Talk with the MetricFire team about how to integrate Amazon Firehose and webhooks and get Amazon Firehose and webhooks 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
